diff --git a/.cursor/skills/tdd/SKILL.md b/.cursor/skills/tdd/SKILL.md new file mode 100644 index 000000000..79cdaf999 --- /dev/null +++ b/.cursor/skills/tdd/SKILL.md @@ -0,0 +1,112 @@ +--- +name: tdd +description: Strict Python TDD workflow using pytest (Red-Green-Refactor). +--- + +--- +name: tdd +description: Test-driven development with red-green-refactor loop. Use when user wants to build features or fix bugs using TDD, mentions "red-green-refactor", wants integration tests, or asks for test-first development. +--- + +# Test-Driven Development + +## Philosophy + +**Core principle**: Tests should verify behavior through public interfaces, not implementation details. Code can change entirely; tests shouldn't. + +**Good tests** are integration-style: they exercise real code paths through public APIs. They describe _what_ the system does, not _how_ it does it. A good test reads like a specification - "user can checkout with valid cart" tells you exactly what capability exists. These tests survive refactors because they don't care about internal structure. + +**Bad tests** are coupled to implementation. They mock internal collaborators, test private methods, or verify through external means (like querying a database directly instead of using the interface). The warning sign: your test breaks when you refactor, but behavior hasn't changed. If you rename an internal function and tests fail, those tests were testing implementation, not behavior. + +See [tests.md](tests.md) for examples and [mocking.md](mocking.md) for mocking guidelines. + +## Anti-Pattern: Horizontal Slices + +**DO NOT write all tests first, then all implementation.** This is "horizontal slicing" - treating RED as "write all tests" and GREEN as "write all code." + +This produces **crap tests**: + +- Tests written in bulk test _imagined_ behavior, not _actual_ behavior +- You end up testing the _shape_ of things (data structures, function signatures) rather than user-facing behavior +- Tests become insensitive to real changes - they pass when behavior breaks, fail when behavior is fine +- You outrun your headlights, committing to test structure before understanding the implementation + +**Correct approach**: Vertical slices via tracer bullets. One test → one implementation → repeat. Each test responds to what you learned from the previous cycle. Because you just wrote the code, you know exactly what behavior matters and how to verify it. + +``` +WRONG (horizontal): + RED: test1, test2, test3, test4, test5 + GREEN: impl1, impl2, impl3, impl4, impl5 + +RIGHT (vertical): + RED→GREEN: test1→impl1 + RED→GREEN: test2→impl2 + RED→GREEN: test3→impl3 + ... +``` + +## Workflow + +### 1. Planning + +Before writing any code: + +- [ ] Confirm with user what interface changes are needed +- [ ] Confirm with user which behaviors to test (prioritize) +- [ ] Identify opportunities for [deep modules](deep-modules.md) (small interface, deep implementation) +- [ ] Design interfaces for [testability](interface-design.md) +- [ ] List the behaviors to test (not implementation steps) +- [ ] Get user approval on the plan + +Ask: "What should the public interface look like? Which behaviors are most important to test?" + +**You can't test everything.** Confirm with the user exactly which behaviors matter most. Focus testing effort on critical paths and complex logic, not every possible edge case. + +### 2. Tracer Bullet + +Write ONE test that confirms ONE thing about the system: + +``` +RED: Write test for first behavior → test fails +GREEN: Write minimal code to pass → test passes +``` + +This is your tracer bullet - proves the path works end-to-end. + +### 3. Incremental Loop + +For each remaining behavior: + +``` +RED: Write next test → fails +GREEN: Minimal code to pass → passes +``` + +Rules: + +- One test at a time +- Only enough code to pass current test +- Don't anticipate future tests +- Keep tests focused on observable behavior + +### 4. Refactor + +After all tests pass, look for [refactor candidates](refactoring.md): + +- [ ] Extract duplication +- [ ] Deepen modules (move complexity behind simple interfaces) +- [ ] Apply SOLID principles where natural +- [ ] Consider what new code reveals about existing code +- [ ] Run tests after each refactor step + +**Never refactor while RED.** Get to GREEN first. + +## Checklist Per Cycle + +``` +[ ] Test describes behavior, not implementation +[ ] Test uses public interface only +[ ] Test would survive internal refactor +[ ] Code is minimal for this test +[ ] No speculative features added +``` \ No newline at end of file diff --git a/.cursor/skills/tdd/deep-modules.md b/.cursor/skills/tdd/deep-modules.md new file mode 100644 index 000000000..13a1b9106 --- /dev/null +++ b/.cursor/skills/tdd/deep-modules.md @@ -0,0 +1,33 @@ +# Deep Modules + +From "A Philosophy of Software Design": + +**Deep module** = small interface + lots of implementation + +``` +┌─────────────────────┐ +│ Small Interface │ ← Few methods, simple params +├─────────────────────┤ +│ │ +│ │ +│ Deep Implementation│ ← Complex logic hidden +│ │ +│ │ +└─────────────────────┘ +``` + +**Shallow module** = large interface + little implementation (avoid) + +``` +┌─────────────────────────────────┐ +│ Large Interface │ ← Many methods, complex params +├─────────────────────────────────┤ +│ Thin Implementation │ ← Just passes through +└─────────────────────────────────┘ +``` + +When designing interfaces, ask: + +- Can I reduce the number of methods? +- Can I simplify the parameters? +- Can I hide more complexity inside? \ No newline at end of file diff --git a/.cursor/skills/tdd/interface-design.md b/.cursor/skills/tdd/interface-design.md new file mode 100644 index 000000000..2fff0021f --- /dev/null +++ b/.cursor/skills/tdd/interface-design.md @@ -0,0 +1,33 @@ +# Interface Design for Testability + +Good interfaces make testing natural: + +1. **Accept dependencies, don't create them** +```python +# Testable +def process_order(order, payment_gateway): + pass + +# Hard to test +def process_order(order): + gateway = StripeGateway() + +``` + + +2. **Return results, don't produce side effects** +```python +# Testable +def calculate_discount(cart) -> float: + return discount + +# Hard to test +def apply_discount(cart) -> None: + cart.total -= discount + +``` + + +3. **Small surface area** +* Fewer methods = fewer tests needed +* Fewer params = simpler test setup diff --git a/.cursor/skills/tdd/mocking.md b/.cursor/skills/tdd/mocking.md new file mode 100644 index 000000000..15e9a116c --- /dev/null +++ b/.cursor/skills/tdd/mocking.md @@ -0,0 +1,69 @@ + +# When to Mock + +Mock at **system boundaries** only: + +* External APIs (payment, email, etc.) +* Databases (sometimes - prefer test DB) +* Time/randomness +* File system (sometimes) + +Don't mock: + +* Your own classes/modules +* Internal collaborators +* Anything you control + +## Designing for Mockability + +At system boundaries, design interfaces that are easy to mock: + +**1. Use dependency injection** + +Pass external dependencies in rather than creating them internally: + +```python +import os + +# Easy to mock +def process_payment(order, payment_client): + return payment_client.charge(order.total) + +# Hard to mock +def process_payment(order): + client = StripeClient(os.getenv("STRIPE_KEY")) + return client.charge(order.total) + +``` + +**2. Prefer SDK-style interfaces over generic fetchers** + +Create specific functions for each external operation instead of one generic function with conditional logic: + +```python +import requests + +# GOOD: Each function is independently mockable +class UserAPI: + def get_user(self, user_id): + return requests.get(f"/users/{user_id}") + + def get_orders(self, user_id): + return requests.get(f"/users/{user_id}/orders") + + def create_order(self, data): + return requests.post("/orders", json=data) + +# BAD: Mocking requires conditional logic inside the mock +class GenericAPI: + def fetch(self, endpoint, method="GET", data=None): + return requests.request(method, endpoint, json=data) + +``` + +The SDK approach means: + +* Each mock returns one specific shape +* No conditional logic in test setup +* Easier to see which endpoints a test exercises +* Type safety per endpoint \ No newline at end of file diff --git a/.cursor/skills/tdd/refactoring.md b/.cursor/skills/tdd/refactoring.md new file mode 100644 index 000000000..e184a1518 --- /dev/null +++ b/.cursor/skills/tdd/refactoring.md @@ -0,0 +1,10 @@ +# Refactor Candidates + +After TDD cycle, look for: + +- **Duplication** → Extract function/class +- **Long methods** → Break into private helpers (keep tests on public interface) +- **Shallow modules** → Combine or deepen +- **Feature envy** → Move logic to where data lives +- **Primitive obsession** → Introduce value objects +- **Existing code** the new code reveals as problematic \ No newline at end of file diff --git a/.cursor/skills/tdd/tests.md b/.cursor/skills/tdd/tests.md new file mode 100644 index 000000000..b454a6956 --- /dev/null +++ b/.cursor/skills/tdd/tests.md @@ -0,0 +1,60 @@ +# Good and Bad Tests + +## Good Tests + +**Integration-style**: Test through real interfaces, not mocks of internal parts. + +```python +# GOOD: Tests observable behavior +def test_user_can_checkout_with_valid_cart(): + cart = create_cart() + cart.add(product) + result = checkout(cart, payment_method) + assert result.status == "confirmed" + +``` + +Characteristics: + +* Tests behavior users/callers care about +* Uses public API only +* Survives internal refactors +* Describes WHAT, not HOW +* One logical assertion per test + +## Bad Tests + +**Implementation-detail tests**: Coupled to internal structure. + +```python +# BAD: Tests implementation details +def test_checkout_calls_payment_service_process(): + mock_payment = MagicMock() + checkout(cart, mock_payment) + mock_payment.process.assert_called_with(cart.total) + +``` + +Red flags: + +* Mocking internal collaborators +* Testing private methods +* Asserting on call counts/order +* Test breaks when refactoring without behavior change +* Test name describes HOW not WHAT +* Verifying through external means instead of interface + +```python +# BAD: Bypasses interface to verify +def test_create_user_saves_to_database(): + create_user({"name": "Alice"}) + row = db.query("SELECT * FROM users WHERE name = ?", ["Alice"]) + assert row is not None + +# GOOD: Verifies through interface +def test_create_user_makes_user_retrievable(): + user = create_user({"name": "Alice"}) + retrieved = get_user(user.id) + assert retrieved.name == "Alice" + +``` \ No newline at end of file diff --git a/.env.example b/.env.example deleted file mode 100644 index 894a989cc..000000000 --- a/.env.example +++ /dev/null @@ -1,41 +0,0 @@ -# Docker Specific Env's Only - Can skip if needed - -# Celery Config -REDIS_PORT=6379 -FLOWER_PORT=5555 - -# Frontend Configuration -FRONTEND_PORT=3000 -NEXT_PUBLIC_FASTAPI_BACKEND_URL=http://localhost:8000 (Default: http://localhost:8000) -NEXT_PUBLIC_FASTAPI_BACKEND_AUTH_TYPE=LOCAL or GOOGLE (Default: LOCAL) -NEXT_PUBLIC_ETL_SERVICE=UNSTRUCTURED or LLAMACLOUD or DOCLING (Default: DOCLING) -# Backend Configuration -BACKEND_PORT=8000 -# Auth type for backend login flow (Default: LOCAL) -# Set to GOOGLE if using Google OAuth -AUTH_TYPE=LOCAL -# Frontend URL used by backend for CORS allowed origins and OAuth redirects -# Must match the URL your browser uses to access the frontend -NEXT_FRONTEND_URL=http://localhost:3000 - -# Database Configuration -POSTGRES_USER=postgres -POSTGRES_PASSWORD=postgres -POSTGRES_DB=surfsense -POSTGRES_PORT=5432 - -# Electric-SQL Configuration -ELECTRIC_PORT=5133 -# PostgreSQL host for Electric connection -# - 'db' for Docker PostgreSQL (service name in docker-compose) -# - 'host.docker.internal' for local PostgreSQL (recommended when Electric runs in Docker) -# Note: host.docker.internal works on Docker Desktop (Mac/Windows) and can be enabled on Linux -POSTGRES_HOST=db -ELECTRIC_DB_USER=electric -ELECTRIC_DB_PASSWORD=electric_password -NEXT_PUBLIC_ELECTRIC_URL=http://localhost:5133 - -# pgAdmin Configuration -PGADMIN_PORT=5050 -PGADMIN_DEFAULT_EMAIL=admin@surfsense.com -PGADMIN_DEFAULT_PASSWORD=surfsense diff --git a/.github/workflows/backend-tests.yml b/.github/workflows/backend-tests.yml new file mode 100644 index 000000000..6e0a6db6d --- /dev/null +++ b/.github/workflows/backend-tests.yml @@ -0,0 +1,161 @@ +name: Backend Tests + +on: + pull_request: + branches: [main, dev] + types: [opened, synchronize, reopened, ready_for_review] + +concurrency: + group: ${{ github.workflow }}-${{ github.ref }} + cancel-in-progress: true + +jobs: + unit-tests: + name: Unit Tests + runs-on: ubuntu-latest + if: github.event.pull_request.draft == false + env: + EMBEDDING_MODEL: sentence-transformers/all-MiniLM-L6-v2 + + steps: + - name: Checkout code + uses: actions/checkout@v6 + + - name: Check if backend files changed + id: backend-changes + uses: dorny/paths-filter@v3 + with: + filters: | + backend: + - 'surfsense_backend/**' + + - name: Set up Python + if: steps.backend-changes.outputs.backend == 'true' + uses: actions/setup-python@v5 + with: + python-version: '3.12' + + - name: Install UV + if: steps.backend-changes.outputs.backend == 'true' + uses: astral-sh/setup-uv@v7 + + - name: Cache dependencies + if: steps.backend-changes.outputs.backend == 'true' + uses: actions/cache@v5 + with: + path: | + ~/.cache/uv + surfsense_backend/.venv + key: python-deps-${{ hashFiles('surfsense_backend/uv.lock') }} + restore-keys: | + python-deps- + + - name: Cache HuggingFace models + if: steps.backend-changes.outputs.backend == 'true' + uses: actions/cache@v5 + with: + path: ~/.cache/huggingface + key: hf-models-${{ env.EMBEDDING_MODEL }} + + - name: Install dependencies + if: steps.backend-changes.outputs.backend == 'true' + working-directory: surfsense_backend + run: uv sync + + - name: Run unit tests + if: steps.backend-changes.outputs.backend == 'true' + working-directory: surfsense_backend + run: uv run pytest -m unit + + integration-tests: + name: Integration Tests + runs-on: ubuntu-latest + if: github.event.pull_request.draft == false + env: + EMBEDDING_MODEL: sentence-transformers/all-MiniLM-L6-v2 + + services: + postgres: + image: pgvector/pgvector:pg17 + env: + POSTGRES_USER: postgres + POSTGRES_PASSWORD: postgres + POSTGRES_DB: surfsense_test + ports: + - 5432:5432 + options: >- + --health-cmd "pg_isready -U postgres -d surfsense_test" + --health-interval 10s + --health-timeout 5s + --health-retries 5 + + steps: + - name: Checkout code + uses: actions/checkout@v6 + + - name: Check if backend files changed + id: backend-changes + uses: dorny/paths-filter@v3 + with: + filters: | + backend: + - 'surfsense_backend/**' + + - name: Set up Python + if: steps.backend-changes.outputs.backend == 'true' + uses: actions/setup-python@v5 + with: + python-version: '3.12' + + - name: Install UV + if: steps.backend-changes.outputs.backend == 'true' + uses: astral-sh/setup-uv@v7 + + - name: Cache dependencies + if: steps.backend-changes.outputs.backend == 'true' + uses: actions/cache@v5 + with: + path: | + ~/.cache/uv + surfsense_backend/.venv + key: python-deps-${{ hashFiles('surfsense_backend/uv.lock') }} + restore-keys: | + python-deps- + + - name: Cache HuggingFace models + if: steps.backend-changes.outputs.backend == 'true' + uses: actions/cache@v5 + with: + path: ~/.cache/huggingface + key: hf-models-${{ env.EMBEDDING_MODEL }} + + - name: Install dependencies + if: steps.backend-changes.outputs.backend == 'true' + working-directory: surfsense_backend + run: uv sync + + - name: Run integration tests + if: steps.backend-changes.outputs.backend == 'true' + working-directory: surfsense_backend + env: + TEST_DATABASE_URL: postgresql+asyncpg://postgres:postgres@localhost:5432/surfsense_test + SECRET_KEY: ci-test-secret-key-not-for-production + ETL_SERVICE: DOCLING + run: uv run pytest -m integration + + test-gate: + name: Test Gate + runs-on: ubuntu-latest + needs: [unit-tests, integration-tests] + if: always() + + steps: + - name: Check all test jobs + run: | + if [[ "${{ needs.unit-tests.result }}" == "failure" || + "${{ needs.integration-tests.result }}" == "failure" ]]; then + echo "Backend tests failed" + exit 1 + else + echo "All backend tests passed" + fi diff --git a/.github/workflows/docker_build.yaml b/.github/workflows/docker_build.yaml index ff6c838d1..15b89198e 100644 --- a/.github/workflows/docker_build.yaml +++ b/.github/workflows/docker_build.yaml @@ -1,6 +1,13 @@ -name: Build and Push Docker Image +name: Build and Push Docker Images on: + push: + branches: + - main + - dev + paths: + - 'surfsense_backend/**' + - 'surfsense_web/**' workflow_dispatch: inputs: branch: @@ -8,6 +15,10 @@ on: required: false default: '' +concurrency: + group: docker-build + cancel-in-progress: false + permissions: contents: write packages: write @@ -28,33 +39,28 @@ jobs: - name: Read app version and calculate next Docker build version id: tag_version run: | - # Read version from pyproject.toml APP_VERSION=$(grep -E '^version = ' surfsense_backend/pyproject.toml | sed 's/version = "\(.*\)"/\1/') echo "App version from pyproject.toml: $APP_VERSION" - + if [ -z "$APP_VERSION" ]; then echo "Error: Could not read version from surfsense_backend/pyproject.toml" exit 1 fi - - # Fetch all tags + git fetch --tags - - # Find the latest docker build tag for this app version (format: APP_VERSION.BUILD_NUMBER) - # Tags follow pattern: 0.0.11.1, 0.0.11.2, etc. + LATEST_BUILD_TAG=$(git tag --list "${APP_VERSION}.*" --sort='-v:refname' | head -n 1) - + if [ -z "$LATEST_BUILD_TAG" ]; then echo "No previous Docker build tag found for version ${APP_VERSION}. Starting with ${APP_VERSION}.1" NEXT_VERSION="${APP_VERSION}.1" else echo "Latest Docker build tag found: $LATEST_BUILD_TAG" - # Extract the build number (4th component) BUILD_NUMBER=$(echo "$LATEST_BUILD_TAG" | rev | cut -d. -f1 | rev) NEXT_BUILD=$((BUILD_NUMBER + 1)) NEXT_VERSION="${APP_VERSION}.${NEXT_BUILD}" fi - + echo "Calculated next Docker version: $NEXT_VERSION" echo "next_version=$NEXT_VERSION" >> $GITHUB_OUTPUT @@ -78,67 +84,35 @@ jobs: git ls-remote --tags origin | grep "refs/tags/${{ steps.tag_version.outputs.next_version }}" || (echo "Tag push verification failed!" && exit 1) echo "Tag successfully pushed." - # Build for AMD64 on native x64 runner - build_amd64: - runs-on: ubuntu-latest + build: needs: tag_release + runs-on: ${{ matrix.os }} permissions: packages: write contents: read - outputs: - digest: ${{ steps.build.outputs.digest }} + strategy: + fail-fast: false + matrix: + platform: [linux/amd64, linux/arm64] + image: [backend, web] + include: + - platform: linux/amd64 + suffix: amd64 + os: ubuntu-latest + - platform: linux/arm64 + suffix: arm64 + os: ubuntu-24.04-arm + - image: backend + name: surfsense-backend + context: ./surfsense_backend + file: ./surfsense_backend/Dockerfile + - image: web + name: surfsense-web + context: ./surfsense_web + file: ./surfsense_web/Dockerfile env: - REGISTRY_IMAGE: ghcr.io/${{ github.repository_owner }}/surfsense - steps: - - name: Checkout code - uses: actions/checkout@v4 + REGISTRY_IMAGE: ghcr.io/${{ github.repository_owner }}/${{ matrix.name }} - - name: Set lowercase image name - id: image - run: echo "name=${REGISTRY_IMAGE,,}" >> $GITHUB_OUTPUT - - - name: Login to GitHub Container Registry - uses: docker/login-action@v3 - with: - registry: ghcr.io - username: ${{ github.repository_owner }} - password: ${{ secrets.GITHUB_TOKEN }} - - - name: Set up Docker Buildx - uses: docker/setup-buildx-action@v3 - - - name: Free up disk space - run: | - sudo rm -rf /usr/share/dotnet - sudo rm -rf /opt/ghc - sudo rm -rf /usr/local/share/boost - sudo rm -rf "$AGENT_TOOLSDIRECTORY" - docker system prune -af - - - name: Build and push AMD64 image - id: build - uses: docker/build-push-action@v5 - with: - context: . - file: ./Dockerfile.allinone - push: true - tags: ${{ steps.image.outputs.name }}:${{ needs.tag_release.outputs.new_tag }}-amd64 - platforms: linux/amd64 - cache-from: type=gha,scope=amd64 - cache-to: type=gha,mode=max,scope=amd64 - provenance: false - - # Build for ARM64 on native arm64 runner (no QEMU emulation!) - build_arm64: - runs-on: ubuntu-24.04-arm - needs: tag_release - permissions: - packages: write - contents: read - outputs: - digest: ${{ steps.build.outputs.digest }} - env: - REGISTRY_IMAGE: ghcr.io/${{ github.repository_owner }}/surfsense steps: - name: Checkout code uses: actions/checkout@v4 @@ -165,28 +139,41 @@ jobs: sudo rm -rf "$AGENT_TOOLSDIRECTORY" || true docker system prune -af - - name: Build and push ARM64 image + - name: Build and push ${{ matrix.name }} (${{ matrix.suffix }}) id: build - uses: docker/build-push-action@v5 + uses: docker/build-push-action@v6 with: - context: . - file: ./Dockerfile.allinone + context: ${{ matrix.context }} + file: ${{ matrix.file }} push: true - tags: ${{ steps.image.outputs.name }}:${{ needs.tag_release.outputs.new_tag }}-arm64 - platforms: linux/arm64 - cache-from: type=gha,scope=arm64 - cache-to: type=gha,mode=max,scope=arm64 + tags: ${{ steps.image.outputs.name }}:${{ needs.tag_release.outputs.new_tag }}-${{ matrix.suffix }} + platforms: ${{ matrix.platform }} + cache-from: type=gha,scope=${{ matrix.image }}-${{ matrix.suffix }} + cache-to: type=gha,mode=max,scope=${{ matrix.image }}-${{ matrix.suffix }} provenance: false + build-args: | + ${{ matrix.image == 'web' && 'NEXT_PUBLIC_FASTAPI_BACKEND_URL=__NEXT_PUBLIC_FASTAPI_BACKEND_URL__' || '' }} + ${{ matrix.image == 'web' && 'NEXT_PUBLIC_FASTAPI_BACKEND_AUTH_TYPE=__NEXT_PUBLIC_FASTAPI_BACKEND_AUTH_TYPE__' || '' }} + ${{ matrix.image == 'web' && 'NEXT_PUBLIC_ETL_SERVICE=__NEXT_PUBLIC_ETL_SERVICE__' || '' }} + ${{ matrix.image == 'web' && 'NEXT_PUBLIC_ELECTRIC_URL=__NEXT_PUBLIC_ELECTRIC_URL__' || '' }} + ${{ matrix.image == 'web' && 'NEXT_PUBLIC_ELECTRIC_AUTH_MODE=__NEXT_PUBLIC_ELECTRIC_AUTH_MODE__' || '' }} + ${{ matrix.image == 'web' && 'NEXT_PUBLIC_DEPLOYMENT_MODE=__NEXT_PUBLIC_DEPLOYMENT_MODE__' || '' }} - # Create multi-arch manifest combining both platform images create_manifest: runs-on: ubuntu-latest - needs: [tag_release, build_amd64, build_arm64] + needs: [tag_release, build] permissions: packages: write contents: read + strategy: + fail-fast: false + matrix: + include: + - name: surfsense-backend + - name: surfsense-web env: - REGISTRY_IMAGE: ghcr.io/${{ github.repository_owner }}/surfsense + REGISTRY_IMAGE: ghcr.io/${{ github.repository_owner }}/${{ matrix.name }} + steps: - name: Set lowercase image name id: image @@ -203,28 +190,31 @@ jobs: run: | VERSION_TAG="${{ needs.tag_release.outputs.new_tag }}" IMAGE="${{ steps.image.outputs.name }}" - - # Create manifest for version tag + APP_VERSION=$(echo "$VERSION_TAG" | rev | cut -d. -f2- | rev) + docker manifest create ${IMAGE}:${VERSION_TAG} \ ${IMAGE}:${VERSION_TAG}-amd64 \ ${IMAGE}:${VERSION_TAG}-arm64 - + docker manifest push ${IMAGE}:${VERSION_TAG} - - # Create/update latest tag if on default branch + if [[ "${{ github.ref }}" == "refs/heads/${{ github.event.repository.default_branch }}" ]] || [[ "${{ github.event.inputs.branch }}" == "${{ github.event.repository.default_branch }}" ]]; then + docker manifest create ${IMAGE}:${APP_VERSION} \ + ${IMAGE}:${VERSION_TAG}-amd64 \ + ${IMAGE}:${VERSION_TAG}-arm64 + + docker manifest push ${IMAGE}:${APP_VERSION} + docker manifest create ${IMAGE}:latest \ ${IMAGE}:${VERSION_TAG}-amd64 \ ${IMAGE}:${VERSION_TAG}-arm64 - + docker manifest push ${IMAGE}:latest fi - - name: Clean up architecture-specific tags (optional) - continue-on-error: true + - name: Summary run: | - # Note: GHCR doesn't support tag deletion via API easily - # The arch-specific tags will remain but users should use the main tags - echo "Multi-arch manifest created successfully!" - echo "Users should pull: ${{ steps.image.outputs.name }}:${{ needs.tag_release.outputs.new_tag }}" - echo "Or for latest: ${{ steps.image.outputs.name }}:latest" + echo "Multi-arch manifest created for ${{ matrix.name }}!" + echo "Versioned: ${{ steps.image.outputs.name }}:${{ needs.tag_release.outputs.new_tag }}" + echo "App version: ${{ steps.image.outputs.name }}:$(echo '${{ needs.tag_release.outputs.new_tag }}' | rev | cut -d. -f2- | rev)" + echo "Latest: ${{ steps.image.outputs.name }}:latest" diff --git a/.gitignore b/.gitignore index cb6d28b4e..559918a61 100644 --- a/.gitignore +++ b/.gitignore @@ -5,3 +5,4 @@ node_modules/ .ruff_cache/ .venv .pnpm-store +.DS_Store diff --git a/Dockerfile.allinone b/Dockerfile.allinone deleted file mode 100644 index e96618adc..000000000 --- a/Dockerfile.allinone +++ /dev/null @@ -1,285 +0,0 @@ -# SurfSense All-in-One Docker Image -# This image bundles PostgreSQL+pgvector, Redis, Electric SQL, Backend, and Frontend -# Usage: docker run -d -p 3000:3000 -p 8000:8000 -p 5133:5133 -v surfsense-data:/data --name surfsense ghcr.io/modsetter/surfsense:latest -# -# Included Services (all run locally by default): -# - PostgreSQL 14 + pgvector (vector database) -# - Redis (task queue) -# - Electric SQL (real-time sync) -# - Docling (document processing, CPU-only, OCR disabled) -# - Kokoro TTS (local text-to-speech for podcasts) -# - Faster-Whisper (local speech-to-text for audio files) -# - Playwright Chromium (web scraping) -# -# Note: This is the CPU-only version. A :cuda tagged image with GPU support -# will be available in the future for faster AI inference. - -# ==================== -# Stage 1: Get Electric SQL Binary -# ==================== -FROM electricsql/electric:latest AS electric-builder - -# ==================== -# Stage 2: Build Frontend -# ==================== -FROM node:20-alpine AS frontend-builder - -WORKDIR /app - -# Install pnpm -RUN corepack enable pnpm - -# Copy package files -COPY surfsense_web/package.json surfsense_web/pnpm-lock.yaml* ./ -COPY surfsense_web/source.config.ts ./ -COPY surfsense_web/content ./content - -# Install dependencies (skip postinstall which requires all source files) -RUN pnpm install --frozen-lockfile --ignore-scripts - -# Copy source -COPY surfsense_web/ ./ - -# Run fumadocs-mdx postinstall now that source files are available -RUN pnpm fumadocs-mdx - -# Build with placeholder values that will be replaced at runtime -# These unique strings allow runtime substitution via entrypoint script -ENV NEXT_PUBLIC_FASTAPI_BACKEND_URL=__NEXT_PUBLIC_FASTAPI_BACKEND_URL__ -ENV NEXT_PUBLIC_FASTAPI_BACKEND_AUTH_TYPE=__NEXT_PUBLIC_FASTAPI_BACKEND_AUTH_TYPE__ -ENV NEXT_PUBLIC_ETL_SERVICE=__NEXT_PUBLIC_ETL_SERVICE__ -ENV NEXT_PUBLIC_ELECTRIC_URL=__NEXT_PUBLIC_ELECTRIC_URL__ -ENV NEXT_PUBLIC_ELECTRIC_AUTH_MODE=__NEXT_PUBLIC_ELECTRIC_AUTH_MODE__ -ENV NEXT_PUBLIC_DEPLOYMENT_MODE=__NEXT_PUBLIC_DEPLOYMENT_MODE__ - -# Build -RUN pnpm run build - -# ==================== -# Stage 3: Runtime Image -# ==================== -FROM ubuntu:22.04 AS runtime - -# Prevent interactive prompts -ENV DEBIAN_FRONTEND=noninteractive - -# Install system dependencies -RUN apt-get update && apt-get install -y --no-install-recommends \ - # PostgreSQL - postgresql-14 \ - postgresql-contrib-14 \ - # Build tools for pgvector - build-essential \ - postgresql-server-dev-14 \ - git \ - # Redis - redis-server \ - # Node.js prerequisites - curl \ - ca-certificates \ - gnupg \ - # Backend dependencies - gcc \ - wget \ - unzip \ - dos2unix \ - # For PPAs - software-properties-common \ - # ============================ - # Local TTS (Kokoro) dependencies - # ============================ - espeak-ng \ - libespeak-ng1 \ - # ============================ - # Local STT (Faster-Whisper) dependencies - # ============================ - ffmpeg \ - # ============================ - # Audio processing (soundfile) - # ============================ - libsndfile1 \ - # ============================ - # Image/OpenCV dependencies (for Docling) - # ============================ - libgl1 \ - libglib2.0-0 \ - libsm6 \ - libxext6 \ - libxrender1 \ - # ============================ - # Playwright browser dependencies - # ============================ - libnspr4 \ - libnss3 \ - libatk1.0-0 \ - libatk-bridge2.0-0 \ - libcups2 \ - libxkbcommon0 \ - libatspi2.0-0 \ - libxcomposite1 \ - libxdamage1 \ - libxrandr2 \ - libgbm1 \ - libcairo2 \ - libpango-1.0-0 \ - && rm -rf /var/lib/apt/lists/* - -# Install Pandoc 3.x from GitHub (apt ships 2.9 which has broken table rendering). -RUN ARCH=$(dpkg --print-architecture) && \ - wget -qO /tmp/pandoc.deb "https://github.com/jgm/pandoc/releases/download/3.9/pandoc-3.9-1-${ARCH}.deb" && \ - dpkg -i /tmp/pandoc.deb && \ - rm /tmp/pandoc.deb - - -# Install Node.js 20.x (for running frontend) -RUN curl -fsSL https://deb.nodesource.com/setup_20.x | bash - \ - && apt-get install -y nodejs \ - && rm -rf /var/lib/apt/lists/* - -# Install Python 3.12 from deadsnakes PPA -RUN add-apt-repository ppa:deadsnakes/ppa -y \ - && apt-get update \ - && apt-get install -y --no-install-recommends \ - python3.12 \ - python3.12-venv \ - python3.12-dev \ - && rm -rf /var/lib/apt/lists/* - -# Set Python 3.12 as default -RUN update-alternatives --install /usr/bin/python python /usr/bin/python3.12 1 \ - && update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.12 1 - -# Install pip for Python 3.12 -RUN python3.12 -m ensurepip --upgrade \ - && python3.12 -m pip install --upgrade pip - -# Install supervisor via pip (system package incompatible with Python 3.12) -RUN pip install --no-cache-dir supervisor - -# Build and install pgvector -RUN cd /tmp \ - && git clone --branch v0.7.4 https://github.com/pgvector/pgvector.git \ - && cd pgvector \ - && make \ - && make install \ - && rm -rf /tmp/pgvector - -# Update certificates -RUN update-ca-certificates - -# Create data directories -RUN mkdir -p /data/postgres /data/redis /data/surfsense \ - && chown -R postgres:postgres /data/postgres - -# ==================== -# Copy Frontend Build -# ==================== -WORKDIR /app/frontend - -# Copy only the standalone build (not node_modules) -COPY --from=frontend-builder /app/.next/standalone ./ -COPY --from=frontend-builder /app/.next/static ./.next/static -COPY --from=frontend-builder /app/public ./public - -COPY surfsense_web/content/docs /app/surfsense_web/content/docs - -# ==================== -# Copy Electric SQL Release -# ==================== -COPY --from=electric-builder /app /app/electric-release - -# ==================== -# Setup Backend -# ==================== -WORKDIR /app/backend - -# Copy backend dependency files -COPY surfsense_backend/pyproject.toml surfsense_backend/uv.lock ./ - -# Install PyTorch CPU-only (Docling needs it but OCR is disabled, no GPU needed) -RUN pip install --no-cache-dir torch torchvision --index-url https://download.pytorch.org/whl/cpu - -# Install python dependencies -RUN pip install --no-cache-dir certifi pip-system-certs uv \ - && uv pip install --system --no-cache-dir -e . - -# Set SSL environment variables -RUN CERTIFI_PATH=$(python -c "import certifi; print(certifi.where())") \ - && echo "export SSL_CERT_FILE=$CERTIFI_PATH" >> /etc/profile.d/ssl.sh \ - && echo "export REQUESTS_CA_BUNDLE=$CERTIFI_PATH" >> /etc/profile.d/ssl.sh - -# Note: EasyOCR models NOT downloaded - OCR is disabled in docling_service.py -# GPU support will be added in a future :cuda tagged image - -# Install Playwright browsers -RUN pip install --no-cache-dir playwright \ - && playwright install chromium \ - && rm -rf /root/.cache/ms-playwright/ffmpeg* - -# Copy backend source -COPY surfsense_backend/ ./ - -# ==================== -# Configuration -# ==================== -WORKDIR /app - -# Copy supervisor configuration -COPY scripts/docker/supervisor-allinone.conf /etc/supervisor/conf.d/surfsense.conf - -# Copy entrypoint script -COPY scripts/docker/entrypoint-allinone.sh /app/entrypoint.sh -RUN dos2unix /app/entrypoint.sh && chmod +x /app/entrypoint.sh - -# PostgreSQL initialization script -COPY scripts/docker/init-postgres.sh /app/init-postgres.sh -RUN dos2unix /app/init-postgres.sh && chmod +x /app/init-postgres.sh - -# Clean up build dependencies to reduce image size -RUN apt-get purge -y build-essential postgresql-server-dev-14 \ - && apt-get autoremove -y \ - && rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/* - -# Environment variables with defaults -ENV POSTGRES_USER=surfsense -ENV POSTGRES_PASSWORD=surfsense -ENV POSTGRES_DB=surfsense -ENV DATABASE_URL=postgresql+asyncpg://surfsense:surfsense@localhost:5432/surfsense -ENV CELERY_BROKER_URL=redis://localhost:6379/0 -ENV CELERY_RESULT_BACKEND=redis://localhost:6379/0 -ENV CELERY_TASK_DEFAULT_QUEUE=surfsense -ENV PYTHONPATH=/app/backend -ENV NEXT_FRONTEND_URL=http://localhost:3000 -ENV AUTH_TYPE=LOCAL -ENV ETL_SERVICE=DOCLING -ENV EMBEDDING_MODEL=sentence-transformers/all-MiniLM-L6-v2 - -# Frontend configuration (can be overridden at runtime) -# These are injected into the Next.js build at container startup -ENV NEXT_PUBLIC_FASTAPI_BACKEND_URL=http://localhost:8000 -ENV NEXT_PUBLIC_FASTAPI_BACKEND_AUTH_TYPE=LOCAL -ENV NEXT_PUBLIC_ETL_SERVICE=DOCLING - -# Electric SQL configuration (ELECTRIC_DATABASE_URL is built dynamically by entrypoint from these values) -ENV ELECTRIC_DB_USER=electric -ENV ELECTRIC_DB_PASSWORD=electric_password -# Note: ELECTRIC_DATABASE_URL is NOT set here - entrypoint builds it dynamically from ELECTRIC_DB_USER/PASSWORD -ENV ELECTRIC_INSECURE=true -ENV ELECTRIC_WRITE_TO_PG_MODE=direct -ENV ELECTRIC_PORT=5133 -ENV PORT=5133 -ENV NEXT_PUBLIC_ELECTRIC_URL=http://localhost:5133 -ENV NEXT_PUBLIC_ELECTRIC_AUTH_MODE=insecure - -# Data volume -VOLUME ["/data"] - -# Expose ports (Frontend: 3000, Backend: 8000, Electric: 5133) -EXPOSE 3000 8000 5133 - -# Health check -HEALTHCHECK --interval=30s --timeout=10s --start-period=120s --retries=3 \ - CMD curl -f http://localhost:3000 || exit 1 - -# Run entrypoint -CMD ["/app/entrypoint.sh"] diff --git a/README.es.md b/README.es.md index 5472ad069..06dc7abbc 100644 --- a/README.es.md +++ b/README.es.md @@ -81,13 +81,21 @@ https://github.com/user-attachments/assets/a0a16566-6967-4374-ac51-9b3e07fbecd7 Ejecuta SurfSense en tu propia infraestructura para control total de datos y privacidad. -**Inicio Rápido (Docker en un solo comando):** +**Requisitos previos:** [Docker Desktop](https://www.docker.com/products/docker-desktop/) debe estar instalado y en ejecución. + +#### Para usuarios de Linux/MacOS: ```bash -docker run -d -p 3000:3000 -p 8000:8000 -p 5133:5133 -v surfsense-data:/data --name surfsense --restart unless-stopped ghcr.io/modsetter/surfsense:latest +curl -fsSL https://raw.githubusercontent.com/MODSetter/SurfSense/main/docker/scripts/install.sh | bash ``` -Después de iniciar, abre [http://localhost:3000](http://localhost:3000) en tu navegador. +#### Para usuarios de Windows: + +```powershell +irm https://raw.githubusercontent.com/MODSetter/SurfSense/main/docker/scripts/install.ps1 | iex +``` + +El script de instalación configura [Watchtower](https://github.com/nicholas-fedor/watchtower) automáticamente para actualizaciones diarias. Para omitirlo, agrega la bandera `--no-watchtower`. Para Docker Compose, instalación manual y otras opciones de despliegue, consulta la [documentación](https://www.surfsense.com/docs/). diff --git a/README.hi.md b/README.hi.md index d4388b616..22acebb8c 100644 --- a/README.hi.md +++ b/README.hi.md @@ -81,13 +81,21 @@ https://github.com/user-attachments/assets/a0a16566-6967-4374-ac51-9b3e07fbecd7 पूर्ण डेटा नियंत्रण और गोपनीयता के लिए SurfSense को अपने स्वयं के बुनियादी ढांचे पर चलाएं। -**त्वरित शुरुआत (Docker एक कमांड में):** +**आवश्यकताएँ:** [Docker Desktop](https://www.docker.com/products/docker-desktop/) इंस्टॉल और चालू होना चाहिए। + +#### Linux/MacOS उपयोगकर्ताओं के लिए: ```bash -docker run -d -p 3000:3000 -p 8000:8000 -p 5133:5133 -v surfsense-data:/data --name surfsense --restart unless-stopped ghcr.io/modsetter/surfsense:latest +curl -fsSL https://raw.githubusercontent.com/MODSetter/SurfSense/main/docker/scripts/install.sh | bash ``` -शुरू करने के बाद, अपने ब्राउज़र में [http://localhost:3000](http://localhost:3000) खोलें। +#### Windows उपयोगकर्ताओं के लिए: + +```powershell +irm https://raw.githubusercontent.com/MODSetter/SurfSense/main/docker/scripts/install.ps1 | iex +``` + +इंस्टॉल स्क्रिप्ट दैनिक ऑटो-अपडेट के लिए स्वचालित रूप से [Watchtower](https://github.com/nicholas-fedor/watchtower) सेटअप करती है। इसे छोड़ने के लिए, `--no-watchtower` फ्लैग जोड़ें। Docker Compose, मैनुअल इंस्टॉलेशन और अन्य डिप्लॉयमेंट विकल्पों के लिए, [डॉक्स](https://www.surfsense.com/docs/) देखें। diff --git a/README.md b/README.md index 9056c27f2..0ca61c746 100644 --- a/README.md +++ b/README.md @@ -81,21 +81,23 @@ https://github.com/user-attachments/assets/a0a16566-6967-4374-ac51-9b3e07fbecd7 Run SurfSense on your own infrastructure for full data control and privacy. -**Quick Start (Docker one-liner):** +**Prerequisites:** [Docker Desktop](https://www.docker.com/products/docker-desktop/) must be installed and running. + +#### For Linux/MacOS users: ```bash -docker run -d -p 3000:3000 -p 8000:8000 -p 5133:5133 -v surfsense-data:/data --name surfsense --restart unless-stopped ghcr.io/modsetter/surfsense:latest +curl -fsSL https://raw.githubusercontent.com/MODSetter/SurfSense/main/docker/scripts/install.sh | bash ``` -After starting, open [http://localhost:3000](http://localhost:3000) in your browser. - -**Update (Automatic updates with Watchtower):** +#### For Windows users: ```bash -docker run --rm -v /var/run/docker.sock:/var/run/docker.sock nickfedor/watchtower --run-once surfsense +irm https://raw.githubusercontent.com/MODSetter/SurfSense/main/docker/scripts/install.ps1 | iex ``` -For Docker Compose, manual installation, and other deployment options, check the [docs](https://www.surfsense.com/docs/). +The install script sets up [Watchtower](https://github.com/nicholas-fedor/watchtower) automatically for daily auto-updates. To skip it, add the `--no-watchtower` flag. + +For Docker Compose, manual installation, and other deployment options, see the [docs](https://www.surfsense.com/docs/). ### How to Realtime Collaborate (Beta) diff --git a/README.pt-BR.md b/README.pt-BR.md index 351cdb85b..e537cb37f 100644 --- a/README.pt-BR.md +++ b/README.pt-BR.md @@ -81,13 +81,21 @@ https://github.com/user-attachments/assets/a0a16566-6967-4374-ac51-9b3e07fbecd7 Execute o SurfSense na sua própria infraestrutura para controle total de dados e privacidade. -**Início Rápido (Docker em um único comando):** +**Pré-requisitos:** [Docker Desktop](https://www.docker.com/products/docker-desktop/) deve estar instalado e em execução. + +#### Para usuários de Linux/MacOS: ```bash -docker run -d -p 3000:3000 -p 8000:8000 -p 5133:5133 -v surfsense-data:/data --name surfsense --restart unless-stopped ghcr.io/modsetter/surfsense:latest +curl -fsSL https://raw.githubusercontent.com/MODSetter/SurfSense/main/docker/scripts/install.sh | bash ``` -Após iniciar, abra [http://localhost:3000](http://localhost:3000) no seu navegador. +#### Para usuários do Windows: + +```powershell +irm https://raw.githubusercontent.com/MODSetter/SurfSense/main/docker/scripts/install.ps1 | iex +``` + +O script de instalação configura o [Watchtower](https://github.com/nicholas-fedor/watchtower) automaticamente para atualizações diárias. Para pular, adicione a flag `--no-watchtower`. Para Docker Compose, instalação manual e outras opções de implantação, consulte a [documentação](https://www.surfsense.com/docs/). diff --git a/README.zh-CN.md b/README.zh-CN.md index 49ef64619..128a9780a 100644 --- a/README.zh-CN.md +++ b/README.zh-CN.md @@ -81,13 +81,21 @@ https://github.com/user-attachments/assets/a0a16566-6967-4374-ac51-9b3e07fbecd7 在您自己的基础设施上运行 SurfSense，实现完全的数据控制和隐私保护。 -**快速开始（Docker 一行命令）：** +**前置条件：** 需要安装并运行 [Docker Desktop](https://www.docker.com/products/docker-desktop/)。 + +#### Linux/MacOS 用户： ```bash -docker run -d -p 3000:3000 -p 8000:8000 -p 5133:5133 -v surfsense-data:/data --name surfsense --restart unless-stopped ghcr.io/modsetter/surfsense:latest +curl -fsSL https://raw.githubusercontent.com/MODSetter/SurfSense/main/docker/scripts/install.sh | bash ``` -启动后，在浏览器中打开 [http://localhost:3000](http://localhost:3000)。 +#### Windows 用户： + +```powershell +irm https://raw.githubusercontent.com/MODSetter/SurfSense/main/docker/scripts/install.ps1 | iex +``` + +安装脚本会自动配置 [Watchtower](https://github.com/nicholas-fedor/watchtower) 以实现每日自动更新。如需跳过，请添加 `--no-watchtower` 参数。 如需 Docker Compose、手动安装及其他部署方式，请查看[文档](https://www.surfsense.com/docs/)。 diff --git a/docker-compose.quickstart.yml b/docker-compose.quickstart.yml deleted file mode 100644 index ff72618b7..000000000 --- a/docker-compose.quickstart.yml +++ /dev/null @@ -1,80 +0,0 @@ -# SurfSense Quick Start Docker Compose -# -# This is a simplified docker-compose for quick local deployment using pre-built images. -# For production or customized deployments, use the main docker-compose.yml -# -# Usage: -# 1. (Optional) Create a .env file with your configuration -# 2. Run: docker compose -f docker-compose.quickstart.yml up -d -# 3. Access SurfSense at http://localhost:3000 -# -# All Environment Variables are Optional: -# - SECRET_KEY: JWT secret key (auto-generated and persisted if not set) -# - EMBEDDING_MODEL: Embedding model to use (default: sentence-transformers/all-MiniLM-L6-v2) -# - ETL_SERVICE: Document parsing service - DOCLING, UNSTRUCTURED, or LLAMACLOUD (default: DOCLING) -# - TTS_SERVICE: Text-to-speech service for podcasts (default: local/kokoro) -# - STT_SERVICE: Speech-to-text service with model size (default: local/base) -# - FIRECRAWL_API_KEY: For web crawling features - -version: "3.8" - -services: - # All-in-one SurfSense container - surfsense: - image: ghcr.io/modsetter/surfsense:latest - container_name: surfsense - ports: - - "${FRONTEND_PORT:-3000}:3000" - - "${BACKEND_PORT:-8000}:8000" - volumes: - - surfsense-data:/data - environment: - # Authentication (auto-generated if not set) - - SECRET_KEY=${SECRET_KEY:-} - - # Auth Configuration - - AUTH_TYPE=${AUTH_TYPE:-LOCAL} - - GOOGLE_OAUTH_CLIENT_ID=${GOOGLE_OAUTH_CLIENT_ID:-} - - GOOGLE_OAUTH_CLIENT_SECRET=${GOOGLE_OAUTH_CLIENT_SECRET:-} - - # AI/ML Configuration - - EMBEDDING_MODEL=${EMBEDDING_MODEL:-sentence-transformers/all-MiniLM-L6-v2} - - RERANKERS_ENABLED=${RERANKERS_ENABLED:-FALSE} - - RERANKERS_MODEL_NAME=${RERANKERS_MODEL_NAME:-} - - RERANKERS_MODEL_TYPE=${RERANKERS_MODEL_TYPE:-} - - # Document Processing - - ETL_SERVICE=${ETL_SERVICE:-DOCLING} - - UNSTRUCTURED_API_KEY=${UNSTRUCTURED_API_KEY:-} - - LLAMA_CLOUD_API_KEY=${LLAMA_CLOUD_API_KEY:-} - - # Audio Services - - TTS_SERVICE=${TTS_SERVICE:-local/kokoro} - - TTS_SERVICE_API_KEY=${TTS_SERVICE_API_KEY:-} - - STT_SERVICE=${STT_SERVICE:-local/base} - - STT_SERVICE_API_KEY=${STT_SERVICE_API_KEY:-} - - # Web Crawling - - FIRECRAWL_API_KEY=${FIRECRAWL_API_KEY:-} - - # Optional Features - - REGISTRATION_ENABLED=${REGISTRATION_ENABLED:-TRUE} - - SCHEDULE_CHECKER_INTERVAL=${SCHEDULE_CHECKER_INTERVAL:-1m} - - # LangSmith Observability (optional) - - LANGSMITH_TRACING=${LANGSMITH_TRACING:-false} - - LANGSMITH_ENDPOINT=${LANGSMITH_ENDPOINT:-} - - LANGSMITH_API_KEY=${LANGSMITH_API_KEY:-} - - LANGSMITH_PROJECT=${LANGSMITH_PROJECT:-} - restart: unless-stopped - healthcheck: - test: ["CMD", "curl", "-f", "http://localhost:3000", "&&", "curl", "-f", "http://localhost:8000/docs"] - interval: 30s - timeout: 10s - retries: 3 - start_period: 120s - -volumes: - surfsense-data: - name: surfsense-data - diff --git a/docker-compose.yml b/docker-compose.yml deleted file mode 100644 index a94cea2e5..000000000 --- a/docker-compose.yml +++ /dev/null @@ -1,167 +0,0 @@ -version: "3.8" - -services: - db: - image: ankane/pgvector:latest - ports: - - "${POSTGRES_PORT:-5432}:5432" - volumes: - - postgres_data:/var/lib/postgresql/data - - ./scripts/docker/postgresql.conf:/etc/postgresql/postgresql.conf:ro - - ./scripts/docker/init-electric-user.sh:/docker-entrypoint-initdb.d/init-electric-user.sh:ro - environment: - - POSTGRES_USER=${POSTGRES_USER:-postgres} - - POSTGRES_PASSWORD=${POSTGRES_PASSWORD:-postgres} - - POSTGRES_DB=${POSTGRES_DB:-surfsense} - - ELECTRIC_DB_USER=${ELECTRIC_DB_USER:-electric} - - ELECTRIC_DB_PASSWORD=${ELECTRIC_DB_PASSWORD:-electric_password} - command: postgres -c config_file=/etc/postgresql/postgresql.conf - - pgadmin: - image: dpage/pgadmin4 - ports: - - "${PGADMIN_PORT:-5050}:80" - environment: - - PGADMIN_DEFAULT_EMAIL=${PGADMIN_DEFAULT_EMAIL:-admin@surfsense.com} - - PGADMIN_DEFAULT_PASSWORD=${PGADMIN_DEFAULT_PASSWORD:-surfsense} - volumes: - - pgadmin_data:/var/lib/pgadmin - depends_on: - - db - - redis: - image: redis:7-alpine - ports: - - "${REDIS_PORT:-6379}:6379" - volumes: - - redis_data:/data - command: redis-server --appendonly yes - - backend: - build: ./surfsense_backend - # image: ghcr.io/modsetter/surfsense_backend:latest - ports: - - "${BACKEND_PORT:-8000}:8000" - volumes: - - ./surfsense_backend/app:/app/app - - shared_temp:/tmp - # Uncomment and edit the line below to enable Obsidian vault indexing - # - /path/to/your/obsidian/vault:/obsidian-vault:ro - env_file: - - ./surfsense_backend/.env - environment: - - DATABASE_URL=postgresql+asyncpg://${POSTGRES_USER:-postgres}:${POSTGRES_PASSWORD:-postgres}@db:5432/${POSTGRES_DB:-surfsense} - - CELERY_BROKER_URL=redis://redis:${REDIS_PORT:-6379}/0 - - CELERY_RESULT_BACKEND=redis://redis:${REDIS_PORT:-6379}/0 - - REDIS_APP_URL=redis://redis:${REDIS_PORT:-6379}/0 - # Queue name isolation - prevents task collision if Redis is shared with other apps - - CELERY_TASK_DEFAULT_QUEUE=surfsense - - PYTHONPATH=/app - - UVICORN_LOOP=asyncio - - UNSTRUCTURED_HAS_PATCHED_LOOP=1 - - LANGCHAIN_TRACING_V2=false - - LANGSMITH_TRACING=false - - ELECTRIC_DB_USER=${ELECTRIC_DB_USER:-electric} - - ELECTRIC_DB_PASSWORD=${ELECTRIC_DB_PASSWORD:-electric_password} - - AUTH_TYPE=${AUTH_TYPE:-LOCAL} - - NEXT_FRONTEND_URL=${NEXT_FRONTEND_URL:-http://localhost:3000} - depends_on: - - db - - redis - - # Run these services separately in production - # celery_worker: - # build: ./surfsense_backend - # # image: ghcr.io/modsetter/surfsense_backend:latest - # command: celery -A app.celery_app worker --loglevel=info --concurrency=1 --pool=solo - # volumes: - # - ./surfsense_backend:/app - # - shared_temp:/tmp - # env_file: - # - ./surfsense_backend/.env - # environment: - # - DATABASE_URL=postgresql+asyncpg://${POSTGRES_USER:-postgres}:${POSTGRES_PASSWORD:-postgres}@db:5432/${POSTGRES_DB:-surfsense} - # - CELERY_BROKER_URL=redis://redis:${REDIS_PORT:-6379}/0 - # - CELERY_RESULT_BACKEND=redis://redis:${REDIS_PORT:-6379}/0 - # - PYTHONPATH=/app - # depends_on: - # - db - # - redis - # - backend - - # celery_beat: - # build: ./surfsense_backend - # # image: ghcr.io/modsetter/surfsense_backend:latest - # command: celery -A app.celery_app beat --loglevel=info - # volumes: - # - ./surfsense_backend:/app - # - shared_temp:/tmp - # env_file: - # - ./surfsense_backend/.env - # environment: - # - DATABASE_URL=postgresql+asyncpg://${POSTGRES_USER:-postgres}:${POSTGRES_PASSWORD:-postgres}@db:5432/${POSTGRES_DB:-surfsense} - # - CELERY_BROKER_URL=redis://redis:${REDIS_PORT:-6379}/0 - # - CELERY_RESULT_BACKEND=redis://redis:${REDIS_PORT:-6379}/0 - # - PYTHONPATH=/app - # depends_on: - # - db - # - redis - # - celery_worker - - # flower: - # build: ./surfsense_backend - # # image: ghcr.io/modsetter/surfsense_backend:latest - # command: celery -A app.celery_app flower --port=5555 - # ports: - # - "${FLOWER_PORT:-5555}:5555" - # env_file: - # - ./surfsense_backend/.env - # environment: - # - CELERY_BROKER_URL=redis://redis:${REDIS_PORT:-6379}/0 - # - CELERY_RESULT_BACKEND=redis://redis:${REDIS_PORT:-6379}/0 - # - PYTHONPATH=/app - # depends_on: - # - redis - # - celery_worker - - electric: - image: electricsql/electric:latest - ports: - - "${ELECTRIC_PORT:-5133}:3000" - environment: - - DATABASE_URL=${ELECTRIC_DATABASE_URL:-postgresql://${ELECTRIC_DB_USER:-electric}:${ELECTRIC_DB_PASSWORD:-electric_password}@${POSTGRES_HOST:-db}:${POSTGRES_PORT:-5432}/${POSTGRES_DB:-surfsense}?sslmode=disable} - - ELECTRIC_INSECURE=true - - ELECTRIC_WRITE_TO_PG_MODE=direct - restart: unless-stopped - # depends_on: - # - db - healthcheck: - test: ["CMD", "curl", "-f", "http://localhost:3000/v1/health"] - interval: 10s - timeout: 5s - retries: 5 - - frontend: - build: - context: ./surfsense_web - # image: ghcr.io/modsetter/surfsense_ui:latest - args: - NEXT_PUBLIC_FASTAPI_BACKEND_URL: ${NEXT_PUBLIC_FASTAPI_BACKEND_URL:-http://localhost:8000} - NEXT_PUBLIC_FASTAPI_BACKEND_AUTH_TYPE: ${NEXT_PUBLIC_FASTAPI_BACKEND_AUTH_TYPE:-LOCAL} - NEXT_PUBLIC_ETL_SERVICE: ${NEXT_PUBLIC_ETL_SERVICE:-DOCLING} - ports: - - "${FRONTEND_PORT:-3000}:3000" - env_file: - - ./surfsense_web/.env - environment: - - NEXT_PUBLIC_ELECTRIC_URL=${NEXT_PUBLIC_ELECTRIC_URL:-http://localhost:5133} - - NEXT_PUBLIC_ELECTRIC_AUTH_MODE=insecure - depends_on: - - backend - - electric - -volumes: - postgres_data: - pgadmin_data: - redis_data: - shared_temp: diff --git a/docker/.env.example b/docker/.env.example new file mode 100644 index 000000000..7025cac52 --- /dev/null +++ b/docker/.env.example @@ -0,0 +1,256 @@ +# ============================================================================== +# SurfSense Docker Configuration +# ============================================================================== +# Database, Redis, and internal service wiring are handled automatically. +# ============================================================================== + +# SurfSense version (use "latest", a clean version like "0.0.14", or a specific build like "0.0.14.1") +SURFSENSE_VERSION=latest + +# ------------------------------------------------------------------------------ +# Core Settings +# ------------------------------------------------------------------------------ + +# REQUIRED: Generate a secret key with: openssl rand -base64 32 +SECRET_KEY=replace_me_with_a_random_string + +# Auth type: LOCAL (email/password) or GOOGLE (OAuth) +AUTH_TYPE=LOCAL + +# Allow new user registrations (TRUE or FALSE) +# REGISTRATION_ENABLED=TRUE + +# Document parsing service: DOCLING, UNSTRUCTURED, or LLAMACLOUD +ETL_SERVICE=DOCLING + +# Embedding model for vector search +# Local: sentence-transformers/all-MiniLM-L6-v2 +# OpenAI: openai://text-embedding-ada-002 (set OPENAI_API_KEY below) +# Cohere: cohere://embed-english-light-v3.0 (set COHERE_API_KEY below) +EMBEDDING_MODEL=sentence-transformers/all-MiniLM-L6-v2 + +# ------------------------------------------------------------------------------ +# Ports (change to avoid conflicts with other services on your machine) +# ------------------------------------------------------------------------------ + +# BACKEND_PORT=8000 +# FRONTEND_PORT=3000 +# ELECTRIC_PORT=5133 +# FLOWER_PORT=5555 + +# ============================================================================== +# DEV COMPOSE ONLY (docker-compose.dev.yml) +# You only need them only if you are running `docker-compose.dev.yml`. +# ============================================================================== + +# -- pgAdmin (database GUI) -- +# PGADMIN_PORT=5050 +# PGADMIN_DEFAULT_EMAIL=admin@surfsense.com +# PGADMIN_DEFAULT_PASSWORD=surfsense + +# -- Redis exposed port (dev only; Redis is internal-only in prod) -- +# REDIS_PORT=6379 + +# -- Frontend Build Args -- +# In dev, the frontend is built from source and these are passed as build args. +# In prod, they are automatically derived from AUTH_TYPE, ETL_SERVICE, and the port settings above. +# NEXT_PUBLIC_FASTAPI_BACKEND_AUTH_TYPE=LOCAL +# NEXT_PUBLIC_ETL_SERVICE=DOCLING +# NEXT_PUBLIC_DEPLOYMENT_MODE=self-hosted +# NEXT_PUBLIC_ELECTRIC_AUTH_MODE=insecure + +# ------------------------------------------------------------------------------ +# Custom Domain / Reverse Proxy +# ------------------------------------------------------------------------------ +# ONLY set these if you are serving SurfSense on a real domain via a reverse +# proxy (e.g. Caddy, Nginx, Cloudflare Tunnel). +# For standard localhost deployments, leave all of these commented out — +# they are automatically derived from the port settings above. +# +# NEXT_FRONTEND_URL=https://app.yourdomain.com +# BACKEND_URL=https://api.yourdomain.com +# NEXT_PUBLIC_FASTAPI_BACKEND_URL=https://api.yourdomain.com +# NEXT_PUBLIC_ELECTRIC_URL=https://electric.yourdomain.com + + +# ------------------------------------------------------------------------------ +# Database (defaults work out of the box, change for security) +# ------------------------------------------------------------------------------ + +# DB_USER=surfsense +# DB_PASSWORD=surfsense +# DB_NAME=surfsense +# DB_HOST=db +# DB_PORT=5432 + +# SSL mode for database connections: disable, require, verify-ca, verify-full +# DB_SSLMODE=disable + +# Full DATABASE_URL override — when set, takes precedence over the individual +# DB_USER / DB_PASSWORD / DB_NAME / DB_HOST / DB_PORT settings above. +# Use this for managed databases (AWS RDS, GCP Cloud SQL, Supabase, etc.) +# DATABASE_URL=postgresql+asyncpg://user:password@your-rds-host:5432/surfsense?sslmode=require + +# ------------------------------------------------------------------------------ +# Redis (defaults work out of the box) +# ------------------------------------------------------------------------------ +# Full Redis URL override for Celery broker, result backend, and app cache. +# Use this for managed Redis (AWS ElastiCache, Redis Cloud, etc.) +# Supports auth: redis://:password@host:port/0 +# Supports TLS: rediss://:password@host:6380/0 +# REDIS_URL=redis://redis:6379/0 + +# ------------------------------------------------------------------------------ +# Electric SQL (real-time sync credentials) +# ------------------------------------------------------------------------------ +# These must match on the db, backend, and electric services. +# Change for security; defaults work out of the box. + +# ELECTRIC_DB_USER=electric +# ELECTRIC_DB_PASSWORD=electric_password +# Full override for the Electric → Postgres connection URL. +# Leave commented out to use the Docker-managed `db` container (default). +# Uncomment and set `db` to `host.docker.internal` when pointing Electric at a local Postgres instance (e.g. Postgres.app on macOS): +# ELECTRIC_DATABASE_URL=postgresql://electric:electric_password@db:5432/surfsense?sslmode=disable + +# ------------------------------------------------------------------------------ +# TTS & STT (Text-to-Speech / Speech-to-Text) +# ------------------------------------------------------------------------------ + +# Local Kokoro TTS (default) or LiteLLM provider +TTS_SERVICE=local/kokoro +# TTS_SERVICE_API_KEY= +# TTS_SERVICE_API_BASE= + +# Local Faster-Whisper STT: local/MODEL_SIZE (tiny, base, small, medium, large-v3) +STT_SERVICE=local/base +# Or use LiteLLM: openai/whisper-1 +# STT_SERVICE_API_KEY= +# STT_SERVICE_API_BASE= + +# ------------------------------------------------------------------------------ +# Rerankers (optional, disabled by default) +# ------------------------------------------------------------------------------ + +# RERANKERS_ENABLED=TRUE +# RERANKERS_MODEL_NAME=ms-marco-MiniLM-L-12-v2 +# RERANKERS_MODEL_TYPE=flashrank + +# ------------------------------------------------------------------------------ +# Google OAuth (only if AUTH_TYPE=GOOGLE) +# ------------------------------------------------------------------------------ + +# GOOGLE_OAUTH_CLIENT_ID= +# GOOGLE_OAUTH_CLIENT_SECRET= + +# ------------------------------------------------------------------------------ +# Connector OAuth Keys (uncomment connectors you want to use) +# ------------------------------------------------------------------------------ + +# -- Google Connectors -- +# GOOGLE_CALENDAR_REDIRECT_URI=http://localhost:8000/api/v1/auth/google/calendar/connector/callback +# GOOGLE_GMAIL_REDIRECT_URI=http://localhost:8000/api/v1/auth/google/gmail/connector/callback +# GOOGLE_DRIVE_REDIRECT_URI=http://localhost:8000/api/v1/auth/google/drive/connector/callback + +# -- Notion -- +# NOTION_CLIENT_ID= +# NOTION_CLIENT_SECRET= +# NOTION_REDIRECT_URI=http://localhost:8000/api/v1/auth/notion/connector/callback + +# -- Slack -- +# SLACK_CLIENT_ID= +# SLACK_CLIENT_SECRET= +# SLACK_REDIRECT_URI=http://localhost:8000/api/v1/auth/slack/connector/callback + +# -- Discord -- +# DISCORD_CLIENT_ID= +# DISCORD_CLIENT_SECRET= +# DISCORD_REDIRECT_URI=http://localhost:8000/api/v1/auth/discord/connector/callback +# DISCORD_BOT_TOKEN= + +# -- Atlassian (Jira & Confluence) -- +# ATLASSIAN_CLIENT_ID= +# ATLASSIAN_CLIENT_SECRET= +# JIRA_REDIRECT_URI=http://localhost:8000/api/v1/auth/jira/connector/callback +# CONFLUENCE_REDIRECT_URI=http://localhost:8000/api/v1/auth/confluence/connector/callback + +# -- Linear -- +# LINEAR_CLIENT_ID= +# LINEAR_CLIENT_SECRET= +# LINEAR_REDIRECT_URI=http://localhost:8000/api/v1/auth/linear/connector/callback + +# -- ClickUp -- +# CLICKUP_CLIENT_ID= +# CLICKUP_CLIENT_SECRET= +# CLICKUP_REDIRECT_URI=http://localhost:8000/api/v1/auth/clickup/connector/callback + +# -- Airtable -- +# AIRTABLE_CLIENT_ID= +# AIRTABLE_CLIENT_SECRET= +# AIRTABLE_REDIRECT_URI=http://localhost:8000/api/v1/auth/airtable/connector/callback + +# -- Microsoft Teams -- +# TEAMS_CLIENT_ID= +# TEAMS_CLIENT_SECRET= +# TEAMS_REDIRECT_URI=http://localhost:8000/api/v1/auth/teams/connector/callback + +# -- Composio -- +# COMPOSIO_API_KEY= +# COMPOSIO_ENABLED=TRUE +# COMPOSIO_REDIRECT_URI=http://localhost:8000/api/v1/auth/composio/connector/callback + +# ------------------------------------------------------------------------------ +# Daytona Sandbox (optional — cloud code execution for the deep agent) +# ------------------------------------------------------------------------------ +# Set DAYTONA_SANDBOX_ENABLED=TRUE and provide credentials to give the agent +# an isolated code execution environment via the Daytona cloud API. +# DAYTONA_SANDBOX_ENABLED=FALSE +# DAYTONA_API_KEY= +# DAYTONA_API_URL=https://app.daytona.io/api +# DAYTONA_TARGET=us + +# ------------------------------------------------------------------------------ +# External API Keys (optional) +# ------------------------------------------------------------------------------ + +# Firecrawl (web scraping) +# FIRECRAWL_API_KEY= + +# Unstructured (if ETL_SERVICE=UNSTRUCTURED) +# UNSTRUCTURED_API_KEY= + +# LlamaCloud (if ETL_SERVICE=LLAMACLOUD) +# LLAMA_CLOUD_API_KEY= + +# ------------------------------------------------------------------------------ +# Observability (optional) +# ------------------------------------------------------------------------------ + +# LANGSMITH_TRACING=true +# LANGSMITH_ENDPOINT=https://api.smith.langchain.com +# LANGSMITH_API_KEY= +# LANGSMITH_PROJECT=surfsense + +# ------------------------------------------------------------------------------ +# Advanced (optional) +# ------------------------------------------------------------------------------ + +# Periodic connector sync interval (default: 5m) +# SCHEDULE_CHECKER_INTERVAL=5m + +# JWT token lifetimes +# ACCESS_TOKEN_LIFETIME_SECONDS=86400 +# REFRESH_TOKEN_LIFETIME_SECONDS=1209600 + +# Pages limit per user for ETL (default: unlimited) +# PAGES_LIMIT=500 + +# Connector indexing lock TTL in seconds (default: 28800 = 8 hours) +# CONNECTOR_INDEXING_LOCK_TTL_SECONDS=28800 + +# Residential proxy for web crawling +# RESIDENTIAL_PROXY_USERNAME= +# RESIDENTIAL_PROXY_PASSWORD= +# RESIDENTIAL_PROXY_HOSTNAME= +# RESIDENTIAL_PROXY_LOCATION= +# RESIDENTIAL_PROXY_TYPE=1 diff --git a/docker/docker-compose.dev.yml b/docker/docker-compose.dev.yml new file mode 100644 index 000000000..b76f26b2d --- /dev/null +++ b/docker/docker-compose.dev.yml @@ -0,0 +1,206 @@ +# ============================================================================= +# SurfSense — Development Docker Compose +# ============================================================================= +# Usage (from repo root): +# docker compose -f docker/docker-compose.dev.yml up --build +# +# This file builds from source and includes dev tools like pgAdmin. +# For production with prebuilt images, use docker/docker-compose.yml instead. +# ============================================================================= + +name: surfsense + +services: + db: + image: pgvector/pgvector:pg17 + ports: + - "${POSTGRES_PORT:-5432}:5432" + volumes: + - postgres_data:/var/lib/postgresql/data + - ./postgresql.conf:/etc/postgresql/postgresql.conf:ro + - ./scripts/init-electric-user.sh:/docker-entrypoint-initdb.d/init-electric-user.sh:ro + environment: + - POSTGRES_USER=${DB_USER:-postgres} + - POSTGRES_PASSWORD=${DB_PASSWORD:-postgres} + - POSTGRES_DB=${DB_NAME:-surfsense} + - ELECTRIC_DB_USER=${ELECTRIC_DB_USER:-electric} + - ELECTRIC_DB_PASSWORD=${ELECTRIC_DB_PASSWORD:-electric_password} + command: postgres -c config_file=/etc/postgresql/postgresql.conf + healthcheck: + test: ["CMD-SHELL", "pg_isready -U ${DB_USER:-postgres} -d ${DB_NAME:-surfsense}"] + interval: 10s + timeout: 5s + retries: 5 + + pgadmin: + image: dpage/pgadmin4 + ports: + - "${PGADMIN_PORT:-5050}:80" + environment: + - PGADMIN_DEFAULT_EMAIL=${PGADMIN_DEFAULT_EMAIL:-admin@surfsense.com} + - PGADMIN_DEFAULT_PASSWORD=${PGADMIN_DEFAULT_PASSWORD:-surfsense} + volumes: + - pgadmin_data:/var/lib/pgadmin + depends_on: + - db + + redis: + image: redis:8-alpine + ports: + - "${REDIS_PORT:-6379}:6379" + volumes: + - redis_data:/data + command: redis-server --appendonly yes + healthcheck: + test: ["CMD", "redis-cli", "ping"] + interval: 10s + timeout: 5s + retries: 5 + + backend: + build: ../surfsense_backend + ports: + - "${BACKEND_PORT:-8000}:8000" + volumes: + - ../surfsense_backend/app:/app/app + - shared_temp:/shared_tmp + env_file: + - ../surfsense_backend/.env + environment: + - DATABASE_URL=${DATABASE_URL:-postgresql+asyncpg://${DB_USER:-postgres}:${DB_PASSWORD:-postgres}@${DB_HOST:-db}:${DB_PORT:-5432}/${DB_NAME:-surfsense}} + - CELERY_BROKER_URL=${REDIS_URL:-redis://redis:6379/0} + - CELERY_RESULT_BACKEND=${REDIS_URL:-redis://redis:6379/0} + - REDIS_APP_URL=${REDIS_URL:-redis://redis:6379/0} + - CELERY_TASK_DEFAULT_QUEUE=surfsense + - PYTHONPATH=/app + - UVICORN_LOOP=asyncio + - UNSTRUCTURED_HAS_PATCHED_LOOP=1 + - LANGCHAIN_TRACING_V2=false + - LANGSMITH_TRACING=false + - ELECTRIC_DB_USER=${ELECTRIC_DB_USER:-electric} + - ELECTRIC_DB_PASSWORD=${ELECTRIC_DB_PASSWORD:-electric_password} + - AUTH_TYPE=${AUTH_TYPE:-LOCAL} + - NEXT_FRONTEND_URL=${NEXT_FRONTEND_URL:-http://localhost:3000} + # Daytona Sandbox – uncomment and set credentials to enable cloud code execution + # - DAYTONA_SANDBOX_ENABLED=TRUE + # - DAYTONA_API_KEY=${DAYTONA_API_KEY:-} + # - DAYTONA_API_URL=${DAYTONA_API_URL:-https://app.daytona.io/api} + # - DAYTONA_TARGET=${DAYTONA_TARGET:-us} + - SERVICE_ROLE=api + depends_on: + db: + condition: service_healthy + redis: + condition: service_healthy + healthcheck: + test: ["CMD", "curl", "-f", "http://localhost:8000/health"] + interval: 15s + timeout: 5s + retries: 30 + start_period: 200s + + celery_worker: + build: ../surfsense_backend + volumes: + - ../surfsense_backend/app:/app/app + - shared_temp:/shared_tmp + env_file: + - ../surfsense_backend/.env + environment: + - DATABASE_URL=${DATABASE_URL:-postgresql+asyncpg://${DB_USER:-postgres}:${DB_PASSWORD:-postgres}@${DB_HOST:-db}:${DB_PORT:-5432}/${DB_NAME:-surfsense}} + - CELERY_BROKER_URL=${REDIS_URL:-redis://redis:6379/0} + - CELERY_RESULT_BACKEND=${REDIS_URL:-redis://redis:6379/0} + - REDIS_APP_URL=${REDIS_URL:-redis://redis:6379/0} + - CELERY_TASK_DEFAULT_QUEUE=surfsense + - PYTHONPATH=/app + - ELECTRIC_DB_USER=${ELECTRIC_DB_USER:-electric} + - ELECTRIC_DB_PASSWORD=${ELECTRIC_DB_PASSWORD:-electric_password} + - SERVICE_ROLE=worker + depends_on: + db: + condition: service_healthy + redis: + condition: service_healthy + backend: + condition: service_healthy + + celery_beat: + build: ../surfsense_backend + env_file: + - ../surfsense_backend/.env + environment: + - DATABASE_URL=${DATABASE_URL:-postgresql+asyncpg://${DB_USER:-postgres}:${DB_PASSWORD:-postgres}@${DB_HOST:-db}:${DB_PORT:-5432}/${DB_NAME:-surfsense}} + - CELERY_BROKER_URL=${REDIS_URL:-redis://redis:6379/0} + - CELERY_RESULT_BACKEND=${REDIS_URL:-redis://redis:6379/0} + - CELERY_TASK_DEFAULT_QUEUE=surfsense + - PYTHONPATH=/app + - SERVICE_ROLE=beat + depends_on: + db: + condition: service_healthy + redis: + condition: service_healthy + celery_worker: + condition: service_started + + # flower: + # build: ../surfsense_backend + # ports: + # - "${FLOWER_PORT:-5555}:5555" + # env_file: + # - ../surfsense_backend/.env + # environment: + # - CELERY_BROKER_URL=${REDIS_URL:-redis://redis:6379/0} + # - CELERY_RESULT_BACKEND=${REDIS_URL:-redis://redis:6379/0} + # - PYTHONPATH=/app + # command: celery -A app.celery_app flower --port=5555 + # depends_on: + # - redis + # - celery_worker + + electric: + image: electricsql/electric:1.4.10 + ports: + - "${ELECTRIC_PORT:-5133}:3000" + # depends_on: + # - db + environment: + - DATABASE_URL=${ELECTRIC_DATABASE_URL:-postgresql://${ELECTRIC_DB_USER:-electric}:${ELECTRIC_DB_PASSWORD:-electric_password}@${DB_HOST:-db}:${DB_PORT:-5432}/${DB_NAME:-surfsense}?sslmode=${DB_SSLMODE:-disable}} + - ELECTRIC_INSECURE=true + - ELECTRIC_WRITE_TO_PG_MODE=direct + restart: unless-stopped + healthcheck: + test: ["CMD", "curl", "-f", "http://localhost:3000/v1/health"] + interval: 10s + timeout: 5s + retries: 5 + + frontend: + build: + context: ../surfsense_web + args: + NEXT_PUBLIC_FASTAPI_BACKEND_URL: ${NEXT_PUBLIC_FASTAPI_BACKEND_URL:-http://localhost:8000} + NEXT_PUBLIC_FASTAPI_BACKEND_AUTH_TYPE: ${NEXT_PUBLIC_FASTAPI_BACKEND_AUTH_TYPE:-LOCAL} + NEXT_PUBLIC_ETL_SERVICE: ${NEXT_PUBLIC_ETL_SERVICE:-DOCLING} + NEXT_PUBLIC_ELECTRIC_URL: ${NEXT_PUBLIC_ELECTRIC_URL:-http://localhost:5133} + NEXT_PUBLIC_ELECTRIC_AUTH_MODE: ${NEXT_PUBLIC_ELECTRIC_AUTH_MODE:-insecure} + NEXT_PUBLIC_DEPLOYMENT_MODE: ${NEXT_PUBLIC_DEPLOYMENT_MODE:-self-hosted} + ports: + - "${FRONTEND_PORT:-3000}:3000" + env_file: + - ../surfsense_web/.env + depends_on: + backend: + condition: service_healthy + electric: + condition: service_healthy + +volumes: + postgres_data: + name: surfsense-postgres + pgadmin_data: + name: surfsense-pgadmin + redis_data: + name: surfsense-redis + shared_temp: + name: surfsense-shared-temp diff --git a/docker/docker-compose.yml b/docker/docker-compose.yml new file mode 100644 index 000000000..9fca4dfb5 --- /dev/null +++ b/docker/docker-compose.yml @@ -0,0 +1,195 @@ +# ============================================================================= +# SurfSense — Production Docker Compose +# Docs: https://docs.surfsense.com/docs/docker-installation +# ============================================================================= +# Usage: +# 1. Copy .env.example to .env and edit the required values +# 2. docker compose up -d +# ============================================================================= + +name: surfsense + +services: + db: + image: pgvector/pgvector:pg17 + volumes: + - postgres_data:/var/lib/postgresql/data + - ./postgresql.conf:/etc/postgresql/postgresql.conf:ro + - ./scripts/init-electric-user.sh:/docker-entrypoint-initdb.d/init-electric-user.sh:ro + environment: + POSTGRES_USER: ${DB_USER:-surfsense} + POSTGRES_PASSWORD: ${DB_PASSWORD:-surfsense} + POSTGRES_DB: ${DB_NAME:-surfsense} + ELECTRIC_DB_USER: ${ELECTRIC_DB_USER:-electric} + ELECTRIC_DB_PASSWORD: ${ELECTRIC_DB_PASSWORD:-electric_password} + command: postgres -c config_file=/etc/postgresql/postgresql.conf + restart: unless-stopped + healthcheck: + test: ["CMD-SHELL", "pg_isready -U ${DB_USER:-surfsense} -d ${DB_NAME:-surfsense}"] + interval: 10s + timeout: 5s + retries: 5 + + redis: + image: redis:8-alpine + volumes: + - redis_data:/data + command: redis-server --appendonly yes + restart: unless-stopped + healthcheck: + test: ["CMD", "redis-cli", "ping"] + interval: 10s + timeout: 5s + retries: 5 + + backend: + image: ghcr.io/modsetter/surfsense-backend:${SURFSENSE_VERSION:-latest} + ports: + - "${BACKEND_PORT:-8000}:8000" + volumes: + - shared_temp:/shared_tmp + env_file: + - .env + environment: + DATABASE_URL: ${DATABASE_URL:-postgresql+asyncpg://${DB_USER:-surfsense}:${DB_PASSWORD:-surfsense}@${DB_HOST:-db}:${DB_PORT:-5432}/${DB_NAME:-surfsense}} + CELERY_BROKER_URL: ${REDIS_URL:-redis://redis:6379/0} + CELERY_RESULT_BACKEND: ${REDIS_URL:-redis://redis:6379/0} + REDIS_APP_URL: ${REDIS_URL:-redis://redis:6379/0} + CELERY_TASK_DEFAULT_QUEUE: surfsense + PYTHONPATH: /app + UVICORN_LOOP: asyncio + UNSTRUCTURED_HAS_PATCHED_LOOP: "1" + ELECTRIC_DB_USER: ${ELECTRIC_DB_USER:-electric} + ELECTRIC_DB_PASSWORD: ${ELECTRIC_DB_PASSWORD:-electric_password} + NEXT_FRONTEND_URL: ${NEXT_FRONTEND_URL:-http://localhost:${FRONTEND_PORT:-3000}} + # Daytona Sandbox – uncomment and set credentials to enable cloud code execution + # DAYTONA_SANDBOX_ENABLED: "TRUE" + # DAYTONA_API_KEY: ${DAYTONA_API_KEY:-} + # DAYTONA_API_URL: ${DAYTONA_API_URL:-https://app.daytona.io/api} + # DAYTONA_TARGET: ${DAYTONA_TARGET:-us} + SERVICE_ROLE: api + labels: + - "com.centurylinklabs.watchtower.enable=true" + depends_on: + db: + condition: service_healthy + redis: + condition: service_healthy + restart: unless-stopped + healthcheck: + test: ["CMD", "curl", "-f", "http://localhost:8000/health"] + interval: 15s + timeout: 5s + retries: 30 + start_period: 200s + + celery_worker: + image: ghcr.io/modsetter/surfsense-backend:${SURFSENSE_VERSION:-latest} + volumes: + - shared_temp:/shared_tmp + env_file: + - .env + environment: + DATABASE_URL: ${DATABASE_URL:-postgresql+asyncpg://${DB_USER:-surfsense}:${DB_PASSWORD:-surfsense}@${DB_HOST:-db}:${DB_PORT:-5432}/${DB_NAME:-surfsense}} + CELERY_BROKER_URL: ${REDIS_URL:-redis://redis:6379/0} + CELERY_RESULT_BACKEND: ${REDIS_URL:-redis://redis:6379/0} + REDIS_APP_URL: ${REDIS_URL:-redis://redis:6379/0} + CELERY_TASK_DEFAULT_QUEUE: surfsense + PYTHONPATH: /app + ELECTRIC_DB_USER: ${ELECTRIC_DB_USER:-electric} + ELECTRIC_DB_PASSWORD: ${ELECTRIC_DB_PASSWORD:-electric_password} + SERVICE_ROLE: worker + depends_on: + db: + condition: service_healthy + redis: + condition: service_healthy + backend: + condition: service_healthy + labels: + - "com.centurylinklabs.watchtower.enable=true" + restart: unless-stopped + + celery_beat: + image: ghcr.io/modsetter/surfsense-backend:${SURFSENSE_VERSION:-latest} + env_file: + - .env + environment: + DATABASE_URL: ${DATABASE_URL:-postgresql+asyncpg://${DB_USER:-surfsense}:${DB_PASSWORD:-surfsense}@${DB_HOST:-db}:${DB_PORT:-5432}/${DB_NAME:-surfsense}} + CELERY_BROKER_URL: ${REDIS_URL:-redis://redis:6379/0} + CELERY_RESULT_BACKEND: ${REDIS_URL:-redis://redis:6379/0} + CELERY_TASK_DEFAULT_QUEUE: surfsense + PYTHONPATH: /app + SERVICE_ROLE: beat + depends_on: + db: + condition: service_healthy + redis: + condition: service_healthy + celery_worker: + condition: service_started + labels: + - "com.centurylinklabs.watchtower.enable=true" + restart: unless-stopped + + # flower: + # image: ghcr.io/modsetter/surfsense-backend:${SURFSENSE_VERSION:-latest} + # ports: + # - "${FLOWER_PORT:-5555}:5555" + # env_file: + # - .env + # environment: + # CELERY_BROKER_URL: ${REDIS_URL:-redis://redis:6379/0} + # CELERY_RESULT_BACKEND: ${REDIS_URL:-redis://redis:6379/0} + # PYTHONPATH: /app + # command: celery -A app.celery_app flower --port=5555 + # depends_on: + # - redis + # - celery_worker + # restart: unless-stopped + + electric: + image: electricsql/electric:1.4.10 + ports: + - "${ELECTRIC_PORT:-5133}:3000" + environment: + DATABASE_URL: ${ELECTRIC_DATABASE_URL:-postgresql://${ELECTRIC_DB_USER:-electric}:${ELECTRIC_DB_PASSWORD:-electric_password}@${DB_HOST:-db}:${DB_PORT:-5432}/${DB_NAME:-surfsense}?sslmode=${DB_SSLMODE:-disable}} + ELECTRIC_INSECURE: "true" + ELECTRIC_WRITE_TO_PG_MODE: direct + restart: unless-stopped + depends_on: + db: + condition: service_healthy + healthcheck: + test: ["CMD", "curl", "-f", "http://localhost:3000/v1/health"] + interval: 10s + timeout: 5s + retries: 5 + + frontend: + image: ghcr.io/modsetter/surfsense-web:${SURFSENSE_VERSION:-latest} + ports: + - "${FRONTEND_PORT:-3000}:3000" + environment: + NEXT_PUBLIC_FASTAPI_BACKEND_URL: ${NEXT_PUBLIC_FASTAPI_BACKEND_URL:-http://localhost:${BACKEND_PORT:-8000}} + NEXT_PUBLIC_ELECTRIC_URL: ${NEXT_PUBLIC_ELECTRIC_URL:-http://localhost:${ELECTRIC_PORT:-5133}} + NEXT_PUBLIC_FASTAPI_BACKEND_AUTH_TYPE: ${AUTH_TYPE:-LOCAL} + NEXT_PUBLIC_ETL_SERVICE: ${ETL_SERVICE:-DOCLING} + NEXT_PUBLIC_DEPLOYMENT_MODE: ${DEPLOYMENT_MODE:-self-hosted} + NEXT_PUBLIC_ELECTRIC_AUTH_MODE: ${NEXT_PUBLIC_ELECTRIC_AUTH_MODE:-insecure} + labels: + - "com.centurylinklabs.watchtower.enable=true" + depends_on: + backend: + condition: service_healthy + electric: + condition: service_healthy + restart: unless-stopped + +volumes: + postgres_data: + name: surfsense-postgres + redis_data: + name: surfsense-redis + shared_temp: + name: surfsense-shared-temp diff --git a/scripts/docker/postgresql.conf b/docker/postgresql.conf similarity index 100% rename from scripts/docker/postgresql.conf rename to docker/postgresql.conf diff --git a/scripts/docker/init-electric-user.sh b/docker/scripts/init-electric-user.sh similarity index 57% rename from scripts/docker/init-electric-user.sh rename to docker/scripts/init-electric-user.sh index b3856c573..fbd1c361a 100755 --- a/scripts/docker/init-electric-user.sh +++ b/docker/scripts/init-electric-user.sh @@ -1,26 +1,9 @@ #!/bin/sh -# ============================================================================ -# Electric SQL User Initialization Script (docker-compose only) -# ============================================================================ -# This script is ONLY used when running via docker-compose. -# -# How it works: -# - docker-compose.yml mounts this script into the PostgreSQL container's -# /docker-entrypoint-initdb.d/ directory -# - PostgreSQL automatically executes scripts in that directory on first -# container initialization -# -# For local PostgreSQL users (non-Docker), this script is NOT used. -# Instead, the Electric user is created by Alembic migration 66 -# (66_add_notifications_table_and_electric_replication.py). -# -# Both approaches are idempotent (use IF NOT EXISTS), so running both -# will not cause conflicts. -# ============================================================================ +# Creates the Electric SQL replication user on first DB initialization. +# Idempotent — safe to run alongside Alembic migration 66. set -e -# Use environment variables with defaults ELECTRIC_DB_USER="${ELECTRIC_DB_USER:-electric}" ELECTRIC_DB_PASSWORD="${ELECTRIC_DB_PASSWORD:-electric_password}" @@ -43,7 +26,6 @@ psql -v ON_ERROR_STOP=1 --username "$POSTGRES_USER" --dbname "$POSTGRES_DB" <<-E ALTER DEFAULT PRIVILEGES IN SCHEMA public GRANT SELECT ON TABLES TO $ELECTRIC_DB_USER; ALTER DEFAULT PRIVILEGES IN SCHEMA public GRANT SELECT ON SEQUENCES TO $ELECTRIC_DB_USER; - -- Create the publication for Electric SQL (if not exists) DO \$\$ BEGIN IF NOT EXISTS (SELECT FROM pg_publication WHERE pubname = 'electric_publication_default') THEN diff --git a/docker/scripts/install.ps1 b/docker/scripts/install.ps1 new file mode 100644 index 000000000..fc9c75a28 --- /dev/null +++ b/docker/scripts/install.ps1 @@ -0,0 +1,350 @@ +# ============================================================================= +# SurfSense — One-line Install Script (Windows / PowerShell) +# +# +# Usage: irm https://raw.githubusercontent.com/MODSetter/SurfSense/main/docker/scripts/install.ps1 | iex +# +# To pass flags, save and run locally: +# .\install.ps1 -NoWatchtower +# .\install.ps1 -WatchtowerInterval 3600 +# +# Handles two cases automatically: +# 1. Fresh install — no prior SurfSense data detected +# 2. Migration from the legacy all-in-one container (surfsense-data volume) +# Downloads and runs migrate-database.sh --yes, then restores the dump +# into the new PostgreSQL 17 stack. The user runs one command for both. +# ============================================================================= + +param( + [switch]$NoWatchtower, + [int]$WatchtowerInterval = 86400 +) + +$ErrorActionPreference = 'Stop' + +# ── Configuration ─────────────────────────────────────────────────────────── + +$RepoRaw = "https://raw.githubusercontent.com/MODSetter/SurfSense/main" +$InstallDir = ".\surfsense" +$OldVolume = "surfsense-data" +$DumpFile = ".\surfsense_migration_backup.sql" +$KeyFile = ".\surfsense_migration_secret.key" +$MigrationDoneFile = "$InstallDir\.migration_done" +$MigrationMode = $false +$SetupWatchtower = -not $NoWatchtower +$WatchtowerContainer = "watchtower" + +# ── Output helpers ────────────────────────────────────────────────────────── + +function Write-Info { param([string]$Msg) Write-Host "[SurfSense] " -ForegroundColor Cyan -NoNewline; Write-Host $Msg } +function Write-Ok { param([string]$Msg) Write-Host "[SurfSense] " -ForegroundColor Green -NoNewline; Write-Host $Msg } +function Write-Warn { param([string]$Msg) Write-Host "[SurfSense] " -ForegroundColor Yellow -NoNewline; Write-Host $Msg } +function Write-Step { param([string]$Msg) Write-Host "`n-- $Msg" -ForegroundColor Cyan } +function Write-Err { param([string]$Msg) Write-Host "[SurfSense] ERROR: $Msg" -ForegroundColor Red; exit 1 } + +function Invoke-NativeSafe { + param([scriptblock]$Command) + $previousErrorActionPreference = $ErrorActionPreference + try { + $ErrorActionPreference = 'Continue' + & $Command + } finally { + $ErrorActionPreference = $previousErrorActionPreference + } +} + +# ── Pre-flight checks ────────────────────────────────────────────────────── + +Write-Step "Checking prerequisites" + +if (-not (Get-Command docker -ErrorAction SilentlyContinue)) { + Write-Err "Docker is not installed. Install Docker Desktop: https://docs.docker.com/desktop/install/windows-install/" +} +Write-Ok "Docker found." + +Invoke-NativeSafe { docker info *>$null } | Out-Null +if ($LASTEXITCODE -ne 0) { + Write-Err "Docker daemon is not running. Please start Docker Desktop and try again." +} +Write-Ok "Docker daemon is running." + +Invoke-NativeSafe { docker compose version *>$null } | Out-Null +if ($LASTEXITCODE -ne 0) { + Write-Err "Docker Compose is not available. It should be bundled with Docker Desktop." +} +Write-Ok "Docker Compose found." + +# ── Wait-for-postgres helper ──────────────────────────────────────────────── + +function Wait-ForPostgres { + param([string]$DbUser) + $maxAttempts = 45 + $attempt = 0 + + Write-Info "Waiting for PostgreSQL to accept connections..." + do { + $attempt++ + if ($attempt -ge $maxAttempts) { + Write-Err "PostgreSQL did not become ready after $($maxAttempts * 2) seconds.`nCheck logs: cd $InstallDir; docker compose logs db" + } + Start-Sleep -Seconds 2 + Push-Location $InstallDir + Invoke-NativeSafe { docker compose exec -T db pg_isready -U $DbUser -q *>$null } | Out-Null + $ready = $LASTEXITCODE -eq 0 + Pop-Location + } while (-not $ready) + + Write-Ok "PostgreSQL is ready." +} + +# ── Download files ────────────────────────────────────────────────────────── + +Write-Step "Downloading SurfSense files" +Write-Info "Installation directory: $InstallDir" + +New-Item -ItemType Directory -Path "$InstallDir\scripts" -Force | Out-Null + +$Files = @( + @{ Src = "docker/docker-compose.yml"; Dest = "docker-compose.yml" } + @{ Src = "docker/.env.example"; Dest = ".env.example" } + @{ Src = "docker/postgresql.conf"; Dest = "postgresql.conf" } + @{ Src = "docker/scripts/init-electric-user.sh"; Dest = "scripts/init-electric-user.sh" } + @{ Src = "docker/scripts/migrate-database.ps1"; Dest = "scripts/migrate-database.ps1" } +) + +foreach ($f in $Files) { + $destPath = Join-Path $InstallDir $f.Dest + Write-Info "Downloading $($f.Dest)..." + try { + Invoke-WebRequest -Uri "$RepoRaw/$($f.Src)" -OutFile $destPath -UseBasicParsing + } catch { + Write-Err "Failed to download $($f.Dest). Check your internet connection and try again." + } +} + +Write-Ok "All files downloaded to $InstallDir/" + +# ── Legacy all-in-one detection ───────────────────────────────────────────── + +$volumeList = Invoke-NativeSafe { docker volume ls --format '{{.Name}}' 2>$null } +if (($volumeList -split "`n") -contains $OldVolume -and -not (Test-Path $MigrationDoneFile)) { + $MigrationMode = $true + + if (Test-Path $DumpFile) { + Write-Step "Migration mode - using existing dump (skipping extraction)" + Write-Info "Found existing dump: $DumpFile" + Write-Info "Skipping data extraction - proceeding directly to restore." + Write-Info "To force a fresh extraction, remove the dump first: Remove-Item $DumpFile" + } else { + Write-Step "Migration mode - legacy all-in-one container detected" + Write-Warn "Volume '$OldVolume' found. Your data will be migrated automatically." + Write-Warn "PostgreSQL is being upgraded from version 14 to 17." + Write-Warn "Your original data will NOT be deleted." + Write-Host "" + Write-Info "Running data extraction (migrate-database.ps1 -Yes)..." + Write-Info "Full extraction log: ./surfsense-migration.log" + Write-Host "" + + $migrateScript = Join-Path $InstallDir "scripts/migrate-database.ps1" + & $migrateScript -Yes + if ($LASTEXITCODE -ne 0) { + Write-Err "Data extraction failed. See ./surfsense-migration.log for details.`nYou can also run migrate-database.ps1 manually with custom flags." + } + + Write-Host "" + Write-Ok "Data extraction complete. Proceeding with installation and restore." + } +} + +# ── Set up .env ───────────────────────────────────────────────────────────── + +Write-Step "Configuring environment" + +$envPath = Join-Path $InstallDir ".env" +$envExamplePath = Join-Path $InstallDir ".env.example" + +if (-not (Test-Path $envPath)) { + Copy-Item $envExamplePath $envPath + + if ($MigrationMode -and (Test-Path $KeyFile)) { + $SecretKey = (Get-Content $KeyFile -Raw).Trim() + Write-Ok "Using SECRET_KEY recovered from legacy container." + } else { + $bytes = New-Object byte[] 32 + $rng = [System.Security.Cryptography.RNGCryptoServiceProvider]::new() + $rng.GetBytes($bytes) + $rng.Dispose() + $SecretKey = [Convert]::ToBase64String($bytes) + Write-Ok "Generated new random SECRET_KEY." + } + + $content = Get-Content $envPath -Raw + $content = $content -replace 'SECRET_KEY=replace_me_with_a_random_string', "SECRET_KEY=$SecretKey" + Set-Content -Path $envPath -Value $content -NoNewline + + Write-Info "Created $envPath" +} else { + Write-Warn ".env already exists - keeping your existing configuration." +} + +# ── Start containers ──────────────────────────────────────────────────────── + +if ($MigrationMode) { + $envContent = Get-Content $envPath + $DbUser = ($envContent | Select-String '^DB_USER=' | ForEach-Object { ($_ -split '=',2)[1].Trim('"') }) | Select-Object -First 1 + $DbPass = ($envContent | Select-String '^DB_PASSWORD=' | ForEach-Object { ($_ -split '=',2)[1].Trim('"') }) | Select-Object -First 1 + $DbName = ($envContent | Select-String '^DB_NAME=' | ForEach-Object { ($_ -split '=',2)[1].Trim('"') }) | Select-Object -First 1 + if (-not $DbUser) { $DbUser = "surfsense" } + if (-not $DbPass) { $DbPass = "surfsense" } + if (-not $DbName) { $DbName = "surfsense" } + + Write-Step "Starting PostgreSQL 17" + Push-Location $InstallDir + Invoke-NativeSafe { docker compose up -d db } | Out-Null + Pop-Location + Wait-ForPostgres -DbUser $DbUser + + Write-Step "Restoring database" + if (-not (Test-Path $DumpFile)) { + Write-Err "Dump file '$DumpFile' not found. The migration script may have failed." + } + $DumpFilePath = (Resolve-Path $DumpFile).Path + Write-Info "Restoring dump into PostgreSQL 17 - this may take a while for large databases..." + + $restoreErrFile = Join-Path $env:TEMP "surfsense_restore_err.log" + Push-Location $InstallDir + Invoke-NativeSafe { Get-Content -LiteralPath $DumpFilePath | docker compose exec -T -e "PGPASSWORD=$DbPass" db psql -U $DbUser -d $DbName 2>$restoreErrFile | Out-Null } | Out-Null + Pop-Location + + $fatalErrors = @() + if (Test-Path $restoreErrFile) { + $fatalErrors = Get-Content $restoreErrFile | + Where-Object { $_ -match '^ERROR:' } | + Where-Object { $_ -notmatch 'already exists' } | + Where-Object { $_ -notmatch 'multiple primary keys' } + } + + if ($fatalErrors.Count -gt 0) { + Write-Warn "Restore completed with errors (may be harmless pg_dump header noise):" + $fatalErrors | ForEach-Object { Write-Host $_ } + Write-Warn "If SurfSense behaves incorrectly, inspect manually." + } else { + Write-Ok "Database restored with no fatal errors." + } + + # Smoke test + Push-Location $InstallDir + $tableCount = (Invoke-NativeSafe { docker compose exec -T -e "PGPASSWORD=$DbPass" db psql -U $DbUser -d $DbName -t -c "SELECT count(*) FROM information_schema.tables WHERE table_schema = 'public';" 2>$null }).Trim() + Pop-Location + + if (-not $tableCount -or $tableCount -eq "0") { + Write-Warn "Smoke test: no tables found after restore." + Write-Warn "The restore may have failed silently. Check: cd $InstallDir; docker compose logs db" + } else { + Write-Ok "Smoke test passed: $tableCount table(s) restored successfully." + New-Item -Path $MigrationDoneFile -ItemType File -Force | Out-Null + } + + Write-Step "Starting all SurfSense services" + Push-Location $InstallDir + Invoke-NativeSafe { docker compose up -d } + Pop-Location + Write-Ok "All services started." + + Remove-Item $KeyFile -ErrorAction SilentlyContinue + +} else { + Write-Step "Starting SurfSense" + Push-Location $InstallDir + Invoke-NativeSafe { docker compose up -d } + Pop-Location + Write-Ok "All services started." +} + +# ── Watchtower (auto-update) ──────────────────────────────────────────────── + +if ($SetupWatchtower) { + $wtHours = [math]::Floor($WatchtowerInterval / 3600) + Write-Step "Setting up Watchtower (auto-updates every ${wtHours}h)" + + $wtState = Invoke-NativeSafe { docker inspect -f '{{.State.Running}}' $WatchtowerContainer 2>$null } + if ($LASTEXITCODE -ne 0) { $wtState = "missing" } + + if ($wtState -eq "true") { + Write-Ok "Watchtower is already running - skipping." + } else { + if ($wtState -ne "missing") { + Write-Info "Removing stopped Watchtower container..." + Invoke-NativeSafe { docker rm -f $WatchtowerContainer *>$null } | Out-Null + } + Invoke-NativeSafe { + docker run -d ` + --name $WatchtowerContainer ` + --restart unless-stopped ` + -v /var/run/docker.sock:/var/run/docker.sock ` + nickfedor/watchtower ` + --label-enable ` + --interval $WatchtowerInterval *>$null + } | Out-Null + + if ($LASTEXITCODE -eq 0) { + Write-Ok "Watchtower started - labeled SurfSense containers will auto-update." + } else { + Write-Warn "Could not start Watchtower. You can set it up manually or use: docker compose pull; docker compose up -d" + } + } +} else { + Write-Info "Skipping Watchtower setup (-NoWatchtower flag)." +} + +# ── Done ──────────────────────────────────────────────────────────────────── + +Write-Host "" +Write-Host @" + + + .d8888b. .d888 .d8888b. +d88P Y88b d88P" d88P Y88b +Y88b. 888 Y88b. + "Y888b. 888 888 888d888 888888 "Y888b. .d88b. 88888b. .d8888b .d88b. + "Y88b. 888 888 888P" 888 "Y88b. d8P Y8b 888 "88b 88K d8P Y8b + "888 888 888 888 888 "888 88888888 888 888 "Y8888b. 88888888 +Y88b d88P Y88b 888 888 888 Y88b d88P Y8b. 888 888 X88 Y8b. + "Y8888P" "Y88888 888 888 "Y8888P" "Y8888 888 888 88888P' "Y8888 + + +"@ -ForegroundColor White + +$versionDisplay = (Get-Content $envPath | Select-String '^SURFSENSE_VERSION=' | ForEach-Object { ($_ -split '=',2)[1].Trim('"') }) | Select-Object -First 1 +if (-not $versionDisplay) { $versionDisplay = "latest" } +Write-Host " OSS Alternative to NotebookLM for Teams [$versionDisplay]" -ForegroundColor Yellow +Write-Host ("=" * 62) -ForegroundColor Cyan +Write-Host "" + +Write-Info " Frontend: http://localhost:3000" +Write-Info " Backend: http://localhost:8000" +Write-Info " API Docs: http://localhost:8000/docs" +Write-Info "" +Write-Info " Config: $InstallDir\.env" +Write-Info " Logs: cd $InstallDir; docker compose logs -f" +Write-Info " Stop: cd $InstallDir; docker compose down" +Write-Info " Update: cd $InstallDir; docker compose pull; docker compose up -d" +Write-Info "" + +if ($SetupWatchtower) { + Write-Info " Watchtower: auto-updates every ${wtHours}h (stop: docker rm -f $WatchtowerContainer)" +} else { + Write-Warn " Watchtower skipped. For auto-updates, re-run without -NoWatchtower." +} +Write-Info "" + +if ($MigrationMode) { + Write-Warn " Migration complete! Open frontend and verify your data." + Write-Warn " Once verified, clean up the legacy volume and migration files:" + Write-Warn " docker volume rm $OldVolume" + Write-Warn " Remove-Item $DumpFile" + Write-Warn " Remove-Item $MigrationDoneFile" +} else { + Write-Warn " First startup may take a few minutes while images are pulled." + Write-Warn " Edit $InstallDir\.env to configure API keys, OAuth, etc." +} diff --git a/docker/scripts/install.sh b/docker/scripts/install.sh new file mode 100644 index 000000000..c4a0d5c9f --- /dev/null +++ b/docker/scripts/install.sh @@ -0,0 +1,337 @@ +#!/usr/bin/env bash +# ============================================================================= +# SurfSense — One-line Install Script +# +# +# Usage: curl -fsSL https://raw.githubusercontent.com/MODSetter/SurfSense/main/docker/scripts/install.sh | bash +# +# Flags: +# --no-watchtower Skip automatic Watchtower setup +# --watchtower-interval=SECS Check interval in seconds (default: 86400 = 24h) +# +# Handles two cases automatically: +# 1. Fresh install — no prior SurfSense data detected +# 2. Migration from the legacy all-in-one container (surfsense-data volume) +# Downloads and runs migrate-database.sh --yes, then restores the dump +# into the new PostgreSQL 17 stack. The user runs one command for both. +# +# If you used custom database credentials in the old all-in-one container, run +# migrate-database.sh manually first (with --db-user / --db-password flags), +# then re-run this script: +# curl -fsSL .../docker/scripts/migrate-database.sh | bash -s -- --db-user X --db-password Y +# ============================================================================= + +set -euo pipefail + +main() { + +REPO_RAW="https://raw.githubusercontent.com/MODSetter/SurfSense/main" +INSTALL_DIR="./surfsense" +OLD_VOLUME="surfsense-data" +DUMP_FILE="./surfsense_migration_backup.sql" +KEY_FILE="./surfsense_migration_secret.key" +MIGRATION_DONE_FILE="${INSTALL_DIR}/.migration_done" +MIGRATION_MODE=false +SETUP_WATCHTOWER=true +WATCHTOWER_INTERVAL=86400 +WATCHTOWER_CONTAINER="watchtower" + +# ── Parse flags ───────────────────────────────────────────────────────────── +for arg in "$@"; do + case "$arg" in + --no-watchtower) SETUP_WATCHTOWER=false ;; + --watchtower-interval=*) WATCHTOWER_INTERVAL="${arg#*=}" ;; + esac +done + +CYAN='\033[1;36m' +YELLOW='\033[1;33m' +GREEN='\033[0;32m' +RED='\033[0;31m' +BOLD='\033[1m' +NC='\033[0m' + +info() { printf "${CYAN}[SurfSense]${NC} %s\n" "$1"; } +success() { printf "${GREEN}[SurfSense]${NC} %s\n" "$1"; } +warn() { printf "${YELLOW}[SurfSense]${NC} %s\n" "$1"; } +error() { printf "${RED}[SurfSense]${NC} ERROR: %s\n" "$1" >&2; exit 1; } +step() { printf "\n${BOLD}${CYAN}── %s${NC}\n" "$1"; } + +# ── Pre-flight checks ──────────────────────────────────────────────────────── + +step "Checking prerequisites" + +command -v docker >/dev/null 2>&1 \ + || error "Docker is not installed. Install it at: https://docs.docker.com/get-docker/" +success "Docker found." + +docker info >/dev/null 2>&1 < /dev/null \ + || error "Docker daemon is not running. Please start Docker and try again." +success "Docker daemon is running." + +if docker compose version >/dev/null 2>&1 < /dev/null; then + DC="docker compose" +elif command -v docker-compose >/dev/null 2>&1; then + DC="docker-compose" +else + error "Docker Compose is not installed. Install it at: https://docs.docker.com/compose/install/" +fi +success "Docker Compose found ($DC)." + +# ── Wait-for-postgres helper ───────────────────────────────────────────────── +wait_for_pg() { + local db_user="$1" + local max_attempts=45 + local attempt=0 + + info "Waiting for PostgreSQL to accept connections..." + until (cd "${INSTALL_DIR}" && ${DC} exec -T db pg_isready -U "${db_user}" -q 2>/dev/null) < /dev/null; do + attempt=$((attempt + 1)) + if [[ $attempt -ge $max_attempts ]]; then + error "PostgreSQL did not become ready after $((max_attempts * 2)) seconds.\nCheck logs: cd ${INSTALL_DIR} && ${DC} logs db" + fi + printf "." + sleep 2 + done + printf "\n" + success "PostgreSQL is ready." +} + +# ── Download files ─────────────────────────────────────────────────────────── + +step "Downloading SurfSense files" +info "Installation directory: ${INSTALL_DIR}" +mkdir -p "${INSTALL_DIR}/scripts" + +FILES=( + "docker/docker-compose.yml:docker-compose.yml" + "docker/.env.example:.env.example" + "docker/postgresql.conf:postgresql.conf" + "docker/scripts/init-electric-user.sh:scripts/init-electric-user.sh" + "docker/scripts/migrate-database.sh:scripts/migrate-database.sh" +) + +for entry in "${FILES[@]}"; do + src="${entry%%:*}" + dest="${entry##*:}" + info "Downloading ${dest}..." + curl -fsSL "${REPO_RAW}/${src}" -o "${INSTALL_DIR}/${dest}" \ + || error "Failed to download ${dest}. Check your internet connection and try again." +done + +chmod +x "${INSTALL_DIR}/scripts/init-electric-user.sh" +chmod +x "${INSTALL_DIR}/scripts/migrate-database.sh" +success "All files downloaded to ${INSTALL_DIR}/" + +# ── Legacy all-in-one detection ────────────────────────────────────────────── +# Detect surfsense-data volume → migration mode. +# If a dump already exists (from a previous partial run) skip extraction and +# go straight to restore — this makes re-runs safe and idempotent. + +if docker volume ls --format '{{.Name}}' 2>/dev/null < /dev/null | grep -q "^${OLD_VOLUME}$" \ + && [[ ! -f "${MIGRATION_DONE_FILE}" ]]; then + MIGRATION_MODE=true + + if [[ -f "${DUMP_FILE}" ]]; then + step "Migration mode — using existing dump (skipping extraction)" + info "Found existing dump: ${DUMP_FILE}" + info "Skipping data extraction — proceeding directly to restore." + info "To force a fresh extraction, remove the dump first: rm ${DUMP_FILE}" + else + step "Migration mode — legacy all-in-one container detected" + warn "Volume '${OLD_VOLUME}' found. Your data will be migrated automatically." + warn "PostgreSQL is being upgraded from version 14 to 17." + warn "Your original data will NOT be deleted." + printf "\n" + info "Running data extraction (migrate-database.sh --yes)..." + info "Full extraction log: ./surfsense-migration.log" + printf "\n" + + # Run extraction non-interactively. On failure the error from + # migrate-database.sh is printed and install.sh exits here. + bash "${INSTALL_DIR}/scripts/migrate-database.sh" --yes < /dev/null \ + || error "Data extraction failed. See ./surfsense-migration.log for details.\nYou can also run migrate-database.sh manually with custom flags:\n bash ${INSTALL_DIR}/scripts/migrate-database.sh --db-user X --db-password Y" + + printf "\n" + success "Data extraction complete. Proceeding with installation and restore." + fi +fi + +# ── Set up .env ────────────────────────────────────────────────────────────── + +step "Configuring environment" + +if [ ! -f "${INSTALL_DIR}/.env" ]; then + cp "${INSTALL_DIR}/.env.example" "${INSTALL_DIR}/.env" + + if $MIGRATION_MODE && [[ -f "${KEY_FILE}" ]]; then + SECRET_KEY=$(cat "${KEY_FILE}" | tr -d '[:space:]') + success "Using SECRET_KEY recovered from legacy container." + else + SECRET_KEY=$(openssl rand -base64 32 2>/dev/null \ + || head -c 32 /dev/urandom | base64 | tr -d '\n') + success "Generated new random SECRET_KEY." + fi + + if [[ "$OSTYPE" == "darwin"* ]]; then + sed -i '' "s|SECRET_KEY=replace_me_with_a_random_string|SECRET_KEY=${SECRET_KEY}|" "${INSTALL_DIR}/.env" + else + sed -i "s|SECRET_KEY=replace_me_with_a_random_string|SECRET_KEY=${SECRET_KEY}|" "${INSTALL_DIR}/.env" + fi + info "Created ${INSTALL_DIR}/.env" +else + warn ".env already exists — keeping your existing configuration." +fi + +# ── Start containers ───────────────────────────────────────────────────────── + +if $MIGRATION_MODE; then + # Read DB credentials from .env (fall back to defaults from docker-compose.yml) + DB_USER=$(grep '^DB_USER=' "${INSTALL_DIR}/.env" 2>/dev/null | cut -d= -f2 | tr -d '"' | head -1 || true) + DB_PASS=$(grep '^DB_PASSWORD=' "${INSTALL_DIR}/.env" 2>/dev/null | cut -d= -f2 | tr -d '"' | head -1 || true) + DB_NAME=$(grep '^DB_NAME=' "${INSTALL_DIR}/.env" 2>/dev/null | cut -d= -f2 | tr -d '"' | head -1 || true) + DB_USER="${DB_USER:-surfsense}" + DB_PASS="${DB_PASS:-surfsense}" + DB_NAME="${DB_NAME:-surfsense}" + + step "Starting PostgreSQL 17" + (cd "${INSTALL_DIR}" && ${DC} up -d db) < /dev/null + wait_for_pg "${DB_USER}" + + step "Restoring database" + [[ -f "${DUMP_FILE}" ]] \ + || error "Dump file '${DUMP_FILE}' not found. The migration script may have failed.\n Check: ./surfsense-migration.log\n Or run manually: bash ${INSTALL_DIR}/scripts/migrate-database.sh --yes" + info "Restoring dump into PostgreSQL 17 — this may take a while for large databases..." + + RESTORE_ERR="/tmp/surfsense_restore_err.log" + (cd "${INSTALL_DIR}" && ${DC} exec -T \ + -e PGPASSWORD="${DB_PASS}" \ + db psql -U "${DB_USER}" -d "${DB_NAME}" \ + >/dev/null 2>"${RESTORE_ERR}") < "${DUMP_FILE}" || true + + # Surface real errors; ignore benign "already exists" noise from pg_dump headers + FATAL_ERRORS=$(grep -i "^ERROR:" "${RESTORE_ERR}" \ + | grep -iv "already exists" \ + | grep -iv "multiple primary keys" \ + || true) + + if [[ -n "${FATAL_ERRORS}" ]]; then + warn "Restore completed with errors (may be harmless pg_dump header noise):" + printf "%s\n" "${FATAL_ERRORS}" + warn "If SurfSense behaves incorrectly, inspect manually:" + warn " cd ${INSTALL_DIR} && ${DC} exec db psql -U ${DB_USER} -d ${DB_NAME} < ${DUMP_FILE}" + else + success "Database restored with no fatal errors." + fi + + # Smoke test — verify tables are present + TABLE_COUNT=$( + cd "${INSTALL_DIR}" && ${DC} exec -T \ + -e PGPASSWORD="${DB_PASS}" \ + db psql -U "${DB_USER}" -d "${DB_NAME}" -t \ + -c "SELECT count(*) FROM information_schema.tables WHERE table_schema = 'public';" \ + 2>/dev/null < /dev/null | tr -d ' \n' || echo "0" + ) + if [[ "${TABLE_COUNT}" == "0" || -z "${TABLE_COUNT}" ]]; then + warn "Smoke test: no tables found after restore." + warn "The restore may have failed silently. Check: cd ${INSTALL_DIR} && ${DC} logs db" + else + success "Smoke test passed: ${TABLE_COUNT} table(s) restored successfully." + touch "${MIGRATION_DONE_FILE}" + fi + + step "Starting all SurfSense services" + (cd "${INSTALL_DIR}" && ${DC} up -d) < /dev/null + success "All services started." + + # Key file is no longer needed — SECRET_KEY is now in .env + rm -f "${KEY_FILE}" + +else + step "Starting SurfSense" + (cd "${INSTALL_DIR}" && ${DC} up -d) < /dev/null + success "All services started." +fi + +# ── Watchtower (auto-update) ───────────────────────────────────────────────── + +if $SETUP_WATCHTOWER; then + step "Setting up Watchtower (auto-updates every $((WATCHTOWER_INTERVAL / 3600))h)" + + WT_STATE=$(docker inspect -f '{{.State.Running}}' "${WATCHTOWER_CONTAINER}" 2>/dev/null < /dev/null || echo "missing") + + if [[ "${WT_STATE}" == "true" ]]; then + success "Watchtower is already running — skipping." + else + if [[ "${WT_STATE}" != "missing" ]]; then + info "Removing stopped Watchtower container..." + docker rm -f "${WATCHTOWER_CONTAINER}" >/dev/null 2>&1 < /dev/null || true + fi + docker run -d \ + --name "${WATCHTOWER_CONTAINER}" \ + --restart unless-stopped \ + -v /var/run/docker.sock:/var/run/docker.sock \ + nickfedor/watchtower \ + --label-enable \ + --interval "${WATCHTOWER_INTERVAL}" >/dev/null 2>&1 < /dev/null \ + && success "Watchtower started — labeled SurfSense containers will auto-update." \ + || warn "Could not start Watchtower. You can set it up manually or use: docker compose pull && docker compose up -d" + fi +else + info "Skipping Watchtower setup (--no-watchtower flag)." +fi + +# ── Done ───────────────────────────────────────────────────────────────────── + +echo "" +printf '\033[1;37m' +cat << 'EOF' + + + .d8888b. .d888 .d8888b. +d88P Y88b d88P" d88P Y88b +Y88b. 888 Y88b. + "Y888b. 888 888 888d888 888888 "Y888b. .d88b. 88888b. .d8888b .d88b. + "Y88b. 888 888 888P" 888 "Y88b. d8P Y8b 888 "88b 88K d8P Y8b + "888 888 888 888 888 "888 88888888 888 888 "Y8888b. 88888888 +Y88b d88P Y88b 888 888 888 Y88b d88P Y8b. 888 888 X88 Y8b. + "Y8888P" "Y88888 888 888 "Y8888P" "Y8888 888 888 88888P' "Y8888 + + +EOF +_version_display=$(grep '^SURFSENSE_VERSION=' "${INSTALL_DIR}/.env" 2>/dev/null | cut -d= -f2 | tr -d '"' | head -1 || true) +_version_display="${_version_display:-latest}" +printf " OSS Alternative to NotebookLM for Teams ${YELLOW}[%s]${NC}\n" "${_version_display}" +printf "${CYAN}══════════════════════════════════════════════════════════════${NC}\n\n" + +info " Frontend: http://localhost:3000" +info " Backend: http://localhost:8000" +info " API Docs: http://localhost:8000/docs" +info "" +info " Config: ${INSTALL_DIR}/.env" +info " Logs: cd ${INSTALL_DIR} && ${DC} logs -f" +info " Stop: cd ${INSTALL_DIR} && ${DC} down" +info " Update: cd ${INSTALL_DIR} && ${DC} pull && ${DC} up -d" +info "" + +if $SETUP_WATCHTOWER; then + info " Watchtower: auto-updates every $((WATCHTOWER_INTERVAL / 3600))h (stop: docker rm -f ${WATCHTOWER_CONTAINER})" +else + warn " Watchtower skipped. For auto-updates, re-run without --no-watchtower." +fi +info "" + +if $MIGRATION_MODE; then + warn " Migration complete! Open frontend and verify your data." + warn " Once verified, clean up the legacy volume and migration files:" + warn " docker volume rm ${OLD_VOLUME}" + warn " rm ${DUMP_FILE}" + warn " rm ${MIGRATION_DONE_FILE}" +else + warn " First startup may take a few minutes while images are pulled." + warn " Edit ${INSTALL_DIR}/.env to configure API keys, OAuth, etc." +fi + +} # end main() + +main "$@" diff --git a/docker/scripts/migrate-database.ps1 b/docker/scripts/migrate-database.ps1 new file mode 100644 index 000000000..56769fcaf --- /dev/null +++ b/docker/scripts/migrate-database.ps1 @@ -0,0 +1,343 @@ +# ============================================================================= +# SurfSense — Database Migration Script (Windows / PowerShell) +# +# Extracts data from the legacy all-in-one surfsense-data volume (PostgreSQL 14) +# and saves it as a SQL dump + SECRET_KEY file ready for install.ps1 to restore. +# +# Usage: +# .\migrate-database.ps1 [options] +# +# Options: +# -DbUser USER Old PostgreSQL username (default: surfsense) +# -DbPassword PASS Old PostgreSQL password (default: surfsense) +# -DbName NAME Old PostgreSQL database (default: surfsense) +# -Yes Skip all confirmation prompts +# +# Prerequisites: +# - Docker Desktop installed and running +# - The legacy surfsense-data volume must exist +# - ~500 MB free disk space for the dump file +# +# What this script does: +# 1. Stops any container using surfsense-data (to prevent corruption) +# 2. Starts a temporary PG14 container against the old volume +# 3. Dumps the database to .\surfsense_migration_backup.sql +# 4. Recovers the SECRET_KEY to .\surfsense_migration_secret.key +# 5. Exits — leaving installation to install.ps1 +# +# What this script does NOT do: +# - Delete the original surfsense-data volume (do this manually after verifying) +# - Install the new SurfSense stack (install.ps1 handles that automatically) +# +# Note: +# install.ps1 downloads and runs this script automatically when it detects the +# legacy surfsense-data volume. You only need to run this script manually if +# you have custom database credentials (-DbUser / -DbPassword / -DbName) +# or if the automatic migration inside install.ps1 fails at the extraction step. +# ============================================================================= + +param( + [string]$DbUser = "surfsense", + [string]$DbPassword = "surfsense", + [string]$DbName = "surfsense", + [switch]$Yes +) + +$ErrorActionPreference = 'Stop' + +# ── Constants ──────────────────────────────────────────────────────────────── + +$OldVolume = "surfsense-data" +$TempContainer = "surfsense-pg14-migration" +$DumpFile = ".\surfsense_migration_backup.sql" +$KeyFile = ".\surfsense_migration_secret.key" +$PG14Image = "pgvector/pgvector:pg14" +$LogFile = ".\surfsense-migration.log" + +# ── Output helpers ─────────────────────────────────────────────────────────── + +function Write-Info { param([string]$Msg) Write-Host "[SurfSense] " -ForegroundColor Cyan -NoNewline; Write-Host $Msg } +function Write-Ok { param([string]$Msg) Write-Host "[SurfSense] " -ForegroundColor Green -NoNewline; Write-Host $Msg } +function Write-Warn { param([string]$Msg) Write-Host "[SurfSense] " -ForegroundColor Yellow -NoNewline; Write-Host $Msg } +function Write-Step { param([string]$Step, [string]$Msg) Write-Host "`n-- Step ${Step}: $Msg" -ForegroundColor Cyan } +function Write-Err { param([string]$Msg) Write-Host "[SurfSense] ERROR: $Msg" -ForegroundColor Red; exit 1 } + +function Log { param([string]$Msg) Add-Content -Path $LogFile -Value $Msg } + +function Invoke-NativeSafe { + param([scriptblock]$Command) + $previousErrorActionPreference = $ErrorActionPreference + try { + $ErrorActionPreference = 'Continue' + & $Command + } finally { + $ErrorActionPreference = $previousErrorActionPreference + } +} + +function Confirm-Action { + param([string]$Prompt) + if ($Yes) { return } + $reply = Read-Host "[SurfSense] $Prompt [y/N]" + if ($reply -notmatch '^[Yy]$') { + Write-Warn "Aborted." + exit 0 + } +} + +# ── Cleanup helper ─────────────────────────────────────────────────────────── + +function Remove-TempContainer { + $containers = Invoke-NativeSafe { docker ps -a --format '{{.Names}}' 2>$null } + if ($containers -and ($containers -split "`n") -contains $TempContainer) { + Write-Info "Cleaning up temporary container '$TempContainer'..." + Invoke-NativeSafe { docker stop $TempContainer *>$null } | Out-Null + Invoke-NativeSafe { docker rm $TempContainer *>$null } | Out-Null + } +} + +# Register cleanup on script exit +Register-EngineEvent PowerShell.Exiting -Action { + $containers = Invoke-NativeSafe { docker ps -a --format '{{.Names}}' 2>$null } + if ($containers -and ($containers -split "`n") -contains "surfsense-pg14-migration") { + Invoke-NativeSafe { docker stop "surfsense-pg14-migration" *>$null } | Out-Null + Invoke-NativeSafe { docker rm "surfsense-pg14-migration" *>$null } | Out-Null + } +} | Out-Null + +# ── Wait-for-postgres helper ──────────────────────────────────────────────── + +function Wait-ForPostgres { + param( + [string]$Container, + [string]$User, + [string]$Label = "PostgreSQL" + ) + $maxAttempts = 45 + $attempt = 0 + + Write-Info "Waiting for $Label to accept connections..." + do { + $attempt++ + if ($attempt -ge $maxAttempts) { + Write-Err "$Label did not become ready after $($maxAttempts * 2) seconds. Check: docker logs $Container" + } + Start-Sleep -Seconds 2 + Invoke-NativeSafe { docker exec $Container pg_isready -U $User -q 2>$null } | Out-Null + } while ($LASTEXITCODE -ne 0) + + Write-Ok "$Label is ready." +} + +Write-Info "Migrating data from legacy database (PostgreSQL 14 -> 17)" +"Migration started at $(Get-Date)" | Out-File $LogFile + +# ── Step 0: Pre-flight checks ─────────────────────────────────────────────── + +Write-Step "0" "Pre-flight checks" + +if (-not (Get-Command docker -ErrorAction SilentlyContinue)) { + Write-Err "Docker is not installed. Install Docker Desktop: https://docs.docker.com/desktop/install/windows-install/" +} + +Invoke-NativeSafe { docker info *>$null } | Out-Null +if ($LASTEXITCODE -ne 0) { + Write-Err "Docker daemon is not running. Please start Docker Desktop and try again." +} + +$volumeList = Invoke-NativeSafe { docker volume ls --format '{{.Name}}' 2>$null } +if (-not (($volumeList -split "`n") -contains $OldVolume)) { + Write-Err "Legacy volume '$OldVolume' not found. Are you sure you ran the old all-in-one SurfSense container?" +} +Write-Ok "Found legacy volume: $OldVolume" + +$oldContainer = (Invoke-NativeSafe { docker ps --filter "volume=$OldVolume" --format '{{.Names}}' 2>$null } | Select-Object -First 1) +if ($oldContainer) { + Write-Warn "Container '$oldContainer' is running and using the '$OldVolume' volume." + Write-Warn "It must be stopped before migration to prevent data file corruption." + Confirm-Action "Stop '$oldContainer' now and proceed with data extraction?" + Invoke-NativeSafe { docker stop $oldContainer *>$null } | Out-Null + if ($LASTEXITCODE -ne 0) { + Write-Err "Failed to stop '$oldContainer'. Try: docker stop $oldContainer" + } + Write-Ok "Container '$oldContainer' stopped." +} + +if (Test-Path $DumpFile) { + Write-Warn "Dump file '$DumpFile' already exists." + Write-Warn "If a previous extraction succeeded, just run install.ps1 now." + Write-Warn "To re-extract, remove the file first: Remove-Item $DumpFile" + Write-Err "Aborting to avoid overwriting an existing dump." +} + +$staleContainers = Invoke-NativeSafe { docker ps -a --format '{{.Names}}' 2>$null } +if ($staleContainers -and ($staleContainers -split "`n") -contains $TempContainer) { + Write-Warn "Stale migration container '$TempContainer' found - removing it." + Invoke-NativeSafe { docker stop $TempContainer *>$null } | Out-Null + Invoke-NativeSafe { docker rm $TempContainer *>$null } | Out-Null +} + +$drive = (Get-Item .).PSDrive +$freeMB = [math]::Floor($drive.Free / 1MB) +if ($freeMB -lt 500) { + Write-Warn "Low disk space: $freeMB MB free. At least 500 MB recommended for the dump." + Confirm-Action "Continue anyway?" +} else { + Write-Ok "Disk space: $freeMB MB free." +} + +Write-Ok "All pre-flight checks passed." + +# ── Confirmation prompt ────────────────────────────────────────────────────── + +Write-Host "" +Write-Host "Extraction plan:" -ForegroundColor White +Write-Host " Source volume : " -NoNewline; Write-Host "$OldVolume" -ForegroundColor Yellow -NoNewline; Write-Host " (PG14 data at /data/postgres)" +Write-Host " Old credentials : user=" -NoNewline; Write-Host "$DbUser" -ForegroundColor Yellow -NoNewline; Write-Host " db=" -NoNewline; Write-Host "$DbName" -ForegroundColor Yellow +Write-Host " Dump saved to : " -NoNewline; Write-Host "$DumpFile" -ForegroundColor Yellow +Write-Host " SECRET_KEY to : " -NoNewline; Write-Host "$KeyFile" -ForegroundColor Yellow +Write-Host " Log file : " -NoNewline; Write-Host "$LogFile" -ForegroundColor Yellow +Write-Host "" +Confirm-Action "Start data extraction? (Your original data will not be deleted or modified.)" + +# ── Step 1: Start temporary PostgreSQL 14 container ────────────────────────── + +Write-Step "1" "Starting temporary PostgreSQL 14 container" + +Write-Info "Pulling $PG14Image..." +Invoke-NativeSafe { docker pull $PG14Image *>$null } | Out-Null +if ($LASTEXITCODE -ne 0) { + Write-Warn "Could not pull $PG14Image - using cached image if available." +} + +$dataUid = Invoke-NativeSafe { docker run --rm -v "${OldVolume}:/data" alpine stat -c '%u' /data/postgres 2>$null } +if (-not $dataUid -or $dataUid -eq "0") { + Write-Warn "Could not detect data directory UID - falling back to default (may chown files)." + $userFlag = @() +} else { + Write-Info "Data directory owned by UID $dataUid - starting temp container as that user." + $userFlag = @("--user", $dataUid) +} + +$dockerRunArgs = @( + "run", "-d", + "--name", $TempContainer, + "-v", "${OldVolume}:/data", + "-e", "PGDATA=/data/postgres", + "-e", "POSTGRES_USER=$DbUser", + "-e", "POSTGRES_PASSWORD=$DbPassword", + "-e", "POSTGRES_DB=$DbName" +) + $userFlag + @($PG14Image) + +Invoke-NativeSafe { docker @dockerRunArgs *>$null } | Out-Null +if ($LASTEXITCODE -ne 0) { + Write-Err "Failed to start temporary PostgreSQL 14 container." +} + +Write-Ok "Temporary container '$TempContainer' started." +Wait-ForPostgres -Container $TempContainer -User $DbUser -Label "PostgreSQL 14" + +# ── Step 2: Dump the database ──────────────────────────────────────────────── + +Write-Step "2" "Dumping PostgreSQL 14 database" + +Write-Info "Running pg_dump - this may take a while for large databases..." + +$pgDumpErrFile = Join-Path $env:TEMP "surfsense_pgdump_err.log" +Invoke-NativeSafe { docker exec -e "PGPASSWORD=$DbPassword" $TempContainer pg_dump -U $DbUser --no-password $DbName > $DumpFile 2>$pgDumpErrFile } | Out-Null +if ($LASTEXITCODE -ne 0) { + if (Test-Path $pgDumpErrFile) { Get-Content $pgDumpErrFile | Write-Host -ForegroundColor Red } + Remove-TempContainer + Write-Err "pg_dump failed. See above for details." +} + +if (-not (Test-Path $DumpFile) -or (Get-Item $DumpFile).Length -eq 0) { + Remove-TempContainer + Write-Err "Dump file '$DumpFile' is empty. Something went wrong with pg_dump." +} + +$dumpContent = (Get-Content $DumpFile -TotalCount 5) -join "`n" +if ($dumpContent -notmatch "PostgreSQL database dump") { + Remove-TempContainer + Write-Err "Dump file does not contain a valid PostgreSQL dump header - the file may be corrupt." +} + +$dumpLines = (Get-Content $DumpFile | Measure-Object -Line).Lines +if ($dumpLines -lt 10) { + Remove-TempContainer + Write-Err "Dump has only $dumpLines lines - suspiciously small. Aborting." +} + +$dumpSize = "{0:N1} MB" -f ((Get-Item $DumpFile).Length / 1MB) +Write-Ok "Dump complete: $dumpSize ($dumpLines lines) -> $DumpFile" + +Write-Info "Stopping temporary PostgreSQL 14 container..." +Invoke-NativeSafe { docker stop $TempContainer *>$null } | Out-Null +Invoke-NativeSafe { docker rm $TempContainer *>$null } | Out-Null +Write-Ok "Temporary container removed." + +# ── Step 3: Recover SECRET_KEY ─────────────────────────────────────────────── + +Write-Step "3" "Recovering SECRET_KEY" + +$recoveredKey = "" + +$keyCheck = Invoke-NativeSafe { docker run --rm -v "${OldVolume}:/data" alpine sh -c 'test -f /data/.secret_key && cat /data/.secret_key' 2>$null } +if ($LASTEXITCODE -eq 0 -and $keyCheck) { + $recoveredKey = $keyCheck.Trim() + Write-Ok "Recovered SECRET_KEY from '$OldVolume'." +} else { + Write-Warn "No SECRET_KEY file found at /data/.secret_key in '$OldVolume'." + Write-Warn "This means the all-in-one container was launched with SECRET_KEY set as an explicit env var." + + if ($Yes) { + $bytes = New-Object byte[] 32 + $rng = [System.Security.Cryptography.RNGCryptoServiceProvider]::new() + $rng.GetBytes($bytes) + $rng.Dispose() + $recoveredKey = [Convert]::ToBase64String($bytes) + Write-Warn "Non-interactive mode: generated a new SECRET_KEY automatically." + Write-Warn "All active browser sessions will be logged out after migration." + Write-Warn "To restore your original key, update SECRET_KEY in .\surfsense\.env afterwards." + } else { + Write-Warn "Enter the SECRET_KEY from your old container's environment" + $recoveredKey = Read-Host "[SurfSense] (press Enter to generate a new one - existing sessions will be invalidated)" + if (-not $recoveredKey) { + $bytes = New-Object byte[] 32 + $rng = [System.Security.Cryptography.RNGCryptoServiceProvider]::new() + $rng.GetBytes($bytes) + $rng.Dispose() + $recoveredKey = [Convert]::ToBase64String($bytes) + Write-Warn "Generated a new SECRET_KEY. All active browser sessions will be logged out after migration." + } + } +} + +Set-Content -Path $KeyFile -Value $recoveredKey -NoNewline +Write-Ok "SECRET_KEY saved to $KeyFile" + +# ── Done ───────────────────────────────────────────────────────────────────── + +Write-Host "" +Write-Host ("=" * 62) -ForegroundColor Green +Write-Host " Data extraction complete!" -ForegroundColor Green +Write-Host ("=" * 62) -ForegroundColor Green +Write-Host "" + +Write-Ok "Dump file : $DumpFile ($dumpSize)" +Write-Ok "Secret key: $KeyFile" +Write-Host "" +Write-Info "Next step - run install.ps1 from this same directory:" +Write-Host "" +Write-Host " irm https://raw.githubusercontent.com/MODSetter/SurfSense/main/docker/scripts/install.ps1 | iex" -ForegroundColor Cyan +Write-Host "" +Write-Info "install.ps1 will detect the dump, restore your data into PostgreSQL 17," +Write-Info "and start the full SurfSense stack automatically." +Write-Host "" +Write-Warn "Keep both files until you have verified the migration:" +Write-Warn " $DumpFile" +Write-Warn " $KeyFile" +Write-Warn "Full log saved to: $LogFile" +Write-Host "" + +Log "Migration extraction completed successfully at $(Get-Date)" diff --git a/docker/scripts/migrate-database.sh b/docker/scripts/migrate-database.sh new file mode 100755 index 000000000..9bc1d90b7 --- /dev/null +++ b/docker/scripts/migrate-database.sh @@ -0,0 +1,335 @@ +#!/usr/bin/env bash +# ============================================================================= +# SurfSense — Database Migration Script +# +# Extracts data from the legacy all-in-one surfsense-data volume (PostgreSQL 14) +# and saves it as a SQL dump + SECRET_KEY file ready for install.sh to restore. +# +# Usage: +# bash migrate-database.sh [options] +# +# Options: +# --db-user USER Old PostgreSQL username (default: surfsense) +# --db-password PASS Old PostgreSQL password (default: surfsense) +# --db-name NAME Old PostgreSQL database (default: surfsense) +# --yes / -y Skip all confirmation prompts +# --help / -h Show this help +# +# Prerequisites: +# - Docker installed and running +# - The legacy surfsense-data volume must exist +# - ~500 MB free disk space for the dump file +# +# What this script does: +# 1. Stops any container using surfsense-data (to prevent corruption) +# 2. Starts a temporary PG14 container against the old volume +# 3. Dumps the database to ./surfsense_migration_backup.sql +# 4. Recovers the SECRET_KEY to ./surfsense_migration_secret.key +# 5. Exits — leaving installation to install.sh +# +# What this script does NOT do: +# - Delete the original surfsense-data volume (do this manually after verifying) +# - Install the new SurfSense stack (install.sh handles that automatically) +# +# Note: +# install.sh downloads and runs this script automatically when it detects the +# legacy surfsense-data volume. You only need to run this script manually if +# you have custom database credentials (--db-user / --db-password / --db-name) +# or if the automatic migration inside install.sh fails at the extraction step. +# ============================================================================= + +set -euo pipefail + +# ── Colours ────────────────────────────────────────────────────────────────── +CYAN='\033[1;36m' +YELLOW='\033[1;33m' +GREEN='\033[0;32m' +RED='\033[0;31m' +BOLD='\033[1m' +NC='\033[0m' + +# ── Logging — tee everything to a log file ─────────────────────────────────── +LOG_FILE="./surfsense-migration.log" +exec > >(tee -a "${LOG_FILE}") 2>&1 + +# ── Output helpers ──────────────────────────────────────────────────────────── +info() { printf "${CYAN}[SurfSense]${NC} %s\n" "$1"; } +success() { printf "${GREEN}[SurfSense]${NC} %s\n" "$1"; } +warn() { printf "${YELLOW}[SurfSense]${NC} %s\n" "$1"; } +error() { printf "${RED}[SurfSense]${NC} ERROR: %s\n" "$1" >&2; exit 1; } +step() { printf "\n${BOLD}${CYAN}── Step %s: %s${NC}\n" "$1" "$2"; } + +# ── Constants ───────────────────────────────────────────────────────────────── +OLD_VOLUME="surfsense-data" +TEMP_CONTAINER="surfsense-pg14-migration" +DUMP_FILE="./surfsense_migration_backup.sql" +KEY_FILE="./surfsense_migration_secret.key" +PG14_IMAGE="pgvector/pgvector:pg14" + +# ── Defaults ────────────────────────────────────────────────────────────────── +OLD_DB_USER="surfsense" +OLD_DB_PASSWORD="surfsense" +OLD_DB_NAME="surfsense" +AUTO_YES=false + +# ── Argument parsing ────────────────────────────────────────────────────────── +while [[ $# -gt 0 ]]; do + case "$1" in + --db-user) OLD_DB_USER="$2"; shift 2 ;; + --db-password) OLD_DB_PASSWORD="$2"; shift 2 ;; + --db-name) OLD_DB_NAME="$2"; shift 2 ;; + --yes|-y) AUTO_YES=true; shift ;; + --help|-h) + grep '^#' "$0" | grep -v '^#!/' | sed 's/^# \{0,1\}//' + exit 0 + ;; + *) error "Unknown option: $1 — run with --help for usage." ;; + esac +done + +# ── Confirmation helper ─────────────────────────────────────────────────────── +confirm() { + if $AUTO_YES; then return 0; fi + printf "${YELLOW}[SurfSense]${NC} %s [y/N] " "$1" + read -r reply + [[ "$reply" =~ ^[Yy]$ ]] || { warn "Aborted."; exit 0; } +} + +# ── Cleanup trap — always remove the temp container ────────────────────────── +cleanup() { + local exit_code=$? + if docker ps -a --format '{{.Names}}' 2>/dev/null < /dev/null | grep -q "^${TEMP_CONTAINER}$"; then + info "Cleaning up temporary container '${TEMP_CONTAINER}'..." + docker stop "${TEMP_CONTAINER}" >/dev/null 2>&1 < /dev/null || true + docker rm "${TEMP_CONTAINER}" >/dev/null 2>&1 < /dev/null || true + fi + if [[ $exit_code -ne 0 ]]; then + printf "\n${RED}[SurfSense]${NC} Migration data extraction failed (exit code %s).\n" "${exit_code}" >&2 + printf "${RED}[SurfSense]${NC} Full log: %s\n" "${LOG_FILE}" >&2 + printf "${YELLOW}[SurfSense]${NC} Your original data in '${OLD_VOLUME}' is untouched.\n" >&2 + fi +} +trap cleanup EXIT + +# ── Wait-for-postgres helper ────────────────────────────────────────────────── +wait_for_pg() { + local container="$1" + local user="$2" + local label="${3:-PostgreSQL}" + local max_attempts=45 + local attempt=0 + + info "Waiting for ${label} to accept connections..." + until docker exec "${container}" pg_isready -U "${user}" -q 2>/dev/null < /dev/null; do + attempt=$((attempt + 1)) + if [[ $attempt -ge $max_attempts ]]; then + error "${label} did not become ready after $((max_attempts * 2)) seconds. Check: docker logs ${container}" + fi + printf "." + sleep 2 + done + printf "\n" + success "${label} is ready." +} + +info "Migrating data from legacy database (PostgreSQL 14 → 17)" + +# ── Step 0: Pre-flight checks ───────────────────────────────────────────────── +step "0" "Pre-flight checks" + +# Docker CLI +command -v docker >/dev/null 2>&1 \ + || error "Docker is not installed. Install it at: https://docs.docker.com/get-docker/" + +# Docker daemon +docker info >/dev/null 2>&1 < /dev/null \ + || error "Docker daemon is not running. Please start Docker and try again." + +# Old volume must exist +docker volume ls --format '{{.Name}}' < /dev/null | grep -q "^${OLD_VOLUME}$" \ + || error "Legacy volume '${OLD_VOLUME}' not found.\n Are you sure you ran the old all-in-one SurfSense container?" +success "Found legacy volume: ${OLD_VOLUME}" + +# Detect and stop any container currently using the old volume +# (mounting a live PG volume into a second container causes the new container's +# entrypoint to chown the data files, breaking the running container's access) +OLD_CONTAINER=$(docker ps --filter "volume=${OLD_VOLUME}" --format '{{.Names}}' < /dev/null | head -n1 || true) +if [[ -n "${OLD_CONTAINER}" ]]; then + warn "Container '${OLD_CONTAINER}' is running and using the '${OLD_VOLUME}' volume." + warn "It must be stopped before migration to prevent data file corruption." + confirm "Stop '${OLD_CONTAINER}' now and proceed with data extraction?" + docker stop "${OLD_CONTAINER}" >/dev/null 2>&1 < /dev/null \ + || error "Failed to stop '${OLD_CONTAINER}'. Try: docker stop ${OLD_CONTAINER}" + success "Container '${OLD_CONTAINER}' stopped." +fi + +# Bail out if a dump already exists — don't overwrite a previous successful run +if [[ -f "${DUMP_FILE}" ]]; then + warn "Dump file '${DUMP_FILE}' already exists." + warn "If a previous extraction succeeded, just run install.sh now." + warn "To re-extract, remove the file first: rm ${DUMP_FILE}" + error "Aborting to avoid overwriting an existing dump." +fi + +# Clean up any stale temp container from a previous failed run +if docker ps -a --format '{{.Names}}' < /dev/null | grep -q "^${TEMP_CONTAINER}$"; then + warn "Stale migration container '${TEMP_CONTAINER}' found — removing it." + docker stop "${TEMP_CONTAINER}" >/dev/null 2>&1 < /dev/null || true + docker rm "${TEMP_CONTAINER}" >/dev/null 2>&1 < /dev/null || true +fi + +# Disk space (warn if < 500 MB free) +if command -v df >/dev/null 2>&1; then + FREE_KB=$(df -k . | awk 'NR==2 {print $4}') + FREE_MB=$(( FREE_KB / 1024 )) + if [[ $FREE_MB -lt 500 ]]; then + warn "Low disk space: ${FREE_MB} MB free. At least 500 MB recommended for the dump." + confirm "Continue anyway?" + else + success "Disk space: ${FREE_MB} MB free." + fi +fi + +success "All pre-flight checks passed." + +# ── Confirmation prompt ─────────────────────────────────────────────────────── +printf "\n${BOLD}Extraction plan:${NC}\n" +printf " Source volume : ${YELLOW}%s${NC} (PG14 data at /data/postgres)\n" "${OLD_VOLUME}" +printf " Old credentials : user=${YELLOW}%s${NC} db=${YELLOW}%s${NC}\n" "${OLD_DB_USER}" "${OLD_DB_NAME}" +printf " Dump saved to : ${YELLOW}%s${NC}\n" "${DUMP_FILE}" +printf " SECRET_KEY to : ${YELLOW}%s${NC}\n" "${KEY_FILE}" +printf " Log file : ${YELLOW}%s${NC}\n\n" "${LOG_FILE}" +confirm "Start data extraction? (Your original data will not be deleted or modified.)" + +# ── Step 1: Start temporary PostgreSQL 14 container ────────────────────────── +step "1" "Starting temporary PostgreSQL 14 container" + +info "Pulling ${PG14_IMAGE}..." +docker pull "${PG14_IMAGE}" >/dev/null 2>&1 < /dev/null \ + || warn "Could not pull ${PG14_IMAGE} — using cached image if available." + +# Detect the UID that owns the existing data files and run the temp container +# as that user. This prevents the official postgres image entrypoint from +# running as root and doing `chown -R postgres /data/postgres`, which would +# re-own the files to UID 999 and break any subsequent access by the original +# container's postgres process (which may run as a different UID). +DATA_UID=$(docker run --rm -v "${OLD_VOLUME}:/data" alpine \ + stat -c '%u' /data/postgres 2>/dev/null < /dev/null || echo "") +if [[ -z "${DATA_UID}" || "${DATA_UID}" == "0" ]]; then + warn "Could not detect data directory UID — falling back to default (may chown files)." + USER_FLAG="" +else + info "Data directory owned by UID ${DATA_UID} — starting temp container as that user." + USER_FLAG="--user ${DATA_UID}" +fi + +docker run -d \ + --name "${TEMP_CONTAINER}" \ + -v "${OLD_VOLUME}:/data" \ + -e PGDATA=/data/postgres \ + -e POSTGRES_USER="${OLD_DB_USER}" \ + -e POSTGRES_PASSWORD="${OLD_DB_PASSWORD}" \ + -e POSTGRES_DB="${OLD_DB_NAME}" \ + ${USER_FLAG} \ + "${PG14_IMAGE}" >/dev/null < /dev/null + +success "Temporary container '${TEMP_CONTAINER}' started." +wait_for_pg "${TEMP_CONTAINER}" "${OLD_DB_USER}" "PostgreSQL 14" + +# ── Step 2: Dump the database ───────────────────────────────────────────────── +step "2" "Dumping PostgreSQL 14 database" + +info "Running pg_dump — this may take a while for large databases..." + +if ! docker exec \ + -e PGPASSWORD="${OLD_DB_PASSWORD}" \ + "${TEMP_CONTAINER}" \ + pg_dump -U "${OLD_DB_USER}" --no-password "${OLD_DB_NAME}" \ + > "${DUMP_FILE}" 2>/tmp/surfsense_pgdump_err < /dev/null; then + cat /tmp/surfsense_pgdump_err >&2 + error "pg_dump failed. See above for details." +fi + +# Validate: non-empty file +[[ -s "${DUMP_FILE}" ]] \ + || error "Dump file '${DUMP_FILE}' is empty. Something went wrong with pg_dump." + +# Validate: looks like a real PG dump +grep -q "PostgreSQL database dump" "${DUMP_FILE}" \ + || error "Dump file does not contain a valid PostgreSQL dump header — the file may be corrupt." + +# Validate: sanity-check line count +DUMP_LINES=$(wc -l < "${DUMP_FILE}" | tr -d ' ') +[[ $DUMP_LINES -ge 10 ]] \ + || error "Dump has only ${DUMP_LINES} lines — suspiciously small. Aborting." + +DUMP_SIZE=$(du -sh "${DUMP_FILE}" 2>/dev/null | cut -f1) +success "Dump complete: ${DUMP_SIZE} (${DUMP_LINES} lines) → ${DUMP_FILE}" + +# Stop the temp container (trap will also handle it on unexpected exit) +info "Stopping temporary PostgreSQL 14 container..." +docker stop "${TEMP_CONTAINER}" >/dev/null 2>&1 < /dev/null || true +docker rm "${TEMP_CONTAINER}" >/dev/null 2>&1 < /dev/null || true +success "Temporary container removed." + +# ── Step 3: Recover SECRET_KEY ──────────────────────────────────────────────── +step "3" "Recovering SECRET_KEY" + +RECOVERED_KEY="" + +if docker run --rm -v "${OLD_VOLUME}:/data" alpine \ + sh -c 'test -f /data/.secret_key && cat /data/.secret_key' \ + 2>/dev/null < /dev/null | grep -q .; then + RECOVERED_KEY=$( + docker run --rm -v "${OLD_VOLUME}:/data" alpine \ + cat /data/.secret_key 2>/dev/null < /dev/null | tr -d '[:space:]' + ) + success "Recovered SECRET_KEY from '${OLD_VOLUME}'." +else + warn "No SECRET_KEY file found at /data/.secret_key in '${OLD_VOLUME}'." + warn "This means the all-in-one container was launched with SECRET_KEY set as an explicit env var." + if $AUTO_YES; then + # Non-interactive (called from install.sh) — auto-generate rather than hanging on read + RECOVERED_KEY=$(openssl rand -base64 32 2>/dev/null \ + || head -c 32 /dev/urandom | base64 | tr -d '\n') + warn "Non-interactive mode: generated a new SECRET_KEY automatically." + warn "All active browser sessions will be logged out after migration." + warn "To restore your original key, update SECRET_KEY in ./surfsense/.env afterwards." + else + printf "${YELLOW}[SurfSense]${NC} Enter the SECRET_KEY from your old container's environment\n" + printf "${YELLOW}[SurfSense]${NC} (press Enter to generate a new one — existing sessions will be invalidated): " + read -r RECOVERED_KEY + if [[ -z "${RECOVERED_KEY}" ]]; then + RECOVERED_KEY=$(openssl rand -base64 32 2>/dev/null \ + || head -c 32 /dev/urandom | base64 | tr -d '\n') + warn "Generated a new SECRET_KEY. All active browser sessions will be logged out after migration." + fi + fi +fi + +# Save SECRET_KEY to a file for install.sh to pick up +printf '%s' "${RECOVERED_KEY}" > "${KEY_FILE}" +success "SECRET_KEY saved to ${KEY_FILE}" + +# ── Done ────────────────────────────────────────────────────────────────────── +printf "\n${GREEN}${BOLD}" +printf "══════════════════════════════════════════════════════════════\n" +printf " Data extraction complete!\n" +printf "══════════════════════════════════════════════════════════════\n" +printf "${NC}\n" + +success "Dump file : ${DUMP_FILE} (${DUMP_SIZE})" +success "Secret key: ${KEY_FILE}" +printf "\n" +info "Next step — run install.sh from this same directory:" +printf "\n" +printf "${CYAN} curl -fsSL https://raw.githubusercontent.com/MODSetter/SurfSense/main/docker/scripts/install.sh | bash${NC}\n" +printf "\n" +info "install.sh will detect the dump, restore your data into PostgreSQL 17," +info "and start the full SurfSense stack automatically." +printf "\n" +warn "Keep both files until you have verified the migration:" +warn " ${DUMP_FILE}" +warn " ${KEY_FILE}" +warn "Full log saved to: ${LOG_FILE}" +printf "\n" diff --git a/scripts/docker/entrypoint-allinone.sh b/scripts/docker/entrypoint-allinone.sh deleted file mode 100644 index 4f88b3382..000000000 --- a/scripts/docker/entrypoint-allinone.sh +++ /dev/null @@ -1,243 +0,0 @@ -#!/bin/bash -set -e - -echo "===========================================" -echo " 🏄 SurfSense All-in-One Container" -echo "===========================================" - -# Create log directory -mkdir -p /var/log/supervisor - -# ================================================ -# Ensure data directory exists -# ================================================ -mkdir -p /data - -# ================================================ -# Generate SECRET_KEY if not provided -# ================================================ -if [ -z "$SECRET_KEY" ]; then - # Generate a random secret key and persist it - if [ -f /data/.secret_key ]; then - export SECRET_KEY=$(cat /data/.secret_key) - echo "✅ Using existing SECRET_KEY from persistent storage" - else - export SECRET_KEY=$(python3 -c "import secrets; print(secrets.token_urlsafe(32))") - echo "$SECRET_KEY" > /data/.secret_key - chmod 600 /data/.secret_key - echo "✅ Generated new SECRET_KEY (saved for persistence)" - fi -fi - -# ================================================ -# Set default TTS/STT services if not provided -# ================================================ -if [ -z "$TTS_SERVICE" ]; then - export TTS_SERVICE="local/kokoro" - echo "✅ Using default TTS_SERVICE: local/kokoro" -fi - -if [ -z "$STT_SERVICE" ]; then - export STT_SERVICE="local/base" - echo "✅ Using default STT_SERVICE: local/base" -fi - -# ================================================ -# Set Electric SQL configuration -# ================================================ -export ELECTRIC_DB_USER="${ELECTRIC_DB_USER:-electric}" -export ELECTRIC_DB_PASSWORD="${ELECTRIC_DB_PASSWORD:-electric_password}" -if [ -z "$ELECTRIC_DATABASE_URL" ]; then - export ELECTRIC_DATABASE_URL="postgresql://${ELECTRIC_DB_USER}:${ELECTRIC_DB_PASSWORD}@localhost:5432/${POSTGRES_DB:-surfsense}?sslmode=disable" - echo "✅ Electric SQL URL configured dynamically" -else - # Ensure sslmode=disable is in the URL if not already present - if [[ "$ELECTRIC_DATABASE_URL" != *"sslmode="* ]]; then - # Add sslmode=disable (handle both cases: with or without existing query params) - if [[ "$ELECTRIC_DATABASE_URL" == *"?"* ]]; then - export ELECTRIC_DATABASE_URL="${ELECTRIC_DATABASE_URL}&sslmode=disable" - else - export ELECTRIC_DATABASE_URL="${ELECTRIC_DATABASE_URL}?sslmode=disable" - fi - fi - echo "✅ Electric SQL URL configured from environment" -fi - -# Set Electric SQL port -export ELECTRIC_PORT="${ELECTRIC_PORT:-5133}" -export PORT="${ELECTRIC_PORT}" - -# ================================================ -# Initialize PostgreSQL if needed -# ================================================ -if [ ! -f /data/postgres/PG_VERSION ]; then - echo "📦 Initializing PostgreSQL database..." - - # Initialize PostgreSQL data directory - chown -R postgres:postgres /data/postgres - chmod 700 /data/postgres - - # Initialize with UTF8 encoding (required for proper text handling) - su - postgres -c "/usr/lib/postgresql/14/bin/initdb -D /data/postgres --encoding=UTF8 --locale=C.UTF-8" - - # Configure PostgreSQL for connections - echo "host all all 0.0.0.0/0 md5" >> /data/postgres/pg_hba.conf - echo "local all all trust" >> /data/postgres/pg_hba.conf - echo "listen_addresses='*'" >> /data/postgres/postgresql.conf - - # Enable logical replication for Electric SQL - echo "wal_level = logical" >> /data/postgres/postgresql.conf - echo "max_replication_slots = 10" >> /data/postgres/postgresql.conf - echo "max_wal_senders = 10" >> /data/postgres/postgresql.conf - - # Start PostgreSQL temporarily to create database and user - su - postgres -c "/usr/lib/postgresql/14/bin/pg_ctl -D /data/postgres -l /tmp/postgres_init.log start" - - # Wait for PostgreSQL to be ready - sleep 5 - - # Create user and database - su - postgres -c "psql -c \"CREATE USER ${POSTGRES_USER:-surfsense} WITH PASSWORD '${POSTGRES_PASSWORD:-surfsense}' SUPERUSER;\"" - su - postgres -c "psql -c \"CREATE DATABASE ${POSTGRES_DB:-surfsense} OWNER ${POSTGRES_USER:-surfsense};\"" - - # Enable pgvector extension - su - postgres -c "psql -d ${POSTGRES_DB:-surfsense} -c 'CREATE EXTENSION IF NOT EXISTS vector;'" - - # Create Electric SQL replication user (idempotent - uses IF NOT EXISTS) - echo "📡 Creating Electric SQL replication user..." - su - postgres -c "psql -d ${POSTGRES_DB:-surfsense} <<-EOSQL - DO \\\$\\\$ - BEGIN - IF NOT EXISTS (SELECT FROM pg_user WHERE usename = '${ELECTRIC_DB_USER}') THEN - CREATE USER ${ELECTRIC_DB_USER} WITH REPLICATION PASSWORD '${ELECTRIC_DB_PASSWORD}'; - END IF; - END - \\\$\\\$; - - GRANT CONNECT ON DATABASE ${POSTGRES_DB:-surfsense} TO ${ELECTRIC_DB_USER}; - GRANT USAGE ON SCHEMA public TO ${ELECTRIC_DB_USER}; - GRANT SELECT ON ALL TABLES IN SCHEMA public TO ${ELECTRIC_DB_USER}; - GRANT SELECT ON ALL SEQUENCES IN SCHEMA public TO ${ELECTRIC_DB_USER}; - ALTER DEFAULT PRIVILEGES IN SCHEMA public GRANT SELECT ON TABLES TO ${ELECTRIC_DB_USER}; - ALTER DEFAULT PRIVILEGES IN SCHEMA public GRANT SELECT ON SEQUENCES TO ${ELECTRIC_DB_USER}; - - -- Create the publication for Electric SQL (if not exists) - DO \\\$\\\$ - BEGIN - IF NOT EXISTS (SELECT FROM pg_publication WHERE pubname = 'electric_publication_default') THEN - CREATE PUBLICATION electric_publication_default; - END IF; - END - \\\$\\\$; -EOSQL" - echo "✅ Electric SQL user '${ELECTRIC_DB_USER}' created" - - # Stop temporary PostgreSQL - su - postgres -c "/usr/lib/postgresql/14/bin/pg_ctl -D /data/postgres stop" - - echo "✅ PostgreSQL initialized successfully" -else - echo "✅ PostgreSQL data directory already exists" -fi - -# ================================================ -# Initialize Redis data directory -# ================================================ -mkdir -p /data/redis -chmod 755 /data/redis -echo "✅ Redis data directory ready" - -# ================================================ -# Copy frontend build to runtime location -# ================================================ -if [ -d /app/frontend/.next/standalone ]; then - cp -r /app/frontend/.next/standalone/* /app/frontend/ 2>/dev/null || true - cp -r /app/frontend/.next/static /app/frontend/.next/static 2>/dev/null || true -fi - -# ================================================ -# Runtime Environment Variable Replacement -# ================================================ -# Next.js NEXT_PUBLIC_* vars are baked in at build time. -# This replaces placeholder values with actual runtime env vars. -echo "🔧 Applying runtime environment configuration..." - -# Set defaults if not provided -NEXT_PUBLIC_FASTAPI_BACKEND_URL="${NEXT_PUBLIC_FASTAPI_BACKEND_URL:-http://localhost:8000}" -NEXT_PUBLIC_FASTAPI_BACKEND_AUTH_TYPE="${NEXT_PUBLIC_FASTAPI_BACKEND_AUTH_TYPE:-LOCAL}" -NEXT_PUBLIC_ETL_SERVICE="${NEXT_PUBLIC_ETL_SERVICE:-DOCLING}" -NEXT_PUBLIC_ELECTRIC_URL="${NEXT_PUBLIC_ELECTRIC_URL:-http://localhost:5133}" -NEXT_PUBLIC_ELECTRIC_AUTH_MODE="${NEXT_PUBLIC_ELECTRIC_AUTH_MODE:-insecure}" -NEXT_PUBLIC_DEPLOYMENT_MODE="${NEXT_PUBLIC_DEPLOYMENT_MODE:-self-hosted}" - -# Replace placeholders in all JS files -find /app/frontend -type f \( -name "*.js" -o -name "*.json" \) -exec sed -i \ - -e "s|__NEXT_PUBLIC_FASTAPI_BACKEND_URL__|${NEXT_PUBLIC_FASTAPI_BACKEND_URL}|g" \ - -e "s|__NEXT_PUBLIC_FASTAPI_BACKEND_AUTH_TYPE__|${NEXT_PUBLIC_FASTAPI_BACKEND_AUTH_TYPE}|g" \ - -e "s|__NEXT_PUBLIC_ETL_SERVICE__|${NEXT_PUBLIC_ETL_SERVICE}|g" \ - -e "s|__NEXT_PUBLIC_ELECTRIC_URL__|${NEXT_PUBLIC_ELECTRIC_URL}|g" \ - -e "s|__NEXT_PUBLIC_ELECTRIC_AUTH_MODE__|${NEXT_PUBLIC_ELECTRIC_AUTH_MODE}|g" \ - -e "s|__NEXT_PUBLIC_DEPLOYMENT_MODE__|${NEXT_PUBLIC_DEPLOYMENT_MODE}|g" \ - {} + - -echo "✅ Environment configuration applied" -echo " Backend URL: ${NEXT_PUBLIC_FASTAPI_BACKEND_URL}" -echo " Auth Type: ${NEXT_PUBLIC_FASTAPI_BACKEND_AUTH_TYPE}" -echo " ETL Service: ${NEXT_PUBLIC_ETL_SERVICE}" -echo " Electric URL: ${NEXT_PUBLIC_ELECTRIC_URL}" -echo " Deployment Mode: ${NEXT_PUBLIC_DEPLOYMENT_MODE}" - -# ================================================ -# Run database migrations -# ================================================ -run_migrations() { - echo "🔄 Running database migrations..." - - # Start PostgreSQL temporarily for migrations - su - postgres -c "/usr/lib/postgresql/14/bin/pg_ctl -D /data/postgres -l /tmp/postgres_migrate.log start" - sleep 5 - - # Start Redis temporarily for migrations (some might need it) - redis-server --dir /data/redis --daemonize yes - sleep 2 - - # Run alembic migrations - cd /app/backend - alembic upgrade head || echo "⚠️ Migrations may have already been applied" - - # Stop temporary services - redis-cli shutdown || true - su - postgres -c "/usr/lib/postgresql/14/bin/pg_ctl -D /data/postgres stop" - - echo "✅ Database migrations complete" -} - -# Always run migrations on startup - alembic upgrade head is safe to run -# every time. It only applies pending migrations (never re-runs applied ones, -# never calls downgrade). This ensures updates are applied automatically. -run_migrations - -# ================================================ -# Environment Variables Info -# ================================================ -echo "" -echo "===========================================" -echo " 📋 Configuration" -echo "===========================================" -echo " Frontend URL: http://localhost:3000" -echo " Backend API: ${NEXT_PUBLIC_FASTAPI_BACKEND_URL}" -echo " API Docs: ${NEXT_PUBLIC_FASTAPI_BACKEND_URL}/docs" -echo " Electric URL: ${NEXT_PUBLIC_ELECTRIC_URL:-http://localhost:5133}" -echo " Auth Type: ${NEXT_PUBLIC_FASTAPI_BACKEND_AUTH_TYPE}" -echo " ETL Service: ${NEXT_PUBLIC_ETL_SERVICE}" -echo " TTS Service: ${TTS_SERVICE}" -echo " STT Service: ${STT_SERVICE}" -echo "===========================================" -echo "" - -# ================================================ -# Start Supervisor (manages all services) -# ================================================ -echo "🚀 Starting all services..." -exec /usr/local/bin/supervisord -c /etc/supervisor/conf.d/surfsense.conf - diff --git a/scripts/docker/init-postgres.sh b/scripts/docker/init-postgres.sh deleted file mode 100644 index b6ddb6a50..000000000 --- a/scripts/docker/init-postgres.sh +++ /dev/null @@ -1,77 +0,0 @@ -#!/bin/bash -# PostgreSQL initialization script for SurfSense -# This script is called during container startup if the database needs initialization - -set -e - -PGDATA=${PGDATA:-/data/postgres} -POSTGRES_USER=${POSTGRES_USER:-surfsense} -POSTGRES_PASSWORD=${POSTGRES_PASSWORD:-surfsense} -POSTGRES_DB=${POSTGRES_DB:-surfsense} - -# Electric SQL user credentials (configurable) -ELECTRIC_DB_USER=${ELECTRIC_DB_USER:-electric} -ELECTRIC_DB_PASSWORD=${ELECTRIC_DB_PASSWORD:-electric_password} - -echo "Initializing PostgreSQL..." - -# Check if PostgreSQL is already initialized -if [ -f "$PGDATA/PG_VERSION" ]; then - echo "PostgreSQL data directory already exists. Skipping initialization." - exit 0 -fi - -# Initialize the database cluster -/usr/lib/postgresql/14/bin/initdb -D "$PGDATA" --username=postgres - -# Configure PostgreSQL -cat >> "$PGDATA/postgresql.conf" << EOF -listen_addresses = '*' -max_connections = 200 -shared_buffers = 256MB - -# Enable logical replication (required for Electric SQL) -wal_level = logical -max_replication_slots = 10 -max_wal_senders = 10 - -# Performance settings -checkpoint_timeout = 10min -max_wal_size = 1GB -min_wal_size = 80MB -EOF - -cat >> "$PGDATA/pg_hba.conf" << EOF -# Allow connections from anywhere with password -host all all 0.0.0.0/0 md5 -host all all ::0/0 md5 -EOF - -# Start PostgreSQL temporarily -/usr/lib/postgresql/14/bin/pg_ctl -D "$PGDATA" -l /tmp/postgres_init.log start - -# Wait for PostgreSQL to start -sleep 3 - -# Create user and database -psql -U postgres << EOF -CREATE USER $POSTGRES_USER WITH PASSWORD '$POSTGRES_PASSWORD' SUPERUSER; -CREATE DATABASE $POSTGRES_DB OWNER $POSTGRES_USER; -\c $POSTGRES_DB -CREATE EXTENSION IF NOT EXISTS vector; - --- Create Electric SQL replication user -CREATE USER $ELECTRIC_DB_USER WITH REPLICATION PASSWORD '$ELECTRIC_DB_PASSWORD'; -GRANT CONNECT ON DATABASE $POSTGRES_DB TO $ELECTRIC_DB_USER; -GRANT USAGE ON SCHEMA public TO $ELECTRIC_DB_USER; -GRANT SELECT ON ALL TABLES IN SCHEMA public TO $ELECTRIC_DB_USER; -GRANT SELECT ON ALL SEQUENCES IN SCHEMA public TO $ELECTRIC_DB_USER; -ALTER DEFAULT PRIVILEGES IN SCHEMA public GRANT SELECT ON TABLES TO $ELECTRIC_DB_USER; -ALTER DEFAULT PRIVILEGES IN SCHEMA public GRANT SELECT ON SEQUENCES TO $ELECTRIC_DB_USER; -EOF - -echo "PostgreSQL initialized successfully." - -# Stop PostgreSQL (supervisor will start it) -/usr/lib/postgresql/14/bin/pg_ctl -D "$PGDATA" stop - diff --git a/scripts/docker/supervisor-allinone.conf b/scripts/docker/supervisor-allinone.conf deleted file mode 100644 index 1a21fcc04..000000000 --- a/scripts/docker/supervisor-allinone.conf +++ /dev/null @@ -1,121 +0,0 @@ -[supervisord] -nodaemon=true -logfile=/dev/stdout -logfile_maxbytes=0 -pidfile=/var/run/supervisord.pid -loglevel=info -user=root - -[unix_http_server] -file=/var/run/supervisor.sock -chmod=0700 - -[rpcinterface:supervisor] -supervisor.rpcinterface_factory = supervisor.rpcinterface:make_main_rpcinterface - -[supervisorctl] -serverurl=unix:///var/run/supervisor.sock - -# PostgreSQL -[program:postgresql] -command=/usr/lib/postgresql/14/bin/postgres -D /data/postgres -user=postgres -autostart=true -autorestart=true -priority=10 -stdout_logfile=/dev/stdout -stdout_logfile_maxbytes=0 -stderr_logfile=/dev/stderr -stderr_logfile_maxbytes=0 -environment=PGDATA="/data/postgres" - -# Redis -[program:redis] -command=/usr/bin/redis-server --dir /data/redis --appendonly yes -autostart=true -autorestart=true -priority=20 -stdout_logfile=/dev/stdout -stdout_logfile_maxbytes=0 -stderr_logfile=/dev/stderr -stderr_logfile_maxbytes=0 - -# Backend API -[program:backend] -command=python main.py -directory=/app/backend -autostart=true -autorestart=true -priority=30 -startsecs=10 -startretries=3 -stdout_logfile=/dev/stdout -stdout_logfile_maxbytes=0 -stderr_logfile=/dev/stderr -stderr_logfile_maxbytes=0 -environment=PYTHONPATH="/app/backend",UVICORN_LOOP="asyncio",UNSTRUCTURED_HAS_PATCHED_LOOP="1" - -# Celery Worker -[program:celery-worker] -command=celery -A app.celery_app worker --loglevel=info --concurrency=2 --pool=solo --queues=surfsense,surfsense.connectors -directory=/app/backend -autostart=true -autorestart=true -priority=40 -startsecs=15 -startretries=3 -stdout_logfile=/dev/stdout -stdout_logfile_maxbytes=0 -stderr_logfile=/dev/stderr -stderr_logfile_maxbytes=0 -environment=PYTHONPATH="/app/backend" - -# Celery Beat (scheduler) -[program:celery-beat] -command=celery -A app.celery_app beat --loglevel=info -directory=/app/backend -autostart=true -autorestart=true -priority=50 -startsecs=20 -startretries=3 -stdout_logfile=/dev/stdout -stdout_logfile_maxbytes=0 -stderr_logfile=/dev/stderr -stderr_logfile_maxbytes=0 -environment=PYTHONPATH="/app/backend" - -# Electric SQL (real-time sync) -[program:electric] -command=/app/electric-release/bin/entrypoint start -autostart=true -autorestart=true -priority=25 -startsecs=10 -startretries=3 -stdout_logfile=/dev/stdout -stdout_logfile_maxbytes=0 -stderr_logfile=/dev/stderr -stderr_logfile_maxbytes=0 -environment=DATABASE_URL="%(ENV_ELECTRIC_DATABASE_URL)s",ELECTRIC_INSECURE="%(ENV_ELECTRIC_INSECURE)s",ELECTRIC_WRITE_TO_PG_MODE="%(ENV_ELECTRIC_WRITE_TO_PG_MODE)s",RELEASE_COOKIE="surfsense_electric_cookie",PORT="%(ENV_ELECTRIC_PORT)s" - -# Frontend -[program:frontend] -command=node server.js -directory=/app/frontend -autostart=true -autorestart=true -priority=60 -startsecs=5 -startretries=3 -stdout_logfile=/dev/stdout -stdout_logfile_maxbytes=0 -stderr_logfile=/dev/stderr -stderr_logfile_maxbytes=0 -environment=NODE_ENV="production",PORT="3000",HOSTNAME="0.0.0.0" - -# Process Groups -[group:surfsense] -programs=postgresql,redis,electric,backend,celery-worker,celery-beat,frontend -priority=999 - diff --git a/surfsense_backend/.env.example b/surfsense_backend/.env.example index 9aa4b0b34..0af368081 100644 --- a/surfsense_backend/.env.example +++ b/surfsense_backend/.env.example @@ -167,37 +167,12 @@ LANGSMITH_ENDPOINT=https://api.smith.langchain.com LANGSMITH_API_KEY=lsv2_pt_..... LANGSMITH_PROJECT=surfsense -# Uvicorn Server Configuration -# Full documentation for Uvicorn options can be found at: https://www.uvicorn.org/#command-line-options -UVICORN_HOST="0.0.0.0" -UVICORN_PORT=8000 -UVICORN_LOG_LEVEL=info - -# OPTIONAL: Advanced Uvicorn Options (uncomment to use) -# UVICORN_PROXY_HEADERS=false -# UVICORN_FORWARDED_ALLOW_IPS="127.0.0.1" -# UVICORN_WORKERS=1 -# UVICORN_ACCESS_LOG=true -# UVICORN_LOOP="auto" -# UVICORN_HTTP="auto" -# UVICORN_WS="auto" -# UVICORN_LIFESPAN="auto" -# UVICORN_LOG_CONFIG="" -# UVICORN_SERVER_HEADER=true -# UVICORN_DATE_HEADER=true -# UVICORN_LIMIT_CONCURRENCY= -# UVICORN_LIMIT_MAX_REQUESTS= -# UVICORN_TIMEOUT_KEEP_ALIVE=5 -# UVICORN_TIMEOUT_NOTIFY=30 -# UVICORN_SSL_KEYFILE="" -# UVICORN_SSL_CERTFILE="" -# UVICORN_SSL_KEYFILE_PASSWORD="" -# UVICORN_SSL_VERSION="" -# UVICORN_SSL_CERT_REQS="" -# UVICORN_SSL_CA_CERTS="" -# UVICORN_SSL_CIPHERS="" -# UVICORN_HEADERS="" -# UVICORN_USE_COLORS=true -# UVICORN_UDS="" -# UVICORN_FD="" -# UVICORN_ROOT_PATH="" +# Agent Specific Configuration +# Daytona Sandbox (secure cloud code execution for deep agent) +# Set DAYTONA_SANDBOX_ENABLED=TRUE to give the agent an isolated execute tool +DAYTONA_SANDBOX_ENABLED=TRUE +DAYTONA_API_KEY=dtn_asdasfasfafas +DAYTONA_API_URL=https://app.daytona.io/api +DAYTONA_TARGET=us +# Directory for locally-persisted sandbox files (after sandbox deletion) +SANDBOX_FILES_DIR=sandbox_files diff --git a/surfsense_backend/.gitignore b/surfsense_backend/.gitignore index 13a523310..0b1374b29 100644 --- a/surfsense_backend/.gitignore +++ b/surfsense_backend/.gitignore @@ -6,6 +6,7 @@ __pycache__/ .flashrank_cache surf_new_backend.egg-info/ podcasts/ +sandbox_files/ temp_audio/ celerybeat-schedule* celerybeat-schedule.* diff --git a/surfsense_backend/Dockerfile b/surfsense_backend/Dockerfile index 4f24d2b05..1222b36b6 100644 --- a/surfsense_backend/Dockerfile +++ b/surfsense_backend/Dockerfile @@ -88,6 +88,13 @@ ENV TMPDIR=/shared_tmp ENV PYTHONPATH=/app ENV UVICORN_LOOP=asyncio +# Tune glibc malloc to return freed memory to the OS more aggressively. +# Without these, Python's gc.collect() frees objects but the underlying +# C heap pages stay mapped (RSS never drops) due to sbrk fragmentation. +ENV MALLOC_MMAP_THRESHOLD_=65536 +ENV MALLOC_TRIM_THRESHOLD_=131072 +ENV MALLOC_MMAP_MAX_=65536 + # SERVICE_ROLE controls which process this container runs: # api – FastAPI backend only (runs migrations on startup) # worker – Celery worker only diff --git a/surfsense_backend/alembic/versions/102_add_enable_summary_to_connectors.py b/surfsense_backend/alembic/versions/102_add_enable_summary_to_connectors.py new file mode 100644 index 000000000..ae5fc0e02 --- /dev/null +++ b/surfsense_backend/alembic/versions/102_add_enable_summary_to_connectors.py @@ -0,0 +1,46 @@ +"""102_add_enable_summary_to_connectors + +Revision ID: 102 +Revises: 101 +Create Date: 2026-02-26 + +Adds enable_summary boolean column to search_source_connectors. +Defaults to False for all existing and new connectors so LLM-based +summary generation is opt-in. +""" + +from __future__ import annotations + +from collections.abc import Sequence + +import sqlalchemy as sa + +from alembic import op + +# revision identifiers, used by Alembic. +revision: str = "102" +down_revision: str | None = "101" +branch_labels: str | Sequence[str] | None = None +depends_on: str | Sequence[str] | None = None + + +def upgrade() -> None: + conn = op.get_bind() + existing_columns = [ + col["name"] for col in sa.inspect(conn).get_columns("search_source_connectors") + ] + + if "enable_summary" not in existing_columns: + op.add_column( + "search_source_connectors", + sa.Column( + "enable_summary", + sa.Boolean(), + nullable=False, + server_default=sa.text("false"), + ), + ) + + +def downgrade() -> None: + op.drop_column("search_source_connectors", "enable_summary") diff --git a/surfsense_backend/alembic/versions/66_add_notifications_table_and_electric_replication.py b/surfsense_backend/alembic/versions/66_add_notifications_table_and_electric_replication.py index 182bf981c..35418c6ae 100644 --- a/surfsense_backend/alembic/versions/66_add_notifications_table_and_electric_replication.py +++ b/surfsense_backend/alembic/versions/66_add_notifications_table_and_electric_replication.py @@ -8,7 +8,7 @@ Creates notifications table and sets up Electric SQL replication search_source_connectors, and documents tables. NOTE: Electric SQL user creation is idempotent (uses IF NOT EXISTS). -- Docker deployments: user is pre-created by scripts/docker/init-electric-user.sh +- Docker deployments: user is pre-created by docker/scripts/init-electric-user.sh - Local PostgreSQL: user is created here during migration Both approaches are safe to run together without conflicts as this migraiton is idempotent """ diff --git a/surfsense_backend/app/agents/new_chat/chat_deepagent.py b/surfsense_backend/app/agents/new_chat/chat_deepagent.py index f4af16b78..af0d6bdc5 100644 --- a/surfsense_backend/app/agents/new_chat/chat_deepagent.py +++ b/surfsense_backend/app/agents/new_chat/chat_deepagent.py @@ -6,10 +6,14 @@ with configurable tools via the tools registry and configurable prompts via NewLLMConfig. """ +import asyncio +import logging +import time from collections.abc import Sequence from typing import Any from deepagents import create_deep_agent +from deepagents.backends.protocol import SandboxBackendProtocol from langchain_core.language_models import BaseChatModel from langchain_core.tools import BaseTool from langgraph.types import Checkpointer @@ -24,6 +28,9 @@ from app.agents.new_chat.system_prompt import ( from app.agents.new_chat.tools.registry import build_tools_async from app.db import ChatVisibility from app.services.connector_service import ConnectorService +from app.utils.perf import get_perf_logger + +_perf_log = get_perf_logger() # ============================================================================= # Connector Type Mapping @@ -128,6 +135,7 @@ async def create_surfsense_deep_agent( additional_tools: Sequence[BaseTool] | None = None, firecrawl_api_key: str | None = None, thread_visibility: ChatVisibility | None = None, + sandbox_backend: SandboxBackendProtocol | None = None, ): """ Create a SurfSense deep agent with configurable tools and prompts. @@ -167,6 +175,9 @@ async def create_surfsense_deep_agent( These are always added regardless of enabled/disabled settings. firecrawl_api_key: Optional Firecrawl API key for premium web scraping. Falls back to Chromium/Trafilatura if not provided. + sandbox_backend: Optional sandbox backend (e.g. DaytonaSandbox) for + secure code execution. When provided, the agent gets an + isolated ``execute`` tool for running shell commands. Returns: CompiledStateGraph: The configured deep agent @@ -205,32 +216,41 @@ async def create_surfsense_deep_agent( additional_tools=[my_custom_tool] ) """ + _t_agent_total = time.perf_counter() + # Discover available connectors and document types for this search space - # This enables dynamic tool docstrings that inform the LLM about what's actually available available_connectors: list[str] | None = None available_document_types: list[str] | None = None + _t0 = time.perf_counter() try: - # Get enabled search source connectors for this search space connector_types = await connector_service.get_available_connectors( search_space_id ) if connector_types: - # Convert enum values to strings and also include mapped document types available_connectors = _map_connectors_to_searchable_types(connector_types) - # Get document types that have at least one document indexed available_document_types = await connector_service.get_available_document_types( search_space_id ) except Exception as e: - # Log but don't fail - fall back to all connectors if discovery fails - import logging - logging.warning(f"Failed to discover available connectors/document types: {e}") + _perf_log.info( + "[create_agent] Connector/doc-type discovery in %.3fs", + time.perf_counter() - _t0, + ) # Build dependencies dict for the tools registry visibility = thread_visibility or ChatVisibility.PRIVATE + + # Extract the model's context window so tools can size their output. + _model_profile = getattr(llm, "profile", None) + _max_input_tokens: int | None = ( + _model_profile.get("max_input_tokens") + if isinstance(_model_profile, dict) + else None + ) + dependencies = { "search_space_id": search_space_id, "db_session": db_session, @@ -241,6 +261,7 @@ async def create_surfsense_deep_agent( "thread_visibility": visibility, "available_connectors": available_connectors, "available_document_types": available_document_types, + "max_input_tokens": _max_input_tokens, } # Disable Notion action tools if no Notion connector is configured @@ -269,35 +290,61 @@ async def create_surfsense_deep_agent( modified_disabled_tools.extend(linear_tools) # Build tools using the async registry (includes MCP tools) + _t0 = time.perf_counter() tools = await build_tools_async( dependencies=dependencies, enabled_tools=enabled_tools, disabled_tools=modified_disabled_tools, additional_tools=list(additional_tools) if additional_tools else None, ) + _perf_log.info( + "[create_agent] build_tools_async in %.3fs (%d tools)", + time.perf_counter() - _t0, + len(tools), + ) # Build system prompt based on agent_config + _t0 = time.perf_counter() + _sandbox_enabled = sandbox_backend is not None if agent_config is not None: - # Use configurable prompt with settings from NewLLMConfig system_prompt = build_configurable_system_prompt( custom_system_instructions=agent_config.system_instructions, use_default_system_instructions=agent_config.use_default_system_instructions, citations_enabled=agent_config.citations_enabled, thread_visibility=thread_visibility, + sandbox_enabled=_sandbox_enabled, ) else: system_prompt = build_surfsense_system_prompt( thread_visibility=thread_visibility, + sandbox_enabled=_sandbox_enabled, ) + _perf_log.info( + "[create_agent] System prompt built in %.3fs", time.perf_counter() - _t0 + ) - # Create the deep agent with system prompt and checkpointer - # Note: TodoListMiddleware (write_todos) is included by default in create_deep_agent - agent = create_deep_agent( + # Build optional kwargs for the deep agent + deep_agent_kwargs: dict[str, Any] = {} + if sandbox_backend is not None: + deep_agent_kwargs["backend"] = sandbox_backend + + _t0 = time.perf_counter() + agent = await asyncio.to_thread( + create_deep_agent, model=llm, tools=tools, system_prompt=system_prompt, context_schema=SurfSenseContextSchema, checkpointer=checkpointer, + **deep_agent_kwargs, + ) + _perf_log.info( + "[create_agent] Graph compiled (create_deep_agent) in %.3fs", + time.perf_counter() - _t0, ) + _perf_log.info( + "[create_agent] Total agent creation in %.3fs", + time.perf_counter() - _t_agent_total, + ) return agent diff --git a/surfsense_backend/app/agents/new_chat/llm_config.py b/surfsense_backend/app/agents/new_chat/llm_config.py index bf16b2fe9..2b1c07cda 100644 --- a/surfsense_backend/app/agents/new_chat/llm_config.py +++ b/surfsense_backend/app/agents/new_chat/llm_config.py @@ -22,6 +22,7 @@ from app.services.llm_router_service import ( AUTO_MODE_ID, ChatLiteLLMRouter, LLMRouterService, + get_auto_mode_llm, is_auto_mode, ) @@ -389,7 +390,7 @@ def create_chat_litellm_from_agent_config( print("Error: Auto mode requested but LLM Router not initialized") return None try: - return ChatLiteLLMRouter() + return get_auto_mode_llm() except Exception as e: print(f"Error creating ChatLiteLLMRouter: {e}") return None diff --git a/surfsense_backend/app/agents/new_chat/sandbox.py b/surfsense_backend/app/agents/new_chat/sandbox.py new file mode 100644 index 000000000..8b634993b --- /dev/null +++ b/surfsense_backend/app/agents/new_chat/sandbox.py @@ -0,0 +1,282 @@ +""" +Daytona sandbox provider for SurfSense deep agent. + +Manages the lifecycle of sandboxed code execution environments. +Each conversation thread gets its own isolated sandbox instance +via the Daytona cloud API, identified by labels. + +Files created during a session are persisted to local storage before +the sandbox is deleted so they remain downloadable after cleanup. +""" + +from __future__ import annotations + +import asyncio +import contextlib +import logging +import os +import shutil +from pathlib import Path + +from daytona import ( + CreateSandboxFromSnapshotParams, + Daytona, + DaytonaConfig, + SandboxState, +) +from daytona.common.errors import DaytonaError +from deepagents.backends.protocol import ExecuteResponse +from langchain_daytona import DaytonaSandbox + +logger = logging.getLogger(__name__) + + +class _TimeoutAwareSandbox(DaytonaSandbox): + """DaytonaSandbox subclass that accepts the per-command *timeout* + kwarg required by the deepagents middleware. + + The upstream ``langchain-daytona`` ``execute()`` ignores timeout, + so deepagents raises *"This sandbox backend does not support + per-command timeout overrides"* on every first call. This thin + wrapper forwards the parameter to the Daytona SDK. + """ + + def execute(self, command: str, *, timeout: int | None = None) -> ExecuteResponse: + t = timeout if timeout is not None else self._timeout + result = self._sandbox.process.exec(command, timeout=t) + return ExecuteResponse( + output=result.result, + exit_code=result.exit_code, + truncated=False, + ) + + async def aexecute( + self, command: str, *, timeout: int | None = None + ) -> ExecuteResponse: # type: ignore[override] + return await asyncio.to_thread(self.execute, command, timeout=timeout) + + +_daytona_client: Daytona | None = None +_sandbox_cache: dict[str, _TimeoutAwareSandbox] = {} +_SANDBOX_CACHE_MAX_SIZE = 20 +THREAD_LABEL_KEY = "surfsense_thread" + + +def is_sandbox_enabled() -> bool: + return os.environ.get("DAYTONA_SANDBOX_ENABLED", "FALSE").upper() == "TRUE" + + +def _get_client() -> Daytona: + global _daytona_client + if _daytona_client is None: + config = DaytonaConfig( + api_key=os.environ.get("DAYTONA_API_KEY", ""), + api_url=os.environ.get("DAYTONA_API_URL", "https://app.daytona.io/api"), + target=os.environ.get("DAYTONA_TARGET", "us"), + ) + _daytona_client = Daytona(config) + return _daytona_client + + +def _find_or_create(thread_id: str) -> _TimeoutAwareSandbox: + """Find an existing sandbox for *thread_id*, or create a new one. + + If an existing sandbox is found but is stopped/archived, it will be + restarted automatically before returning. + """ + client = _get_client() + labels = {THREAD_LABEL_KEY: thread_id} + + try: + sandbox = client.find_one(labels=labels) + logger.info("Found existing sandbox %s (state=%s)", sandbox.id, sandbox.state) + + if sandbox.state in ( + SandboxState.STOPPED, + SandboxState.STOPPING, + SandboxState.ARCHIVED, + ): + logger.info("Starting stopped sandbox %s …", sandbox.id) + sandbox.start(timeout=60) + logger.info("Sandbox %s is now started", sandbox.id) + elif sandbox.state in ( + SandboxState.ERROR, + SandboxState.BUILD_FAILED, + SandboxState.DESTROYED, + ): + logger.warning( + "Sandbox %s in unrecoverable state %s — creating a new one", + sandbox.id, + sandbox.state, + ) + sandbox = client.create( + CreateSandboxFromSnapshotParams(language="python", labels=labels) + ) + logger.info("Created replacement sandbox: %s", sandbox.id) + elif sandbox.state != SandboxState.STARTED: + sandbox.wait_for_sandbox_start(timeout=60) + + except Exception: + logger.info("No existing sandbox for thread %s — creating one", thread_id) + sandbox = client.create( + CreateSandboxFromSnapshotParams(language="python", labels=labels) + ) + logger.info("Created new sandbox: %s", sandbox.id) + + return _TimeoutAwareSandbox(sandbox=sandbox) + + +async def get_or_create_sandbox(thread_id: int | str) -> _TimeoutAwareSandbox: + """Get or create a sandbox for a conversation thread. + + Uses an in-process cache keyed by thread_id so subsequent messages + in the same conversation reuse the sandbox object without an API call. + + Args: + thread_id: The conversation thread identifier. + + Returns: + DaytonaSandbox connected to the sandbox. + """ + key = str(thread_id) + cached = _sandbox_cache.get(key) + if cached is not None: + logger.info("Reusing cached sandbox for thread %s", key) + return cached + sandbox = await asyncio.to_thread(_find_or_create, key) + _sandbox_cache[key] = sandbox + + if len(_sandbox_cache) > _SANDBOX_CACHE_MAX_SIZE: + oldest_key = next(iter(_sandbox_cache)) + _sandbox_cache.pop(oldest_key, None) + logger.debug("Evicted oldest sandbox cache entry: %s", oldest_key) + + return sandbox + + +async def delete_sandbox(thread_id: int | str) -> None: + """Delete the sandbox for a conversation thread.""" + _sandbox_cache.pop(str(thread_id), None) + + def _delete() -> None: + client = _get_client() + labels = {THREAD_LABEL_KEY: str(thread_id)} + try: + sandbox = client.find_one(labels=labels) + except DaytonaError: + logger.debug( + "No sandbox to delete for thread %s (already removed)", thread_id + ) + return + try: + client.delete(sandbox) + logger.info("Sandbox deleted: %s", sandbox.id) + except Exception: + logger.warning( + "Failed to delete sandbox for thread %s", + thread_id, + exc_info=True, + ) + + await asyncio.to_thread(_delete) + + +# --------------------------------------------------------------------------- +# Local file persistence +# --------------------------------------------------------------------------- + + +def _get_sandbox_files_dir() -> Path: + return Path(os.environ.get("SANDBOX_FILES_DIR", "sandbox_files")) + + +def _local_path_for(thread_id: int | str, sandbox_path: str) -> Path: + """Map a sandbox-internal absolute path to a local filesystem path.""" + relative = sandbox_path.lstrip("/") + return _get_sandbox_files_dir() / str(thread_id) / relative + + +def get_local_sandbox_file(thread_id: int | str, sandbox_path: str) -> bytes | None: + """Read a previously-persisted sandbox file from local storage. + + Returns the file bytes, or *None* if the file does not exist locally. + """ + local = _local_path_for(thread_id, sandbox_path) + if local.is_file(): + return local.read_bytes() + return None + + +def delete_local_sandbox_files(thread_id: int | str) -> None: + """Remove all locally-persisted sandbox files for a thread.""" + thread_dir = _get_sandbox_files_dir() / str(thread_id) + if thread_dir.is_dir(): + shutil.rmtree(thread_dir, ignore_errors=True) + logger.info("Deleted local sandbox files for thread %s", thread_id) + + +async def persist_and_delete_sandbox( + thread_id: int | str, + sandbox_file_paths: list[str], +) -> None: + """Download sandbox files to local storage, then delete the sandbox. + + Each file in *sandbox_file_paths* is downloaded from the Daytona + sandbox and saved under ``{SANDBOX_FILES_DIR}/{thread_id}/…``. + Per-file errors are logged but do **not** prevent the sandbox from + being deleted — freeing Daytona storage is the priority. + """ + _sandbox_cache.pop(str(thread_id), None) + + def _persist_and_delete() -> None: + client = _get_client() + labels = {THREAD_LABEL_KEY: str(thread_id)} + + try: + sandbox = client.find_one(labels=labels) + except Exception: + logger.info( + "No sandbox found for thread %s — nothing to persist", thread_id + ) + return + + # Ensure the sandbox is running so we can download files + if sandbox.state != SandboxState.STARTED: + try: + sandbox.start(timeout=60) + except Exception: + logger.warning( + "Could not start sandbox %s for file download — deleting anyway", + sandbox.id, + exc_info=True, + ) + with contextlib.suppress(Exception): + client.delete(sandbox) + return + + for path in sandbox_file_paths: + try: + content: bytes = sandbox.fs.download_file(path) + local = _local_path_for(thread_id, path) + local.parent.mkdir(parents=True, exist_ok=True) + local.write_bytes(content) + logger.info("Persisted sandbox file %s → %s", path, local) + except Exception: + logger.warning( + "Failed to persist sandbox file %s for thread %s", + path, + thread_id, + exc_info=True, + ) + + try: + client.delete(sandbox) + logger.info("Sandbox deleted after file persistence: %s", sandbox.id) + except Exception: + logger.warning( + "Failed to delete sandbox %s after persistence", + sandbox.id, + exc_info=True, + ) + + await asyncio.to_thread(_persist_and_delete) diff --git a/surfsense_backend/app/agents/new_chat/system_prompt.py b/surfsense_backend/app/agents/new_chat/system_prompt.py index c8dcf5154..1ca036c40 100644 --- a/surfsense_backend/app/agents/new_chat/system_prompt.py +++ b/surfsense_backend/app/agents/new_chat/system_prompt.py @@ -645,6 +645,87 @@ However, from your video learning, it's important to note that asyncio is not su """ +# Sandbox / code execution instructions — appended when sandbox backend is enabled. +# Inspired by Claude's computer-use prompt, scoped to code execution & data analytics. +SANDBOX_EXECUTION_INSTRUCTIONS = """ + +You have access to a secure, isolated Linux sandbox environment for running code and shell commands. +This gives you the `execute` tool alongside the standard filesystem tools (`ls`, `read_file`, `write_file`, `edit_file`, `glob`, `grep`). + +## CRITICAL — CODE-FIRST RULE + +ALWAYS prefer executing code over giving a text-only response when the user's request involves ANY of the following: +- **Creating a chart, plot, graph, or visualization** → Write Python code and generate the actual file. NEVER describe percentages or data in text and offer to "paste into Excel". Just produce the chart. +- **Data analysis, statistics, or computation** → Write code to compute the answer. Do not do math by hand in text. +- **Generating or transforming files** (CSV, PDF, images, etc.) → Write code to create the file. +- **Running, testing, or debugging code** → Execute it in the sandbox. + +This applies even when you first retrieve data from the knowledge base. After `search_knowledge_base` returns relevant data, **immediately proceed to write and execute code** if the user's request matches any of the categories above. Do NOT stop at a text summary and wait for the user to ask you to "use Python" — that extra round-trip is a poor experience. + +Example (CORRECT): + User: "Create a pie chart of my benefits" + → 1. search_knowledge_base → retrieve benefits data + → 2. Immediately execute Python code (matplotlib) to generate the pie chart + → 3. Return the downloadable file + brief description + +Example (WRONG): + User: "Create a pie chart of my benefits" + → 1. search_knowledge_base → retrieve benefits data + → 2. Print a text table with percentages and ask the user if they want a chart ← NEVER do this + +## When to Use Code Execution + +Use the sandbox when the task benefits from actually running code rather than just describing it: +- **Data analysis**: Load CSVs/JSON, compute statistics, filter/aggregate data, pivot tables +- **Visualization**: Generate charts and plots (matplotlib, plotly, seaborn) +- **Calculations**: Math, financial modeling, unit conversions, simulations +- **Code validation**: Run and test code snippets the user provides or asks about +- **File processing**: Parse, transform, or convert data files +- **Quick prototyping**: Demonstrate working code for the user's problem +- **Package exploration**: Install and test libraries the user is evaluating + +## When NOT to Use Code Execution + +Do not use the sandbox for: +- Answering factual questions from your own knowledge +- Summarizing or explaining concepts +- Simple formatting or text generation tasks +- Tasks that don't require running code to answer + +## Package Management + +- Use `pip install ` to install Python packages as needed +- Common data/analytics packages (pandas, numpy, matplotlib, scipy, scikit-learn) may need to be installed on first use +- Always verify a package installed successfully before using it + +## Working Guidelines + +- **Working directory**: The shell starts in the sandbox user's home directory (e.g. `/home/daytona`). Use **relative paths** or `/tmp/` for all files you create. NEVER write directly to `/home/` — that is the parent directory and is not writable. Use `pwd` if you need to discover the current working directory. +- **Iterative approach**: For complex tasks, break work into steps — write code, run it, check output, refine +- **Error handling**: If code fails, read the error, fix the issue, and retry. Don't just report the error without attempting a fix. +- **Show results**: When generating plots or outputs, present the key findings directly in your response. For plots, save to a file and describe the results. +- **Be efficient**: Install packages once per session. Combine related commands when possible. +- **Large outputs**: If command output is very large, use `head`, `tail`, or save to a file and read selectively. + +## Sharing Generated Files + +When your code creates output files (images, CSVs, PDFs, etc.) in the sandbox: +- **Print the absolute path** at the end of your script so the user can download the file. Example: `print("SANDBOX_FILE: /tmp/chart.png")` +- **DO NOT call `display_image`** for files created inside the sandbox. Sandbox files are not accessible via public URLs, so `display_image` will always show "Image not available". The frontend automatically renders a download button from the `SANDBOX_FILE:` marker. +- You can output multiple files, one per line: `print("SANDBOX_FILE: /tmp/report.csv")`, `print("SANDBOX_FILE: /tmp/chart.png")` +- Always describe what the file contains in your response text so the user knows what they are downloading. +- IMPORTANT: Every `execute` call that saves a file MUST print the `SANDBOX_FILE: ` marker. Without it the user cannot download the file. + +## Data Analytics Best Practices + +When the user asks you to analyze data: +1. First, inspect the data structure (`head`, `shape`, `dtypes`, `describe()`) +2. Clean and validate before computing (handle nulls, check types) +3. Perform the analysis and present results clearly +4. Offer follow-up insights or visualizations when appropriate + +""" + # Anti-citation prompt - used when citations are disabled # This explicitly tells the model NOT to include citations SURFSENSE_NO_CITATION_INSTRUCTIONS = """ @@ -670,6 +751,7 @@ Your goal is to provide helpful, informative answers in a clean, readable format def build_surfsense_system_prompt( today: datetime | None = None, thread_visibility: ChatVisibility | None = None, + sandbox_enabled: bool = False, ) -> str: """ Build the SurfSense system prompt with default settings. @@ -678,10 +760,12 @@ def build_surfsense_system_prompt( - Default system instructions - Tools instructions (always included) - Citation instructions enabled + - Sandbox execution instructions (when sandbox_enabled=True) Args: today: Optional datetime for today's date (defaults to current UTC date) thread_visibility: Optional; when provided, used for conditional prompt (e.g. private vs shared memory wording). Defaults to private behavior when None. + sandbox_enabled: Whether the sandbox backend is active (adds code execution instructions). Returns: Complete system prompt string @@ -691,7 +775,13 @@ def build_surfsense_system_prompt( system_instructions = _get_system_instructions(visibility, today) tools_instructions = _get_tools_instructions(visibility) citation_instructions = SURFSENSE_CITATION_INSTRUCTIONS - return system_instructions + tools_instructions + citation_instructions + sandbox_instructions = SANDBOX_EXECUTION_INSTRUCTIONS if sandbox_enabled else "" + return ( + system_instructions + + tools_instructions + + citation_instructions + + sandbox_instructions + ) def build_configurable_system_prompt( @@ -700,14 +790,16 @@ def build_configurable_system_prompt( citations_enabled: bool = True, today: datetime | None = None, thread_visibility: ChatVisibility | None = None, + sandbox_enabled: bool = False, ) -> str: """ Build a configurable SurfSense system prompt based on NewLLMConfig settings. - The prompt is composed of three parts: + The prompt is composed of up to four parts: 1. System Instructions - either custom or default SURFSENSE_SYSTEM_INSTRUCTIONS 2. Tools Instructions - always included (SURFSENSE_TOOLS_INSTRUCTIONS) 3. Citation Instructions - either SURFSENSE_CITATION_INSTRUCTIONS or SURFSENSE_NO_CITATION_INSTRUCTIONS + 4. Sandbox Execution Instructions - when sandbox_enabled=True Args: custom_system_instructions: Custom system instructions to use. If empty/None and @@ -719,6 +811,7 @@ def build_configurable_system_prompt( anti-citation instructions (False). today: Optional datetime for today's date (defaults to current UTC date) thread_visibility: Optional; when provided, used for conditional prompt (e.g. private vs shared memory wording). Defaults to private behavior when None. + sandbox_enabled: Whether the sandbox backend is active (adds code execution instructions). Returns: Complete system prompt string @@ -727,7 +820,6 @@ def build_configurable_system_prompt( # Determine system instructions if custom_system_instructions and custom_system_instructions.strip(): - # Use custom instructions, injecting the date placeholder if present system_instructions = custom_system_instructions.format( resolved_today=resolved_today ) @@ -735,7 +827,6 @@ def build_configurable_system_prompt( visibility = thread_visibility or ChatVisibility.PRIVATE system_instructions = _get_system_instructions(visibility, today) else: - # No system instructions (edge case) system_instructions = "" # Tools instructions: conditional on thread_visibility (private vs shared memory wording) @@ -748,7 +839,14 @@ def build_configurable_system_prompt( else SURFSENSE_NO_CITATION_INSTRUCTIONS ) - return system_instructions + tools_instructions + citation_instructions + sandbox_instructions = SANDBOX_EXECUTION_INSTRUCTIONS if sandbox_enabled else "" + + return ( + system_instructions + + tools_instructions + + citation_instructions + + sandbox_instructions + ) def get_default_system_instructions() -> str: diff --git a/surfsense_backend/app/agents/new_chat/tools/google_drive/create_file.py b/surfsense_backend/app/agents/new_chat/tools/google_drive/create_file.py index 0dd683f7e..af93ddc8f 100644 --- a/surfsense_backend/app/agents/new_chat/tools/google_drive/create_file.py +++ b/surfsense_backend/app/agents/new_chat/tools/google_drive/create_file.py @@ -58,7 +58,9 @@ def create_create_google_drive_file_tool( - "Create a Google Doc called 'Meeting Notes'" - "Create a spreadsheet named 'Budget 2026' with some sample data" """ - logger.info(f"create_google_drive_file called: name='{name}', type='{file_type}'") + logger.info( + f"create_google_drive_file called: name='{name}', type='{file_type}'" + ) if db_session is None or search_space_id is None or user_id is None: return { @@ -74,7 +76,9 @@ def create_create_google_drive_file_tool( try: metadata_service = GoogleDriveToolMetadataService(db_session) - context = await metadata_service.get_creation_context(search_space_id, user_id) + context = await metadata_service.get_creation_context( + search_space_id, user_id + ) if "error" in context: logger.error(f"Failed to fetch creation context: {context['error']}") @@ -100,8 +104,12 @@ def create_create_google_drive_file_tool( } ) - decisions_raw = approval.get("decisions", []) if isinstance(approval, dict) else [] - decisions = decisions_raw if isinstance(decisions_raw, list) else [decisions_raw] + decisions_raw = ( + approval.get("decisions", []) if isinstance(approval, dict) else [] + ) + decisions = ( + decisions_raw if isinstance(decisions_raw, list) else [decisions_raw] + ) decisions = [d for d in decisions if isinstance(d, dict)] if not decisions: logger.warning("No approval decision received") @@ -183,7 +191,9 @@ def create_create_google_drive_file_tool( logger.info( f"Creating Google Drive file: name='{final_name}', type='{final_file_type}', connector={actual_connector_id}" ) - client = GoogleDriveClient(session=db_session, connector_id=actual_connector_id) + client = GoogleDriveClient( + session=db_session, connector_id=actual_connector_id + ) try: created = await client.create_file( name=final_name, @@ -203,7 +213,9 @@ def create_create_google_drive_file_tool( } raise - logger.info(f"Google Drive file created: id={created.get('id')}, name={created.get('name')}") + logger.info( + f"Google Drive file created: id={created.get('id')}, name={created.get('name')}" + ) return { "status": "success", "file_id": created.get("id"), diff --git a/surfsense_backend/app/agents/new_chat/tools/google_drive/trash_file.py b/surfsense_backend/app/agents/new_chat/tools/google_drive/trash_file.py index 600aae983..917ba3376 100644 --- a/surfsense_backend/app/agents/new_chat/tools/google_drive/trash_file.py +++ b/surfsense_backend/app/agents/new_chat/tools/google_drive/trash_file.py @@ -52,7 +52,9 @@ def create_delete_google_drive_file_tool( - "Delete the 'Meeting Notes' file from Google Drive" - "Trash the 'Old Budget' spreadsheet" """ - logger.info(f"delete_google_drive_file called: file_name='{file_name}', delete_from_kb={delete_from_kb}") + logger.info( + f"delete_google_drive_file called: file_name='{file_name}', delete_from_kb={delete_from_kb}" + ) if db_session is None or search_space_id is None or user_id is None: return { @@ -103,8 +105,12 @@ def create_delete_google_drive_file_tool( } ) - decisions_raw = approval.get("decisions", []) if isinstance(approval, dict) else [] - decisions = decisions_raw if isinstance(decisions_raw, list) else [decisions_raw] + decisions_raw = ( + approval.get("decisions", []) if isinstance(approval, dict) else [] + ) + decisions = ( + decisions_raw if isinstance(decisions_raw, list) else [decisions_raw] + ) decisions = [d for d in decisions if isinstance(d, dict)] if not decisions: logger.warning("No approval decision received") @@ -130,11 +136,16 @@ def create_delete_google_drive_file_tool( final_params = decision["args"] final_file_id = final_params.get("file_id", file_id) - final_connector_id = final_params.get("connector_id", connector_id_from_context) + final_connector_id = final_params.get( + "connector_id", connector_id_from_context + ) final_delete_from_kb = final_params.get("delete_from_kb", delete_from_kb) if not final_connector_id: - return {"status": "error", "message": "No connector found for this file."} + return { + "status": "error", + "message": "No connector found for this file.", + } from sqlalchemy.future import select @@ -174,7 +185,9 @@ def create_delete_google_drive_file_tool( } raise - logger.info(f"Google Drive file deleted (moved to trash): file_id={final_file_id}") + logger.info( + f"Google Drive file deleted (moved to trash): file_id={final_file_id}" + ) trash_result: dict[str, Any] = { "status": "success", @@ -195,7 +208,9 @@ def create_delete_google_drive_file_tool( await db_session.delete(document) await db_session.commit() deleted_from_kb = True - logger.info(f"Deleted document {document_id} from knowledge base") + logger.info( + f"Deleted document {document_id} from knowledge base" + ) else: logger.warning(f"Document {document_id} not found in KB") except Exception as e: diff --git a/surfsense_backend/app/agents/new_chat/tools/knowledge_base.py b/surfsense_backend/app/agents/new_chat/tools/knowledge_base.py index cf34e3e85..f1d3d16b8 100644 --- a/surfsense_backend/app/agents/new_chat/tools/knowledge_base.py +++ b/surfsense_backend/app/agents/new_chat/tools/knowledge_base.py @@ -10,6 +10,8 @@ This module provides: import asyncio import json +import re +import time from datetime import datetime from typing import Any @@ -17,8 +19,152 @@ from langchain_core.tools import StructuredTool from pydantic import BaseModel, Field from sqlalchemy.ext.asyncio import AsyncSession -from app.db import async_session_maker +from app.db import shielded_async_session from app.services.connector_service import ConnectorService +from app.utils.perf import get_perf_logger + +# Connectors that call external live-search APIs (no local DB / embedding needed). +# These are never filtered by available_document_types. +_LIVE_SEARCH_CONNECTORS: set[str] = { + "TAVILY_API", + "SEARXNG_API", + "LINKUP_API", + "BAIDU_SEARCH_API", +} + +# Patterns that indicate the query has no meaningful search signal. +# plainto_tsquery('english', '*') produces an empty tsquery and an embedding +# of '*' is random noise, so both keyword and semantic search degrade to +# arbitrary ordering — large documents (many chunks) dominate by chance. +_DEGENERATE_QUERY_RE = re.compile( + r"^[\s*?_.#@!\-/\\]+$" # only wildcards, punctuation, whitespace +) + +# Max chunks per document when doing a recency-based browse instead of +# a real search. We want breadth (many docs) over depth (many chunks). +_BROWSE_MAX_CHUNKS_PER_DOC = 5 + + +def _is_degenerate_query(query: str) -> bool: + """Return True when the query carries no meaningful search signal. + + Catches wildcard patterns (``*``, ``**``), empty / whitespace-only + strings, and single-character non-word tokens. These queries cause + both keyword search (empty tsquery) and semantic search (meaningless + embedding) to return effectively random results. + """ + stripped = query.strip() + if not stripped: + return True + return bool(_DEGENERATE_QUERY_RE.match(stripped)) + + +async def _browse_recent_documents( + search_space_id: int, + document_type: str | None, + top_k: int, + start_date: datetime | None, + end_date: datetime | None, +) -> list[dict[str, Any]]: + """Return the most-recent documents (recency-ordered, no search ranking). + + Used as a fallback when the search query is degenerate (e.g. ``*``) and + semantic / keyword search would produce arbitrary results. Returns + document-grouped dicts in the same shape as ``_combined_rrf_search`` + so the rest of the pipeline works unchanged. + """ + from sqlalchemy import select + from sqlalchemy.orm import joinedload + + from app.db import Chunk, Document, DocumentType + + perf = get_perf_logger() + t0 = time.perf_counter() + + base_conditions = [Document.search_space_id == search_space_id] + + if document_type is not None: + if isinstance(document_type, str): + try: + doc_type_enum = DocumentType[document_type] + base_conditions.append(Document.document_type == doc_type_enum) + except KeyError: + return [] + else: + base_conditions.append(Document.document_type == document_type) + + if start_date is not None: + base_conditions.append(Document.updated_at >= start_date) + if end_date is not None: + base_conditions.append(Document.updated_at <= end_date) + + async with shielded_async_session() as session: + doc_query = ( + select(Document) + .options(joinedload(Document.search_space)) + .where(*base_conditions) + .order_by(Document.updated_at.desc()) + .limit(top_k) + ) + result = await session.execute(doc_query) + documents = result.scalars().unique().all() + + if not documents: + return [] + + doc_ids = [d.id for d in documents] + + chunk_query = ( + select(Chunk) + .where(Chunk.document_id.in_(doc_ids)) + .order_by(Chunk.document_id, Chunk.id) + ) + chunk_result = await session.execute(chunk_query) + raw_chunks = chunk_result.scalars().all() + + doc_chunk_counts: dict[int, int] = {} + doc_chunks: dict[int, list[dict]] = {d.id: [] for d in documents} + for chunk in raw_chunks: + did = chunk.document_id + count = doc_chunk_counts.get(did, 0) + if count < _BROWSE_MAX_CHUNKS_PER_DOC: + doc_chunks[did].append({"chunk_id": chunk.id, "content": chunk.content}) + doc_chunk_counts[did] = count + 1 + + results: list[dict[str, Any]] = [] + for doc in documents: + chunks_list = doc_chunks.get(doc.id, []) + results.append( + { + "document_id": doc.id, + "content": "\n\n".join( + c["content"] for c in chunks_list if c.get("content") + ), + "score": 0.0, + "chunks": chunks_list, + "document": { + "id": doc.id, + "title": doc.title, + "document_type": doc.document_type.value + if getattr(doc, "document_type", None) + else None, + "metadata": doc.document_metadata or {}, + }, + "source": doc.document_type.value + if getattr(doc, "document_type", None) + else None, + } + ) + + perf.info( + "[kb_browse] recency browse in %.3fs docs=%d space=%d type=%s", + time.perf_counter() - t0, + len(results), + search_space_id, + document_type, + ) + return results + # ============================================================================= # Connector Constants and Normalization @@ -172,12 +318,72 @@ def _normalize_connectors( # ============================================================================= -def format_documents_for_context(documents: list[dict[str, Any]]) -> str: +# Fraction of the model's context window (in characters) that a single tool +# result is allowed to occupy. The remainder is reserved for system prompt, +# conversation history, and model output. With ~4 chars/token this gives a +# tool result ≈ 25 % of the context budget in tokens. +_TOOL_OUTPUT_CONTEXT_FRACTION = 0.25 +_CHARS_PER_TOKEN = 4 + +# Hard-floor / ceiling so the budget is always sensible regardless of what +# the model reports. +_MIN_TOOL_OUTPUT_CHARS = 20_000 # ~5K tokens +_MAX_TOOL_OUTPUT_CHARS = 200_000 # ~50K tokens +_MAX_CHUNK_CHARS = 8_000 + +# Rank-adaptive per-document budget allocation. +# Top-ranked (most relevant) documents get a larger share of the budget so +# we pack as much high-quality context as possible. +# +# fraction(rank) = _TOP_DOC_BUDGET_FRACTION / (1 + rank * _RANK_DECAY) +# +# Examples (128K budget, 8K chunk cap): +# rank 0 → 40% → 6 chunks | rank 3 → 19% → 3 chunks +# rank 1 → 30% → 4 chunks | rank 10 → 10% → 3 chunks (floor) +# rank 2 → 24% → 3 chunks | +_TOP_DOC_BUDGET_FRACTION = 0.40 +_RANK_DECAY = 0.35 +_MIN_CHUNKS_PER_DOC = 3 + + +def _compute_tool_output_budget(max_input_tokens: int | None) -> int: + """Derive a character budget from the model's context window. + + Uses ``litellm.get_model_info`` via the value already resolved by + ``ChatLiteLLMRouter`` / ``ChatLiteLLM`` and passed through the dependency + chain as ``max_input_tokens``. Falls back to a conservative default when + the value is unavailable. + """ + if max_input_tokens is None or max_input_tokens <= 0: + return _MIN_TOOL_OUTPUT_CHARS # conservative fallback + + budget = int(max_input_tokens * _CHARS_PER_TOKEN * _TOOL_OUTPUT_CONTEXT_FRACTION) + return max(_MIN_TOOL_OUTPUT_CHARS, min(budget, _MAX_TOOL_OUTPUT_CHARS)) + + +def format_documents_for_context( + documents: list[dict[str, Any]], + *, + max_chars: int = _MAX_TOOL_OUTPUT_CHARS, + max_chunk_chars: int = _MAX_CHUNK_CHARS, + max_chunks_per_doc: int = 0, +) -> str: """ Format retrieved documents into a readable context string for the LLM. + Documents are added in order (highest relevance first) until the character + budget is reached. Individual chunks are capped at ``max_chunk_chars`` and + each document is limited to a dynamically computed chunk cap so a single + large document cannot monopolize the output while still maximising the use + of available context space. + Args: documents: List of document dictionaries from connector search + max_chars: Approximate character budget for the entire output. + max_chunk_chars: Per-chunk character cap (content is tail-truncated). + max_chunks_per_doc: Maximum chunks per document. ``0`` (default) means + auto-compute per document using a rank-adaptive formula so + higher-ranked documents receive more chunks. Returns: Formatted string with document contents and metadata @@ -278,39 +484,85 @@ def format_documents_for_context(documents: list[dict[str, Any]]) -> str: "BAIDU_SEARCH_API", } - # Render XML expected by citation instructions + # Render XML expected by citation instructions, respecting the char budget. parts: list[str] = [] - for g in grouped.values(): + total_chars = 0 + total_docs = len(grouped) + + for doc_idx, g in enumerate(grouped.values()): metadata_json = json.dumps(g["metadata"], ensure_ascii=False) is_live_search = g["document_type"] in live_search_connectors - parts.append("") - parts.append("") - parts.append(f" {g['document_id']}") - parts.append(f" {g['document_type']}") - parts.append(f" <![CDATA[{g['title']}]]>") - parts.append(f" ") - parts.append(f" ") - parts.append("") - parts.append("") - parts.append("") + doc_lines: list[str] = [ + "", + "", + f" {g['document_id']}", + f" {g['document_type']}", + f" <![CDATA[{g['title']}]]>", + f" ", + f" ", + "", + "", + "", + ] - for ch in g["chunks"]: + # Rank-adaptive per-document chunk cap: top results get more chunks. + if max_chunks_per_doc > 0: + chunks_allowed = max_chunks_per_doc + else: + doc_fraction = _TOP_DOC_BUDGET_FRACTION / (1 + doc_idx * _RANK_DECAY) + max_doc_chars = int(max_chars * doc_fraction) + xml_overhead = 500 + chunks_allowed = max( + (max_doc_chars - xml_overhead) // max(max_chunk_chars, 1), + _MIN_CHUNKS_PER_DOC, + ) + + chunks = g["chunks"] + if len(chunks) > chunks_allowed: + chunks = chunks[:chunks_allowed] + + for ch in chunks: ch_content = ch["content"] - # For live search connectors, use the document URL as the chunk id - # so the LLM outputs [citation:https://...] which the frontend - # renders as a clickable link. + if max_chunk_chars and len(ch_content) > max_chunk_chars: + ch_content = ch_content[:max_chunk_chars] + "\n...(truncated)" ch_id = g["url"] if (is_live_search and g["url"]) else ch["chunk_id"] if ch_id is None: - parts.append(f" ") + doc_lines.append(f" ") else: - parts.append(f" ") + doc_lines.append( + f" " + ) - parts.append("") - parts.append("") - parts.append("") + doc_lines.extend(["", "", ""]) - return "\n".join(parts).strip() + doc_xml = "\n".join(doc_lines) + doc_len = len(doc_xml) + + if total_chars + doc_len > max_chars: + remaining = total_docs - doc_idx + if doc_idx == 0: + parts.append(doc_xml) + total_chars += doc_len + parts.append( + f"" + ) + break + + parts.append(doc_xml) + total_chars += doc_len + + result = "\n".join(parts).strip() + + # Hard safety net: if the result is still over budget (e.g. a single massive + # first document), forcibly truncate with a closing comment. + if len(result) > max_chars: + truncation_msg = "\n" + result = result[: max_chars - len(truncation_msg)] + truncation_msg + + return result # ============================================================================= @@ -328,6 +580,8 @@ async def search_knowledge_base_async( start_date: datetime | None = None, end_date: datetime | None = None, available_connectors: list[str] | None = None, + available_document_types: list[str] | None = None, + max_input_tokens: int | None = None, ) -> str: """ Search the user's knowledge base for relevant documents. @@ -345,10 +599,18 @@ async def search_knowledge_base_async( end_date: Optional end datetime (UTC) for filtering documents available_connectors: Optional list of connectors actually available in the search space. If provided, only these connectors will be searched. + available_document_types: Optional list of document types that actually have indexed + data. When provided, local connectors whose document type is + absent are skipped entirely (no embedding / DB round-trip). + max_input_tokens: Model context window size (tokens). Used to dynamically + size the output so it fits within the model's limits. Returns: Formatted string with search results """ + perf = get_perf_logger() + t0 = time.perf_counter() + all_documents: list[dict[str, Any]] = [] # Resolve date range (default last 2 years) @@ -361,88 +623,169 @@ async def search_knowledge_base_async( connectors = _normalize_connectors(connectors_to_search, available_connectors) - connector_specs: dict[str, tuple[str, bool, bool, dict[str, Any]]] = { - "YOUTUBE_VIDEO": ("search_youtube", True, True, {}), - "EXTENSION": ("search_extension", True, True, {}), - "CRAWLED_URL": ("search_crawled_urls", True, True, {}), - "FILE": ("search_files", True, True, {}), - "SLACK_CONNECTOR": ("search_slack", True, True, {}), - "TEAMS_CONNECTOR": ("search_teams", True, True, {}), - "NOTION_CONNECTOR": ("search_notion", True, True, {}), - "GITHUB_CONNECTOR": ("search_github", True, True, {}), - "LINEAR_CONNECTOR": ("search_linear", True, True, {}), + # --- Optimization 1: skip local connectors that have zero indexed documents --- + if available_document_types: + doc_types_set = set(available_document_types) + before_count = len(connectors) + connectors = [ + c for c in connectors if c in _LIVE_SEARCH_CONNECTORS or c in doc_types_set + ] + skipped = before_count - len(connectors) + if skipped: + perf.info( + "[kb_search] skipped %d empty connectors (had %d, now %d)", + skipped, + before_count, + len(connectors), + ) + + perf.info( + "[kb_search] searching %d connectors: %s (space=%d, top_k=%d)", + len(connectors), + connectors[:5], + search_space_id, + top_k, + ) + + # --- Fast-path: degenerate queries (*, **, empty, etc.) --- + # Semantic embedding of '*' is noise and plainto_tsquery('english', '*') + # yields an empty tsquery, so both retrieval signals are useless. + # Fall back to a recency-ordered browse that returns diverse results. + if _is_degenerate_query(query): + perf.info( + "[kb_search] degenerate query %r detected - falling back to recency browse", + query, + ) + local_connectors = [c for c in connectors if c not in _LIVE_SEARCH_CONNECTORS] + if not local_connectors: + local_connectors = [None] # type: ignore[list-item] + + browse_results = await asyncio.gather( + *[ + _browse_recent_documents( + search_space_id=search_space_id, + document_type=c, + top_k=top_k, + start_date=resolved_start_date, + end_date=resolved_end_date, + ) + for c in local_connectors + ] + ) + for docs in browse_results: + all_documents.extend(docs) + + # Skip dedup + formatting below (browse already returns unique docs) + # but still cap output budget. + output_budget = _compute_tool_output_budget(max_input_tokens) + result = format_documents_for_context( + all_documents, + max_chars=output_budget, + max_chunks_per_doc=_BROWSE_MAX_CHUNKS_PER_DOC, + ) + perf.info( + "[kb_search] TOTAL (browse) in %.3fs total_docs=%d output_chars=%d " + "budget=%d space=%d", + time.perf_counter() - t0, + len(all_documents), + len(result), + output_budget, + search_space_id, + ) + return result + + # Specs for live-search connectors (external APIs, no local DB/embedding). + live_connector_specs: dict[str, tuple[str, bool, bool, dict[str, Any]]] = { "TAVILY_API": ("search_tavily", False, True, {}), "SEARXNG_API": ("search_searxng", False, True, {}), "LINKUP_API": ("search_linkup", False, False, {"mode": "standard"}), "BAIDU_SEARCH_API": ("search_baidu", False, True, {}), - "DISCORD_CONNECTOR": ("search_discord", True, True, {}), - "JIRA_CONNECTOR": ("search_jira", True, True, {}), - "GOOGLE_CALENDAR_CONNECTOR": ("search_google_calendar", True, True, {}), - "AIRTABLE_CONNECTOR": ("search_airtable", True, True, {}), - "GOOGLE_GMAIL_CONNECTOR": ("search_google_gmail", True, True, {}), - "GOOGLE_DRIVE_FILE": ("search_google_drive", True, True, {}), - "CONFLUENCE_CONNECTOR": ("search_confluence", True, True, {}), - "CLICKUP_CONNECTOR": ("search_clickup", True, True, {}), - "LUMA_CONNECTOR": ("search_luma", True, True, {}), - "ELASTICSEARCH_CONNECTOR": ("search_elasticsearch", True, True, {}), - "NOTE": ("search_notes", True, True, {}), - "BOOKSTACK_CONNECTOR": ("search_bookstack", True, True, {}), - "CIRCLEBACK": ("search_circleback", True, True, {}), - "OBSIDIAN_CONNECTOR": ("search_obsidian", True, True, {}), - # Composio connectors - "COMPOSIO_GOOGLE_DRIVE_CONNECTOR": ( - "search_composio_google_drive", - True, - True, - {}, - ), - "COMPOSIO_GMAIL_CONNECTOR": ("search_composio_gmail", True, True, {}), - "COMPOSIO_GOOGLE_CALENDAR_CONNECTOR": ( - "search_composio_google_calendar", - True, - True, - {}, - ), } - # Keep a conservative cap to avoid overloading DB/external services. + # --- Optimization 2: compute the query embedding once, share across all local searches --- + precomputed_embedding: list[float] | None = None + has_local_connectors = any(c not in _LIVE_SEARCH_CONNECTORS for c in connectors) + if has_local_connectors: + from app.config import config as app_config + + t_embed = time.perf_counter() + precomputed_embedding = app_config.embedding_model_instance.embed(query) + perf.info( + "[kb_search] shared embedding computed in %.3fs", + time.perf_counter() - t_embed, + ) + max_parallel_searches = 4 semaphore = asyncio.Semaphore(max_parallel_searches) async def _search_one_connector(connector: str) -> list[dict[str, Any]]: - spec = connector_specs.get(connector) - if spec is None: - return [] + is_live = connector in _LIVE_SEARCH_CONNECTORS - method_name, includes_date_range, includes_top_k, extra_kwargs = spec - kwargs: dict[str, Any] = { - "user_query": query, - "search_space_id": search_space_id, - **extra_kwargs, - } - if includes_top_k: - kwargs["top_k"] = top_k - if includes_date_range: - kwargs["start_date"] = resolved_start_date - kwargs["end_date"] = resolved_end_date + if is_live: + spec = live_connector_specs.get(connector) + if spec is None: + return [] + method_name, includes_date_range, includes_top_k, extra_kwargs = spec + kwargs: dict[str, Any] = { + "user_query": query, + "search_space_id": search_space_id, + **extra_kwargs, + } + if includes_top_k: + kwargs["top_k"] = top_k + if includes_date_range: + kwargs["start_date"] = resolved_start_date + kwargs["end_date"] = resolved_end_date + try: + t_conn = time.perf_counter() + async with semaphore, shielded_async_session() as isolated_session: + svc = ConnectorService(isolated_session, search_space_id) + _, chunks = await getattr(svc, method_name)(**kwargs) + perf.info( + "[kb_search] connector=%s results=%d in %.3fs", + connector, + len(chunks), + time.perf_counter() - t_conn, + ) + return chunks + except Exception as e: + perf.warning("[kb_search] connector=%s FAILED: %s", connector, e) + return [] + + # --- Optimization 3: call _combined_rrf_search directly with shared embedding --- try: - # Use isolated session per connector. Shared AsyncSession cannot safely - # run concurrent DB operations. - async with semaphore, async_session_maker() as isolated_session: - isolated_connector_service = ConnectorService( - isolated_session, search_space_id + t_conn = time.perf_counter() + async with semaphore, shielded_async_session() as isolated_session: + svc = ConnectorService(isolated_session, search_space_id) + chunks = await svc._combined_rrf_search( + query_text=query, + search_space_id=search_space_id, + document_type=connector, + top_k=top_k, + start_date=resolved_start_date, + end_date=resolved_end_date, + query_embedding=precomputed_embedding, + ) + perf.info( + "[kb_search] connector=%s results=%d in %.3fs", + connector, + len(chunks), + time.perf_counter() - t_conn, ) - connector_method = getattr(isolated_connector_service, method_name) - _, chunks = await connector_method(**kwargs) return chunks except Exception as e: - print(f"Error searching connector {connector}: {e}") + perf.warning("[kb_search] connector=%s FAILED: %s", connector, e) return [] + t_gather = time.perf_counter() connector_results = await asyncio.gather( *[_search_one_connector(connector) for connector in connectors] ) + perf.info( + "[kb_search] all connectors gathered in %.3fs", + time.perf_counter() - t_gather, + ) for chunks in connector_results: all_documents.extend(chunks) @@ -488,7 +831,29 @@ async def search_knowledge_base_async( deduplicated.append(doc) - return format_documents_for_context(deduplicated) + output_budget = _compute_tool_output_budget(max_input_tokens) + result = format_documents_for_context(deduplicated, max_chars=output_budget) + + if len(result) > output_budget: + perf.warning( + "[kb_search] output STILL exceeds budget after format (%d > %d), " + "hard truncation should have fired", + len(result), + output_budget, + ) + + perf.info( + "[kb_search] TOTAL in %.3fs total_docs=%d deduped=%d output_chars=%d " + "budget=%d max_input_tokens=%s space=%d", + time.perf_counter() - t0, + len(all_documents), + len(deduplicated), + len(result), + output_budget, + max_input_tokens, + search_space_id, + ) + return result def _build_connector_docstring(available_connectors: list[str] | None) -> str: @@ -526,11 +891,15 @@ class SearchKnowledgeBaseInput(BaseModel): """Input schema for the search_knowledge_base tool.""" query: str = Field( - description="The search query - be specific and include key terms" + description=( + "The search query - use specific natural language terms. " + "NEVER use wildcards like '*' or '**'; instead describe what you want " + "(e.g. 'recent meeting notes' or 'project architecture overview')." + ), ) top_k: int = Field( default=10, - description="Number of results to retrieve (default: 10)", + description="Number of results to retrieve (default: 10). Keep ≤20 for focused searches.", ) start_date: str | None = Field( default=None, @@ -552,6 +921,7 @@ def create_search_knowledge_base_tool( connector_service: ConnectorService, available_connectors: list[str] | None = None, available_document_types: list[str] | None = None, + max_input_tokens: int | None = None, ) -> StructuredTool: """ Factory function to create the search_knowledge_base tool with injected dependencies. @@ -564,6 +934,8 @@ def create_search_knowledge_base_tool( Used to dynamically generate the tool docstring. available_document_types: Optional list of document types that have data in the search space. Used to inform the LLM about what data exists. + max_input_tokens: Model context window (tokens) from litellm model info. + Used to dynamically size tool output. Returns: A configured StructuredTool instance @@ -590,6 +962,10 @@ Focus searches on these types for best results.""" Use this tool to find documents, notes, files, web pages, and other content that may help answer the user's question. IMPORTANT: +- Always craft specific, descriptive search queries using natural language keywords. + Good: "quarterly sales report Q3", "Python API authentication design". + Bad: "*", "**", "everything", single characters. Wildcard/empty queries yield poor results. +- Prefer multiple focused searches over a single broad one with high top_k. - If the user requests a specific source type (e.g. "my notes", "Slack messages"), pass `connectors_to_search=[...]` using the enums below. - If `connectors_to_search` is omitted/empty, the system will search broadly. - Only connectors that are enabled/configured for this search space are available.{doc_types_info} @@ -605,6 +981,7 @@ NOTE: `WEBCRAWLER_CONNECTOR` is mapped internally to the canonical document type # Capture for closure _available_connectors = available_connectors + _available_document_types = available_document_types async def _search_knowledge_base_impl( query: str, @@ -634,6 +1011,8 @@ NOTE: `WEBCRAWLER_CONNECTOR` is mapped internally to the canonical document type start_date=parsed_start, end_date=parsed_end, available_connectors=_available_connectors, + available_document_types=_available_document_types, + max_input_tokens=max_input_tokens, ) # Create StructuredTool with dynamic description diff --git a/surfsense_backend/app/agents/new_chat/tools/mcp_tool.py b/surfsense_backend/app/agents/new_chat/tools/mcp_tool.py index 5ccd2e749..2fb7ffb06 100644 --- a/surfsense_backend/app/agents/new_chat/tools/mcp_tool.py +++ b/surfsense_backend/app/agents/new_chat/tools/mcp_tool.py @@ -11,6 +11,7 @@ This implements real MCP protocol support similar to Cursor's implementation. """ import logging +import time from typing import Any from langchain_core.tools import StructuredTool @@ -25,6 +26,24 @@ from app.db import SearchSourceConnector, SearchSourceConnectorType logger = logging.getLogger(__name__) +_MCP_CACHE_TTL_SECONDS = 300 # 5 minutes +_MCP_CACHE_MAX_SIZE = 50 +_mcp_tools_cache: dict[int, tuple[float, list[StructuredTool]]] = {} + + +def _evict_expired_mcp_cache() -> None: + """Remove expired entries from the MCP tools cache to prevent unbounded growth.""" + now = time.monotonic() + expired = [ + k + for k, (ts, _) in _mcp_tools_cache.items() + if now - ts >= _MCP_CACHE_TTL_SECONDS + ] + for k in expired: + del _mcp_tools_cache[k] + if expired: + logger.debug("Evicted %d expired MCP cache entries", len(expired)) + def _create_dynamic_input_model_from_schema( tool_name: str, @@ -355,6 +374,19 @@ async def _load_http_mcp_tools( return tools +def invalidate_mcp_tools_cache(search_space_id: int | None = None) -> None: + """Invalidate cached MCP tools. + + Args: + search_space_id: If provided, only invalidate for this search space. + If None, invalidate all cached MCP tools. + """ + if search_space_id is not None: + _mcp_tools_cache.pop(search_space_id, None) + else: + _mcp_tools_cache.clear() + + async def load_mcp_tools( session: AsyncSession, search_space_id: int, @@ -364,6 +396,9 @@ async def load_mcp_tools( This discovers tools dynamically from MCP servers using the protocol. Supports both stdio (local process) and HTTP (remote server) transports. + Results are cached per search space for up to 5 minutes to avoid + re-spawning MCP server processes on every chat message. + Args: session: Database session search_space_id: User's search space ID @@ -372,8 +407,22 @@ async def load_mcp_tools( List of LangChain StructuredTool instances """ + _evict_expired_mcp_cache() + + now = time.monotonic() + cached = _mcp_tools_cache.get(search_space_id) + if cached is not None: + cached_at, cached_tools = cached + if now - cached_at < _MCP_CACHE_TTL_SECONDS: + logger.info( + "Using cached MCP tools for search space %s (%d tools, age=%.0fs)", + search_space_id, + len(cached_tools), + now - cached_at, + ) + return list(cached_tools) + try: - # Fetch all MCP connectors for this search space result = await session.execute( select(SearchSourceConnector).filter( SearchSourceConnector.connector_type @@ -385,27 +434,22 @@ async def load_mcp_tools( tools: list[StructuredTool] = [] for connector in result.scalars(): try: - # Early validation: Extract and validate connector config config = connector.config or {} server_config = config.get("server_config", {}) - # Validate server_config exists and is a dict if not server_config or not isinstance(server_config, dict): logger.warning( f"MCP connector {connector.id} (name: '{connector.name}') has invalid or missing server_config, skipping" ) continue - # Determine transport type transport = server_config.get("transport", "stdio") if transport in ("streamable-http", "http", "sse"): - # HTTP-based MCP server connector_tools = await _load_http_mcp_tools( connector.id, connector.name, server_config ) else: - # stdio-based MCP server (default) connector_tools = await _load_stdio_mcp_tools( connector.id, connector.name, server_config ) @@ -417,6 +461,12 @@ async def load_mcp_tools( f"Failed to load tools from MCP connector {connector.id}: {e!s}" ) + _mcp_tools_cache[search_space_id] = (now, tools) + + if len(_mcp_tools_cache) > _MCP_CACHE_MAX_SIZE: + oldest_key = min(_mcp_tools_cache, key=lambda k: _mcp_tools_cache[k][0]) + del _mcp_tools_cache[oldest_key] + logger.info(f"Loaded {len(tools)} MCP tools for search space {search_space_id}") return tools diff --git a/surfsense_backend/app/agents/new_chat/tools/registry.py b/surfsense_backend/app/agents/new_chat/tools/registry.py index 01342e920..99cb09b38 100644 --- a/surfsense_backend/app/agents/new_chat/tools/registry.py +++ b/surfsense_backend/app/agents/new_chat/tools/registry.py @@ -47,6 +47,10 @@ from app.db import ChatVisibility from .display_image import create_display_image_tool from .generate_image import create_generate_image_tool +from .google_drive import ( + create_create_google_drive_file_tool, + create_delete_google_drive_file_tool, +) from .knowledge_base import create_search_knowledge_base_tool from .linear import ( create_create_linear_issue_tool, @@ -55,10 +59,6 @@ from .linear import ( ) from .link_preview import create_link_preview_tool from .mcp_tool import load_mcp_tools -from .google_drive import ( - create_create_google_drive_file_tool, - create_delete_google_drive_file_tool, -) from .notion import ( create_create_notion_page_tool, create_delete_notion_page_tool, @@ -118,6 +118,7 @@ BUILTIN_TOOLS: list[ToolDefinition] = [ # Optional: dynamically discovered connectors/document types available_connectors=deps.get("available_connectors"), available_document_types=deps.get("available_document_types"), + max_input_tokens=deps.get("max_input_tokens"), ), requires=["search_space_id", "db_session", "connector_service"], # Note: available_connectors and available_document_types are optional @@ -144,10 +145,12 @@ BUILTIN_TOOLS: list[ToolDefinition] = [ thread_id=deps["thread_id"], connector_service=deps.get("connector_service"), available_connectors=deps.get("available_connectors"), + available_document_types=deps.get("available_document_types"), ), requires=["search_space_id", "thread_id"], - # connector_service and available_connectors are optional — - # when missing, source_strategy="kb_search" degrades gracefully to "provided" + # connector_service, available_connectors, and available_document_types + # are optional — when missing, source_strategy="kb_search" degrades + # gracefully to "provided" ), # Link preview tool - fetches Open Graph metadata for URLs ToolDefinition( @@ -444,8 +447,18 @@ async def build_tools_async( List of configured tool instances ready for the agent, including MCP tools. """ - # Build standard tools + import time + + _perf_log = logging.getLogger("surfsense.perf") + _perf_log.setLevel(logging.DEBUG) + + _t0 = time.perf_counter() tools = build_tools(dependencies, enabled_tools, disabled_tools, additional_tools) + _perf_log.info( + "[build_tools_async] Built-in tools in %.3fs (%d tools)", + time.perf_counter() - _t0, + len(tools), + ) # Load MCP tools if requested and dependencies are available if ( @@ -454,10 +467,16 @@ async def build_tools_async( and "search_space_id" in dependencies ): try: + _t0 = time.perf_counter() mcp_tools = await load_mcp_tools( dependencies["db_session"], dependencies["search_space_id"], ) + _perf_log.info( + "[build_tools_async] MCP tools loaded in %.3fs (%d tools)", + time.perf_counter() - _t0, + len(mcp_tools), + ) tools.extend(mcp_tools) logging.info( f"Registered {len(mcp_tools)} MCP tools: {[t.name for t in mcp_tools]}", diff --git a/surfsense_backend/app/agents/new_chat/tools/report.py b/surfsense_backend/app/agents/new_chat/tools/report.py index 0896fea4b..fe5181f54 100644 --- a/surfsense_backend/app/agents/new_chat/tools/report.py +++ b/surfsense_backend/app/agents/new_chat/tools/report.py @@ -33,7 +33,7 @@ from langchain_core.callbacks import dispatch_custom_event from langchain_core.messages import HumanMessage from langchain_core.tools import tool -from app.db import Report, async_session_maker +from app.db import Report, shielded_async_session from app.services.connector_service import ConnectorService from app.services.llm_service import get_document_summary_llm @@ -559,6 +559,7 @@ def create_generate_report_tool( thread_id: int | None = None, connector_service: ConnectorService | None = None, available_connectors: list[str] | None = None, + available_document_types: list[str] | None = None, ): """ Factory function to create the generate_report tool with injected dependencies. @@ -716,7 +717,7 @@ def create_generate_report_tool( async def _save_failed_report(error_msg: str) -> int | None: """Persist a failed report row using a short-lived session.""" try: - async with async_session_maker() as session: + async with shielded_async_session() as session: failed_report = Report( title=topic, content=None, @@ -750,7 +751,7 @@ def create_generate_report_tool( # ── Phase 1: READ (short-lived session) ────────────────────── # Fetch parent report and LLM config, then close the session # so no DB connection is held during the long LLM call. - async with async_session_maker() as read_session: + async with shielded_async_session() as read_session: if parent_report_id: parent_report = await read_session.get(Report, parent_report_id) if parent_report: @@ -827,7 +828,7 @@ def create_generate_report_tool( # Run all queries in parallel, each with its own session async def _run_single_query(q: str) -> str: - async with async_session_maker() as kb_session: + async with shielded_async_session() as kb_session: kb_connector_svc = ConnectorService( kb_session, search_space_id ) @@ -838,6 +839,7 @@ def create_generate_report_tool( connector_service=kb_connector_svc, top_k=10, available_connectors=available_connectors, + available_document_types=available_document_types, ) kb_results = await asyncio.gather( @@ -1026,7 +1028,7 @@ def create_generate_report_tool( # ── Phase 3: WRITE (short-lived session) ───────────────────── # Save the report to the database, then close the session. - async with async_session_maker() as write_session: + async with shielded_async_session() as write_session: report = Report( title=topic, content=report_content, diff --git a/surfsense_backend/app/agents/new_chat/tools/search_surfsense_docs.py b/surfsense_backend/app/agents/new_chat/tools/search_surfsense_docs.py index b9b370c23..ec86c3ffa 100644 --- a/surfsense_backend/app/agents/new_chat/tools/search_surfsense_docs.py +++ b/surfsense_backend/app/agents/new_chat/tools/search_surfsense_docs.py @@ -14,8 +14,8 @@ from langchain_core.tools import tool from sqlalchemy import select from sqlalchemy.ext.asyncio import AsyncSession -from app.config import config from app.db import SurfsenseDocsChunk, SurfsenseDocsDocument +from app.utils.document_converters import embed_text def format_surfsense_docs_results(results: list[tuple]) -> str: @@ -100,7 +100,7 @@ async def search_surfsense_docs_async( Formatted string with relevant documentation content """ # Get embedding for the query - query_embedding = config.embedding_model_instance.embed(query) + query_embedding = embed_text(query) # Vector similarity search on chunks, joining with documents stmt = ( diff --git a/surfsense_backend/app/agents/new_chat/tools/shared_memory.py b/surfsense_backend/app/agents/new_chat/tools/shared_memory.py index 8cd4148ba..ba69f1ce8 100644 --- a/surfsense_backend/app/agents/new_chat/tools/shared_memory.py +++ b/surfsense_backend/app/agents/new_chat/tools/shared_memory.py @@ -8,8 +8,8 @@ from langchain_core.tools import tool from sqlalchemy import select from sqlalchemy.ext.asyncio import AsyncSession -from app.config import config from app.db import MemoryCategory, SharedMemory, User +from app.utils.document_converters import embed_text logger = logging.getLogger(__name__) @@ -64,7 +64,7 @@ async def save_shared_memory( count = await get_shared_memory_count(db_session, search_space_id) if count >= MAX_MEMORIES_PER_SEARCH_SPACE: await delete_oldest_shared_memory(db_session, search_space_id) - embedding = config.embedding_model_instance.embed(content) + embedding = embed_text(content) row = SharedMemory( search_space_id=search_space_id, created_by_id=_to_uuid(created_by_id), @@ -108,7 +108,7 @@ async def recall_shared_memory( if category and category in valid_categories: stmt = stmt.where(SharedMemory.category == MemoryCategory(category)) if query: - query_embedding = config.embedding_model_instance.embed(query) + query_embedding = embed_text(query) stmt = stmt.order_by( SharedMemory.embedding.op("<=>")(query_embedding) ).limit(top_k) diff --git a/surfsense_backend/app/agents/new_chat/tools/user_memory.py b/surfsense_backend/app/agents/new_chat/tools/user_memory.py index 23a0b8666..8aa516454 100644 --- a/surfsense_backend/app/agents/new_chat/tools/user_memory.py +++ b/surfsense_backend/app/agents/new_chat/tools/user_memory.py @@ -17,8 +17,8 @@ from langchain_core.tools import tool from sqlalchemy import select from sqlalchemy.ext.asyncio import AsyncSession -from app.config import config from app.db import MemoryCategory, UserMemory +from app.utils.document_converters import embed_text logger = logging.getLogger(__name__) @@ -178,7 +178,7 @@ def create_save_memory_tool( await delete_oldest_memory(db_session, user_id, search_space_id) # Generate embedding for the memory - embedding = config.embedding_model_instance.embed(content) + embedding = embed_text(content) # Create new memory using ORM # The pgvector Vector column type handles embedding conversion automatically @@ -268,7 +268,7 @@ def create_recall_memory_tool( if query: # Semantic search using embeddings - query_embedding = config.embedding_model_instance.embed(query) + query_embedding = embed_text(query) # Build query with vector similarity stmt = ( diff --git a/surfsense_backend/app/agents/podcaster/nodes.py b/surfsense_backend/app/agents/podcaster/nodes.py index 3f908737a..4bdfdfc48 100644 --- a/surfsense_backend/app/agents/podcaster/nodes.py +++ b/surfsense_backend/app/agents/podcaster/nodes.py @@ -12,7 +12,7 @@ from litellm import aspeech from app.config import config as app_config from app.services.kokoro_tts_service import get_kokoro_tts_service -from app.services.llm_service import get_document_summary_llm +from app.services.llm_service import get_agent_llm from .configuration import Configuration from .prompts import get_podcast_generation_prompt @@ -31,7 +31,7 @@ async def create_podcast_transcript( user_prompt = configuration.user_prompt # Get search space's document summary LLM - llm = await get_document_summary_llm(state.db_session, search_space_id) + llm = await get_agent_llm(state.db_session, search_space_id) if not llm: error_message = ( f"No document summary LLM configured for search space {search_space_id}" diff --git a/surfsense_backend/app/app.py b/surfsense_backend/app/app.py index 72475e3a7..e6db5670e 100644 --- a/surfsense_backend/app/app.py +++ b/surfsense_backend/app/app.py @@ -1,4 +1,5 @@ import asyncio +import gc import logging import time from collections import defaultdict @@ -15,6 +16,9 @@ from slowapi.errors import RateLimitExceeded from slowapi.middleware import SlowAPIMiddleware from slowapi.util import get_remote_address from sqlalchemy.ext.asyncio import AsyncSession +from starlette.middleware.base import BaseHTTPMiddleware, RequestResponseEndpoint +from starlette.requests import Request as StarletteRequest +from starlette.responses import Response as StarletteResponse from uvicorn.middleware.proxy_headers import ProxyHeadersMiddleware from app.agents.new_chat.checkpointer import ( @@ -28,6 +32,7 @@ from app.routes.auth_routes import router as auth_router from app.schemas import UserCreate, UserRead, UserUpdate from app.tasks.surfsense_docs_indexer import seed_surfsense_docs from app.users import SECRET, auth_backend, current_active_user, fastapi_users +from app.utils.perf import get_perf_logger, log_system_snapshot rate_limit_logger = logging.getLogger("surfsense.rate_limit") @@ -99,22 +104,24 @@ def _check_rate_limit_memory( now = time.monotonic() with _memory_lock: - # Evict timestamps outside the current window - _memory_rate_limits[key] = [ - t for t in _memory_rate_limits[key] if now - t < window_seconds - ] + timestamps = [t for t in _memory_rate_limits[key] if now - t < window_seconds] - if len(_memory_rate_limits[key]) >= max_requests: + if not timestamps: + _memory_rate_limits.pop(key, None) + else: + _memory_rate_limits[key] = timestamps + + if len(timestamps) >= max_requests: rate_limit_logger.warning( f"Rate limit exceeded (in-memory fallback) on {scope} for IP {client_ip} " - f"({len(_memory_rate_limits[key])}/{max_requests} in {window_seconds}s)" + f"({len(timestamps)}/{max_requests} in {window_seconds}s)" ) raise HTTPException( status_code=429, detail="RATE_LIMIT_EXCEEDED", ) - _memory_rate_limits[key].append(now) + _memory_rate_limits[key] = [*timestamps, now] def _check_rate_limit( @@ -175,18 +182,47 @@ def rate_limit_password_reset(request: Request): ) +def _enable_slow_callback_logging(threshold_sec: float = 0.5) -> None: + """Monkey-patch the event loop to warn whenever a callback blocks longer than *threshold_sec*. + + This helps pinpoint synchronous code that freezes the entire FastAPI server. + Only active when the PERF_DEBUG env var is set (to avoid overhead in production). + """ + import os + + if not os.environ.get("PERF_DEBUG"): + return + + _slow_log = logging.getLogger("surfsense.perf.slow") + _slow_log.setLevel(logging.WARNING) + if not _slow_log.handlers: + _h = logging.StreamHandler() + _h.setFormatter(logging.Formatter("%(asctime)s [SLOW-CALLBACK] %(message)s")) + _slow_log.addHandler(_h) + _slow_log.propagate = False + + loop = asyncio.get_running_loop() + loop.slow_callback_duration = threshold_sec # type: ignore[attr-defined] + loop.set_debug(True) + _slow_log.warning( + "Event-loop slow-callback detector ENABLED (threshold=%.1fs). " + "Set PERF_DEBUG='' to disable.", + threshold_sec, + ) + + @asynccontextmanager async def lifespan(app: FastAPI): - # Not needed if you setup a migration system like Alembic + # Tune GC: lower gen-2 threshold so long-lived garbage is collected + # sooner (default 700/10/10 → 700/10/5). This reduces peak RSS + # with minimal CPU overhead. + gc.set_threshold(700, 10, 5) + + _enable_slow_callback_logging(threshold_sec=0.5) await create_db_and_tables() - # Setup LangGraph checkpointer tables for conversation persistence await setup_checkpointer_tables() - # Initialize LLM Router for Auto mode load balancing initialize_llm_router() - # Initialize Image Generation Router for Auto mode load balancing initialize_image_gen_router() - # Seed Surfsense documentation (with timeout so a slow embedding API - # doesn't block startup indefinitely and make the container unresponsive) try: await asyncio.wait_for(seed_surfsense_docs(), timeout=120) except TimeoutError: @@ -194,8 +230,11 @@ async def lifespan(app: FastAPI): "Surfsense docs seeding timed out after 120s — skipping. " "Docs will be indexed on the next restart." ) + + log_system_snapshot("startup_complete") + yield - # Cleanup: close checkpointer connection on shutdown + await close_checkpointer() @@ -213,6 +252,63 @@ app = FastAPI(lifespan=lifespan) app.state.limiter = limiter app.add_exception_handler(RateLimitExceeded, _rate_limit_exceeded_handler) + +# --------------------------------------------------------------------------- +# Request-level performance middleware +# --------------------------------------------------------------------------- +# Logs wall-clock time, method, path, and status for every request so we can +# spot slow endpoints in production logs. + +_PERF_SLOW_REQUEST_THRESHOLD = float( + __import__("os").environ.get("PERF_SLOW_REQUEST_MS", "2000") +) + + +class RequestPerfMiddleware(BaseHTTPMiddleware): + """Middleware that logs per-request wall-clock time. + + - ALL requests are logged at DEBUG level. + - Requests exceeding PERF_SLOW_REQUEST_MS (default 2000ms) are logged at + WARNING level with a system snapshot so we can correlate slow responses + with CPU/memory usage at that moment. + """ + + async def dispatch( + self, request: StarletteRequest, call_next: RequestResponseEndpoint + ) -> StarletteResponse: + perf = get_perf_logger() + t0 = time.perf_counter() + response = await call_next(request) + elapsed_ms = (time.perf_counter() - t0) * 1000 + + path = request.url.path + method = request.method + status = response.status_code + + perf.debug( + "[request] %s %s -> %d in %.1fms", + method, + path, + status, + elapsed_ms, + ) + + if elapsed_ms > _PERF_SLOW_REQUEST_THRESHOLD: + perf.warning( + "[SLOW_REQUEST] %s %s -> %d in %.1fms (threshold=%.0fms)", + method, + path, + status, + elapsed_ms, + _PERF_SLOW_REQUEST_THRESHOLD, + ) + log_system_snapshot("slow_request") + + return response + + +app.add_middleware(RequestPerfMiddleware) + # Add SlowAPI middleware for automatic rate limiting # Uses Starlette BaseHTTPMiddleware (not the raw ASGI variant) to avoid # corrupting StreamingResponse — SlowAPIASGIMiddleware re-sends diff --git a/surfsense_backend/app/connectors/composio_gmail_connector.py b/surfsense_backend/app/connectors/composio_gmail_connector.py index 4764a0a41..e83ba5cfb 100644 --- a/surfsense_backend/app/connectors/composio_gmail_connector.py +++ b/surfsense_backend/app/connectors/composio_gmail_connector.py @@ -14,7 +14,6 @@ from sqlalchemy.ext.asyncio import AsyncSession from sqlalchemy.future import select from sqlalchemy.orm import selectinload -from app.config import config from app.connectors.composio_connector import ComposioConnector from app.db import Document, DocumentStatus, DocumentType from app.services.composio_service import TOOLKIT_TO_DOCUMENT_TYPE @@ -27,6 +26,7 @@ from app.tasks.connector_indexers.base import ( ) from app.utils.document_converters import ( create_document_chunks, + embed_text, generate_content_hash, generate_document_summary, generate_unique_identifier_hash, @@ -383,6 +383,7 @@ async def _process_gmail_messages_phase2( connector_id: int, search_space_id: int, user_id: str, + enable_summary: bool = False, on_heartbeat_callback: HeartbeatCallbackType | None = None, ) -> tuple[int, int]: """ @@ -415,7 +416,7 @@ async def _process_gmail_messages_phase2( session, user_id, search_space_id ) - if user_llm: + if user_llm and enable_summary: document_metadata_for_summary = { "message_id": item["message_id"], "thread_id": item["thread_id"], @@ -427,10 +428,8 @@ async def _process_gmail_messages_phase2( item["markdown_content"], user_llm, document_metadata_for_summary ) else: - summary_content = f"Gmail: {item['subject']}\n\nFrom: {item['sender']}\nDate: {item['date_str']}" - summary_embedding = config.embedding_model_instance.embed( - summary_content - ) + summary_content = f"Gmail: {item['subject']}\n\nFrom: {item['sender']}\nDate: {item['date_str']}\n\n{item['markdown_content']}" + summary_embedding = embed_text(summary_content) chunks = await create_document_chunks(item["markdown_content"]) @@ -646,6 +645,7 @@ async def index_composio_gmail( connector_id=connector_id, search_space_id=search_space_id, user_id=user_id, + enable_summary=getattr(connector, "enable_summary", False), on_heartbeat_callback=on_heartbeat_callback, ) diff --git a/surfsense_backend/app/connectors/composio_google_calendar_connector.py b/surfsense_backend/app/connectors/composio_google_calendar_connector.py index 6593721a1..63bade873 100644 --- a/surfsense_backend/app/connectors/composio_google_calendar_connector.py +++ b/surfsense_backend/app/connectors/composio_google_calendar_connector.py @@ -14,7 +14,6 @@ from sqlalchemy.ext.asyncio import AsyncSession from sqlalchemy.future import select from sqlalchemy.orm import selectinload -from app.config import config from app.connectors.composio_connector import ComposioConnector from app.db import Document, DocumentStatus, DocumentType from app.services.composio_service import TOOLKIT_TO_DOCUMENT_TYPE @@ -27,6 +26,7 @@ from app.tasks.connector_indexers.base import ( ) from app.utils.document_converters import ( create_document_chunks, + embed_text, generate_content_hash, generate_document_summary, generate_unique_identifier_hash, @@ -440,7 +440,7 @@ async def index_composio_google_calendar( session, user_id, search_space_id ) - if user_llm: + if user_llm and connector.enable_summary: document_metadata_for_summary = { "event_id": item["event_id"], "summary": item["summary"], @@ -456,12 +456,10 @@ async def index_composio_google_calendar( document_metadata_for_summary, ) else: - summary_content = f"Calendar: {item['summary']}\n\nStart: {item['start_time']}\nEnd: {item['end_time']}" - if item["location"]: - summary_content += f"\nLocation: {item['location']}" - summary_embedding = config.embedding_model_instance.embed( - summary_content + summary_content = ( + f"Calendar: {item['summary']}\n\n{item['markdown_content']}" ) + summary_embedding = embed_text(summary_content) chunks = await create_document_chunks(item["markdown_content"]) diff --git a/surfsense_backend/app/connectors/composio_google_drive_connector.py b/surfsense_backend/app/connectors/composio_google_drive_connector.py index 4ccd195e6..c10edb7e9 100644 --- a/surfsense_backend/app/connectors/composio_google_drive_connector.py +++ b/surfsense_backend/app/connectors/composio_google_drive_connector.py @@ -31,6 +31,7 @@ from app.tasks.connector_indexers.base import ( ) from app.utils.document_converters import ( create_document_chunks, + embed_text, generate_content_hash, generate_document_summary, generate_unique_identifier_hash, @@ -714,6 +715,7 @@ async def index_composio_google_drive( max_items=max_items, task_logger=task_logger, log_entry=log_entry, + enable_summary=getattr(connector, "enable_summary", False), on_heartbeat_callback=on_heartbeat_callback, ) else: @@ -747,6 +749,7 @@ async def index_composio_google_drive( max_items=max_items, task_logger=task_logger, log_entry=log_entry, + enable_summary=getattr(connector, "enable_summary", False), on_heartbeat_callback=on_heartbeat_callback, ) @@ -829,6 +832,7 @@ async def _index_composio_drive_delta_sync( max_items: int, task_logger: TaskLoggingService, log_entry, + enable_summary: bool = False, on_heartbeat_callback: HeartbeatCallbackType | None = None, ) -> tuple[int, int, list[str]]: """Index Google Drive files using delta sync with real-time document status updates. @@ -1079,7 +1083,7 @@ async def _index_composio_drive_delta_sync( session, user_id, search_space_id ) - if user_llm: + if user_llm and enable_summary: document_metadata_for_summary = { "file_id": item["file_id"], "file_name": item["file_name"], @@ -1090,10 +1094,8 @@ async def _index_composio_drive_delta_sync( markdown_content, user_llm, document_metadata_for_summary ) else: - summary_content = f"Google Drive File: {item['file_name']}\n\nType: {item['mime_type']}" - summary_embedding = config.embedding_model_instance.embed( - summary_content - ) + summary_content = f"Google Drive File: {item['file_name']}\n\nType: {item['mime_type']}\n\n{markdown_content}" + summary_embedding = embed_text(summary_content) chunks = await create_document_chunks(markdown_content) @@ -1155,6 +1157,7 @@ async def _index_composio_drive_full_scan( max_items: int, task_logger: TaskLoggingService, log_entry, + enable_summary: bool = False, on_heartbeat_callback: HeartbeatCallbackType | None = None, ) -> tuple[int, int, list[str]]: """Index Google Drive files using full scan with real-time document status updates.""" @@ -1488,7 +1491,7 @@ async def _index_composio_drive_full_scan( session, user_id, search_space_id ) - if user_llm: + if user_llm and enable_summary: document_metadata_for_summary = { "file_id": item["file_id"], "file_name": item["file_name"], @@ -1499,10 +1502,8 @@ async def _index_composio_drive_full_scan( markdown_content, user_llm, document_metadata_for_summary ) else: - summary_content = f"Google Drive File: {item['file_name']}\n\nType: {item['mime_type']}" - summary_embedding = config.embedding_model_instance.embed( - summary_content - ) + summary_content = f"Google Drive File: {item['file_name']}\n\nType: {item['mime_type']}\n\n{markdown_content}" + summary_embedding = embed_text(summary_content) chunks = await create_document_chunks(markdown_content) diff --git a/surfsense_backend/app/db.py b/surfsense_backend/app/db.py index 1c9181ed2..510f64cc3 100644 --- a/surfsense_backend/app/db.py +++ b/surfsense_backend/app/db.py @@ -1,7 +1,9 @@ from collections.abc import AsyncGenerator +from contextlib import asynccontextmanager from datetime import UTC, datetime -from enum import Enum +from enum import StrEnum +import anyio from fastapi import Depends from fastapi_users.db import SQLAlchemyBaseUserTableUUID, SQLAlchemyUserDatabase from pgvector.sqlalchemy import Vector @@ -31,7 +33,7 @@ if config.AUTH_TYPE == "GOOGLE": DATABASE_URL = config.DATABASE_URL -class DocumentType(str, Enum): +class DocumentType(StrEnum): EXTENSION = "EXTENSION" CRAWLED_URL = "CRAWLED_URL" FILE = "FILE" @@ -60,7 +62,7 @@ class DocumentType(str, Enum): COMPOSIO_GOOGLE_CALENDAR_CONNECTOR = "COMPOSIO_GOOGLE_CALENDAR_CONNECTOR" -class SearchSourceConnectorType(str, Enum): +class SearchSourceConnectorType(StrEnum): SERPER_API = "SERPER_API" # NOT IMPLEMENTED YET : DON'T REMEMBER WHY : MOST PROBABLY BECAUSE WE NEED TO CRAWL THE RESULTS RETURNED BY IT TAVILY_API = "TAVILY_API" SEARXNG_API = "SEARXNG_API" @@ -93,7 +95,7 @@ class SearchSourceConnectorType(str, Enum): COMPOSIO_GOOGLE_CALENDAR_CONNECTOR = "COMPOSIO_GOOGLE_CALENDAR_CONNECTOR" -class PodcastStatus(str, Enum): +class PodcastStatus(StrEnum): PENDING = "pending" GENERATING = "generating" READY = "ready" @@ -177,7 +179,7 @@ class DocumentStatus: return None -class LiteLLMProvider(str, Enum): +class LiteLLMProvider(StrEnum): """ Enum for LLM providers supported by LiteLLM. """ @@ -215,7 +217,7 @@ class LiteLLMProvider(str, Enum): CUSTOM = "CUSTOM" -class ImageGenProvider(str, Enum): +class ImageGenProvider(StrEnum): """ Enum for image generation providers supported by LiteLLM. This is a subset of LLM providers — only those that support image generation. @@ -233,7 +235,7 @@ class ImageGenProvider(str, Enum): NSCALE = "NSCALE" -class LogLevel(str, Enum): +class LogLevel(StrEnum): DEBUG = "DEBUG" INFO = "INFO" WARNING = "WARNING" @@ -241,13 +243,13 @@ class LogLevel(str, Enum): CRITICAL = "CRITICAL" -class LogStatus(str, Enum): +class LogStatus(StrEnum): IN_PROGRESS = "IN_PROGRESS" SUCCESS = "SUCCESS" FAILED = "FAILED" -class IncentiveTaskType(str, Enum): +class IncentiveTaskType(StrEnum): """ Enum for incentive task types that users can complete to earn free pages. Each task can only be completed once per user. @@ -298,7 +300,7 @@ INCENTIVE_TASKS_CONFIG = { } -class Permission(str, Enum): +class Permission(StrEnum): """ Granular permissions for search space resources. Use '*' (FULL_ACCESS) to grant all permissions. @@ -471,7 +473,7 @@ class BaseModel(Base): id = Column(Integer, primary_key=True, index=True) -class NewChatMessageRole(str, Enum): +class NewChatMessageRole(StrEnum): """Role enum for new chat messages.""" USER = "user" @@ -479,7 +481,7 @@ class NewChatMessageRole(str, Enum): SYSTEM = "system" -class ChatVisibility(str, Enum): +class ChatVisibility(StrEnum): """ Visibility/sharing level for chat threads. @@ -788,7 +790,7 @@ class ChatSessionState(BaseModel): ai_responding_to_user = relationship("User") -class MemoryCategory(str, Enum): +class MemoryCategory(StrEnum): """Categories for user memories.""" # Using lowercase keys to match PostgreSQL enum values @@ -1317,6 +1319,12 @@ class SearchSourceConnector(BaseModel, TimestampMixin): last_indexed_at = Column(TIMESTAMP(timezone=True), nullable=True) config = Column(JSON, nullable=False) + # Summary generation (LLM-based) - disabled by default to save resources. + # When enabled, improves hybrid search quality at the cost of LLM calls. + enable_summary = Column( + Boolean, nullable=False, default=False, server_default="false" + ) + # Periodic indexing fields periodic_indexing_enabled = Column(Boolean, nullable=False, default=False) indexing_frequency_minutes = Column(Integer, nullable=True) @@ -1850,10 +1858,37 @@ class RefreshToken(Base, TimestampMixin): return not self.is_expired and not self.is_revoked -engine = create_async_engine(DATABASE_URL) +engine = create_async_engine( + DATABASE_URL, + pool_size=30, + max_overflow=150, + pool_recycle=1800, + pool_pre_ping=True, + pool_timeout=30, +) async_session_maker = async_sessionmaker(engine, expire_on_commit=False) +@asynccontextmanager +async def shielded_async_session(): + """Cancellation-safe async session context manager. + + Starlette's BaseHTTPMiddleware cancels the task via an anyio cancel + scope when a client disconnects. A plain ``async with async_session_maker()`` + has its ``__aexit__`` (which awaits ``session.close()``) cancelled by the + scope, orphaning the underlying database connection. + + This wrapper ensures ``session.close()`` always completes by running it + inside ``anyio.CancelScope(shield=True)``. + """ + session = async_session_maker() + try: + yield session + finally: + with anyio.CancelScope(shield=True): + await session.close() + + async def setup_indexes(): async with engine.begin() as conn: # Create indexes diff --git a/surfsense_backend/app/indexing_pipeline/__init__.py b/surfsense_backend/app/indexing_pipeline/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/surfsense_backend/app/indexing_pipeline/adapters/__init__.py b/surfsense_backend/app/indexing_pipeline/adapters/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/surfsense_backend/app/indexing_pipeline/adapters/file_upload_adapter.py b/surfsense_backend/app/indexing_pipeline/adapters/file_upload_adapter.py new file mode 100644 index 000000000..0bbb67105 --- /dev/null +++ b/surfsense_backend/app/indexing_pipeline/adapters/file_upload_adapter.py @@ -0,0 +1,83 @@ +from sqlalchemy.ext.asyncio import AsyncSession + +from app.db import Document, DocumentStatus, DocumentType +from app.indexing_pipeline.connector_document import ConnectorDocument +from app.indexing_pipeline.document_hashing import compute_content_hash +from app.indexing_pipeline.indexing_pipeline_service import IndexingPipelineService + + +class UploadDocumentAdapter: + def __init__(self, session: AsyncSession) -> None: + self._session = session + self._service = IndexingPipelineService(session) + + async def index( + self, + markdown_content: str, + filename: str, + etl_service: str, + search_space_id: int, + user_id: str, + llm, + should_summarize: bool = False, + ) -> None: + connector_doc = ConnectorDocument( + title=filename, + source_markdown=markdown_content, + unique_id=filename, + document_type=DocumentType.FILE, + search_space_id=search_space_id, + created_by_id=user_id, + connector_id=None, + should_summarize=should_summarize, + should_use_code_chunker=False, + fallback_summary=markdown_content[:4000], + metadata={ + "FILE_NAME": filename, + "ETL_SERVICE": etl_service, + }, + ) + + documents = await self._service.prepare_for_indexing([connector_doc]) + + if not documents: + raise RuntimeError("prepare_for_indexing returned no documents") + + indexed = await self._service.index(documents[0], connector_doc, llm) + + if not DocumentStatus.is_state(indexed.status, DocumentStatus.READY): + raise RuntimeError(indexed.status.get("reason", "Indexing failed")) + + indexed.content_needs_reindexing = False + await self._session.commit() + + async def reindex(self, document: Document, llm) -> None: + """Re-index an existing document after its source_markdown has been updated.""" + if not document.source_markdown: + raise RuntimeError("Document has no source_markdown to reindex") + + metadata = document.document_metadata or {} + + connector_doc = ConnectorDocument( + title=document.title, + source_markdown=document.source_markdown, + unique_id=document.title, + document_type=document.document_type, + search_space_id=document.search_space_id, + created_by_id=str(document.created_by_id), + connector_id=document.connector_id, + should_summarize=True, + should_use_code_chunker=False, + fallback_summary=document.source_markdown[:4000], + metadata=metadata, + ) + + document.content_hash = compute_content_hash(connector_doc) + + indexed = await self._service.index(document, connector_doc, llm) + + if not DocumentStatus.is_state(indexed.status, DocumentStatus.READY): + raise RuntimeError(indexed.status.get("reason", "Reindexing failed")) + + indexed.content_needs_reindexing = False + await self._session.commit() diff --git a/surfsense_backend/app/indexing_pipeline/connector_document.py b/surfsense_backend/app/indexing_pipeline/connector_document.py new file mode 100644 index 000000000..019efe287 --- /dev/null +++ b/surfsense_backend/app/indexing_pipeline/connector_document.py @@ -0,0 +1,26 @@ +from pydantic import BaseModel, Field, field_validator + +from app.db import DocumentType + + +class ConnectorDocument(BaseModel): + """Canonical data transfer object produced by connector adapters and consumed by the indexing pipeline.""" + + title: str + source_markdown: str + unique_id: str + document_type: DocumentType + search_space_id: int = Field(gt=0) + should_summarize: bool = True + should_use_code_chunker: bool = False + fallback_summary: str | None = None + metadata: dict = {} + connector_id: int | None = None + created_by_id: str + + @field_validator("title", "source_markdown", "unique_id", "created_by_id") + @classmethod + def not_empty(cls, v: str, info) -> str: + if not v.strip(): + raise ValueError(f"{info.field_name} must not be empty or whitespace") + return v diff --git a/surfsense_backend/app/indexing_pipeline/document_chunker.py b/surfsense_backend/app/indexing_pipeline/document_chunker.py new file mode 100644 index 000000000..4f3c698ef --- /dev/null +++ b/surfsense_backend/app/indexing_pipeline/document_chunker.py @@ -0,0 +1,9 @@ +from app.config import config + + +def chunk_text(text: str, use_code_chunker: bool = False) -> list[str]: + """Chunk a text string using the configured chunker and return the chunk texts.""" + chunker = ( + config.code_chunker_instance if use_code_chunker else config.chunker_instance + ) + return [c.text for c in chunker.chunk(text)] diff --git a/surfsense_backend/app/indexing_pipeline/document_embedder.py b/surfsense_backend/app/indexing_pipeline/document_embedder.py new file mode 100644 index 000000000..adec24434 --- /dev/null +++ b/surfsense_backend/app/indexing_pipeline/document_embedder.py @@ -0,0 +1,3 @@ +from app.utils.document_converters import embed_text + +__all__ = ["embed_text"] diff --git a/surfsense_backend/app/indexing_pipeline/document_hashing.py b/surfsense_backend/app/indexing_pipeline/document_hashing.py new file mode 100644 index 000000000..5dd7767a4 --- /dev/null +++ b/surfsense_backend/app/indexing_pipeline/document_hashing.py @@ -0,0 +1,15 @@ +import hashlib + +from app.indexing_pipeline.connector_document import ConnectorDocument + + +def compute_unique_identifier_hash(doc: ConnectorDocument) -> str: + """Return a stable SHA-256 hash identifying a document by its source identity.""" + combined = f"{doc.document_type.value}:{doc.unique_id}:{doc.search_space_id}" + return hashlib.sha256(combined.encode("utf-8")).hexdigest() + + +def compute_content_hash(doc: ConnectorDocument) -> str: + """Return a SHA-256 hash of the document's content scoped to its search space.""" + combined = f"{doc.search_space_id}:{doc.source_markdown}" + return hashlib.sha256(combined.encode("utf-8")).hexdigest() diff --git a/surfsense_backend/app/indexing_pipeline/document_persistence.py b/surfsense_backend/app/indexing_pipeline/document_persistence.py new file mode 100644 index 000000000..d7810e516 --- /dev/null +++ b/surfsense_backend/app/indexing_pipeline/document_persistence.py @@ -0,0 +1,39 @@ +from datetime import UTC, datetime + +from sqlalchemy.ext.asyncio import AsyncSession +from sqlalchemy.orm import object_session +from sqlalchemy.orm.attributes import set_committed_value + +from app.db import Document, DocumentStatus + + +async def rollback_and_persist_failure( + session: AsyncSession, document: Document, message: str +) -> None: + """Roll back the current transaction and best-effort persist a failed status. + + Called exclusively from except blocks — must never raise, or the new exception + would chain with the original and mask it entirely. + """ + try: + await session.rollback() + except Exception: + return # Session is completely dead; nothing further we can do. + try: + await session.refresh(document) + document.updated_at = datetime.now(UTC) + document.status = DocumentStatus.failed(message) + await session.commit() + except Exception: + pass # Best-effort; document will be retried on the next sync. + + +def attach_chunks_to_document(document: Document, chunks: list) -> None: + """Assign chunks to a document without triggering SQLAlchemy async lazy loading.""" + set_committed_value(document, "chunks", chunks) + session = object_session(document) + if session is not None: + if document.id is not None: + for chunk in chunks: + chunk.document_id = document.id + session.add_all(chunks) diff --git a/surfsense_backend/app/indexing_pipeline/document_summarizer.py b/surfsense_backend/app/indexing_pipeline/document_summarizer.py new file mode 100644 index 000000000..76cc77377 --- /dev/null +++ b/surfsense_backend/app/indexing_pipeline/document_summarizer.py @@ -0,0 +1,30 @@ +from app.prompts import SUMMARY_PROMPT_TEMPLATE +from app.utils.document_converters import optimize_content_for_context_window + + +async def summarize_document( + source_markdown: str, llm, metadata: dict | None = None +) -> str: + """Generate a text summary of a document using an LLM, prefixed with metadata when provided.""" + model_name = getattr(llm, "model", "gpt-3.5-turbo") + optimized_content = optimize_content_for_context_window( + source_markdown, metadata, model_name + ) + + summary_chain = SUMMARY_PROMPT_TEMPLATE | llm + content_with_metadata = ( + f"\n\n{metadata}\n\n" + f"\n\n\n\n{optimized_content}\n\n" + ) + summary_result = await summary_chain.ainvoke({"document": content_with_metadata}) + summary_content = summary_result.content + + if metadata: + metadata_parts = ["# DOCUMENT METADATA"] + for key, value in metadata.items(): + if value: + metadata_parts.append(f"**{key.replace('_', ' ').title()}:** {value}") + metadata_section = "\n".join(metadata_parts) + return f"{metadata_section}\n\n# DOCUMENT SUMMARY\n\n{summary_content}" + + return summary_content diff --git a/surfsense_backend/app/indexing_pipeline/exceptions.py b/surfsense_backend/app/indexing_pipeline/exceptions.py new file mode 100644 index 000000000..9155e9baa --- /dev/null +++ b/surfsense_backend/app/indexing_pipeline/exceptions.py @@ -0,0 +1,146 @@ +from litellm.exceptions import ( + APIConnectionError, + APIResponseValidationError, + AuthenticationError, + BadGatewayError, + BadRequestError, + InternalServerError, + NotFoundError, + PermissionDeniedError, + RateLimitError, + ServiceUnavailableError, + Timeout, + UnprocessableEntityError, +) +from sqlalchemy.exc import IntegrityError as IntegrityError + +# Tuples for use directly in except clauses. +RETRYABLE_LLM_ERRORS = ( + RateLimitError, + Timeout, + ServiceUnavailableError, + BadGatewayError, + InternalServerError, + APIConnectionError, +) + +PERMANENT_LLM_ERRORS = ( + AuthenticationError, + PermissionDeniedError, + NotFoundError, + BadRequestError, + UnprocessableEntityError, + APIResponseValidationError, +) + +# (LiteLLMEmbeddings, CohereEmbeddings, GeminiEmbeddings all normalize to RuntimeError). +EMBEDDING_ERRORS = ( + RuntimeError, # local device failure or API backend normalization + OSError, # model files missing or corrupted (local backends) + MemoryError, # document too large for available RAM + OSError, # model files missing or corrupted (local backends) + MemoryError, # document too large for available RAM +) + + +class PipelineMessages: + RATE_LIMIT = "LLM rate limit exceeded. Will retry on next sync." + LLM_TIMEOUT = "LLM request timed out. Will retry on next sync." + LLM_UNAVAILABLE = "LLM service temporarily unavailable. Will retry on next sync." + LLM_BAD_GATEWAY = "LLM gateway error. Will retry on next sync." + LLM_SERVER_ERROR = "LLM internal server error. Will retry on next sync." + LLM_CONNECTION = "Could not reach the LLM service. Check network connectivity." + RATE_LIMIT = "LLM rate limit exceeded. Will retry on next sync." + LLM_TIMEOUT = "LLM request timed out. Will retry on next sync." + LLM_UNAVAILABLE = "LLM service temporarily unavailable. Will retry on next sync." + LLM_BAD_GATEWAY = "LLM gateway error. Will retry on next sync." + LLM_SERVER_ERROR = "LLM internal server error. Will retry on next sync." + LLM_CONNECTION = "Could not reach the LLM service. Check network connectivity." + + LLM_AUTH = "LLM authentication failed. Check your API key." + LLM_PERMISSION = "LLM request denied. Check your account permissions." + LLM_NOT_FOUND = "LLM model not found. Check your model configuration." + LLM_BAD_REQUEST = "LLM rejected the request. Document content may be invalid." + LLM_UNPROCESSABLE = ( + "Document exceeds the LLM context window even after optimization." + ) + LLM_RESPONSE = "LLM returned an invalid response." + LLM_AUTH = "LLM authentication failed. Check your API key." + LLM_PERMISSION = "LLM request denied. Check your account permissions." + LLM_NOT_FOUND = "LLM model not found. Check your model configuration." + LLM_BAD_REQUEST = "LLM rejected the request. Document content may be invalid." + LLM_UNPROCESSABLE = ( + "Document exceeds the LLM context window even after optimization." + ) + LLM_RESPONSE = "LLM returned an invalid response." + + EMBEDDING_FAILED = ( + "Embedding failed. Check your embedding model configuration or service." + ) + EMBEDDING_MODEL = "Embedding model files are missing or corrupted." + EMBEDDING_MEMORY = "Not enough memory to embed this document." + EMBEDDING_FAILED = ( + "Embedding failed. Check your embedding model configuration or service." + ) + EMBEDDING_MODEL = "Embedding model files are missing or corrupted." + EMBEDDING_MEMORY = "Not enough memory to embed this document." + + CHUNKING_OVERFLOW = "Document structure is too deeply nested to chunk." + + +def safe_exception_message(exc: Exception) -> str: + try: + return str(exc) + except Exception: + return "Something went wrong during indexing. Error details could not be retrieved." + + +def llm_retryable_message(exc: Exception) -> str: + try: + if isinstance(exc, RateLimitError): + return PipelineMessages.RATE_LIMIT + if isinstance(exc, Timeout): + return PipelineMessages.LLM_TIMEOUT + if isinstance(exc, ServiceUnavailableError): + return PipelineMessages.LLM_UNAVAILABLE + if isinstance(exc, BadGatewayError): + return PipelineMessages.LLM_BAD_GATEWAY + if isinstance(exc, InternalServerError): + return PipelineMessages.LLM_SERVER_ERROR + if isinstance(exc, APIConnectionError): + return PipelineMessages.LLM_CONNECTION + return safe_exception_message(exc) + except Exception: + return "Something went wrong when calling the LLM." + + +def llm_permanent_message(exc: Exception) -> str: + try: + if isinstance(exc, AuthenticationError): + return PipelineMessages.LLM_AUTH + if isinstance(exc, PermissionDeniedError): + return PipelineMessages.LLM_PERMISSION + if isinstance(exc, NotFoundError): + return PipelineMessages.LLM_NOT_FOUND + if isinstance(exc, BadRequestError): + return PipelineMessages.LLM_BAD_REQUEST + if isinstance(exc, UnprocessableEntityError): + return PipelineMessages.LLM_UNPROCESSABLE + if isinstance(exc, APIResponseValidationError): + return PipelineMessages.LLM_RESPONSE + return safe_exception_message(exc) + except Exception: + return "Something went wrong when calling the LLM." + + +def embedding_message(exc: Exception) -> str: + try: + if isinstance(exc, RuntimeError): + return PipelineMessages.EMBEDDING_FAILED + if isinstance(exc, OSError): + return PipelineMessages.EMBEDDING_MODEL + if isinstance(exc, MemoryError): + return PipelineMessages.EMBEDDING_MEMORY + return safe_exception_message(exc) + except Exception: + return "Something went wrong when generating the embedding." diff --git a/surfsense_backend/app/indexing_pipeline/indexing_pipeline_service.py b/surfsense_backend/app/indexing_pipeline/indexing_pipeline_service.py new file mode 100644 index 000000000..9460f900c --- /dev/null +++ b/surfsense_backend/app/indexing_pipeline/indexing_pipeline_service.py @@ -0,0 +1,272 @@ +import contextlib +import time +from datetime import UTC, datetime + +from sqlalchemy import delete, select +from sqlalchemy.exc import IntegrityError +from sqlalchemy.ext.asyncio import AsyncSession + +from app.db import Chunk, Document, DocumentStatus +from app.indexing_pipeline.connector_document import ConnectorDocument +from app.indexing_pipeline.document_chunker import chunk_text +from app.indexing_pipeline.document_embedder import embed_text +from app.indexing_pipeline.document_hashing import ( + compute_content_hash, + compute_unique_identifier_hash, +) +from app.indexing_pipeline.document_persistence import ( + attach_chunks_to_document, + rollback_and_persist_failure, +) +from app.indexing_pipeline.document_summarizer import summarize_document +from app.indexing_pipeline.exceptions import ( + EMBEDDING_ERRORS, + PERMANENT_LLM_ERRORS, + RETRYABLE_LLM_ERRORS, + PipelineMessages, + embedding_message, + llm_permanent_message, + llm_retryable_message, + safe_exception_message, +) +from app.indexing_pipeline.pipeline_logger import ( + PipelineLogContext, + log_batch_aborted, + log_chunking_overflow, + log_doc_skipped_unknown, + log_document_queued, + log_document_requeued, + log_document_updated, + log_embedding_error, + log_index_started, + log_index_success, + log_permanent_llm_error, + log_race_condition, + log_retryable_llm_error, + log_unexpected_error, +) +from app.utils.perf import get_perf_logger + + +class IndexingPipelineService: + """Single pipeline for indexing connector documents. All connectors use this service.""" + + def __init__(self, session: AsyncSession) -> None: + self.session = session + + async def prepare_for_indexing( + self, connector_docs: list[ConnectorDocument] + ) -> list[Document]: + """ + Persist new documents and detect changes, returning only those that need indexing. + """ + perf = get_perf_logger() + t0 = time.perf_counter() + + documents = [] + seen_hashes: set[str] = set() + batch_ctx = PipelineLogContext( + connector_id=connector_docs[0].connector_id if connector_docs else 0, + search_space_id=connector_docs[0].search_space_id if connector_docs else 0, + unique_id="batch", + ) + + for connector_doc in connector_docs: + ctx = PipelineLogContext( + connector_id=connector_doc.connector_id, + search_space_id=connector_doc.search_space_id, + unique_id=connector_doc.unique_id, + ) + try: + unique_identifier_hash = compute_unique_identifier_hash(connector_doc) + content_hash = compute_content_hash(connector_doc) + + if unique_identifier_hash in seen_hashes: + continue + seen_hashes.add(unique_identifier_hash) + + result = await self.session.execute( + select(Document).filter( + Document.unique_identifier_hash == unique_identifier_hash + ) + ) + existing = result.scalars().first() + + if existing is not None: + if existing.content_hash == content_hash: + if existing.title != connector_doc.title: + existing.title = connector_doc.title + existing.updated_at = datetime.now(UTC) + if not DocumentStatus.is_state( + existing.status, DocumentStatus.READY + ): + existing.status = DocumentStatus.pending() + existing.updated_at = datetime.now(UTC) + documents.append(existing) + log_document_requeued(ctx) + continue + + existing.title = connector_doc.title + existing.content_hash = content_hash + existing.source_markdown = connector_doc.source_markdown + existing.document_metadata = connector_doc.metadata + existing.updated_at = datetime.now(UTC) + existing.status = DocumentStatus.pending() + documents.append(existing) + log_document_updated(ctx) + continue + + duplicate = await self.session.execute( + select(Document).filter(Document.content_hash == content_hash) + ) + if duplicate.scalars().first() is not None: + continue + + document = Document( + title=connector_doc.title, + document_type=connector_doc.document_type, + content="Pending...", + content_hash=content_hash, + unique_identifier_hash=unique_identifier_hash, + source_markdown=connector_doc.source_markdown, + document_metadata=connector_doc.metadata, + search_space_id=connector_doc.search_space_id, + connector_id=connector_doc.connector_id, + created_by_id=connector_doc.created_by_id, + updated_at=datetime.now(UTC), + status=DocumentStatus.pending(), + ) + self.session.add(document) + documents.append(document) + log_document_queued(ctx) + + except Exception as e: + log_doc_skipped_unknown(ctx, e) + + try: + await self.session.commit() + perf.info( + "[indexing] prepare_for_indexing in %.3fs input=%d output=%d", + time.perf_counter() - t0, + len(connector_docs), + len(documents), + ) + return documents + except IntegrityError: + log_race_condition(batch_ctx) + await self.session.rollback() + return [] + except Exception as e: + log_batch_aborted(batch_ctx, e) + await self.session.rollback() + return [] + + async def index( + self, document: Document, connector_doc: ConnectorDocument, llm + ) -> Document: + """ + Run summarization, embedding, and chunking for a document and persist the results. + """ + ctx = PipelineLogContext( + connector_id=connector_doc.connector_id, + search_space_id=connector_doc.search_space_id, + unique_id=connector_doc.unique_id, + doc_id=document.id, + ) + perf = get_perf_logger() + t_index = time.perf_counter() + try: + log_index_started(ctx) + document.status = DocumentStatus.processing() + await self.session.commit() + + t_step = time.perf_counter() + if connector_doc.should_summarize and llm is not None: + content = await summarize_document( + connector_doc.source_markdown, llm, connector_doc.metadata + ) + perf.info( + "[indexing] summarize_document doc=%d in %.3fs", + document.id, + time.perf_counter() - t_step, + ) + elif connector_doc.should_summarize and connector_doc.fallback_summary: + content = connector_doc.fallback_summary + else: + content = connector_doc.source_markdown + + t_step = time.perf_counter() + embedding = embed_text(content) + perf.debug( + "[indexing] embed_text (summary) doc=%d in %.3fs", + document.id, + time.perf_counter() - t_step, + ) + + await self.session.execute( + delete(Chunk).where(Chunk.document_id == document.id) + ) + + t_step = time.perf_counter() + chunks = [ + Chunk(content=text, embedding=embed_text(text)) + for text in chunk_text( + connector_doc.source_markdown, + use_code_chunker=connector_doc.should_use_code_chunker, + ) + ] + perf.info( + "[indexing] chunk+embed doc=%d chunks=%d in %.3fs", + document.id, + len(chunks), + time.perf_counter() - t_step, + ) + + document.content = content + document.embedding = embedding + attach_chunks_to_document(document, chunks) + document.updated_at = datetime.now(UTC) + document.status = DocumentStatus.ready() + await self.session.commit() + perf.info( + "[indexing] index TOTAL doc=%d chunks=%d in %.3fs", + document.id, + len(chunks), + time.perf_counter() - t_index, + ) + log_index_success(ctx, chunk_count=len(chunks)) + + except RETRYABLE_LLM_ERRORS as e: + log_retryable_llm_error(ctx, e) + await rollback_and_persist_failure( + self.session, document, llm_retryable_message(e) + ) + + except PERMANENT_LLM_ERRORS as e: + log_permanent_llm_error(ctx, e) + await rollback_and_persist_failure( + self.session, document, llm_permanent_message(e) + ) + + except RecursionError as e: + log_chunking_overflow(ctx, e) + await rollback_and_persist_failure( + self.session, document, PipelineMessages.CHUNKING_OVERFLOW + ) + + except EMBEDDING_ERRORS as e: + log_embedding_error(ctx, e) + await rollback_and_persist_failure( + self.session, document, embedding_message(e) + ) + + except Exception as e: + log_unexpected_error(ctx, e) + await rollback_and_persist_failure( + self.session, document, safe_exception_message(e) + ) + + with contextlib.suppress(Exception): + await self.session.refresh(document) + + return document diff --git a/surfsense_backend/app/indexing_pipeline/pipeline_logger.py b/surfsense_backend/app/indexing_pipeline/pipeline_logger.py new file mode 100644 index 000000000..281a92c52 --- /dev/null +++ b/surfsense_backend/app/indexing_pipeline/pipeline_logger.py @@ -0,0 +1,126 @@ +import logging +from dataclasses import dataclass + +logger = logging.getLogger(__name__) + + +@dataclass +class PipelineLogContext: + connector_id: int | None + search_space_id: int + unique_id: str # always available from ConnectorDocument + doc_id: int | None = None # set once the DB row exists (index phase only) + + +class LogMessages: + # prepare_for_indexing + DOCUMENT_QUEUED = "New document queued for indexing." + DOCUMENT_UPDATED = "Document content changed, re-queued for indexing." + DOCUMENT_REQUEUED = "Stuck document re-queued for indexing." + DOC_SKIPPED_UNKNOWN = "Unexpected error — document skipped." + BATCH_ABORTED = "Fatal DB error — aborting prepare batch." + RACE_CONDITION = "Concurrent worker beat us to the commit — rolling back batch." + + # index + INDEX_STARTED = "Document indexing started." + INDEX_SUCCESS = "Document indexed successfully." + LLM_RETRYABLE = ( + "Retryable LLM error — document marked failed, will retry on next sync." + ) + LLM_PERMANENT = "Permanent LLM error — document marked failed." + EMBEDDING_FAILED = "Embedding error — document marked failed." + CHUNKING_OVERFLOW = "Chunking overflow — document marked failed." + UNEXPECTED = "Unexpected error — document marked failed." + + +def _format_context(ctx: PipelineLogContext) -> str: + parts = [ + f"connector_id={ctx.connector_id}", + f"search_space_id={ctx.search_space_id}", + f"unique_id={ctx.unique_id}", + ] + if ctx.doc_id is not None: + parts.append(f"doc_id={ctx.doc_id}") + return " ".join(parts) + + +def _build_message(msg: str, ctx: PipelineLogContext, **extra) -> str: + try: + parts = [msg, _format_context(ctx)] + for key, val in extra.items(): + parts.append(f"{key}={val}") + return " ".join(parts) + except Exception: + return msg + + +def _safe_log( + level_fn, msg: str, ctx: PipelineLogContext, exc_info=None, **extra +) -> None: + # Logging must never raise — a broken log call inside an except block would + # chain with the original exception and mask it entirely. + try: + message = _build_message(msg, ctx, **extra) + level_fn(message, exc_info=exc_info) + except Exception: + pass + + +# ── prepare_for_indexing ────────────────────────────────────────────────────── + + +def log_document_queued(ctx: PipelineLogContext) -> None: + _safe_log(logger.info, LogMessages.DOCUMENT_QUEUED, ctx) + + +def log_document_updated(ctx: PipelineLogContext) -> None: + _safe_log(logger.info, LogMessages.DOCUMENT_UPDATED, ctx) + + +def log_document_requeued(ctx: PipelineLogContext) -> None: + _safe_log(logger.info, LogMessages.DOCUMENT_REQUEUED, ctx) + + +def log_doc_skipped_unknown(ctx: PipelineLogContext, exc: Exception) -> None: + _safe_log( + logger.warning, LogMessages.DOC_SKIPPED_UNKNOWN, ctx, exc_info=exc, error=exc + ) + + +def log_race_condition(ctx: PipelineLogContext) -> None: + _safe_log(logger.warning, LogMessages.RACE_CONDITION, ctx) + + +def log_batch_aborted(ctx: PipelineLogContext, exc: Exception) -> None: + _safe_log(logger.error, LogMessages.BATCH_ABORTED, ctx, exc_info=exc, error=exc) + + +# ── index ───────────────────────────────────────────────────────────────────── + + +def log_index_started(ctx: PipelineLogContext) -> None: + _safe_log(logger.info, LogMessages.INDEX_STARTED, ctx) + + +def log_index_success(ctx: PipelineLogContext, chunk_count: int) -> None: + _safe_log(logger.info, LogMessages.INDEX_SUCCESS, ctx, chunk_count=chunk_count) + + +def log_retryable_llm_error(ctx: PipelineLogContext, exc: Exception) -> None: + _safe_log(logger.warning, LogMessages.LLM_RETRYABLE, ctx, exc_info=exc, error=exc) + + +def log_permanent_llm_error(ctx: PipelineLogContext, exc: Exception) -> None: + _safe_log(logger.error, LogMessages.LLM_PERMANENT, ctx, exc_info=exc, error=exc) + + +def log_embedding_error(ctx: PipelineLogContext, exc: Exception) -> None: + _safe_log(logger.error, LogMessages.EMBEDDING_FAILED, ctx, exc_info=exc, error=exc) + + +def log_chunking_overflow(ctx: PipelineLogContext, exc: Exception) -> None: + _safe_log(logger.error, LogMessages.CHUNKING_OVERFLOW, ctx, exc_info=exc, error=exc) + + +def log_unexpected_error(ctx: PipelineLogContext, exc: Exception) -> None: + _safe_log(logger.error, LogMessages.UNEXPECTED, ctx, exc_info=exc, error=exc) diff --git a/surfsense_backend/app/retriever/chunks_hybrid_search.py b/surfsense_backend/app/retriever/chunks_hybrid_search.py index 9aa301386..4787e8147 100644 --- a/surfsense_backend/app/retriever/chunks_hybrid_search.py +++ b/surfsense_backend/app/retriever/chunks_hybrid_search.py @@ -1,5 +1,10 @@ +import time from datetime import datetime +from app.utils.perf import get_perf_logger + +_MAX_FETCH_CHUNKS_PER_DOC = 30 + class ChucksHybridSearchRetriever: def __init__(self, db_session): @@ -38,9 +43,17 @@ class ChucksHybridSearchRetriever: from app.config import config from app.db import Chunk, Document + perf = get_perf_logger() + t0 = time.perf_counter() + # Get embedding for the query embedding_model = config.embedding_model_instance + t_embed = time.perf_counter() query_embedding = embedding_model.embed(query_text) + perf.debug( + "[chunk_search] vector_search embedding in %.3fs", + time.perf_counter() - t_embed, + ) # Build the query filtered by search space query = ( @@ -60,8 +73,16 @@ class ChucksHybridSearchRetriever: query = query.order_by(Chunk.embedding.op("<=>")(query_embedding)).limit(top_k) # Execute the query + t_db = time.perf_counter() result = await self.db_session.execute(query) chunks = result.scalars().all() + perf.info( + "[chunk_search] vector_search DB query in %.3fs results=%d (total %.3fs) space=%d", + time.perf_counter() - t_db, + len(chunks), + time.perf_counter() - t0, + search_space_id, + ) return chunks @@ -91,6 +112,9 @@ class ChucksHybridSearchRetriever: from app.db import Chunk, Document + perf = get_perf_logger() + t0 = time.perf_counter() + # Create tsvector and tsquery for PostgreSQL full-text search tsvector = func.to_tsvector("english", Chunk.content) tsquery = func.plainto_tsquery("english", query_text) @@ -118,6 +142,12 @@ class ChucksHybridSearchRetriever: # Execute the query result = await self.db_session.execute(query) chunks = result.scalars().all() + perf.info( + "[chunk_search] full_text_search in %.3fs results=%d space=%d", + time.perf_counter() - t0, + len(chunks), + search_space_id, + ) return chunks @@ -129,6 +159,7 @@ class ChucksHybridSearchRetriever: document_type: str | None = None, start_date: datetime | None = None, end_date: datetime | None = None, + query_embedding: list | None = None, ) -> list: """ Hybrid search that returns **documents** (not individual chunks). @@ -143,6 +174,7 @@ class ChucksHybridSearchRetriever: document_type: Optional document type to filter results (e.g., "FILE", "CRAWLED_URL") start_date: Optional start date for filtering documents by updated_at end_date: Optional end date for filtering documents by updated_at + query_embedding: Pre-computed embedding vector. If None, will be computed here. Returns: List of dictionaries containing document data and relevance scores. Each dict contains: @@ -157,9 +189,17 @@ class ChucksHybridSearchRetriever: from app.config import config from app.db import Chunk, Document, DocumentType - # Get embedding for the query - embedding_model = config.embedding_model_instance - query_embedding = embedding_model.embed(query_text) + perf = get_perf_logger() + t0 = time.perf_counter() + + if query_embedding is None: + embedding_model = config.embedding_model_instance + t_embed = time.perf_counter() + query_embedding = embedding_model.embed(query_text) + perf.debug( + "[chunk_search] hybrid_search embedding in %.3fs", + time.perf_counter() - t_embed, + ) # RRF constants k = 60 @@ -254,9 +294,17 @@ class ChucksHybridSearchRetriever: .limit(top_k) ) - # Execute the query + # Execute the RRF query + t_rrf = time.perf_counter() result = await self.db_session.execute(final_query) chunks_with_scores = result.all() + perf.info( + "[chunk_search] hybrid_search RRF query in %.3fs results=%d space=%d type=%s", + time.perf_counter() - t_rrf, + len(chunks_with_scores), + search_space_id, + document_type, + ) # If no results were found, return an empty list if not chunks_with_scores: @@ -300,8 +348,9 @@ class ChucksHybridSearchRetriever: if not doc_ids: return [] - # Fetch ALL chunks for selected documents in a single query so the final prompt can cite - # any chunk from those documents. + # Fetch chunks for selected documents. We cap per document to avoid + # loading hundreds of chunks for a single large file while still + # ensuring the chunks that matched the RRF query are always included. chunk_query = ( select(Chunk) .options(joinedload(Chunk.document)) @@ -311,7 +360,20 @@ class ChucksHybridSearchRetriever: .order_by(Chunk.document_id, Chunk.id) ) chunks_result = await self.db_session.execute(chunk_query) - all_chunks = chunks_result.scalars().all() + raw_chunks = chunks_result.scalars().all() + + matched_chunk_ids: set[int] = { + item["chunk_id"] for item in serialized_chunk_results + } + + doc_chunk_counts: dict[int, int] = {} + all_chunks: list = [] + for chunk in raw_chunks: + did = chunk.document_id + count = doc_chunk_counts.get(did, 0) + if chunk.id in matched_chunk_ids or count < _MAX_FETCH_CHUNKS_PER_DOC: + all_chunks.append(chunk) + doc_chunk_counts[did] = count + 1 # Assemble final doc-grouped results in the same order as doc_ids doc_map: dict[int, dict] = { @@ -354,4 +416,11 @@ class ChucksHybridSearchRetriever: ) final_docs.append(entry) + perf.info( + "[chunk_search] hybrid_search TOTAL in %.3fs docs=%d space=%d type=%s", + time.perf_counter() - t0, + len(final_docs), + search_space_id, + document_type, + ) return final_docs diff --git a/surfsense_backend/app/retriever/documents_hybrid_search.py b/surfsense_backend/app/retriever/documents_hybrid_search.py index 9ff104ff0..69e97384f 100644 --- a/surfsense_backend/app/retriever/documents_hybrid_search.py +++ b/surfsense_backend/app/retriever/documents_hybrid_search.py @@ -1,5 +1,10 @@ +import time from datetime import datetime +from app.utils.perf import get_perf_logger + +_MAX_FETCH_CHUNKS_PER_DOC = 30 + class DocumentHybridSearchRetriever: def __init__(self, db_session): @@ -38,6 +43,9 @@ class DocumentHybridSearchRetriever: from app.config import config from app.db import Document + perf = get_perf_logger() + t0 = time.perf_counter() + # Get embedding for the query embedding_model = config.embedding_model_instance query_embedding = embedding_model.embed(query_text) @@ -63,6 +71,12 @@ class DocumentHybridSearchRetriever: # Execute the query result = await self.db_session.execute(query) documents = result.scalars().all() + perf.info( + "[doc_search] vector_search in %.3fs results=%d space=%d", + time.perf_counter() - t0, + len(documents), + search_space_id, + ) return documents @@ -92,6 +106,9 @@ class DocumentHybridSearchRetriever: from app.db import Document + perf = get_perf_logger() + t0 = time.perf_counter() + # Create tsvector and tsquery for PostgreSQL full-text search tsvector = func.to_tsvector("english", Document.content) tsquery = func.plainto_tsquery("english", query_text) @@ -118,6 +135,12 @@ class DocumentHybridSearchRetriever: # Execute the query result = await self.db_session.execute(query) documents = result.scalars().all() + perf.info( + "[doc_search] full_text_search in %.3fs results=%d space=%d", + time.perf_counter() - t0, + len(documents), + search_space_id, + ) return documents @@ -129,6 +152,7 @@ class DocumentHybridSearchRetriever: document_type: str | None = None, start_date: datetime | None = None, end_date: datetime | None = None, + query_embedding: list | None = None, ) -> list: """ Hybrid search that returns **documents** (not individual chunks). @@ -143,7 +167,7 @@ class DocumentHybridSearchRetriever: document_type: Optional document type to filter results (e.g., "FILE", "CRAWLED_URL") start_date: Optional start date for filtering documents by updated_at end_date: Optional end date for filtering documents by updated_at - + query_embedding: Pre-computed embedding vector. If None, will be computed here. """ from sqlalchemy import func, select, text from sqlalchemy.orm import joinedload @@ -151,9 +175,12 @@ class DocumentHybridSearchRetriever: from app.config import config from app.db import Chunk, Document, DocumentType - # Get embedding for the query - embedding_model = config.embedding_model_instance - query_embedding = embedding_model.embed(query_text) + perf = get_perf_logger() + t0 = time.perf_counter() + + if query_embedding is None: + embedding_model = config.embedding_model_instance + query_embedding = embedding_model.embed(query_text) # RRF constants k = 60 @@ -254,7 +281,8 @@ class DocumentHybridSearchRetriever: # Collect document IDs for chunk fetching doc_ids: list[int] = [doc.id for doc, _score in documents_with_scores] - # Fetch ALL chunks for these documents in a single query + # Fetch chunks for these documents, capped per document to avoid + # loading hundreds of chunks for a single large file. chunks_query = ( select(Chunk) .options(joinedload(Chunk.document)) @@ -262,7 +290,16 @@ class DocumentHybridSearchRetriever: .order_by(Chunk.document_id, Chunk.id) ) chunks_result = await self.db_session.execute(chunks_query) - chunks = chunks_result.scalars().all() + raw_chunks = chunks_result.scalars().all() + + doc_chunk_counts: dict[int, int] = {} + chunks: list = [] + for chunk in raw_chunks: + did = chunk.document_id + count = doc_chunk_counts.get(did, 0) + if count < _MAX_FETCH_CHUNKS_PER_DOC: + chunks.append(chunk) + doc_chunk_counts[did] = count + 1 # Assemble doc-grouped results doc_map: dict[int, dict] = { @@ -303,4 +340,11 @@ class DocumentHybridSearchRetriever: ) final_docs.append(entry) + perf.info( + "[doc_search] hybrid_search TOTAL in %.3fs docs=%d space=%d type=%s", + time.perf_counter() - t0, + len(final_docs), + search_space_id, + document_type, + ) return final_docs diff --git a/surfsense_backend/app/routes/__init__.py b/surfsense_backend/app/routes/__init__.py index f8e22f872..6114dd207 100644 --- a/surfsense_backend/app/routes/__init__.py +++ b/surfsense_backend/app/routes/__init__.py @@ -36,6 +36,7 @@ from .podcasts_routes import router as podcasts_router from .public_chat_routes import router as public_chat_router from .rbac_routes import router as rbac_router from .reports_routes import router as reports_router +from .sandbox_routes import router as sandbox_router from .search_source_connectors_routes import router as search_source_connectors_router from .search_spaces_routes import router as search_spaces_router from .slack_add_connector_route import router as slack_add_connector_router @@ -50,6 +51,7 @@ router.include_router(editor_router) router.include_router(documents_router) router.include_router(notes_router) router.include_router(new_chat_router) # Chat with assistant-ui persistence +router.include_router(sandbox_router) # Sandbox file downloads (Daytona) router.include_router(chat_comments_router) router.include_router(podcasts_router) # Podcast task status and audio router.include_router(reports_router) # Report CRUD and export (PDF/DOCX) diff --git a/surfsense_backend/app/routes/chat_comments_routes.py b/surfsense_backend/app/routes/chat_comments_routes.py index 1c21c0f4a..f5a8fd0af 100644 --- a/surfsense_backend/app/routes/chat_comments_routes.py +++ b/surfsense_backend/app/routes/chat_comments_routes.py @@ -7,6 +7,8 @@ from sqlalchemy.ext.asyncio import AsyncSession from app.db import User, get_async_session from app.schemas.chat_comments import ( + CommentBatchRequest, + CommentBatchResponse, CommentCreateRequest, CommentListResponse, CommentReplyResponse, @@ -19,6 +21,7 @@ from app.services.chat_comments_service import ( create_reply, delete_comment, get_comments_for_message, + get_comments_for_messages_batch, get_user_mentions, update_comment, ) @@ -27,6 +30,16 @@ from app.users import current_active_user router = APIRouter() +@router.post("/messages/comments/batch", response_model=CommentBatchResponse) +async def batch_list_comments( + request: CommentBatchRequest, + session: AsyncSession = Depends(get_async_session), + user: User = Depends(current_active_user), +): + """Batch-fetch comments for multiple messages in one request.""" + return await get_comments_for_messages_batch(session, request.message_ids, user) + + @router.get("/messages/{message_id}/comments", response_model=CommentListResponse) async def list_comments( message_id: int, diff --git a/surfsense_backend/app/routes/documents_routes.py b/surfsense_backend/app/routes/documents_routes.py index 4349edc20..865fdf7b3 100644 --- a/surfsense_backend/app/routes/documents_routes.py +++ b/surfsense_backend/app/routes/documents_routes.py @@ -28,6 +28,7 @@ from app.schemas import ( DocumentWithChunksRead, PaginatedResponse, ) +from app.services.task_dispatcher import TaskDispatcher, get_task_dispatcher from app.users import current_active_user from app.utils.rbac import check_permission @@ -44,6 +45,10 @@ os.environ["UNSTRUCTURED_HAS_PATCHED_LOOP"] = "1" router = APIRouter() +MAX_FILES_PER_UPLOAD = 10 +MAX_FILE_SIZE_BYTES = 50 * 1024 * 1024 # 50 MB per file +MAX_TOTAL_SIZE_BYTES = 200 * 1024 * 1024 # 200 MB total + @router.post("/documents") async def create_documents( @@ -114,8 +119,10 @@ async def create_documents( async def create_documents_file_upload( files: list[UploadFile], search_space_id: int = Form(...), + should_summarize: bool = Form(False), session: AsyncSession = Depends(get_async_session), user: User = Depends(current_active_user), + dispatcher: TaskDispatcher = Depends(get_task_dispatcher), ): """ Upload files as documents with real-time status tracking. @@ -126,6 +133,8 @@ async def create_documents_file_upload( Requires DOCUMENTS_CREATE permission. """ + import os + import tempfile from datetime import datetime from app.db import DocumentStatus @@ -136,7 +145,6 @@ async def create_documents_file_upload( from app.utils.document_converters import generate_unique_identifier_hash try: - # Check permission await check_permission( session, user, @@ -148,51 +156,88 @@ async def create_documents_file_upload( if not files: raise HTTPException(status_code=400, detail="No files provided") + if len(files) > MAX_FILES_PER_UPLOAD: + raise HTTPException( + status_code=413, + detail=f"Too many files. Maximum {MAX_FILES_PER_UPLOAD} files per upload.", + ) + + total_size = 0 + for file in files: + file_size = file.size or 0 + if file_size > MAX_FILE_SIZE_BYTES: + raise HTTPException( + status_code=413, + detail=f"File '{file.filename}' ({file_size / (1024 * 1024):.1f} MB) " + f"exceeds the {MAX_FILE_SIZE_BYTES // (1024 * 1024)} MB per-file limit.", + ) + total_size += file_size + + if total_size > MAX_TOTAL_SIZE_BYTES: + raise HTTPException( + status_code=413, + detail=f"Total upload size ({total_size / (1024 * 1024):.1f} MB) " + f"exceeds the {MAX_TOTAL_SIZE_BYTES // (1024 * 1024)} MB limit.", + ) + + # ===== Read all files concurrently to avoid blocking the event loop ===== + async def _read_and_save(file: UploadFile) -> tuple[str, str, int]: + """Read upload content and write to temp file off the event loop.""" + content = await file.read() + file_size = len(content) + filename = file.filename or "unknown" + + if file_size > MAX_FILE_SIZE_BYTES: + raise HTTPException( + status_code=413, + detail=f"File '{filename}' ({file_size / (1024 * 1024):.1f} MB) " + f"exceeds the {MAX_FILE_SIZE_BYTES // (1024 * 1024)} MB per-file limit.", + ) + + def _write_temp() -> str: + with tempfile.NamedTemporaryFile( + delete=False, suffix=os.path.splitext(filename)[1] + ) as tmp: + tmp.write(content) + return tmp.name + + temp_path = await asyncio.to_thread(_write_temp) + return temp_path, filename, file_size + + saved_files = await asyncio.gather(*(_read_and_save(f) for f in files)) + + actual_total_size = sum(size for _, _, size in saved_files) + if actual_total_size > MAX_TOTAL_SIZE_BYTES: + for temp_path, _, _ in saved_files: + os.unlink(temp_path) + raise HTTPException( + status_code=413, + detail=f"Total upload size ({actual_total_size / (1024 * 1024):.1f} MB) " + f"exceeds the {MAX_TOTAL_SIZE_BYTES // (1024 * 1024)} MB limit.", + ) + + # ===== PHASE 1: Create pending documents for all files ===== created_documents: list[Document] = [] - files_to_process: list[ - tuple[Document, str, str] - ] = [] # (document, temp_path, filename) + files_to_process: list[tuple[Document, str, str]] = [] skipped_duplicates = 0 duplicate_document_ids: list[int] = [] - # ===== PHASE 1: Create pending documents for all files ===== - # This makes ALL documents visible in the UI immediately with pending status - for file in files: + for temp_path, filename, file_size in saved_files: try: - import os - import tempfile - - # Save file to temp location - with tempfile.NamedTemporaryFile( - delete=False, suffix=os.path.splitext(file.filename or "")[1] - ) as temp_file: - temp_path = temp_file.name - - content = await file.read() - with open(temp_path, "wb") as f: - f.write(content) - - file_size = len(content) - - # Generate unique identifier for deduplication check unique_identifier_hash = generate_unique_identifier_hash( - DocumentType.FILE, file.filename or "unknown", search_space_id + DocumentType.FILE, filename, search_space_id ) - # Check if document already exists (by unique identifier) existing = await check_document_by_unique_identifier( session, unique_identifier_hash ) if existing: if DocumentStatus.is_state(existing.status, DocumentStatus.READY): - # True duplicate — content already indexed, skip os.unlink(temp_path) skipped_duplicates += 1 duplicate_document_ids.append(existing.id) continue - # Existing document is stuck (failed/pending/processing) - # Reset it to pending and re-dispatch for processing existing.status = DocumentStatus.pending() existing.content = "Processing..." existing.document_metadata = { @@ -202,61 +247,53 @@ async def create_documents_file_upload( } existing.updated_at = get_current_timestamp() created_documents.append(existing) - files_to_process.append( - (existing, temp_path, file.filename or "unknown") - ) + files_to_process.append((existing, temp_path, filename)) continue - # Create pending document (visible immediately in UI via ElectricSQL) document = Document( search_space_id=search_space_id, - title=file.filename or "Uploaded File", + title=filename if filename != "unknown" else "Uploaded File", document_type=DocumentType.FILE, document_metadata={ - "FILE_NAME": file.filename, + "FILE_NAME": filename, "file_size": file_size, "upload_time": datetime.now().isoformat(), }, - content="Processing...", # Placeholder until processed - content_hash=unique_identifier_hash, # Temporary, updated when ready + content="Processing...", + content_hash=unique_identifier_hash, unique_identifier_hash=unique_identifier_hash, embedding=None, - status=DocumentStatus.pending(), # Shows "pending" in UI + status=DocumentStatus.pending(), updated_at=get_current_timestamp(), created_by_id=str(user.id), ) session.add(document) created_documents.append(document) - files_to_process.append( - (document, temp_path, file.filename or "unknown") - ) + files_to_process.append((document, temp_path, filename)) + except HTTPException: + raise except Exception as e: + os.unlink(temp_path) raise HTTPException( status_code=422, - detail=f"Failed to process file {file.filename}: {e!s}", + detail=f"Failed to process file {filename}: {e!s}", ) from e - # Commit all pending documents - they appear in UI immediately via ElectricSQL if created_documents: await session.commit() - # Refresh to get generated IDs for doc in created_documents: await session.refresh(doc) - # ===== PHASE 2: Dispatch Celery tasks for each file ===== - # Each task will update document status: pending → processing → ready/failed - from app.tasks.celery_tasks.document_tasks import ( - process_file_upload_with_document_task, - ) - + # ===== PHASE 2: Dispatch tasks for each file ===== for document, temp_path, filename in files_to_process: - process_file_upload_with_document_task.delay( + await dispatcher.dispatch_file_processing( document_id=document.id, temp_path=temp_path, filename=filename, search_space_id=search_space_id, user_id=str(user.id), + should_summarize=should_summarize, ) return { diff --git a/surfsense_backend/app/routes/new_chat_routes.py b/surfsense_backend/app/routes/new_chat_routes.py index 1713f4ea8..e0d78696f 100644 --- a/surfsense_backend/app/routes/new_chat_routes.py +++ b/surfsense_backend/app/routes/new_chat_routes.py @@ -10,6 +10,8 @@ These endpoints support the ThreadHistoryAdapter pattern from assistant-ui: - POST /threads/{thread_id}/messages - Append message """ +import asyncio +import logging from datetime import UTC, datetime from fastapi import APIRouter, Depends, HTTPException, Request @@ -30,6 +32,7 @@ from app.db import ( SearchSpace, User, get_async_session, + shielded_async_session, ) from app.schemas.new_chat import ( NewChatMessageAppend, @@ -52,9 +55,50 @@ from app.tasks.chat.stream_new_chat import stream_new_chat, stream_resume_chat from app.users import current_active_user from app.utils.rbac import check_permission +_logger = logging.getLogger(__name__) +_background_tasks: set[asyncio.Task] = set() + router = APIRouter() +def _try_delete_sandbox(thread_id: int) -> None: + """Fire-and-forget sandbox + local file deletion so the HTTP response isn't blocked.""" + from app.agents.new_chat.sandbox import ( + delete_local_sandbox_files, + delete_sandbox, + is_sandbox_enabled, + ) + + if not is_sandbox_enabled(): + return + + async def _bg() -> None: + try: + await delete_sandbox(thread_id) + except Exception: + _logger.warning( + "Background sandbox delete failed for thread %s", + thread_id, + exc_info=True, + ) + try: + delete_local_sandbox_files(thread_id) + except Exception: + _logger.warning( + "Local sandbox file cleanup failed for thread %s", + thread_id, + exc_info=True, + ) + + try: + loop = asyncio.get_running_loop() + task = loop.create_task(_bg()) + _background_tasks.add(task) + task.add_done_callback(_background_tasks.discard) + except RuntimeError: + pass + + async def check_thread_access( session: AsyncSession, thread: NewChatThread, @@ -648,6 +692,9 @@ async def delete_thread( await session.delete(db_thread) await session.commit() + + _try_delete_sandbox(thread_id) + return {"message": "Thread deleted successfully"} except HTTPException: @@ -1046,13 +1093,18 @@ async def handle_new_chat( # on searchspaces/documents for the entire duration of the stream. # expire_on_commit=False keeps loaded ORM attrs usable. await session.commit() + # Close the dependency session now so its connection returns to + # the pool before streaming begins. Without this, Starlette's + # BaseHTTPMiddleware cancels the scope on client disconnect and + # the dependency generator's __aexit__ never runs, orphaning the + # connection (the "Exception terminating connection" errors). + await session.close() return StreamingResponse( stream_new_chat( user_query=request.user_query, search_space_id=request.search_space_id, chat_id=request.chat_id, - session=session, user_id=str(user.id), llm_config_id=llm_config_id, mentioned_document_ids=request.mentioned_document_ids, @@ -1277,6 +1329,7 @@ async def regenerate_response( # on searchspaces/documents for the entire duration of the stream. # expire_on_commit=False keeps loaded ORM attrs (including messages_to_delete PKs) usable. await session.commit() + await session.close() # Create a wrapper generator that deletes messages only AFTER streaming succeeds # This prevents data loss if streaming fails (network error, LLM error, etc.) @@ -1287,7 +1340,6 @@ async def regenerate_response( user_query=user_query_to_use, search_space_id=request.search_space_id, chat_id=thread_id, - session=session, user_id=str(user.id), llm_config_id=llm_config_id, mentioned_document_ids=request.mentioned_document_ids, @@ -1298,29 +1350,35 @@ async def regenerate_response( current_user_display_name=user.display_name or "A team member", ): yield chunk - # If we get here, streaming completed successfully streaming_completed = True finally: - # Only delete old messages if streaming completed successfully - # This ensures we don't lose data on streaming failures - if streaming_completed and messages_to_delete: + # Only delete old messages if streaming completed successfully. + # Uses a fresh session since stream_new_chat manages its own. + if streaming_completed and message_ids_to_delete: try: - for msg in messages_to_delete: - await session.delete(msg) - await session.commit() + async with shielded_async_session() as cleanup_session: + for msg_id in message_ids_to_delete: + _res = await cleanup_session.execute( + select(NewChatMessage).filter( + NewChatMessage.id == msg_id + ) + ) + _msg = _res.scalars().first() + if _msg: + await cleanup_session.delete(_msg) + await cleanup_session.commit() - # Delete any public snapshots that contain the modified messages - from app.services.public_chat_service import ( - delete_affected_snapshots, - ) + from app.services.public_chat_service import ( + delete_affected_snapshots, + ) - await delete_affected_snapshots( - session, thread_id, message_ids_to_delete - ) + await delete_affected_snapshots( + cleanup_session, thread_id, message_ids_to_delete + ) except Exception as cleanup_error: - # Log but don't fail - the new messages are already streamed - print( - f"[regenerate] Warning: Failed to delete old messages: {cleanup_error}" + _logger.warning( + "[regenerate] Failed to delete old messages: %s", + cleanup_error, ) # Return streaming response with checkpoint_id for rewinding @@ -1394,13 +1452,13 @@ async def resume_chat( # Release the read-transaction so we don't hold ACCESS SHARE locks # on searchspaces/documents for the entire duration of the stream. await session.commit() + await session.close() return StreamingResponse( stream_resume_chat( chat_id=thread_id, search_space_id=request.search_space_id, decisions=decisions, - session=session, user_id=str(user.id), llm_config_id=llm_config_id, thread_visibility=thread.visibility, diff --git a/surfsense_backend/app/routes/reports_routes.py b/surfsense_backend/app/routes/reports_routes.py index e32d7adcd..652d267fd 100644 --- a/surfsense_backend/app/routes/reports_routes.py +++ b/surfsense_backend/app/routes/reports_routes.py @@ -17,7 +17,7 @@ import logging import os import re import tempfile -from enum import Enum +from enum import StrEnum import pypandoc import typst @@ -46,7 +46,7 @@ router = APIRouter() MAX_REPORT_LIST_LIMIT = 500 -class ExportFormat(str, Enum): +class ExportFormat(StrEnum): PDF = "pdf" DOCX = "docx" diff --git a/surfsense_backend/app/routes/sandbox_routes.py b/surfsense_backend/app/routes/sandbox_routes.py new file mode 100644 index 000000000..2c12c3a1e --- /dev/null +++ b/surfsense_backend/app/routes/sandbox_routes.py @@ -0,0 +1,105 @@ +"""Routes for downloading files from Daytona sandbox environments.""" + +from __future__ import annotations + +import asyncio +import logging + +from fastapi import APIRouter, Depends, HTTPException, Query +from fastapi.responses import Response +from sqlalchemy.ext.asyncio import AsyncSession +from sqlalchemy.future import select + +from app.db import NewChatThread, Permission, User, get_async_session +from app.users import current_active_user +from app.utils.rbac import check_permission + +logger = logging.getLogger(__name__) + +router = APIRouter() + +MIME_TYPES: dict[str, str] = { + ".png": "image/png", + ".jpg": "image/jpeg", + ".jpeg": "image/jpeg", + ".gif": "image/gif", + ".webp": "image/webp", + ".svg": "image/svg+xml", + ".pdf": "application/pdf", + ".csv": "text/csv", + ".json": "application/json", + ".txt": "text/plain", + ".html": "text/html", + ".md": "text/markdown", + ".py": "text/x-python", + ".xlsx": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet", + ".zip": "application/zip", +} + + +def _guess_media_type(filename: str) -> str: + ext = ("." + filename.rsplit(".", 1)[-1].lower()) if "." in filename else "" + return MIME_TYPES.get(ext, "application/octet-stream") + + +@router.get("/threads/{thread_id}/sandbox/download") +async def download_sandbox_file( + thread_id: int, + path: str = Query(..., description="Absolute path of the file inside the sandbox"), + session: AsyncSession = Depends(get_async_session), + user: User = Depends(current_active_user), +): + """Download a file from the Daytona sandbox associated with a chat thread.""" + + from app.agents.new_chat.sandbox import get_or_create_sandbox, is_sandbox_enabled + + if not is_sandbox_enabled(): + raise HTTPException(status_code=404, detail="Sandbox is not enabled") + + result = await session.execute( + select(NewChatThread).filter(NewChatThread.id == thread_id) + ) + thread = result.scalars().first() + if not thread: + raise HTTPException(status_code=404, detail="Thread not found") + + await check_permission( + session, + user, + thread.search_space_id, + Permission.CHATS_READ.value, + "You don't have permission to access files in this thread", + ) + + from app.agents.new_chat.sandbox import get_local_sandbox_file + + # Prefer locally-persisted copy (sandbox may already be deleted) + local_content = get_local_sandbox_file(thread_id, path) + if local_content is not None: + filename = path.rsplit("/", 1)[-1] if "/" in path else path + media_type = _guess_media_type(filename) + return Response( + content=local_content, + media_type=media_type, + headers={"Content-Disposition": f'attachment; filename="{filename}"'}, + ) + + # Fall back to live sandbox download + try: + sandbox = await get_or_create_sandbox(thread_id) + raw_sandbox = sandbox._sandbox + content: bytes = await asyncio.to_thread(raw_sandbox.fs.download_file, path) + except Exception as exc: + logger.warning("Sandbox file download failed for %s: %s", path, exc) + raise HTTPException( + status_code=404, detail=f"Could not download file: {exc}" + ) from exc + + filename = path.rsplit("/", 1)[-1] if "/" in path else path + media_type = _guess_media_type(filename) + + return Response( + content=content, + media_type=media_type, + headers={"Content-Disposition": f'attachment; filename="{filename}"'}, + ) diff --git a/surfsense_backend/app/routes/search_source_connectors_routes.py b/surfsense_backend/app/routes/search_source_connectors_routes.py index b69238837..e808635e6 100644 --- a/surfsense_backend/app/routes/search_source_connectors_routes.py +++ b/surfsense_backend/app/routes/search_source_connectors_routes.py @@ -2735,7 +2735,10 @@ async def create_mcp_connector( f"for user {user.id} in search space {search_space_id}" ) - # Convert to read schema + from app.agents.new_chat.tools.mcp_tool import invalidate_mcp_tools_cache + + invalidate_mcp_tools_cache(search_space_id) + connector_read = SearchSourceConnectorRead.model_validate(db_connector) return MCPConnectorRead.from_connector(connector_read) @@ -2910,6 +2913,10 @@ async def update_mcp_connector( logger.info(f"Updated MCP connector {connector_id}") + from app.agents.new_chat.tools.mcp_tool import invalidate_mcp_tools_cache + + invalidate_mcp_tools_cache(connector.search_space_id) + connector_read = SearchSourceConnectorRead.model_validate(connector) return MCPConnectorRead.from_connector(connector_read) @@ -2960,9 +2967,14 @@ async def delete_mcp_connector( "You don't have permission to delete this connector", ) + search_space_id = connector.search_space_id await session.delete(connector) await session.commit() + from app.agents.new_chat.tools.mcp_tool import invalidate_mcp_tools_cache + + invalidate_mcp_tools_cache(search_space_id) + logger.info(f"Deleted MCP connector {connector_id}") except HTTPException: diff --git a/surfsense_backend/app/schemas/chat_comments.py b/surfsense_backend/app/schemas/chat_comments.py index b87ee58a4..984e8b812 100644 --- a/surfsense_backend/app/schemas/chat_comments.py +++ b/surfsense_backend/app/schemas/chat_comments.py @@ -87,6 +87,18 @@ class CommentListResponse(BaseModel): total_count: int +class CommentBatchRequest(BaseModel): + """Request for batch-fetching comments for multiple messages.""" + + message_ids: list[int] = Field(..., min_length=1, max_length=200) + + +class CommentBatchResponse(BaseModel): + """Batch response keyed by message_id.""" + + comments_by_message: dict[int, CommentListResponse] + + # ============================================================================= # Mention Schemas # ============================================================================= diff --git a/surfsense_backend/app/schemas/podcasts.py b/surfsense_backend/app/schemas/podcasts.py index 60f9d7dc0..d41f1ca36 100644 --- a/surfsense_backend/app/schemas/podcasts.py +++ b/surfsense_backend/app/schemas/podcasts.py @@ -1,13 +1,13 @@ """Podcast schemas for API responses.""" from datetime import datetime -from enum import Enum +from enum import StrEnum from typing import Any from pydantic import BaseModel -class PodcastStatusEnum(str, Enum): +class PodcastStatusEnum(StrEnum): PENDING = "pending" GENERATING = "generating" READY = "ready" diff --git a/surfsense_backend/app/schemas/search_source_connector.py b/surfsense_backend/app/schemas/search_source_connector.py index b8ff3e649..1b0ed0b13 100644 --- a/surfsense_backend/app/schemas/search_source_connector.py +++ b/surfsense_backend/app/schemas/search_source_connector.py @@ -16,6 +16,7 @@ class SearchSourceConnectorBase(BaseModel): is_indexable: bool last_indexed_at: datetime | None = None config: dict[str, Any] + enable_summary: bool = False periodic_indexing_enabled: bool = False indexing_frequency_minutes: int | None = None next_scheduled_at: datetime | None = None @@ -65,6 +66,7 @@ class SearchSourceConnectorUpdate(BaseModel): is_indexable: bool | None = None last_indexed_at: datetime | None = None config: dict[str, Any] | None = None + enable_summary: bool | None = None periodic_indexing_enabled: bool | None = None indexing_frequency_minutes: int | None = None next_scheduled_at: datetime | None = None diff --git a/surfsense_backend/app/services/chat_comments_service.py b/surfsense_backend/app/services/chat_comments_service.py index c9ca920f6..c2bb65aee 100644 --- a/surfsense_backend/app/services/chat_comments_service.py +++ b/surfsense_backend/app/services/chat_comments_service.py @@ -22,6 +22,7 @@ from app.db import ( ) from app.schemas.chat_comments import ( AuthorResponse, + CommentBatchResponse, CommentListResponse, CommentReplyResponse, CommentResponse, @@ -264,6 +265,146 @@ async def get_comments_for_message( ) +async def get_comments_for_messages_batch( + session: AsyncSession, + message_ids: list[int], + user: User, +) -> CommentBatchResponse: + """ + Batch-fetch comments for multiple messages in a single DB round-trip. + + Validates that all messages exist and belong to search spaces the user + can read comments in, then loads all comments with eager-loaded authors + and replies. + """ + if not message_ids: + return CommentBatchResponse(comments_by_message={}) + + unique_ids = list(set(message_ids)) + + result = await session.execute( + select(NewChatMessage) + .options(selectinload(NewChatMessage.thread)) + .filter(NewChatMessage.id.in_(unique_ids)) + ) + messages = result.scalars().all() + msg_map = {m.id: m for m in messages} + + search_space_ids = {m.thread.search_space_id for m in messages} + permissions_cache: dict[int, set] = {} + for ss_id in search_space_ids: + await check_permission( + session, + user, + ss_id, + Permission.COMMENTS_READ.value, + "You don't have permission to read comments in this search space", + ) + permissions_cache[ss_id] = await get_user_permissions(session, user.id, ss_id) + + result = await session.execute( + select(ChatComment) + .options( + selectinload(ChatComment.author), + selectinload(ChatComment.replies).selectinload(ChatComment.author), + ) + .filter( + ChatComment.message_id.in_(unique_ids), + ChatComment.parent_id.is_(None), + ) + .order_by(ChatComment.created_at) + ) + top_level_comments = result.scalars().all() + + all_mentioned_uuids: set[UUID] = set() + for comment in top_level_comments: + all_mentioned_uuids.update(parse_mentions(comment.content)) + for reply in comment.replies: + all_mentioned_uuids.update(parse_mentions(reply.content)) + + user_names = await get_user_names_for_mentions(session, all_mentioned_uuids) + + comments_by_msg: dict[int, list[ChatComment]] = {mid: [] for mid in unique_ids} + for comment in top_level_comments: + comments_by_msg.setdefault(comment.message_id, []).append(comment) + + comments_by_message: dict[int, CommentListResponse] = {} + for mid in unique_ids: + msg = msg_map.get(mid) + if msg is None: + comments_by_message[mid] = CommentListResponse(comments=[], total_count=0) + continue + + ss_id = msg.thread.search_space_id + user_perms = permissions_cache.get(ss_id, set()) + can_delete_any = has_permission(user_perms, Permission.COMMENTS_DELETE.value) + + comment_responses = [] + for comment in comments_by_msg.get(mid, []): + author = None + if comment.author: + author = AuthorResponse( + id=comment.author.id, + display_name=comment.author.display_name, + avatar_url=comment.author.avatar_url, + email=comment.author.email, + ) + + replies = [] + for reply in sorted(comment.replies, key=lambda r: r.created_at): + reply_author = None + if reply.author: + reply_author = AuthorResponse( + id=reply.author.id, + display_name=reply.author.display_name, + avatar_url=reply.author.avatar_url, + email=reply.author.email, + ) + is_reply_author = ( + reply.author_id == user.id if reply.author_id else False + ) + replies.append( + CommentReplyResponse( + id=reply.id, + content=reply.content, + content_rendered=render_mentions(reply.content, user_names), + author=reply_author, + created_at=reply.created_at, + updated_at=reply.updated_at, + is_edited=reply.updated_at > reply.created_at, + can_edit=is_reply_author, + can_delete=is_reply_author or can_delete_any, + ) + ) + + is_comment_author = ( + comment.author_id == user.id if comment.author_id else False + ) + comment_responses.append( + CommentResponse( + id=comment.id, + message_id=comment.message_id, + content=comment.content, + content_rendered=render_mentions(comment.content, user_names), + author=author, + created_at=comment.created_at, + updated_at=comment.updated_at, + is_edited=comment.updated_at > comment.created_at, + can_edit=is_comment_author, + can_delete=is_comment_author or can_delete_any, + reply_count=len(replies), + replies=replies, + ) + ) + + comments_by_message[mid] = CommentListResponse( + comments=comment_responses, + total_count=len(comment_responses), + ) + + return CommentBatchResponse(comments_by_message=comments_by_message) + + async def create_comment( session: AsyncSession, message_id: int, diff --git a/surfsense_backend/app/services/connector_service.py b/surfsense_backend/app/services/connector_service.py index 251241e96..0aa48eccd 100644 --- a/surfsense_backend/app/services/connector_service.py +++ b/surfsense_backend/app/services/connector_service.py @@ -1,4 +1,5 @@ import asyncio +import time from datetime import datetime from typing import Any from urllib.parse import urljoin @@ -15,9 +16,11 @@ from app.db import ( Document, SearchSourceConnector, SearchSourceConnectorType, + async_session_maker, ) from app.retriever.chunks_hybrid_search import ChucksHybridSearchRetriever from app.retriever.documents_hybrid_search import DocumentHybridSearchRetriever +from app.utils.perf import get_perf_logger class ConnectorService: @@ -221,6 +224,7 @@ class ConnectorService: top_k: int = 20, start_date: datetime | None = None, end_date: datetime | None = None, + query_embedding: list[float] | None = None, ) -> list[dict[str, Any]]: """ Perform combined search using both chunk-based and document-based hybrid search, @@ -246,34 +250,60 @@ class ConnectorService: Returns: List of combined and deduplicated document results """ + from app.config import config + + perf = get_perf_logger() + t0 = time.perf_counter() + # RRF constant k = 60 # Get more results from each retriever for better fusion retriever_top_k = top_k * 2 - # IMPORTANT: - # These retrievers share the same AsyncSession. AsyncSession does not permit - # concurrent awaits that require DB IO on the same session/connection. - # Running these in parallel can raise: - # "This session is provisioning a new connection; concurrent operations are not permitted" - # - # So we run them sequentially. - chunk_results = await self.chunk_retriever.hybrid_search( - query_text=query_text, - top_k=retriever_top_k, - search_space_id=search_space_id, - document_type=document_type, - start_date=start_date, - end_date=end_date, + # Reuse caller-provided embedding or compute once for both retrievers. + if query_embedding is None: + t_embed = time.perf_counter() + query_embedding = config.embedding_model_instance.embed(query_text) + perf.info( + "[connector_svc] _combined_rrf embedding in %.3fs type=%s", + time.perf_counter() - t_embed, + document_type, + ) + + search_kwargs = { + "query_text": query_text, + "top_k": retriever_top_k, + "search_space_id": search_space_id, + "document_type": document_type, + "start_date": start_date, + "end_date": end_date, + "query_embedding": query_embedding, + } + + # Run chunk and document retrievers in parallel using separate DB sessions + # so they don't contend on a shared AsyncSession connection. + async def _run_chunk_search() -> list[dict[str, Any]]: + async with async_session_maker() as session: + retriever = ChucksHybridSearchRetriever(session) + return await retriever.hybrid_search(**search_kwargs) + + async def _run_doc_search() -> list[dict[str, Any]]: + async with async_session_maker() as session: + retriever = DocumentHybridSearchRetriever(session) + return await retriever.hybrid_search(**search_kwargs) + + t_parallel = time.perf_counter() + chunk_results, doc_results = await asyncio.gather( + _run_chunk_search(), _run_doc_search() ) - doc_results = await self.document_retriever.hybrid_search( - query_text=query_text, - top_k=retriever_top_k, - search_space_id=search_space_id, - document_type=document_type, - start_date=start_date, - end_date=end_date, + perf.info( + "[connector_svc] _combined_rrf parallel retrievers in %.3fs " + "chunk_results=%d doc_results=%d type=%s", + time.perf_counter() - t_parallel, + len(chunk_results), + len(doc_results), + document_type, ) # Helper to extract document_id from our doc-grouped result @@ -335,6 +365,13 @@ class ConnectorService: result["chunks"] = doc_data[did]["chunks"] combined_results.append(result) + perf.info( + "[connector_svc] _combined_rrf_search TOTAL in %.3fs results=%d type=%s space=%d", + time.perf_counter() - t0, + len(combined_results), + document_type, + search_space_id, + ) return combined_results def _get_doc_url(self, metadata: dict[str, Any]) -> str: @@ -1303,10 +1340,9 @@ class ConnectorService: sources_list = self._build_chunk_sources_from_documents( github_docs, - description_fn=lambda chunk, _doc_info, metadata: metadata.get( - "description" - ) - or chunk.get("content", ""), + description_fn=lambda chunk, _doc_info, metadata: ( + metadata.get("description") or chunk.get("content", "") + ), url_fn=lambda _doc_info, metadata: metadata.get("url", "") or "", ) diff --git a/surfsense_backend/app/services/linear/kb_sync_service.py b/surfsense_backend/app/services/linear/kb_sync_service.py index bbae8c6e8..8d1bc47c7 100644 --- a/surfsense_backend/app/services/linear/kb_sync_service.py +++ b/surfsense_backend/app/services/linear/kb_sync_service.py @@ -4,12 +4,12 @@ from datetime import datetime from sqlalchemy import delete from sqlalchemy.ext.asyncio import AsyncSession -from app.config import config from app.connectors.linear_connector import LinearConnector from app.db import Chunk, Document from app.services.llm_service import get_user_long_context_llm from app.utils.document_converters import ( create_document_chunks, + embed_text, generate_content_hash, generate_document_summary, ) @@ -80,7 +80,7 @@ class LinearKBSyncService: state = formatted_issue.get("state", "Unknown") priority = issue_raw.get("priorityLabel", "Unknown") comment_count = len(formatted_issue.get("comments", [])) - description = formatted_issue.get("description", "") + formatted_issue.get("description", "") user_llm = await get_user_long_context_llm( self.db_session, user_id, search_space_id, disable_streaming=True @@ -100,18 +100,10 @@ class LinearKBSyncService: issue_content, user_llm, document_metadata_for_summary ) else: - if description and len(description) > 1000: - description = description[:997] + "..." summary_content = ( - f"Linear Issue {issue_identifier}: {issue_title}\n\n" - f"Status: {state}\n\n" - ) - if description: - summary_content += f"Description: {description}\n\n" - summary_content += f"Comments: {comment_count}" - summary_embedding = config.embedding_model_instance.embed( - summary_content + f"Linear Issue {issue_identifier}: {issue_title}\n\n{issue_content}" ) + summary_embedding = embed_text(summary_content) await self.db_session.execute( delete(Chunk).where(Chunk.document_id == document.id) diff --git a/surfsense_backend/app/services/llm_router_service.py b/surfsense_backend/app/services/llm_router_service.py index 58a75cf54..e8c0d2d47 100644 --- a/surfsense_backend/app/services/llm_router_service.py +++ b/surfsense_backend/app/services/llm_router_service.py @@ -12,16 +12,42 @@ synchronous ChatLiteLLM-like interface and async methods. """ import logging +import re +import time from typing import Any +import litellm from langchain_core.callbacks import CallbackManagerForLLMRun +from langchain_core.exceptions import ContextOverflowError from langchain_core.language_models import BaseChatModel from langchain_core.messages import AIMessage, AIMessageChunk, BaseMessage from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult from litellm import Router +from litellm.exceptions import ( + BadRequestError as LiteLLMBadRequestError, + ContextWindowExceededError, +) + +from app.utils.perf import get_perf_logger + +litellm.json_logs = False +litellm.store_audit_logs = False logger = logging.getLogger(__name__) +_CONTEXT_OVERFLOW_PATTERNS = re.compile( + r"(input tokens exceed|context.{0,20}(length|window|limit)|" + r"maximum context length|token.{0,20}(limit|exceed)|" + r"too many tokens|reduce the length)", + re.IGNORECASE, +) + + +def _is_context_overflow_error(exc: LiteLLMBadRequestError) -> bool: + """Check if a BadRequestError is actually a context window overflow.""" + return bool(_CONTEXT_OVERFLOW_PATTERNS.search(str(exc))) + + # Special ID for Auto mode - uses router for load balancing AUTO_MODE_ID = 0 @@ -133,26 +159,95 @@ class LLMRouterService: # Merge with provided settings final_settings = {**default_settings, **instance._router_settings} + # Build a "auto-large" fallback group with deployments whose context + # window exceeds the smallest deployment. This lets the router + # automatically fall back to a bigger-context model when gpt-4o (128K) + # hits ContextWindowExceededError. + full_model_list, ctx_fallbacks = cls._build_context_fallback_groups(model_list) + try: - instance._router = Router( - model_list=model_list, - routing_strategy=final_settings.get( + router_kwargs: dict[str, Any] = { + "model_list": full_model_list, + "routing_strategy": final_settings.get( "routing_strategy", "usage-based-routing" ), - num_retries=final_settings.get("num_retries", 3), - allowed_fails=final_settings.get("allowed_fails", 3), - cooldown_time=final_settings.get("cooldown_time", 60), - set_verbose=False, # Disable verbose logging in production - ) + "num_retries": final_settings.get("num_retries", 3), + "allowed_fails": final_settings.get("allowed_fails", 3), + "cooldown_time": final_settings.get("cooldown_time", 60), + "set_verbose": False, + } + if ctx_fallbacks: + router_kwargs["context_window_fallbacks"] = ctx_fallbacks + + instance._router = Router(**router_kwargs) instance._initialized = True logger.info( - f"LLM Router initialized with {len(model_list)} deployments, " - f"strategy: {final_settings.get('routing_strategy')}" + "LLM Router initialized with %d deployments, " + "strategy: %s, context_window_fallbacks: %s", + len(model_list), + final_settings.get("routing_strategy"), + ctx_fallbacks or "none", ) except Exception as e: logger.error(f"Failed to initialize LLM Router: {e}") instance._router = None + @classmethod + def _build_context_fallback_groups( + cls, model_list: list[dict] + ) -> tuple[list[dict], list[dict[str, list[str]]] | None]: + """Create an ``auto-large`` model group for context-window fallbacks. + + Uses ``litellm.get_model_info`` to discover the context window of each + deployment. Deployments whose ``max_input_tokens`` exceeds the smallest + window are duplicated into an ``auto-large`` group. The returned + fallback config tells the Router: on ``ContextWindowExceededError`` for + ``auto``, retry with ``auto-large``. + + Returns: + (full_model_list, context_window_fallbacks) — ``full_model_list`` + contains the original entries plus any ``auto-large`` duplicates. + ``context_window_fallbacks`` is ``None`` when every deployment has + the same context size (no useful fallback). + """ + from litellm import get_model_info + + ctx_map: dict[str, int] = {} + for dep in model_list: + params = dep.get("litellm_params", {}) + base_model = params.get("base_model") or params.get("model", "") + try: + info = get_model_info(base_model) + ctx = info.get("max_input_tokens") + if isinstance(ctx, int) and ctx > 0: + ctx_map[base_model] = ctx + except Exception: + continue + + if not ctx_map: + return model_list, None + + min_ctx = min(ctx_map.values()) + + large_deployments: list[dict] = [] + for dep in model_list: + params = dep.get("litellm_params", {}) + base_model = params.get("base_model") or params.get("model", "") + if ctx_map.get(base_model, 0) > min_ctx: + dup = {**dep, "model_name": "auto-large"} + large_deployments.append(dup) + + if not large_deployments: + return model_list, None + + logger.info( + "Context-window fallback: %d large-context deployments " + "(min_ctx=%d) added to 'auto-large' group", + len(large_deployments), + min_ctx, + ) + return model_list + large_deployments, [{"auto": ["auto-large"]}] + @classmethod def _config_to_deployment(cls, config: dict) -> dict | None: """ @@ -228,12 +323,62 @@ class LLMRouterService: return len(instance._model_list) +_cached_context_profile: dict | None = None +_cached_context_profile_computed: bool = False + +# Cached singleton instances keyed by (streaming,) to avoid re-creating on every call +_router_instance_cache: dict[bool, "ChatLiteLLMRouter"] = {} + + +def _get_cached_context_profile(router: Router) -> dict | None: + """Compute and cache the min context profile across all router deployments. + + Called once on first ChatLiteLLMRouter creation; subsequent calls return + the cached value. This avoids calling litellm.get_model_info() for every + deployment on every request. + """ + global _cached_context_profile, _cached_context_profile_computed + if _cached_context_profile_computed: + return _cached_context_profile + + from litellm import get_model_info + + min_ctx: int | None = None + for deployment in router.model_list: + params = deployment.get("litellm_params", {}) + base_model = params.get("base_model") or params.get("model", "") + try: + info = get_model_info(base_model) + ctx = info.get("max_input_tokens") + if isinstance(ctx, int) and ctx > 0 and (min_ctx is None or ctx < min_ctx): + min_ctx = ctx + except Exception: + continue + + if min_ctx is not None: + logger.info("ChatLiteLLMRouter profile: max_input_tokens=%d", min_ctx) + _cached_context_profile = {"max_input_tokens": min_ctx} + else: + _cached_context_profile = None + + _cached_context_profile_computed = True + return _cached_context_profile + + class ChatLiteLLMRouter(BaseChatModel): """ A LangChain-compatible chat model that uses LiteLLM Router for load balancing. This wraps the LiteLLM Router to provide the same interface as ChatLiteLLM, making it a drop-in replacement for auto-mode routing. + + Exposes a ``profile`` with ``max_input_tokens`` set to the smallest context + window across all router deployments so that deepagents + SummarizationMiddleware can use fraction-based triggers. + + **Singleton-ish**: Use ``get_auto_mode_llm()`` or call ``ChatLiteLLMRouter()`` + directly — instances without bound tools are cached per streaming flag to + avoid per-request re-initialization overhead and memory growth. """ # Use model_config for Pydantic v2 compatibility @@ -255,17 +400,8 @@ class ChatLiteLLMRouter(BaseChatModel): tool_choice: str | dict | None = None, **kwargs, ): - """ - Initialize the ChatLiteLLMRouter. - - Args: - router: LiteLLM Router instance. If None, uses the global singleton. - bound_tools: Pre-bound tools for tool calling - tool_choice: Tool choice configuration - """ try: super().__init__(**kwargs) - # Store router and tools as private attributes resolved_router = router or LLMRouterService.get_router() object.__setattr__(self, "_router", resolved_router) object.__setattr__(self, "_bound_tools", bound_tools) @@ -274,8 +410,16 @@ class ChatLiteLLMRouter(BaseChatModel): raise ValueError( "LLM Router not initialized. Call LLMRouterService.initialize() first." ) - logger.info( - f"ChatLiteLLMRouter initialized with {LLMRouterService.get_model_count()} models" + + computed_profile = _get_cached_context_profile(self._router) + if computed_profile is not None: + object.__setattr__(self, "profile", computed_profile) + + logger.debug( + "ChatLiteLLMRouter ready (models=%d, streaming=%s, has_tools=%s)", + LLMRouterService.get_model_count(), + self.streaming, + bound_tools is not None, ) except Exception as e: logger.error(f"Failed to initialize ChatLiteLLMRouter: {e}") @@ -349,6 +493,10 @@ class ChatLiteLLMRouter(BaseChatModel): if not self._router: raise ValueError("Router not initialized") + perf = get_perf_logger() + t0 = time.perf_counter() + msg_count = len(messages) + # Convert LangChain messages to OpenAI format formatted_messages = self._convert_messages(messages) @@ -359,12 +507,36 @@ class ChatLiteLLMRouter(BaseChatModel): if self._tool_choice is not None: call_kwargs["tool_choice"] = self._tool_choice - # Call router completion - response = self._router.completion( - model=self.model, - messages=formatted_messages, - stop=stop, - **call_kwargs, + try: + response = self._router.completion( + model=self.model, + messages=formatted_messages, + stop=stop, + **call_kwargs, + ) + except ContextWindowExceededError as e: + perf.warning( + "[llm_router] _generate CONTEXT_OVERFLOW msgs=%d in %.3fs", + msg_count, + time.perf_counter() - t0, + ) + raise ContextOverflowError(str(e)) from e + except LiteLLMBadRequestError as e: + if _is_context_overflow_error(e): + perf.warning( + "[llm_router] _generate CONTEXT_OVERFLOW msgs=%d in %.3fs", + msg_count, + time.perf_counter() - t0, + ) + raise ContextOverflowError(str(e)) from e + raise + + elapsed = time.perf_counter() - t0 + perf.info( + "[llm_router] _generate completed msgs=%d tools=%d in %.3fs", + msg_count, + len(self._bound_tools) if self._bound_tools else 0, + elapsed, ) # Convert response to ChatResult with potential tool calls @@ -386,6 +558,10 @@ class ChatLiteLLMRouter(BaseChatModel): if not self._router: raise ValueError("Router not initialized") + perf = get_perf_logger() + t0 = time.perf_counter() + msg_count = len(messages) + # Convert LangChain messages to OpenAI format formatted_messages = self._convert_messages(messages) @@ -396,12 +572,36 @@ class ChatLiteLLMRouter(BaseChatModel): if self._tool_choice is not None: call_kwargs["tool_choice"] = self._tool_choice - # Call router async completion - response = await self._router.acompletion( - model=self.model, - messages=formatted_messages, - stop=stop, - **call_kwargs, + try: + response = await self._router.acompletion( + model=self.model, + messages=formatted_messages, + stop=stop, + **call_kwargs, + ) + except ContextWindowExceededError as e: + perf.warning( + "[llm_router] _agenerate CONTEXT_OVERFLOW msgs=%d in %.3fs", + msg_count, + time.perf_counter() - t0, + ) + raise ContextOverflowError(str(e)) from e + except LiteLLMBadRequestError as e: + if _is_context_overflow_error(e): + perf.warning( + "[llm_router] _agenerate CONTEXT_OVERFLOW msgs=%d in %.3fs", + msg_count, + time.perf_counter() - t0, + ) + raise ContextOverflowError(str(e)) from e + raise + + elapsed = time.perf_counter() - t0 + perf.info( + "[llm_router] _agenerate completed msgs=%d tools=%d in %.3fs", + msg_count, + len(self._bound_tools) if self._bound_tools else 0, + elapsed, ) # Convert response to ChatResult with potential tool calls @@ -432,14 +632,20 @@ class ChatLiteLLMRouter(BaseChatModel): if self._tool_choice is not None: call_kwargs["tool_choice"] = self._tool_choice - # Call router completion with streaming - response = self._router.completion( - model=self.model, - messages=formatted_messages, - stop=stop, - stream=True, - **call_kwargs, - ) + try: + response = self._router.completion( + model=self.model, + messages=formatted_messages, + stop=stop, + stream=True, + **call_kwargs, + ) + except ContextWindowExceededError as e: + raise ContextOverflowError(str(e)) from e + except LiteLLMBadRequestError as e: + if _is_context_overflow_error(e): + raise ContextOverflowError(str(e)) from e + raise # Yield chunks for chunk in response: @@ -462,6 +668,10 @@ class ChatLiteLLMRouter(BaseChatModel): if not self._router: raise ValueError("Router not initialized") + perf = get_perf_logger() + t0 = time.perf_counter() + msg_count = len(messages) + formatted_messages = self._convert_messages(messages) # Add tools if bound @@ -471,23 +681,61 @@ class ChatLiteLLMRouter(BaseChatModel): if self._tool_choice is not None: call_kwargs["tool_choice"] = self._tool_choice - # Call router async completion with streaming - response = await self._router.acompletion( - model=self.model, - messages=formatted_messages, - stop=stop, - stream=True, - **call_kwargs, + try: + response = await self._router.acompletion( + model=self.model, + messages=formatted_messages, + stop=stop, + stream=True, + **call_kwargs, + ) + except ContextWindowExceededError as e: + perf.warning( + "[llm_router] _astream CONTEXT_OVERFLOW msgs=%d in %.3fs", + msg_count, + time.perf_counter() - t0, + ) + raise ContextOverflowError(str(e)) from e + except LiteLLMBadRequestError as e: + if _is_context_overflow_error(e): + perf.warning( + "[llm_router] _astream CONTEXT_OVERFLOW msgs=%d in %.3fs", + msg_count, + time.perf_counter() - t0, + ) + raise ContextOverflowError(str(e)) from e + raise + + t_first_chunk = time.perf_counter() + perf.info( + "[llm_router] _astream connection established msgs=%d in %.3fs", + msg_count, + t_first_chunk - t0, ) - # Yield chunks asynchronously + chunk_count = 0 + first_chunk_logged = False async for chunk in response: if hasattr(chunk, "choices") and chunk.choices: delta = chunk.choices[0].delta chunk_msg = self._convert_delta_to_chunk(delta) if chunk_msg: + chunk_count += 1 + if not first_chunk_logged: + perf.info( + "[llm_router] _astream first chunk in %.3fs (total %.3fs from start)", + time.perf_counter() - t_first_chunk, + time.perf_counter() - t0, + ) + first_chunk_logged = True yield ChatGenerationChunk(message=chunk_msg) + perf.info( + "[llm_router] _astream completed chunks=%d total=%.3fs", + chunk_count, + time.perf_counter() - t0, + ) + def _convert_messages(self, messages: list[BaseMessage]) -> list[dict]: """Convert LangChain messages to OpenAI format.""" from langchain_core.messages import ( @@ -602,19 +850,28 @@ class ChatLiteLLMRouter(BaseChatModel): return None -def get_auto_mode_llm() -> ChatLiteLLMRouter | None: - """ - Get a ChatLiteLLMRouter instance for auto mode. +def get_auto_mode_llm( + *, + streaming: bool = True, +) -> ChatLiteLLMRouter | None: + """Return a cached ChatLiteLLMRouter for auto mode. - Returns: - ChatLiteLLMRouter instance or None if router not initialized + Base (no tools) instances are cached per ``streaming`` flag so we + avoid re-constructing them on every request. ``bind_tools()`` still + returns a fresh instance because bound tools differ per agent. """ if not LLMRouterService.is_initialized(): logger.warning("LLM Router not initialized for auto mode") return None + cached = _router_instance_cache.get(streaming) + if cached is not None: + return cached + try: - return ChatLiteLLMRouter() + instance = ChatLiteLLMRouter(streaming=streaming) + _router_instance_cache[streaming] = instance + return instance except Exception as e: logger.error(f"Failed to create ChatLiteLLMRouter: {e}") return None diff --git a/surfsense_backend/app/services/llm_service.py b/surfsense_backend/app/services/llm_service.py index 4833e62a6..fc28f477f 100644 --- a/surfsense_backend/app/services/llm_service.py +++ b/surfsense_backend/app/services/llm_service.py @@ -12,12 +12,20 @@ from app.services.llm_router_service import ( AUTO_MODE_ID, ChatLiteLLMRouter, LLMRouterService, + get_auto_mode_llm, is_auto_mode, ) # Configure litellm to automatically drop unsupported parameters litellm.drop_params = True +# Memory controls: prevent unbounded internal accumulation +litellm.telemetry = False +litellm.cache = None +litellm.success_callback = [] +litellm.failure_callback = [] +litellm.input_callback = [] + logger = logging.getLogger(__name__) @@ -221,7 +229,7 @@ async def get_search_space_llm_instance( logger.debug( f"Using Auto mode (LLM Router) for search space {search_space_id}, role {role}" ) - return ChatLiteLLMRouter(disable_streaming=disable_streaming) + return get_auto_mode_llm(streaming=not disable_streaming) except Exception as e: logger.error(f"Failed to create ChatLiteLLMRouter: {e}") return None diff --git a/surfsense_backend/app/services/notion/kb_sync_service.py b/surfsense_backend/app/services/notion/kb_sync_service.py index 40b9f0ef1..ce31e0d35 100644 --- a/surfsense_backend/app/services/notion/kb_sync_service.py +++ b/surfsense_backend/app/services/notion/kb_sync_service.py @@ -4,11 +4,11 @@ from datetime import datetime from sqlalchemy import delete from sqlalchemy.ext.asyncio import AsyncSession -from app.config import config from app.db import Chunk, Document from app.services.llm_service import get_user_long_context_llm from app.utils.document_converters import ( create_document_chunks, + embed_text, generate_content_hash, generate_document_summary, ) @@ -127,10 +127,8 @@ class NotionKBSyncService: logger.debug(f"Generated summary length: {len(summary_content)} chars") else: logger.warning("No LLM configured - using fallback summary") - summary_content = f"Notion Page: {document.document_metadata.get('page_title')}\n\n{full_content[:500]}..." - summary_embedding = config.embedding_model_instance.embed( - summary_content - ) + summary_content = f"Notion Page: {document.document_metadata.get('page_title')}\n\n{full_content}" + summary_embedding = embed_text(summary_content) logger.debug(f"Deleting old chunks for document {document_id}") await self.db_session.execute( diff --git a/surfsense_backend/app/services/task_dispatcher.py b/surfsense_backend/app/services/task_dispatcher.py new file mode 100644 index 000000000..9a6fc7d63 --- /dev/null +++ b/surfsense_backend/app/services/task_dispatcher.py @@ -0,0 +1,53 @@ +"""Task dispatcher abstraction for background document processing. + +Decouples the upload endpoint from Celery so tests can swap in a +synchronous (inline) implementation that needs only PostgreSQL. +""" + +from __future__ import annotations + +from typing import Protocol + + +class TaskDispatcher(Protocol): + async def dispatch_file_processing( + self, + *, + document_id: int, + temp_path: str, + filename: str, + search_space_id: int, + user_id: str, + should_summarize: bool = False, + ) -> None: ... + + +class CeleryTaskDispatcher: + """Production dispatcher — fires Celery tasks via Redis broker.""" + + async def dispatch_file_processing( + self, + *, + document_id: int, + temp_path: str, + filename: str, + search_space_id: int, + user_id: str, + should_summarize: bool = False, + ) -> None: + from app.tasks.celery_tasks.document_tasks import ( + process_file_upload_with_document_task, + ) + + process_file_upload_with_document_task.delay( + document_id=document_id, + temp_path=temp_path, + filename=filename, + search_space_id=search_space_id, + user_id=user_id, + should_summarize=should_summarize, + ) + + +async def get_task_dispatcher() -> TaskDispatcher: + return CeleryTaskDispatcher() diff --git a/surfsense_backend/app/tasks/celery_tasks/__init__.py b/surfsense_backend/app/tasks/celery_tasks/__init__.py index 9abc472fe..5b1f2cd13 100644 --- a/surfsense_backend/app/tasks/celery_tasks/__init__.py +++ b/surfsense_backend/app/tasks/celery_tasks/__init__.py @@ -1 +1,28 @@ """Celery tasks package.""" + +from sqlalchemy.ext.asyncio import async_sessionmaker, create_async_engine +from sqlalchemy.pool import NullPool + +from app.config import config + +_celery_engine = None +_celery_session_maker = None + + +def get_celery_session_maker() -> async_sessionmaker: + """Return a shared async session maker for Celery tasks. + + A single NullPool engine is created per worker process and reused + across all task invocations to avoid leaking engine objects. + """ + global _celery_engine, _celery_session_maker + if _celery_session_maker is None: + _celery_engine = create_async_engine( + config.DATABASE_URL, + poolclass=NullPool, + echo=False, + ) + _celery_session_maker = async_sessionmaker( + _celery_engine, expire_on_commit=False + ) + return _celery_session_maker diff --git a/surfsense_backend/app/tasks/celery_tasks/connector_tasks.py b/surfsense_backend/app/tasks/celery_tasks/connector_tasks.py index a35528a93..9d52add9c 100644 --- a/surfsense_backend/app/tasks/celery_tasks/connector_tasks.py +++ b/surfsense_backend/app/tasks/celery_tasks/connector_tasks.py @@ -3,11 +3,8 @@ import logging import traceback -from sqlalchemy.ext.asyncio import async_sessionmaker, create_async_engine -from sqlalchemy.pool import NullPool - from app.celery_app import celery_app -from app.config import config +from app.tasks.celery_tasks import get_celery_session_maker logger = logging.getLogger(__name__) @@ -42,20 +39,6 @@ def _handle_greenlet_error(e: Exception, task_name: str, connector_id: int) -> N ) -def get_celery_session_maker(): - """ - Create a new async session maker for Celery tasks. - This is necessary because Celery tasks run in a new event loop, - and the default session maker is bound to the main app's event loop. - """ - engine = create_async_engine( - config.DATABASE_URL, - poolclass=NullPool, # Don't use connection pooling for Celery tasks - echo=False, - ) - return async_sessionmaker(engine, expire_on_commit=False) - - @celery_app.task(name="index_slack_messages", bind=True) def index_slack_messages_task( self, diff --git a/surfsense_backend/app/tasks/celery_tasks/document_reindex_tasks.py b/surfsense_backend/app/tasks/celery_tasks/document_reindex_tasks.py index a2a0d635d..c2dbe7700 100644 --- a/surfsense_backend/app/tasks/celery_tasks/document_reindex_tasks.py +++ b/surfsense_backend/app/tasks/celery_tasks/document_reindex_tasks.py @@ -2,35 +2,20 @@ import logging -from sqlalchemy import delete, select +from sqlalchemy import select from sqlalchemy.exc import SQLAlchemyError -from sqlalchemy.ext.asyncio import async_sessionmaker, create_async_engine from sqlalchemy.orm import selectinload -from sqlalchemy.pool import NullPool from app.celery_app import celery_app -from app.config import config from app.db import Document +from app.indexing_pipeline.adapters.file_upload_adapter import UploadDocumentAdapter from app.services.llm_service import get_user_long_context_llm from app.services.task_logging_service import TaskLoggingService -from app.utils.document_converters import ( - create_document_chunks, - generate_document_summary, -) +from app.tasks.celery_tasks import get_celery_session_maker logger = logging.getLogger(__name__) -def get_celery_session_maker(): - """Create async session maker for Celery tasks.""" - engine = create_async_engine( - config.DATABASE_URL, - poolclass=NullPool, - echo=False, - ) - return async_sessionmaker(engine, expire_on_commit=False) - - @celery_app.task(name="reindex_document", bind=True) def reindex_document_task(self, document_id: int, user_id: str): """ @@ -54,7 +39,6 @@ def reindex_document_task(self, document_id: int, user_id: str): async def _reindex_document(document_id: int, user_id: str): """Async function to reindex a document.""" async with get_celery_session_maker()() as session: - # First, get the document to get search_space_id for logging result = await session.execute( select(Document) .options(selectinload(Document.chunks)) @@ -66,10 +50,8 @@ async def _reindex_document(document_id: int, user_id: str): logger.error(f"Document {document_id} not found") return - # Initialize task logger task_logger = TaskLoggingService(session, document.search_space_id) - # Log task start log_entry = await task_logger.log_task_start( task_name="document_reindex", source="editor", @@ -83,10 +65,7 @@ async def _reindex_document(document_id: int, user_id: str): ) try: - # Read markdown directly from source_markdown - markdown_content = document.source_markdown - - if not markdown_content: + if not document.source_markdown: await task_logger.log_task_failure( log_entry, f"Document {document_id} has no source_markdown to reindex", @@ -97,51 +76,17 @@ async def _reindex_document(document_id: int, user_id: str): logger.info(f"Reindexing document {document_id} ({document.title})") - # 1. Delete old chunks explicitly - from app.db import Chunk - - await session.execute(delete(Chunk).where(Chunk.document_id == document_id)) - await session.flush() # Ensure old chunks are deleted - - # 2. Create new chunks from source_markdown - new_chunks = await create_document_chunks(markdown_content) - - # 3. Add new chunks to session - for chunk in new_chunks: - chunk.document_id = document_id - session.add(chunk) - - logger.info(f"Created {len(new_chunks)} chunks for document {document_id}") - - # 4. Regenerate summary user_llm = await get_user_long_context_llm( session, user_id, document.search_space_id ) - document_metadata = { - "title": document.title, - "document_type": document.document_type.value, - } + adapter = UploadDocumentAdapter(session) + await adapter.reindex(document=document, llm=user_llm) - summary_content, summary_embedding = await generate_document_summary( - markdown_content, user_llm, document_metadata - ) - - # 5. Update document - document.content = summary_content - document.embedding = summary_embedding - document.content_needs_reindexing = False - - await session.commit() - - # Log success await task_logger.log_task_success( log_entry, f"Successfully reindexed document: {document.title}", - { - "chunks_created": len(new_chunks), - "document_id": document_id, - }, + {"document_id": document_id}, ) logger.info(f"Successfully reindexed document {document_id}") diff --git a/surfsense_backend/app/tasks/celery_tasks/document_tasks.py b/surfsense_backend/app/tasks/celery_tasks/document_tasks.py index 3e60b5819..dcb791d3b 100644 --- a/surfsense_backend/app/tasks/celery_tasks/document_tasks.py +++ b/surfsense_backend/app/tasks/celery_tasks/document_tasks.py @@ -5,13 +5,11 @@ import logging import os from uuid import UUID -from sqlalchemy.ext.asyncio import async_sessionmaker, create_async_engine -from sqlalchemy.pool import NullPool - from app.celery_app import celery_app from app.config import config from app.services.notification_service import NotificationService from app.services.task_logging_service import TaskLoggingService +from app.tasks.celery_tasks import get_celery_session_maker from app.tasks.document_processors import ( add_extension_received_document, add_youtube_video_document, @@ -91,20 +89,6 @@ async def _run_heartbeat_loop(notification_id: int): pass # Normal cancellation when task completes -def get_celery_session_maker(): - """ - Create a new async session maker for Celery tasks. - This is necessary because Celery tasks run in a new event loop, - and the default session maker is bound to the main app's event loop. - """ - engine = create_async_engine( - config.DATABASE_URL, - poolclass=NullPool, # Don't use connection pooling for Celery tasks - echo=False, - ) - return async_sessionmaker(engine, expire_on_commit=False) - - @celery_app.task(name="process_extension_document", bind=True) def process_extension_document_task( self, individual_document_dict, search_space_id: int, user_id: str @@ -626,6 +610,7 @@ def process_file_upload_with_document_task( filename: str, search_space_id: int, user_id: str, + should_summarize: bool = False, ): """ Celery task to process uploaded file with existing pending document. @@ -640,6 +625,7 @@ def process_file_upload_with_document_task( filename: Original filename search_space_id: ID of the search space user_id: ID of the user + should_summarize: Whether to generate an LLM summary """ import traceback @@ -674,7 +660,12 @@ def process_file_upload_with_document_task( try: loop.run_until_complete( _process_file_with_document( - document_id, temp_path, filename, search_space_id, user_id + document_id, + temp_path, + filename, + search_space_id, + user_id, + should_summarize=should_summarize, ) ) logger.info( @@ -710,6 +701,7 @@ async def _process_file_with_document( filename: str, search_space_id: int, user_id: str, + should_summarize: bool = False, ): """ Process file and update existing pending document status. @@ -811,6 +803,7 @@ async def _process_file_with_document( task_logger=task_logger, log_entry=log_entry, notification=notification, + should_summarize=should_summarize, ) # Update notification on success diff --git a/surfsense_backend/app/tasks/celery_tasks/podcast_tasks.py b/surfsense_backend/app/tasks/celery_tasks/podcast_tasks.py index 973e7e750..42378fe5e 100644 --- a/surfsense_backend/app/tasks/celery_tasks/podcast_tasks.py +++ b/surfsense_backend/app/tasks/celery_tasks/podcast_tasks.py @@ -5,14 +5,13 @@ import logging import sys from sqlalchemy import select -from sqlalchemy.ext.asyncio import async_sessionmaker, create_async_engine -from sqlalchemy.pool import NullPool from app.agents.podcaster.graph import graph as podcaster_graph from app.agents.podcaster.state import State as PodcasterState from app.celery_app import celery_app from app.config import config from app.db import Podcast, PodcastStatus +from app.tasks.celery_tasks import get_celery_session_maker logger = logging.getLogger(__name__) @@ -25,20 +24,6 @@ if sys.platform.startswith("win"): ) -def get_celery_session_maker(): - """ - Create a new async session maker for Celery tasks. - This is necessary because Celery tasks run in a new event loop, - and the default session maker is bound to the main app's event loop. - """ - engine = create_async_engine( - config.DATABASE_URL, - poolclass=NullPool, # Don't use connection pooling for Celery tasks - echo=False, - ) - return async_sessionmaker(engine, expire_on_commit=False) - - # ============================================================================= # Content-based podcast generation (for new-chat) # ============================================================================= diff --git a/surfsense_backend/app/tasks/celery_tasks/schedule_checker_task.py b/surfsense_backend/app/tasks/celery_tasks/schedule_checker_task.py index 80d271aaa..0ba8bc80a 100644 --- a/surfsense_backend/app/tasks/celery_tasks/schedule_checker_task.py +++ b/surfsense_backend/app/tasks/celery_tasks/schedule_checker_task.py @@ -3,28 +3,16 @@ import logging from datetime import UTC, datetime -from sqlalchemy.ext.asyncio import async_sessionmaker, create_async_engine from sqlalchemy.future import select -from sqlalchemy.pool import NullPool from app.celery_app import celery_app -from app.config import config from app.db import Notification, SearchSourceConnector, SearchSourceConnectorType +from app.tasks.celery_tasks import get_celery_session_maker from app.utils.indexing_locks import is_connector_indexing_locked logger = logging.getLogger(__name__) -def get_celery_session_maker(): - """Create async session maker for Celery tasks.""" - engine = create_async_engine( - config.DATABASE_URL, - poolclass=NullPool, - echo=False, - ) - return async_sessionmaker(engine, expire_on_commit=False) - - @celery_app.task(name="check_periodic_schedules") def check_periodic_schedules_task(): """ diff --git a/surfsense_backend/app/tasks/celery_tasks/stale_notification_cleanup_task.py b/surfsense_backend/app/tasks/celery_tasks/stale_notification_cleanup_task.py index c2c82dd2c..e05ae9435 100644 --- a/surfsense_backend/app/tasks/celery_tasks/stale_notification_cleanup_task.py +++ b/surfsense_backend/app/tasks/celery_tasks/stale_notification_cleanup_task.py @@ -29,20 +29,17 @@ from datetime import UTC, datetime import redis from sqlalchemy import and_, or_, text -from sqlalchemy.ext.asyncio import async_sessionmaker, create_async_engine from sqlalchemy.future import select -from sqlalchemy.pool import NullPool from app.celery_app import celery_app from app.config import config from app.db import Document, DocumentStatus, Notification +from app.tasks.celery_tasks import get_celery_session_maker logger = logging.getLogger(__name__) -# Redis client for checking heartbeats _redis_client: redis.Redis | None = None -# Error messages shown to users when tasks are interrupted STALE_SYNC_ERROR_MESSAGE = "Sync was interrupted unexpectedly. Please retry." STALE_PROCESSING_ERROR_MESSAGE = "Syncing was interrupted unexpectedly. Please retry." @@ -60,16 +57,6 @@ def _get_heartbeat_key(notification_id: int) -> str: return f"indexing:heartbeat:{notification_id}" -def get_celery_session_maker(): - """Create async session maker for Celery tasks.""" - engine = create_async_engine( - config.DATABASE_URL, - poolclass=NullPool, - echo=False, - ) - return async_sessionmaker(engine, expire_on_commit=False) - - @celery_app.task(name="cleanup_stale_indexing_notifications") def cleanup_stale_indexing_notifications_task(): """ diff --git a/surfsense_backend/app/tasks/chat/stream_new_chat.py b/surfsense_backend/app/tasks/chat/stream_new_chat.py index ec319345b..8d09ff387 100644 --- a/surfsense_backend/app/tasks/chat/stream_new_chat.py +++ b/surfsense_backend/app/tasks/chat/stream_new_chat.py @@ -9,17 +9,23 @@ Supports loading LLM configurations from: - NewLLMConfig database table (positive IDs for user-created configs with prompt settings) """ +import asyncio +import contextlib +import gc import json +import logging +import re +import time from collections.abc import AsyncGenerator -from dataclasses import dataclass +from dataclasses import dataclass, field from typing import Any from uuid import UUID -import logging - +import anyio from langchain_core.messages import HumanMessage -from sqlalchemy.ext.asyncio import AsyncSession +from sqlalchemy import func from sqlalchemy.future import select +from sqlalchemy.orm import selectinload from app.agents.new_chat.chat_deepagent import create_surfsense_deep_agent from app.agents.new_chat.checkpointer import get_checkpointer @@ -30,7 +36,21 @@ from app.agents.new_chat.llm_config import ( load_agent_config, load_llm_config_from_yaml, ) -from app.db import ChatVisibility, Document, Report, SurfsenseDocsDocument, async_session_maker +from app.agents.new_chat.sandbox import ( + get_or_create_sandbox, + is_sandbox_enabled, +) +from app.db import ( + ChatVisibility, + Document, + NewChatMessage, + NewChatThread, + Report, + SearchSourceConnectorType, + SurfsenseDocsDocument, + async_session_maker, + shielded_async_session, +) from app.prompts import TITLE_GENERATION_PROMPT_TEMPLATE from app.services.chat_session_state_service import ( clear_ai_responding, @@ -39,6 +59,11 @@ from app.services.chat_session_state_service import ( from app.services.connector_service import ConnectorService from app.services.new_streaming_service import VercelStreamingService from app.utils.content_utils import bootstrap_history_from_db +from app.utils.perf import get_perf_logger, log_system_snapshot, trim_native_heap + +_perf_log = get_perf_logger() + +_background_tasks: set[asyncio.Task] = set() def format_mentioned_documents_as_context(documents: list[Document]) -> str: @@ -187,6 +212,7 @@ class StreamResult: accumulated_text: str = "" is_interrupted: bool = False interrupt_value: dict[str, Any] | None = None + sandbox_files: list[str] = field(default_factory=list) async def _stream_agent_events( @@ -404,6 +430,21 @@ async def _stream_agent_events( status="in_progress", items=last_active_step_items, ) + elif tool_name == "execute": + cmd = ( + tool_input.get("command", "") + if isinstance(tool_input, dict) + else str(tool_input) + ) + display_cmd = cmd[:80] + ("…" if len(cmd) > 80 else "") + last_active_step_title = "Running command" + last_active_step_items = [f"$ {display_cmd}"] + yield streaming_service.format_thinking_step( + step_id=tool_step_id, + title="Running command", + status="in_progress", + items=last_active_step_items, + ) else: last_active_step_title = f"Using {tool_name.replace('_', ' ')}" last_active_step_items = [] @@ -620,6 +661,32 @@ async def _stream_agent_events( status="completed", items=completed_items, ) + elif tool_name == "execute": + raw_text = ( + tool_output.get("result", "") + if isinstance(tool_output, dict) + else str(tool_output) + ) + m = re.match(r"^Exit code:\s*(\d+)", raw_text) + exit_code_val = int(m.group(1)) if m else None + if exit_code_val is not None and exit_code_val == 0: + completed_items = [ + *last_active_step_items, + "Completed successfully", + ] + elif exit_code_val is not None: + completed_items = [ + *last_active_step_items, + f"Exit code: {exit_code_val}", + ] + else: + completed_items = [*last_active_step_items, "Finished"] + yield streaming_service.format_thinking_step( + step_id=original_step_id, + title="Running command", + status="completed", + items=completed_items, + ) elif tool_name == "ls": if isinstance(tool_output, dict): ls_output = tool_output.get("result", "") @@ -813,6 +880,36 @@ async def _stream_agent_events( if isinstance(tool_output, dict) else {"result": tool_output}, ) + elif tool_name == "execute": + raw_text = ( + tool_output.get("result", "") + if isinstance(tool_output, dict) + else str(tool_output) + ) + exit_code: int | None = None + output_text = raw_text + m = re.match(r"^Exit code:\s*(\d+)", raw_text) + if m: + exit_code = int(m.group(1)) + om = re.search(r"\nOutput:\n([\s\S]*)", raw_text) + output_text = om.group(1) if om else "" + thread_id_str = config.get("configurable", {}).get("thread_id", "") + + for sf_match in re.finditer( + r"^SANDBOX_FILE:\s*(.+)$", output_text, re.MULTILINE + ): + fpath = sf_match.group(1).strip() + if fpath and fpath not in result.sandbox_files: + result.sandbox_files.append(fpath) + + yield streaming_service.format_tool_output_available( + tool_call_id, + { + "exit_code": exit_code, + "output": output_text, + "thread_id": thread_id_str, + }, + ) else: yield streaming_service.format_tool_output_available( tool_call_id, @@ -881,11 +978,42 @@ async def _stream_agent_events( yield streaming_service.format_interrupt_request(result.interrupt_value) +def _try_persist_and_delete_sandbox( + thread_id: int, + sandbox_files: list[str], +) -> None: + """Fire-and-forget: persist sandbox files locally then delete the sandbox.""" + from app.agents.new_chat.sandbox import ( + is_sandbox_enabled, + persist_and_delete_sandbox, + ) + + if not is_sandbox_enabled(): + return + + async def _run() -> None: + try: + await persist_and_delete_sandbox(thread_id, sandbox_files) + except Exception: + logging.getLogger(__name__).warning( + "persist_and_delete_sandbox failed for thread %s", + thread_id, + exc_info=True, + ) + + try: + loop = asyncio.get_running_loop() + task = loop.create_task(_run()) + _background_tasks.add(task) + task.add_done_callback(_background_tasks.discard) + except RuntimeError: + pass + + async def stream_new_chat( user_query: str, search_space_id: int, chat_id: int, - session: AsyncSession, user_id: str | None = None, llm_config_id: int = -1, mentioned_document_ids: list[int] | None = None, @@ -901,11 +1029,13 @@ async def stream_new_chat( This uses the Vercel AI SDK Data Stream Protocol (SSE format) for streaming. The chat_id is used as LangGraph's thread_id for memory/checkpointing. + The function creates and manages its own database session to guarantee proper + cleanup even when Starlette's middleware cancels the task on client disconnect. + Args: user_query: The user's query search_space_id: The search space ID chat_id: The chat ID (used as LangGraph thread_id for memory) - session: The database session user_id: The current user's UUID string (for memory tools and session state) llm_config_id: The LLM configuration ID (default: -1 for first global config) needs_history_bootstrap: If True, load message history from DB (for cloned chats) @@ -917,7 +1047,11 @@ async def stream_new_chat( str: SSE formatted response strings """ streaming_service = VercelStreamingService() + stream_result = StreamResult() + _t_total = time.perf_counter() + log_system_snapshot("stream_new_chat_START") + session = async_session_maker() try: # Mark AI as responding to this user for live collaboration if user_id: @@ -925,6 +1059,7 @@ async def stream_new_chat( # Load LLM config - supports both YAML (negative IDs) and database (positive IDs) agent_config: AgentConfig | None = None + _t0 = time.perf_counter() if llm_config_id >= 0: # Positive ID: Load from NewLLMConfig database table agent_config = await load_agent_config( @@ -955,6 +1090,11 @@ async def stream_new_chat( llm = create_chat_litellm_from_config(llm_config) # Create AgentConfig from YAML for consistency (uses defaults for prompt settings) agent_config = AgentConfig.from_yaml_config(llm_config) + _perf_log.info( + "[stream_new_chat] LLM config loaded in %.3fs (config_id=%s)", + time.perf_counter() - _t0, + llm_config_id, + ) if not llm: yield streaming_service.format_error("Failed to create LLM instance") @@ -962,22 +1102,45 @@ async def stream_new_chat( return # Create connector service + _t0 = time.perf_counter() connector_service = ConnectorService(session, search_space_id=search_space_id) - # Get Firecrawl API key from webcrawler connector if configured - from app.db import SearchSourceConnectorType - firecrawl_api_key = None webcrawler_connector = await connector_service.get_connector_by_type( SearchSourceConnectorType.WEBCRAWLER_CONNECTOR, search_space_id ) if webcrawler_connector and webcrawler_connector.config: firecrawl_api_key = webcrawler_connector.config.get("FIRECRAWL_API_KEY") + _perf_log.info( + "[stream_new_chat] Connector service + firecrawl key in %.3fs", + time.perf_counter() - _t0, + ) # Get the PostgreSQL checkpointer for persistent conversation memory + _t0 = time.perf_counter() checkpointer = await get_checkpointer() + _perf_log.info( + "[stream_new_chat] Checkpointer ready in %.3fs", time.perf_counter() - _t0 + ) + + sandbox_backend = None + _t0 = time.perf_counter() + if is_sandbox_enabled(): + try: + sandbox_backend = await get_or_create_sandbox(chat_id) + except Exception as sandbox_err: + logging.getLogger(__name__).warning( + "Sandbox creation failed, continuing without execute tool: %s", + sandbox_err, + ) + _perf_log.info( + "[stream_new_chat] Sandbox provisioning in %.3fs (enabled=%s)", + time.perf_counter() - _t0, + sandbox_backend is not None, + ) visibility = thread_visibility or ChatVisibility.PRIVATE + _t0 = time.perf_counter() agent = await create_surfsense_deep_agent( llm=llm, search_space_id=search_space_id, @@ -989,20 +1152,22 @@ async def stream_new_chat( agent_config=agent_config, firecrawl_api_key=firecrawl_api_key, thread_visibility=visibility, + sandbox_backend=sandbox_backend, + ) + _perf_log.info( + "[stream_new_chat] Agent created in %.3fs", time.perf_counter() - _t0 ) # Build input with message history langchain_messages = [] + _t0 = time.perf_counter() # Bootstrap history for cloned chats (no LangGraph checkpoint exists yet) if needs_history_bootstrap: langchain_messages = await bootstrap_history_from_db( session, chat_id, thread_visibility=visibility ) - # Clear the flag so we don't bootstrap again on next message - from app.db import NewChatThread - thread_result = await session.execute( select(NewChatThread).filter(NewChatThread.id == chat_id) ) @@ -1014,11 +1179,9 @@ async def stream_new_chat( # Fetch mentioned documents if any (with chunks for proper citations) mentioned_documents: list[Document] = [] if mentioned_document_ids: - from sqlalchemy.orm import selectinload as doc_selectinload - result = await session.execute( select(Document) - .options(doc_selectinload(Document.chunks)) + .options(selectinload(Document.chunks)) .filter( Document.id.in_(mentioned_document_ids), Document.search_space_id == search_space_id, @@ -1029,8 +1192,6 @@ async def stream_new_chat( # Fetch mentioned SurfSense docs if any mentioned_surfsense_docs: list[SurfsenseDocsDocument] = [] if mentioned_surfsense_doc_ids: - from sqlalchemy.orm import selectinload - result = await session.execute( select(SurfsenseDocsDocument) .options(selectinload(SurfsenseDocsDocument.chunks)) @@ -1114,6 +1275,11 @@ async def stream_new_chat( "search_space_id": search_space_id, } + _perf_log.info( + "[stream_new_chat] History bootstrap + doc/report queries in %.3fs", + time.perf_counter() - _t0, + ) + # All pre-streaming DB reads are done. Commit to release the # transaction and its ACCESS SHARE locks so we don't block DDL # (e.g. migrations) for the entire duration of LLM streaming. @@ -1121,6 +1287,18 @@ async def stream_new_chat( # short-lived transactions (or use isolated sessions). await session.commit() + # Detach heavy ORM objects (documents with chunks, reports, etc.) + # from the session identity map now that we've extracted the data + # we need. This prevents them from accumulating in memory for the + # entire duration of LLM streaming (which can be several minutes). + session.expunge_all() + + _perf_log.info( + "[stream_new_chat] Total pre-stream setup in %.3fs (chat_id=%s)", + time.perf_counter() - _t_total, + chat_id, + ) + # Configure LangGraph with thread_id for memory # If checkpoint_id is provided, fork from that checkpoint (for edit/reload) configurable = {"thread_id": str(chat_id)} @@ -1182,7 +1360,14 @@ async def stream_new_chat( items=initial_items, ) - stream_result = StreamResult() + # These ORM objects (with eagerly-loaded chunks) can be very large. + # They're only needed to build context strings already copied into + # final_query / langchain_messages — release them before streaming. + del mentioned_documents, mentioned_surfsense_docs, recent_reports + del langchain_messages, final_query + + _t_stream_start = time.perf_counter() + _first_event_logged = False async for sse in _stream_agent_events( agent=agent, config=config, @@ -1194,8 +1379,24 @@ async def stream_new_chat( initial_step_title=initial_title, initial_step_items=initial_items, ): + if not _first_event_logged: + _perf_log.info( + "[stream_new_chat] First agent event in %.3fs (time since stream start), " + "%.3fs (total since request start) (chat_id=%s)", + time.perf_counter() - _t_stream_start, + time.perf_counter() - _t_total, + chat_id, + ) + _first_event_logged = True yield sse + _perf_log.info( + "[stream_new_chat] Agent stream completed in %.3fs (chat_id=%s)", + time.perf_counter() - _t_stream_start, + chat_id, + ) + log_system_snapshot("stream_new_chat_END") + if stream_result.is_interrupted: yield streaming_service.format_finish_step() yield streaming_service.format_finish() @@ -1204,12 +1405,6 @@ async def stream_new_chat( accumulated_text = stream_result.accumulated_text - # Generate LLM title for new chats after first response - # Check if this is the first assistant response by counting existing assistant messages - from sqlalchemy import func - - from app.db import NewChatMessage, NewChatThread - assistant_count_result = await session.execute( select(func.count(NewChatMessage.id)).filter( NewChatMessage.thread_id == chat_id, @@ -1280,39 +1475,72 @@ async def stream_new_chat( yield streaming_service.format_done() finally: - # Clear AI responding state for live collaboration. - # The original session may be broken (client disconnect / CancelledError - # can corrupt the underlying DB connection), so we try a rollback first - # and fall back to a fresh session if the original is unusable. - try: - await session.rollback() - await clear_ai_responding(session, chat_id) - except Exception: + # Shield the ENTIRE async cleanup from anyio cancel-scope + # cancellation. Starlette's BaseHTTPMiddleware uses anyio task + # groups; on client disconnect, it cancels the scope with + # level-triggered cancellation — every unshielded `await` inside + # the cancelled scope raises CancelledError immediately. Without + # this shield the very first `await` (session.rollback) would + # raise CancelledError, `except Exception` wouldn't catch it + # (CancelledError is a BaseException), and the rest of the + # finally block — including session.close() — would never run. + with anyio.CancelScope(shield=True): try: - async with async_session_maker() as fresh_session: - await clear_ai_responding(fresh_session, chat_id) + await session.rollback() + await clear_ai_responding(session, chat_id) except Exception: - logging.getLogger(__name__).warning( - "Failed to clear AI responding state for thread %s", chat_id - ) + try: + async with shielded_async_session() as fresh_session: + await clear_ai_responding(fresh_session, chat_id) + except Exception: + logging.getLogger(__name__).warning( + "Failed to clear AI responding state for thread %s", chat_id + ) + + _try_persist_and_delete_sandbox(chat_id, stream_result.sandbox_files) + + with contextlib.suppress(Exception): + session.expunge_all() + + with contextlib.suppress(Exception): + await session.close() + + # Break circular refs held by the agent graph, tools, and LLM + # wrappers so the GC can reclaim them in a single pass. + agent = llm = connector_service = sandbox_backend = None + input_state = stream_result = None + session = None + + collected = gc.collect(0) + gc.collect(1) + gc.collect(2) + if collected: + _perf_log.info( + "[stream_new_chat] gc.collect() reclaimed %d objects (chat_id=%s)", + collected, + chat_id, + ) + trim_native_heap() + log_system_snapshot("stream_new_chat_END") async def stream_resume_chat( chat_id: int, search_space_id: int, decisions: list[dict], - session: AsyncSession, user_id: str | None = None, llm_config_id: int = -1, thread_visibility: ChatVisibility | None = None, ) -> AsyncGenerator[str, None]: streaming_service = VercelStreamingService() + stream_result = StreamResult() + _t_total = time.perf_counter() + session = async_session_maker() try: if user_id: await set_ai_responding(session, chat_id, UUID(user_id)) agent_config: AgentConfig | None = None + _t0 = time.perf_counter() if llm_config_id >= 0: agent_config = await load_agent_config( session=session, @@ -1336,26 +1564,54 @@ async def stream_resume_chat( return llm = create_chat_litellm_from_config(llm_config) agent_config = AgentConfig.from_yaml_config(llm_config) + _perf_log.info( + "[stream_resume] LLM config loaded in %.3fs", time.perf_counter() - _t0 + ) if not llm: yield streaming_service.format_error("Failed to create LLM instance") yield streaming_service.format_done() return + _t0 = time.perf_counter() connector_service = ConnectorService(session, search_space_id=search_space_id) - from app.db import SearchSourceConnectorType - firecrawl_api_key = None webcrawler_connector = await connector_service.get_connector_by_type( SearchSourceConnectorType.WEBCRAWLER_CONNECTOR, search_space_id ) if webcrawler_connector and webcrawler_connector.config: firecrawl_api_key = webcrawler_connector.config.get("FIRECRAWL_API_KEY") + _perf_log.info( + "[stream_resume] Connector service + firecrawl key in %.3fs", + time.perf_counter() - _t0, + ) + _t0 = time.perf_counter() checkpointer = await get_checkpointer() + _perf_log.info( + "[stream_resume] Checkpointer ready in %.3fs", time.perf_counter() - _t0 + ) + + sandbox_backend = None + _t0 = time.perf_counter() + if is_sandbox_enabled(): + try: + sandbox_backend = await get_or_create_sandbox(chat_id) + except Exception as sandbox_err: + logging.getLogger(__name__).warning( + "Sandbox creation failed, continuing without execute tool: %s", + sandbox_err, + ) + _perf_log.info( + "[stream_resume] Sandbox provisioning in %.3fs (enabled=%s)", + time.perf_counter() - _t0, + sandbox_backend is not None, + ) + visibility = thread_visibility or ChatVisibility.PRIVATE + _t0 = time.perf_counter() agent = await create_surfsense_deep_agent( llm=llm, search_space_id=search_space_id, @@ -1367,10 +1623,21 @@ async def stream_resume_chat( agent_config=agent_config, firecrawl_api_key=firecrawl_api_key, thread_visibility=visibility, + sandbox_backend=sandbox_backend, + ) + _perf_log.info( + "[stream_resume] Agent created in %.3fs", time.perf_counter() - _t0 ) # Release the transaction before streaming (same rationale as stream_new_chat). await session.commit() + session.expunge_all() + + _perf_log.info( + "[stream_resume] Total pre-stream setup in %.3fs (chat_id=%s)", + time.perf_counter() - _t_total, + chat_id, + ) from langgraph.types import Command @@ -1382,7 +1649,8 @@ async def stream_resume_chat( yield streaming_service.format_message_start() yield streaming_service.format_start_step() - stream_result = StreamResult() + _t_stream_start = time.perf_counter() + _first_event_logged = False async for sse in _stream_agent_events( agent=agent, config=config, @@ -1391,7 +1659,20 @@ async def stream_resume_chat( result=stream_result, step_prefix="thinking-resume", ): + if not _first_event_logged: + _perf_log.info( + "[stream_resume] First agent event in %.3fs (stream), %.3fs (total) (chat_id=%s)", + time.perf_counter() - _t_stream_start, + time.perf_counter() - _t_total, + chat_id, + ) + _first_event_logged = True yield sse + _perf_log.info( + "[stream_resume] Agent stream completed in %.3fs (chat_id=%s)", + time.perf_counter() - _t_stream_start, + chat_id, + ) if stream_result.is_interrupted: yield streaming_service.format_finish_step() yield streaming_service.format_finish() @@ -1414,14 +1695,37 @@ async def stream_resume_chat( yield streaming_service.format_done() finally: - try: - await session.rollback() - await clear_ai_responding(session, chat_id) - except Exception: + with anyio.CancelScope(shield=True): try: - async with async_session_maker() as fresh_session: - await clear_ai_responding(fresh_session, chat_id) + await session.rollback() + await clear_ai_responding(session, chat_id) except Exception: - logging.getLogger(__name__).warning( - "Failed to clear AI responding state for thread %s", chat_id - ) + try: + async with shielded_async_session() as fresh_session: + await clear_ai_responding(fresh_session, chat_id) + except Exception: + logging.getLogger(__name__).warning( + "Failed to clear AI responding state for thread %s", chat_id + ) + + _try_persist_and_delete_sandbox(chat_id, stream_result.sandbox_files) + + with contextlib.suppress(Exception): + session.expunge_all() + + with contextlib.suppress(Exception): + await session.close() + + agent = llm = connector_service = sandbox_backend = None + stream_result = None + session = None + + collected = gc.collect(0) + gc.collect(1) + gc.collect(2) + if collected: + _perf_log.info( + "[stream_resume] gc.collect() reclaimed %d objects (chat_id=%s)", + collected, + chat_id, + ) + trim_native_heap() + log_system_snapshot("stream_resume_chat_END") diff --git a/surfsense_backend/app/tasks/connector_indexers/airtable_indexer.py b/surfsense_backend/app/tasks/connector_indexers/airtable_indexer.py index 46cd069c9..438a93815 100644 --- a/surfsense_backend/app/tasks/connector_indexers/airtable_indexer.py +++ b/surfsense_backend/app/tasks/connector_indexers/airtable_indexer.py @@ -12,13 +12,13 @@ from collections.abc import Awaitable, Callable from sqlalchemy.exc import SQLAlchemyError from sqlalchemy.ext.asyncio import AsyncSession -from app.config import config from app.connectors.airtable_history import AirtableHistoryConnector from app.db import Document, DocumentStatus, DocumentType, SearchSourceConnectorType from app.services.llm_service import get_user_long_context_llm from app.services.task_logging_service import TaskLoggingService from app.utils.document_converters import ( create_document_chunks, + embed_text, generate_content_hash, generate_document_summary, generate_unique_identifier_hash, @@ -399,7 +399,7 @@ async def index_airtable_records( session, user_id, search_space_id ) - if user_llm: + if user_llm and connector.enable_summary: document_metadata_for_summary = { "record_id": item["record_id"], "created_time": item["record"].get("CREATED_TIME()", ""), @@ -415,11 +415,8 @@ async def index_airtable_records( document_metadata_for_summary, ) else: - # Fallback to simple summary if no LLM configured - summary_content = f"Airtable Record: {item['record_id']}\n\n" - summary_embedding = config.embedding_model_instance.embed( - summary_content - ) + summary_content = f"Airtable Record: {item['record_id']}\n\n{item['markdown_content']}" + summary_embedding = embed_text(summary_content) chunks = await create_document_chunks(item["markdown_content"]) diff --git a/surfsense_backend/app/tasks/connector_indexers/bookstack_indexer.py b/surfsense_backend/app/tasks/connector_indexers/bookstack_indexer.py index d60884539..bf3aaa35f 100644 --- a/surfsense_backend/app/tasks/connector_indexers/bookstack_indexer.py +++ b/surfsense_backend/app/tasks/connector_indexers/bookstack_indexer.py @@ -13,13 +13,13 @@ from datetime import datetime from sqlalchemy.exc import SQLAlchemyError from sqlalchemy.ext.asyncio import AsyncSession -from app.config import config from app.connectors.bookstack_connector import BookStackConnector from app.db import Document, DocumentStatus, DocumentType, SearchSourceConnectorType from app.services.llm_service import get_user_long_context_llm from app.services.task_logging_service import TaskLoggingService from app.utils.document_converters import ( create_document_chunks, + embed_text, generate_content_hash, generate_document_summary, generate_unique_identifier_hash, @@ -403,7 +403,7 @@ async def index_bookstack_pages( "connector_id": connector_id, } - if user_llm: + if user_llm and connector.enable_summary: summary_metadata = { "page_name": item["page_name"], "page_id": item["page_id"], @@ -418,17 +418,8 @@ async def index_bookstack_pages( item["full_content"], user_llm, summary_metadata ) else: - # Fallback to simple summary if no LLM configured - summary_content = f"BookStack Page: {item['page_name']}\n\nBook ID: {item['book_id']}\n\n" - if item["page_content"]: - # Take first 1000 characters of content for summary - content_preview = item["page_content"][:1000] - if len(item["page_content"]) > 1000: - content_preview += "..." - summary_content += f"Content Preview: {content_preview}\n\n" - summary_embedding = config.embedding_model_instance.embed( - summary_content - ) + summary_content = f"BookStack Page: {item['page_name']}\n\nBook ID: {item['book_id']}\n\n{item['full_content']}" + summary_embedding = embed_text(summary_content) # Process chunks - using the full page content chunks = await create_document_chunks(item["full_content"]) diff --git a/surfsense_backend/app/tasks/connector_indexers/clickup_indexer.py b/surfsense_backend/app/tasks/connector_indexers/clickup_indexer.py index 47c5d8b3b..fd0233e87 100644 --- a/surfsense_backend/app/tasks/connector_indexers/clickup_indexer.py +++ b/surfsense_backend/app/tasks/connector_indexers/clickup_indexer.py @@ -14,13 +14,13 @@ from datetime import datetime from sqlalchemy.exc import SQLAlchemyError from sqlalchemy.ext.asyncio import AsyncSession -from app.config import config from app.connectors.clickup_history import ClickUpHistoryConnector from app.db import Document, DocumentStatus, DocumentType, SearchSourceConnectorType from app.services.llm_service import get_user_long_context_llm from app.services.task_logging_service import TaskLoggingService from app.utils.document_converters import ( create_document_chunks, + embed_text, generate_content_hash, generate_document_summary, generate_unique_identifier_hash, @@ -398,7 +398,7 @@ async def index_clickup_tasks( session, user_id, search_space_id ) - if user_llm: + if user_llm and connector.enable_summary: document_metadata_for_summary = { "task_id": item["task_id"], "task_name": item["task_name"], @@ -418,9 +418,7 @@ async def index_clickup_tasks( ) else: summary_content = item["task_content"] - summary_embedding = config.embedding_model_instance.embed( - item["task_content"] - ) + summary_embedding = embed_text(item["task_content"]) chunks = await create_document_chunks(item["task_content"]) diff --git a/surfsense_backend/app/tasks/connector_indexers/confluence_indexer.py b/surfsense_backend/app/tasks/connector_indexers/confluence_indexer.py index a3a059d4e..c28e82b8f 100644 --- a/surfsense_backend/app/tasks/connector_indexers/confluence_indexer.py +++ b/surfsense_backend/app/tasks/connector_indexers/confluence_indexer.py @@ -14,13 +14,13 @@ from datetime import datetime from sqlalchemy.exc import SQLAlchemyError from sqlalchemy.ext.asyncio import AsyncSession -from app.config import config from app.connectors.confluence_history import ConfluenceHistoryConnector from app.db import Document, DocumentStatus, DocumentType, SearchSourceConnectorType from app.services.llm_service import get_user_long_context_llm from app.services.task_logging_service import TaskLoggingService from app.utils.document_converters import ( create_document_chunks, + embed_text, generate_content_hash, generate_document_summary, generate_unique_identifier_hash, @@ -378,7 +378,7 @@ async def index_confluence_pages( session, user_id, search_space_id ) - if user_llm: + if user_llm and connector.enable_summary: document_metadata = { "page_title": item["page_title"], "page_id": item["page_id"], @@ -394,18 +394,8 @@ async def index_confluence_pages( item["full_content"], user_llm, document_metadata ) else: - # Fallback to simple summary if no LLM configured - summary_content = f"Confluence Page: {item['page_title']}\n\nSpace ID: {item['space_id']}\n\n" - if item["page_content"]: - # Take first 1000 characters of content for summary - content_preview = item["page_content"][:1000] - if len(item["page_content"]) > 1000: - content_preview += "..." - summary_content += f"Content Preview: {content_preview}\n\n" - summary_content += f"Comments: {item['comment_count']}" - summary_embedding = config.embedding_model_instance.embed( - summary_content - ) + summary_content = f"Confluence Page: {item['page_title']}\n\nSpace ID: {item['space_id']}\n\n{item['full_content']}" + summary_embedding = embed_text(summary_content) # Process chunks - using the full page content with comments chunks = await create_document_chunks(item["full_content"]) diff --git a/surfsense_backend/app/tasks/connector_indexers/discord_indexer.py b/surfsense_backend/app/tasks/connector_indexers/discord_indexer.py index 8769d03c5..0421352ff 100644 --- a/surfsense_backend/app/tasks/connector_indexers/discord_indexer.py +++ b/surfsense_backend/app/tasks/connector_indexers/discord_indexer.py @@ -23,6 +23,7 @@ from app.db import Document, DocumentStatus, DocumentType, SearchSourceConnector from app.services.task_logging_service import TaskLoggingService from app.utils.document_converters import ( create_document_chunks, + embed_text, generate_content_hash, generate_unique_identifier_hash, ) @@ -669,9 +670,7 @@ async def index_discord_messages( # Heavy processing (embeddings, chunks) chunks = await create_document_chunks(item["combined_document_string"]) - doc_embedding = config.embedding_model_instance.embed( - item["combined_document_string"] - ) + doc_embedding = embed_text(item["combined_document_string"]) # Update document to READY with actual content document.title = f"{item['guild_name']}#{item['channel_name']}" diff --git a/surfsense_backend/app/tasks/connector_indexers/github_indexer.py b/surfsense_backend/app/tasks/connector_indexers/github_indexer.py index e1a1ddd4d..fc6634024 100644 --- a/surfsense_backend/app/tasks/connector_indexers/github_indexer.py +++ b/surfsense_backend/app/tasks/connector_indexers/github_indexer.py @@ -16,13 +16,13 @@ from datetime import UTC, datetime from sqlalchemy.exc import SQLAlchemyError from sqlalchemy.ext.asyncio import AsyncSession -from app.config import config from app.connectors.github_connector import GitHubConnector from app.db import Document, DocumentStatus, DocumentType, SearchSourceConnectorType from app.services.llm_service import get_user_long_context_llm from app.services.task_logging_service import TaskLoggingService from app.utils.document_converters import ( create_document_chunks, + embed_text, generate_content_hash, generate_document_summary, generate_unique_identifier_hash, @@ -367,7 +367,7 @@ async def index_github_repos( "estimated_tokens": digest.estimated_tokens, } - if user_llm: + if user_llm and connector.enable_summary: # Prepare content for summarization summary_content = digest.full_digest if len(summary_content) > MAX_DIGEST_CHARS: @@ -381,15 +381,12 @@ async def index_github_repos( summary_content, user_llm, document_metadata_for_summary ) else: - # Fallback to simple summary if no LLM configured summary_text = ( f"# GitHub Repository: {repo_full_name}\n\n" f"## Summary\n{digest.summary}\n\n" - f"## File Structure\n{digest.tree[:3000]}" - ) - summary_embedding = config.embedding_model_instance.embed( - summary_text + f"## File Structure\n{digest.tree}" ) + summary_embedding = embed_text(summary_text) # Chunk the full digest content for granular search try: @@ -551,7 +548,7 @@ async def _simple_chunk_content(content: str, chunk_size: int = 4000) -> list: chunks.append( Chunk( content=chunk_text, - embedding=config.embedding_model_instance.embed(chunk_text), + embedding=embed_text(chunk_text), ) ) diff --git a/surfsense_backend/app/tasks/connector_indexers/google_calendar_indexer.py b/surfsense_backend/app/tasks/connector_indexers/google_calendar_indexer.py index 1476f3f40..1407d98dd 100644 --- a/surfsense_backend/app/tasks/connector_indexers/google_calendar_indexer.py +++ b/surfsense_backend/app/tasks/connector_indexers/google_calendar_indexer.py @@ -20,6 +20,7 @@ from app.services.llm_service import get_user_long_context_llm from app.services.task_logging_service import TaskLoggingService from app.utils.document_converters import ( create_document_chunks, + embed_text, generate_content_hash, generate_document_summary, generate_unique_identifier_hash, @@ -489,7 +490,7 @@ async def index_google_calendar_events( session, user_id, search_space_id ) - if user_llm: + if user_llm and connector.enable_summary: document_metadata_for_summary = { "event_id": item["event_id"], "event_summary": item["event_summary"], @@ -507,22 +508,8 @@ async def index_google_calendar_events( item["event_markdown"], user_llm, document_metadata_for_summary ) else: - summary_content = ( - f"Google Calendar Event: {item['event_summary']}\n\n" - ) - summary_content += f"Calendar: {item['calendar_id']}\n" - summary_content += f"Start: {item['start_time']}\n" - summary_content += f"End: {item['end_time']}\n" - if item["location"]: - summary_content += f"Location: {item['location']}\n" - if item["description"]: - desc_preview = item["description"][:1000] - if len(item["description"]) > 1000: - desc_preview += "..." - summary_content += f"Description: {desc_preview}\n" - summary_embedding = config.embedding_model_instance.embed( - summary_content - ) + summary_content = f"Google Calendar Event: {item['event_summary']}\n\n{item['event_markdown']}" + summary_embedding = embed_text(summary_content) chunks = await create_document_chunks(item["event_markdown"]) diff --git a/surfsense_backend/app/tasks/connector_indexers/google_drive_indexer.py b/surfsense_backend/app/tasks/connector_indexers/google_drive_indexer.py index f7624cffe..20c54d3fc 100644 --- a/surfsense_backend/app/tasks/connector_indexers/google_drive_indexer.py +++ b/surfsense_backend/app/tasks/connector_indexers/google_drive_indexer.py @@ -352,7 +352,7 @@ async def index_google_drive_single_file( await session.commit() # Process the file - indexed, skipped, failed = await _process_single_file( + indexed, _skipped, failed = await _process_single_file( drive_client=drive_client, session=session, file=file, @@ -608,7 +608,7 @@ async def _index_with_delta_sync( {"stage": "delta_sync", "start_token": start_page_token}, ) - changes, final_token, error = await fetch_all_changes( + changes, _final_token, error = await fetch_all_changes( drive_client, start_page_token, folder_id ) @@ -1011,7 +1011,7 @@ async def _process_single_file( pending_document.status = DocumentStatus.processing() await session.commit() - _, error, metadata = await download_and_process_file( + _, error, _metadata = await download_and_process_file( client=drive_client, file=file, search_space_id=search_space_id, diff --git a/surfsense_backend/app/tasks/connector_indexers/google_gmail_indexer.py b/surfsense_backend/app/tasks/connector_indexers/google_gmail_indexer.py index c7caee4da..1a8b2b176 100644 --- a/surfsense_backend/app/tasks/connector_indexers/google_gmail_indexer.py +++ b/surfsense_backend/app/tasks/connector_indexers/google_gmail_indexer.py @@ -25,6 +25,7 @@ from app.services.llm_service import get_user_long_context_llm from app.services.task_logging_service import TaskLoggingService from app.utils.document_converters import ( create_document_chunks, + embed_text, generate_content_hash, generate_document_summary, generate_unique_identifier_hash, @@ -413,7 +414,7 @@ async def index_google_gmail_messages( session, user_id, search_space_id ) - if user_llm: + if user_llm and connector.enable_summary: document_metadata_for_summary = { "message_id": item["message_id"], "thread_id": item["thread_id"], @@ -432,12 +433,8 @@ async def index_google_gmail_messages( document_metadata_for_summary, ) else: - summary_content = f"Google Gmail Message: {item['subject']}\n\n" - summary_content += f"Sender: {item['sender']}\n" - summary_content += f"Date: {item['date_str']}\n" - summary_embedding = config.embedding_model_instance.embed( - summary_content - ) + summary_content = f"Google Gmail Message: {item['subject']}\n\nFrom: {item['sender']}\nDate: {item['date_str']}\n\n{item['markdown_content']}" + summary_embedding = embed_text(summary_content) chunks = await create_document_chunks(item["markdown_content"]) diff --git a/surfsense_backend/app/tasks/connector_indexers/jira_indexer.py b/surfsense_backend/app/tasks/connector_indexers/jira_indexer.py index 65f56ce46..dec37428a 100644 --- a/surfsense_backend/app/tasks/connector_indexers/jira_indexer.py +++ b/surfsense_backend/app/tasks/connector_indexers/jira_indexer.py @@ -14,13 +14,13 @@ from datetime import datetime from sqlalchemy.exc import SQLAlchemyError from sqlalchemy.ext.asyncio import AsyncSession -from app.config import config from app.connectors.jira_history import JiraHistoryConnector from app.db import Document, DocumentStatus, DocumentType, SearchSourceConnectorType from app.services.llm_service import get_user_long_context_llm from app.services.task_logging_service import TaskLoggingService from app.utils.document_converters import ( create_document_chunks, + embed_text, generate_content_hash, generate_document_summary, generate_unique_identifier_hash, @@ -356,7 +356,7 @@ async def index_jira_issues( session, user_id, search_space_id ) - if user_llm: + if user_llm and connector.enable_summary: document_metadata = { "issue_key": item["issue_identifier"], "issue_title": item["issue_title"], @@ -373,14 +373,8 @@ async def index_jira_issues( item["issue_content"], user_llm, document_metadata ) else: - # Fallback to simple summary if no LLM configured - summary_content = f"Jira Issue {item['issue_identifier']}: {item['issue_title']}\n\nStatus: {item['formatted_issue'].get('status', 'Unknown')}\n\n" - if item["formatted_issue"].get("description"): - summary_content += f"Description: {item['formatted_issue'].get('description')}\n\n" - summary_content += f"Comments: {item['comment_count']}" - summary_embedding = config.embedding_model_instance.embed( - summary_content - ) + summary_content = f"Jira Issue {item['issue_identifier']}: {item['issue_title']}\n\n{item['issue_content']}" + summary_embedding = embed_text(summary_content) # Process chunks - using the full issue content with comments chunks = await create_document_chunks(item["issue_content"]) diff --git a/surfsense_backend/app/tasks/connector_indexers/linear_indexer.py b/surfsense_backend/app/tasks/connector_indexers/linear_indexer.py index 87bafb3c0..1a2254c5b 100644 --- a/surfsense_backend/app/tasks/connector_indexers/linear_indexer.py +++ b/surfsense_backend/app/tasks/connector_indexers/linear_indexer.py @@ -13,13 +13,13 @@ from datetime import datetime from sqlalchemy.exc import SQLAlchemyError from sqlalchemy.ext.asyncio import AsyncSession -from app.config import config from app.connectors.linear_connector import LinearConnector from app.db import Document, DocumentStatus, DocumentType, SearchSourceConnectorType from app.services.llm_service import get_user_long_context_llm from app.services.task_logging_service import TaskLoggingService from app.utils.document_converters import ( create_document_chunks, + embed_text, generate_content_hash, generate_document_summary, generate_unique_identifier_hash, @@ -395,7 +395,7 @@ async def index_linear_issues( session, user_id, search_space_id ) - if user_llm: + if user_llm and connector.enable_summary: document_metadata_for_summary = { "issue_id": item["issue_identifier"], "issue_title": item["issue_title"], @@ -412,17 +412,8 @@ async def index_linear_issues( item["issue_content"], user_llm, document_metadata_for_summary ) else: - # Fallback to simple summary if no LLM configured - description = item["description"] - if description and len(description) > 1000: - description = description[:997] + "..." - summary_content = f"Linear Issue {item['issue_identifier']}: {item['issue_title']}\n\nStatus: {item['state']}\n\n" - if description: - summary_content += f"Description: {description}\n\n" - summary_content += f"Comments: {item['comment_count']}" - summary_embedding = config.embedding_model_instance.embed( - summary_content - ) + summary_content = f"Linear Issue {item['issue_identifier']}: {item['issue_title']}\n\nStatus: {item['state']}\n\n{item['issue_content']}" + summary_embedding = embed_text(summary_content) chunks = await create_document_chunks(item["issue_content"]) diff --git a/surfsense_backend/app/tasks/connector_indexers/luma_indexer.py b/surfsense_backend/app/tasks/connector_indexers/luma_indexer.py index 04af80e53..2d86b09c1 100644 --- a/surfsense_backend/app/tasks/connector_indexers/luma_indexer.py +++ b/surfsense_backend/app/tasks/connector_indexers/luma_indexer.py @@ -13,13 +13,13 @@ from datetime import datetime, timedelta from sqlalchemy.exc import SQLAlchemyError from sqlalchemy.ext.asyncio import AsyncSession -from app.config import config from app.connectors.luma_connector import LumaConnector from app.db import Document, DocumentStatus, DocumentType, SearchSourceConnectorType from app.services.llm_service import get_user_long_context_llm from app.services.task_logging_service import TaskLoggingService from app.utils.document_converters import ( create_document_chunks, + embed_text, generate_content_hash, generate_document_summary, generate_unique_identifier_hash, @@ -441,7 +441,7 @@ async def index_luma_events( session, user_id, search_space_id ) - if user_llm: + if user_llm and connector.enable_summary: document_metadata_for_summary = { "event_id": item["event_id"], "event_name": item["event_name"], @@ -462,29 +462,10 @@ async def index_luma_events( item["event_markdown"], user_llm, document_metadata_for_summary ) else: - # Fallback to simple summary if no LLM configured - summary_content = f"Luma Event: {item['event_name']}\n\n" - if item["event_url"]: - summary_content += f"URL: {item['event_url']}\n" - summary_content += f"Start: {item['start_at']}\n" - summary_content += f"End: {item['end_at']}\n" - if item["timezone"]: - summary_content += f"Timezone: {item['timezone']}\n" - if item["location"]: - summary_content += f"Location: {item['location']}\n" - if item["city"]: - summary_content += f"City: {item['city']}\n" - if item["host_names"]: - summary_content += f"Hosts: {item['host_names']}\n" - if item["description"]: - desc_preview = item["description"][:1000] - if len(item["description"]) > 1000: - desc_preview += "..." - summary_content += f"Description: {desc_preview}\n" - - summary_embedding = config.embedding_model_instance.embed( - summary_content + summary_content = ( + f"Luma Event: {item['event_name']}\n\n{item['event_markdown']}" ) + summary_embedding = embed_text(summary_content) chunks = await create_document_chunks(item["event_markdown"]) diff --git a/surfsense_backend/app/tasks/connector_indexers/notion_indexer.py b/surfsense_backend/app/tasks/connector_indexers/notion_indexer.py index d2b1c9137..b0c49dea5 100644 --- a/surfsense_backend/app/tasks/connector_indexers/notion_indexer.py +++ b/surfsense_backend/app/tasks/connector_indexers/notion_indexer.py @@ -13,13 +13,13 @@ from datetime import datetime from sqlalchemy.exc import SQLAlchemyError from sqlalchemy.ext.asyncio import AsyncSession -from app.config import config from app.connectors.notion_history import NotionHistoryConnector from app.db import Document, DocumentStatus, DocumentType, SearchSourceConnectorType from app.services.llm_service import get_user_long_context_llm from app.services.task_logging_service import TaskLoggingService from app.utils.document_converters import ( create_document_chunks, + embed_text, generate_content_hash, generate_document_summary, generate_unique_identifier_hash, @@ -447,7 +447,7 @@ async def index_notion_pages( session, user_id, search_space_id ) - if user_llm: + if user_llm and connector.enable_summary: document_metadata_for_summary = { "page_title": item["page_title"], "page_id": item["page_id"], @@ -463,11 +463,8 @@ async def index_notion_pages( document_metadata_for_summary, ) else: - # Fallback to simple summary if no LLM configured - summary_content = f"Notion Page: {item['page_title']}\n\n{item['markdown_content'][:500]}..." - summary_embedding = config.embedding_model_instance.embed( - summary_content - ) + summary_content = f"Notion Page: {item['page_title']}\n\n{item['markdown_content']}" + summary_embedding = embed_text(summary_content) chunks = await create_document_chunks(item["markdown_content"]) diff --git a/surfsense_backend/app/tasks/connector_indexers/obsidian_indexer.py b/surfsense_backend/app/tasks/connector_indexers/obsidian_indexer.py index 6dea1a730..c0eef84d5 100644 --- a/surfsense_backend/app/tasks/connector_indexers/obsidian_indexer.py +++ b/surfsense_backend/app/tasks/connector_indexers/obsidian_indexer.py @@ -26,6 +26,7 @@ from app.services.llm_service import get_user_long_context_llm from app.services.task_logging_service import TaskLoggingService from app.utils.document_converters import ( create_document_chunks, + embed_text, generate_content_hash, generate_document_summary, generate_unique_identifier_hash, @@ -546,7 +547,7 @@ async def index_obsidian_vault( # Generate summary summary_content = "" - if long_context_llm: + if long_context_llm and connector.enable_summary: summary_content, _ = await generate_document_summary( document_string, long_context_llm, @@ -554,7 +555,7 @@ async def index_obsidian_vault( ) # Generate embedding - embedding = config.embedding_model_instance.embed(document_string) + embedding = embed_text(document_string) # Add URL and summary to metadata document_metadata["url"] = f"obsidian://{vault_name}/{relative_path}" diff --git a/surfsense_backend/app/tasks/connector_indexers/slack_indexer.py b/surfsense_backend/app/tasks/connector_indexers/slack_indexer.py index 01771d2ac..f83b171bc 100644 --- a/surfsense_backend/app/tasks/connector_indexers/slack_indexer.py +++ b/surfsense_backend/app/tasks/connector_indexers/slack_indexer.py @@ -17,12 +17,12 @@ from slack_sdk.errors import SlackApiError from sqlalchemy.exc import SQLAlchemyError from sqlalchemy.ext.asyncio import AsyncSession -from app.config import config from app.connectors.slack_history import SlackHistory from app.db import Document, DocumentStatus, DocumentType, SearchSourceConnectorType from app.services.task_logging_service import TaskLoggingService from app.utils.document_converters import ( create_document_chunks, + embed_text, generate_content_hash, generate_unique_identifier_hash, ) @@ -542,9 +542,7 @@ async def index_slack_messages( # Heavy processing (embeddings, chunks) chunks = await create_document_chunks(item["combined_document_string"]) - doc_embedding = config.embedding_model_instance.embed( - item["combined_document_string"] - ) + doc_embedding = embed_text(item["combined_document_string"]) # Update document to READY with actual content document.title = f"{item['team_name']}#{item['channel_name']}" diff --git a/surfsense_backend/app/tasks/connector_indexers/teams_indexer.py b/surfsense_backend/app/tasks/connector_indexers/teams_indexer.py index cf6828268..ad34e8696 100644 --- a/surfsense_backend/app/tasks/connector_indexers/teams_indexer.py +++ b/surfsense_backend/app/tasks/connector_indexers/teams_indexer.py @@ -16,12 +16,12 @@ from datetime import UTC, datetime from sqlalchemy.exc import SQLAlchemyError from sqlalchemy.ext.asyncio import AsyncSession -from app.config import config from app.connectors.teams_history import TeamsHistory from app.db import Document, DocumentStatus, DocumentType, SearchSourceConnectorType from app.services.task_logging_service import TaskLoggingService from app.utils.document_converters import ( create_document_chunks, + embed_text, generate_content_hash, generate_unique_identifier_hash, ) @@ -581,9 +581,7 @@ async def index_teams_messages( # Heavy processing (embeddings, chunks) chunks = await create_document_chunks(item["combined_document_string"]) - doc_embedding = config.embedding_model_instance.embed( - item["combined_document_string"] - ) + doc_embedding = embed_text(item["combined_document_string"]) # Update document to READY with actual content document.title = f"{item['team_name']} - {item['channel_name']}" diff --git a/surfsense_backend/app/tasks/connector_indexers/webcrawler_indexer.py b/surfsense_backend/app/tasks/connector_indexers/webcrawler_indexer.py index 8b6005b54..94361cc27 100644 --- a/surfsense_backend/app/tasks/connector_indexers/webcrawler_indexer.py +++ b/surfsense_backend/app/tasks/connector_indexers/webcrawler_indexer.py @@ -13,13 +13,13 @@ from datetime import datetime from sqlalchemy.exc import SQLAlchemyError from sqlalchemy.ext.asyncio import AsyncSession -from app.config import config from app.connectors.webcrawler_connector import WebCrawlerConnector from app.db import Document, DocumentStatus, DocumentType, SearchSourceConnectorType from app.services.llm_service import get_user_long_context_llm from app.services.task_logging_service import TaskLoggingService from app.utils.document_converters import ( create_document_chunks, + embed_text, generate_content_hash, generate_document_summary, generate_unique_identifier_hash, @@ -377,7 +377,7 @@ async def index_crawled_urls( session, user_id, search_space_id ) - if user_llm: + if user_llm and connector.enable_summary: document_metadata_for_summary = { "url": url, "title": title, @@ -393,24 +393,8 @@ async def index_crawled_urls( structured_document, user_llm, document_metadata_for_summary ) else: - # Fallback to simple summary if no LLM configured - summary_content = f"Crawled URL: {title}\n\n" - summary_content += f"URL: {url}\n" - if description: - summary_content += f"Description: {description}\n" - if language: - summary_content += f"Language: {language}\n" - summary_content += f"Crawler: {crawler_type}\n\n" - - # Add content preview - content_preview = content[:1000] - if len(content) > 1000: - content_preview += "..." - summary_content += f"Content Preview:\n{content_preview}\n" - - summary_embedding = config.embedding_model_instance.embed( - summary_content - ) + summary_content = f"Crawled URL: {title}\n\nURL: {url}\n\n{content}" + summary_embedding = embed_text(summary_content) # Process chunks chunks = await create_document_chunks(content) diff --git a/surfsense_backend/app/tasks/document_processors/file_processors.py b/surfsense_backend/app/tasks/document_processors/file_processors.py index 041053a04..5e97951bd 100644 --- a/surfsense_backend/app/tasks/document_processors/file_processors.py +++ b/surfsense_backend/app/tasks/document_processors/file_processors.py @@ -18,12 +18,14 @@ from sqlalchemy.ext.asyncio import AsyncSession from app.config import config as app_config from app.db import Document, DocumentStatus, DocumentType, Log, Notification +from app.indexing_pipeline.adapters.file_upload_adapter import UploadDocumentAdapter from app.services.llm_service import get_user_long_context_llm from app.services.notification_service import NotificationService from app.services.task_logging_service import TaskLoggingService from app.utils.document_converters import ( convert_document_to_markdown, create_document_chunks, + embed_text, generate_content_hash, generate_document_summary, generate_unique_identifier_hash, @@ -33,7 +35,6 @@ from .base import ( check_document_by_unique_identifier, check_duplicate_document, get_current_timestamp, - safe_set_chunks, ) from .markdown_processor import add_received_markdown_file_document @@ -760,11 +761,7 @@ async def add_received_file_document_using_docling( f"{metadata_section}\n\n# DOCUMENT SUMMARY\n\n{summary_content}" ) - from app.config import config - - summary_embedding = config.embedding_model_instance.embed( - enhanced_summary_content - ) + summary_embedding = embed_text(enhanced_summary_content) # Process chunks chunks = await create_document_chunks(file_in_markdown) @@ -1599,6 +1596,7 @@ async def process_file_in_background_with_document( log_entry: Log, connector: dict | None = None, notification: Notification | None = None, + should_summarize: bool = False, ) -> Document | None: """ Process file and update existing pending document (2-phase pattern). @@ -1632,6 +1630,8 @@ async def process_file_in_background_with_document( from app.config import config as app_config from app.services.llm_service import get_user_long_context_llm + doc_id = document.id + try: markdown_content = None etl_service = None @@ -1855,7 +1855,7 @@ async def process_file_in_background_with_document( content_hash = generate_content_hash(markdown_content, search_space_id) existing_by_content = await check_duplicate_document(session, content_hash) - if existing_by_content and existing_by_content.id != document.id: + if existing_by_content and existing_by_content.id != doc_id: # Duplicate content found - mark this document as failed logging.info( f"Duplicate content detected for {filename}, " @@ -1863,7 +1863,7 @@ async def process_file_in_background_with_document( ) return None - # ===== STEP 3: Generate embeddings and chunks ===== + # ===== STEP 3+4: Index via pipeline ===== if notification: await NotificationService.document_processing.notify_processing_progress( session, notification, stage="chunking" @@ -1871,57 +1871,24 @@ async def process_file_in_background_with_document( user_llm = await get_user_long_context_llm(session, user_id, search_space_id) - if user_llm: - document_metadata = { - "file_name": filename, - "etl_service": etl_service, - "document_type": "File Document", - } - summary_content, summary_embedding = await generate_document_summary( - markdown_content, user_llm, document_metadata - ) - else: - # Fallback: use truncated content as summary - summary_content = markdown_content[:4000] - from app.config import config - - summary_embedding = config.embedding_model_instance.embed(summary_content) - - chunks = await create_document_chunks(markdown_content) - - # ===== STEP 4: Update document to READY ===== - from sqlalchemy.orm.attributes import flag_modified - - document.title = filename - document.content = summary_content - document.content_hash = content_hash - document.embedding = summary_embedding - document.document_metadata = { - "FILE_NAME": filename, - "ETL_SERVICE": etl_service or "UNKNOWN", - **(document.document_metadata or {}), - } - flag_modified(document, "document_metadata") - - # Use safe_set_chunks to avoid async issues - safe_set_chunks(document, chunks) - - document.source_markdown = markdown_content - document.content_needs_reindexing = False - document.updated_at = get_current_timestamp() - document.status = DocumentStatus.ready() # Shows checkmark in UI - - await session.commit() - await session.refresh(document) + adapter = UploadDocumentAdapter(session) + await adapter.index( + markdown_content=markdown_content, + filename=filename, + etl_service=etl_service, + search_space_id=search_space_id, + user_id=user_id, + llm=user_llm, + should_summarize=should_summarize, + ) await task_logger.log_task_success( log_entry, f"Successfully processed file: {filename}", { - "document_id": document.id, + "document_id": doc_id, "content_hash": content_hash, "file_type": etl_service, - "chunks_count": len(chunks), }, ) @@ -1946,7 +1913,7 @@ async def process_file_in_background_with_document( { "error_type": type(e).__name__, "filename": filename, - "document_id": document.id, + "document_id": doc_id, }, ) logging.error(f"Error processing file with document: {error_message}") diff --git a/surfsense_backend/app/tasks/surfsense_docs_indexer.py b/surfsense_backend/app/tasks/surfsense_docs_indexer.py index ef287bc65..ca4a83de3 100644 --- a/surfsense_backend/app/tasks/surfsense_docs_indexer.py +++ b/surfsense_backend/app/tasks/surfsense_docs_indexer.py @@ -15,6 +15,7 @@ from sqlalchemy.orm import selectinload from app.config import config from app.db import SurfsenseDocsChunk, SurfsenseDocsDocument, async_session_maker +from app.utils.document_converters import embed_text logger = logging.getLogger(__name__) @@ -89,7 +90,7 @@ def create_surfsense_docs_chunks(content: str) -> list[SurfsenseDocsChunk]: return [ SurfsenseDocsChunk( content=chunk.text, - embedding=config.embedding_model_instance.embed(chunk.text), + embedding=embed_text(chunk.text), ) for chunk in config.chunker_instance.chunk(content) ] @@ -154,7 +155,7 @@ async def index_surfsense_docs(session: AsyncSession) -> tuple[int, int, int, in existing_doc.title = title existing_doc.content = content existing_doc.content_hash = content_hash - existing_doc.embedding = config.embedding_model_instance.embed(content) + existing_doc.embedding = embed_text(content) existing_doc.chunks = chunks existing_doc.updated_at = datetime.now(UTC) @@ -170,7 +171,7 @@ async def index_surfsense_docs(session: AsyncSession) -> tuple[int, int, int, in title=title, content=content, content_hash=content_hash, - embedding=config.embedding_model_instance.embed(content), + embedding=embed_text(content), chunks=chunks, updated_at=datetime.now(UTC), ) diff --git a/surfsense_backend/app/utils/document_converters.py b/surfsense_backend/app/utils/document_converters.py index d7e1db71d..8049b0de5 100644 --- a/surfsense_backend/app/utils/document_converters.py +++ b/surfsense_backend/app/utils/document_converters.py @@ -1,11 +1,59 @@ import hashlib +import logging +import warnings +import numpy as np from litellm import get_model_info, token_counter from app.config import config from app.db import Chunk, DocumentType from app.prompts import SUMMARY_PROMPT_TEMPLATE +logger = logging.getLogger(__name__) + + +def _get_embedding_max_tokens() -> int: + """Get the max token limit for the configured embedding model. + + Checks model properties in order: max_seq_length, _max_tokens. + Falls back to 8192 (OpenAI embedding default). + """ + model = config.embedding_model_instance + for attr in ("max_seq_length", "_max_tokens"): + val = getattr(model, attr, None) + if isinstance(val, int) and val > 0: + return val + return 8192 + + +def truncate_for_embedding(text: str) -> str: + """Truncate text to fit within the embedding model's context window. + + Uses the embedding model's own tokenizer for accurate token counting, + so the result is model-agnostic regardless of the underlying provider. + """ + max_tokens = _get_embedding_max_tokens() + if len(text) // 3 <= max_tokens: + return text + + tokenizer = config.embedding_model_instance.get_tokenizer() + tokens = tokenizer.encode(text) + if len(tokens) <= max_tokens: + return text + + warnings.warn( + f"Truncating text from {len(tokens)} to {max_tokens} tokens for embedding.", + stacklevel=2, + ) + return tokenizer.decode(tokens[:max_tokens]) + + +def embed_text(text: str) -> np.ndarray: + """Truncate text to fit and embed it. Drop-in replacement for + ``config.embedding_model_instance.embed(text)`` that never exceeds the + model's context window.""" + return config.embedding_model_instance.embed(truncate_for_embedding(text)) + def get_model_context_window(model_name: str) -> int: """Get the total context window size for a model (input + output tokens).""" @@ -146,7 +194,7 @@ async def generate_document_summary( else: enhanced_summary_content = summary_content - summary_embedding = config.embedding_model_instance.embed(enhanced_summary_content) + summary_embedding = embed_text(enhanced_summary_content) return enhanced_summary_content, summary_embedding @@ -164,7 +212,7 @@ async def create_document_chunks(content: str) -> list[Chunk]: return [ Chunk( content=chunk.text, - embedding=config.embedding_model_instance.embed(chunk.text), + embedding=embed_text(chunk.text), ) for chunk in config.chunker_instance.chunk(content) ] diff --git a/surfsense_backend/app/utils/perf.py b/surfsense_backend/app/utils/perf.py new file mode 100644 index 000000000..b2b26897c --- /dev/null +++ b/surfsense_backend/app/utils/perf.py @@ -0,0 +1,174 @@ +""" +Centralized performance monitoring for SurfSense backend. + +Provides: +- A shared [PERF] logger used across all modules +- perf_timer context manager for timing code blocks +- perf_async_timer for async code blocks +- system_snapshot() for CPU/memory profiling +- RequestPerfMiddleware for per-request timing +""" + +import gc +import logging +import os +import time +from contextlib import asynccontextmanager, contextmanager +from typing import Any + +_perf_log: logging.Logger | None = None +_last_rss_mb: float = 0.0 + + +def get_perf_logger() -> logging.Logger: + """Return the singleton [PERF] logger, creating it once on first call.""" + global _perf_log + if _perf_log is None: + _perf_log = logging.getLogger("surfsense.perf") + _perf_log.setLevel(logging.DEBUG) + if not _perf_log.handlers: + h = logging.StreamHandler() + h.setFormatter(logging.Formatter("%(asctime)s [PERF] %(message)s")) + _perf_log.addHandler(h) + _perf_log.propagate = False + return _perf_log + + +@contextmanager +def perf_timer(label: str, *, extra: dict[str, Any] | None = None): + """Synchronous context manager that logs elapsed wall-clock time. + + Usage: + with perf_timer("[my_func] heavy computation"): + ... + """ + log = get_perf_logger() + t0 = time.perf_counter() + yield + elapsed = time.perf_counter() - t0 + suffix = "" + if extra: + suffix = " " + " ".join(f"{k}={v}" for k, v in extra.items()) + log.info("%s in %.3fs%s", label, elapsed, suffix) + + +@asynccontextmanager +async def perf_async_timer(label: str, *, extra: dict[str, Any] | None = None): + """Async context manager that logs elapsed wall-clock time. + + Usage: + async with perf_async_timer("[search] vector search"): + ... + """ + log = get_perf_logger() + t0 = time.perf_counter() + yield + elapsed = time.perf_counter() - t0 + suffix = "" + if extra: + suffix = " " + " ".join(f"{k}={v}" for k, v in extra.items()) + log.info("%s in %.3fs%s", label, elapsed, suffix) + + +def system_snapshot() -> dict[str, Any]: + """Capture a lightweight CPU + memory snapshot of the current process. + + Returns a dict with: + - rss_mb: Resident Set Size in MB + - rss_delta_mb: Change in RSS since the last snapshot + - cpu_percent: CPU usage % since last call (per-process) + - threads: number of active threads + - open_fds: number of open file descriptors (Linux only) + - asyncio_tasks: number of asyncio tasks currently alive + - gc_counts: tuple of object counts per gc generation + """ + import asyncio + + global _last_rss_mb + + snapshot: dict[str, Any] = {} + try: + import psutil + + proc = psutil.Process(os.getpid()) + mem = proc.memory_info() + rss_mb = round(mem.rss / 1024 / 1024, 1) + snapshot["rss_mb"] = rss_mb + snapshot["rss_delta_mb"] = ( + round(rss_mb - _last_rss_mb, 1) if _last_rss_mb else 0.0 + ) + _last_rss_mb = rss_mb + snapshot["cpu_percent"] = proc.cpu_percent(interval=None) + snapshot["threads"] = proc.num_threads() + try: + snapshot["open_fds"] = proc.num_fds() + except AttributeError: + snapshot["open_fds"] = -1 + except ImportError: + snapshot["rss_mb"] = -1 + snapshot["rss_delta_mb"] = 0.0 + snapshot["cpu_percent"] = -1 + snapshot["threads"] = -1 + snapshot["open_fds"] = -1 + + try: + all_tasks = asyncio.all_tasks() + snapshot["asyncio_tasks"] = len(all_tasks) + except RuntimeError: + snapshot["asyncio_tasks"] = -1 + + snapshot["gc_counts"] = gc.get_count() + + return snapshot + + +def log_system_snapshot(label: str = "system_snapshot") -> None: + """Capture and log a system snapshot with memory delta tracking.""" + snap = system_snapshot() + delta_str = "" + if snap["rss_delta_mb"]: + sign = "+" if snap["rss_delta_mb"] > 0 else "" + delta_str = f" delta={sign}{snap['rss_delta_mb']}MB" + get_perf_logger().info( + "[%s] rss=%.1fMB%s cpu=%.1f%% threads=%d fds=%d asyncio_tasks=%d gc=%s", + label, + snap["rss_mb"], + delta_str, + snap["cpu_percent"], + snap["threads"], + snap["open_fds"], + snap["asyncio_tasks"], + snap["gc_counts"], + ) + + if snap["rss_mb"] > 0 and snap["rss_delta_mb"] > 500: + get_perf_logger().warning( + "[MEMORY_SPIKE] %s: RSS jumped by %.1fMB (now %.1fMB). " + "Possible leak — check recent operations.", + label, + snap["rss_delta_mb"], + snap["rss_mb"], + ) + + +def trim_native_heap() -> bool: + """Ask glibc to return free heap pages to the OS via ``malloc_trim(0)``. + + On Linux (glibc), ``free()`` does not release memory back to the OS if + it sits below the brk watermark. ``malloc_trim`` forces the allocator + to give back as many freed pages as possible. + + Returns True if trimming was performed, False otherwise (non-Linux or + libc unavailable). + """ + import ctypes + import sys + + if sys.platform != "linux": + return False + try: + libc = ctypes.CDLL("libc.so.6") + libc.malloc_trim(0) + return True + except (OSError, AttributeError): + return False diff --git a/surfsense_backend/main.py b/surfsense_backend/main.py index 9c1b5c342..4a7a9b7b1 100644 --- a/surfsense_backend/main.py +++ b/surfsense_backend/main.py @@ -29,4 +29,7 @@ if __name__ == "__main__": config = uvicorn.Config(**config_kwargs) server = uvicorn.Server(config) - server.run() + if sys.platform == "win32": + asyncio.run(server.serve(), loop_factory=asyncio.SelectorEventLoop) + else: + server.run() diff --git a/surfsense_backend/pyproject.toml b/surfsense_backend/pyproject.toml index d852dfd13..08775b31f 100644 --- a/surfsense_backend/pyproject.toml +++ b/surfsense_backend/pyproject.toml @@ -66,11 +66,16 @@ dependencies = [ "pypandoc_binary>=1.16.2", "typst>=0.14.0", "deepagents>=0.4.3", + "langchain-daytona>=0.0.2", ] [dependency-groups] dev = [ "ruff>=0.12.5", + "pytest>=9.0.2", + "pytest-asyncio>=1.3.0", + "pytest-mock>=3.14", + "httpx>=0.28.1", ] [tool.ruff] @@ -158,10 +163,27 @@ line-ending = "auto" [tool.ruff.lint.isort] # Group imports by type -known-first-party = ["app"] +known-first-party = ["app", "tests"] force-single-line = false combine-as-imports = true +[tool.pytest.ini_options] +asyncio_mode = "auto" +asyncio_default_fixture_loop_scope = "session" +asyncio_default_test_loop_scope = "session" +testpaths = ["tests"] +python_files = ["test_*.py"] +python_classes = ["Test*"] +python_functions = ["test_*"] +addopts = "-v --tb=short -x --strict-markers -ra --durations=5" +markers = [ + "unit: pure logic tests, no DB or external services", + "integration: tests that require a real PostgreSQL database" +] +filterwarnings = [ + "ignore::UserWarning:chonkie", +] + [tool.setuptools.packages.find] where = ["."] include = ["app*", "alembic*"] diff --git a/surfsense_backend/scripts/docker/entrypoint.sh b/surfsense_backend/scripts/docker/entrypoint.sh index e1a2778fc..7bfcfce86 100644 --- a/surfsense_backend/scripts/docker/entrypoint.sh +++ b/surfsense_backend/scripts/docker/entrypoint.sh @@ -53,7 +53,7 @@ run_migrations() { sleep 1 done - if timeout 60 alembic upgrade head 2>&1; then + if timeout 300 alembic upgrade head 2>&1; then echo "Migrations completed successfully." else echo "WARNING: Migration failed or timed out. Continuing anyway..." diff --git a/surfsense_backend/tests/__init__.py b/surfsense_backend/tests/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/surfsense_backend/tests/conftest.py b/surfsense_backend/tests/conftest.py new file mode 100644 index 000000000..e2b586aa2 --- /dev/null +++ b/surfsense_backend/tests/conftest.py @@ -0,0 +1,61 @@ +"""Root conftest — shared fixtures available to all test modules.""" + +from __future__ import annotations + +import os + +_DEFAULT_TEST_DB = ( + "postgresql+asyncpg://postgres:postgres@localhost:5432/surfsense_test" +) +TEST_DATABASE_URL = os.environ.get("TEST_DATABASE_URL", _DEFAULT_TEST_DB) + +# Force the app to use the test database regardless of any pre-existing +# DATABASE_URL in the environment (e.g. from .env or shell profile). +os.environ["DATABASE_URL"] = TEST_DATABASE_URL + +import pytest # noqa: E402 + +from app.db import DocumentType # noqa: E402 +from app.indexing_pipeline.connector_document import ConnectorDocument # noqa: E402 + +# --------------------------------------------------------------------------- +# Unit test fixtures +# --------------------------------------------------------------------------- + + +@pytest.fixture +def sample_user_id() -> str: + return "00000000-0000-0000-0000-000000000001" + + +@pytest.fixture +def sample_search_space_id() -> int: + return 1 + + +@pytest.fixture +def sample_connector_id() -> int: + return 42 + + +@pytest.fixture +def make_connector_document(): + """ + Generic factory for unit tests. Overridden in tests/integration/conftest.py + with real DB-backed IDs for integration tests. + """ + + def _make(**overrides): + defaults = { + "title": "Test Document", + "source_markdown": "## Heading\n\nSome content.", + "unique_id": "test-id-001", + "document_type": DocumentType.CLICKUP_CONNECTOR, + "search_space_id": 1, + "connector_id": 1, + "created_by_id": "00000000-0000-0000-0000-000000000001", + } + defaults.update(overrides) + return ConnectorDocument(**defaults) + + return _make diff --git a/surfsense_backend/tests/fixtures/empty.pdf b/surfsense_backend/tests/fixtures/empty.pdf new file mode 100644 index 000000000..e69de29bb diff --git a/surfsense_backend/tests/fixtures/sample.md b/surfsense_backend/tests/fixtures/sample.md new file mode 100644 index 000000000..7217540d8 --- /dev/null +++ b/surfsense_backend/tests/fixtures/sample.md @@ -0,0 +1,51 @@ +# SurfSense Test Document + +## Overview + +This is a **sample markdown document** used for end-to-end testing of the manual +document upload pipeline. It includes various markdown formatting elements. + +## Key Features + +- Document upload and processing +- Automatic chunking of content +- Embedding generation for semantic search +- Real-time status tracking via ElectricSQL + +## Technical Architecture + +### Backend Stack + +The SurfSense backend is built with: + +1. **FastAPI** for the REST API +2. **PostgreSQL** with pgvector for vector storage +3. **Celery** with Redis for background task processing +4. **Docling/Unstructured** for document parsing (ETL) + +### Processing Pipeline + +Documents go through a multi-stage pipeline: + +| Stage | Description | +|-------|-------------| +| Upload | File received via API endpoint | +| Parsing | Content extracted using ETL service | +| Chunking | Text split into semantic chunks | +| Embedding | Vector representations generated | +| Storage | Chunks stored with embeddings in pgvector | + +## Code Example + +```python +async def process_document(file_path: str) -> Document: + content = extract_content(file_path) + chunks = create_chunks(content) + embeddings = generate_embeddings(chunks) + return store_document(chunks, embeddings) +``` + +## Conclusion + +This document serves as a test fixture to validate the complete document processing +pipeline from upload through to chunk creation and embedding storage. diff --git a/surfsense_backend/tests/fixtures/sample.pdf b/surfsense_backend/tests/fixtures/sample.pdf new file mode 100644 index 000000000..228071def Binary files /dev/null and b/surfsense_backend/tests/fixtures/sample.pdf differ diff --git a/surfsense_backend/tests/fixtures/sample.txt b/surfsense_backend/tests/fixtures/sample.txt new file mode 100644 index 000000000..0ee6513b9 --- /dev/null +++ b/surfsense_backend/tests/fixtures/sample.txt @@ -0,0 +1,34 @@ +SurfSense Document Upload Test + +This is a sample text document used for end-to-end testing of the manual document +upload pipeline in SurfSense. The document contains multiple paragraphs to ensure +that the chunking system has enough content to work with. + +Artificial Intelligence and Machine Learning + +Artificial intelligence (AI) is a broad field of computer science concerned with +building smart machines capable of performing tasks that typically require human +intelligence. Machine learning is a subset of AI that enables systems to learn and +improve from experience without being explicitly programmed. + +Natural Language Processing + +Natural language processing (NLP) is a subfield of linguistics, computer science, +and artificial intelligence concerned with the interactions between computers and +human language. Key applications include machine translation, sentiment analysis, +text summarization, and question answering systems. + +Vector Databases and Semantic Search + +Vector databases store data as high-dimensional vectors, enabling efficient +similarity search operations. When combined with embedding models, they power +semantic search systems that understand the meaning behind queries rather than +relying on exact keyword matches. This technology is fundamental to modern +retrieval-augmented generation (RAG) systems. + +Document Processing Pipelines + +Modern document processing pipelines involve several stages: extraction, transformation, +chunking, embedding generation, and storage. Each stage plays a critical role in +converting raw documents into searchable, structured knowledge that can be retrieved +and used by AI systems for accurate information retrieval and generation. diff --git a/surfsense_backend/tests/integration/__init__.py b/surfsense_backend/tests/integration/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/surfsense_backend/tests/integration/conftest.py b/surfsense_backend/tests/integration/conftest.py new file mode 100644 index 000000000..8b92a5aa8 --- /dev/null +++ b/surfsense_backend/tests/integration/conftest.py @@ -0,0 +1,168 @@ +import uuid +from unittest.mock import AsyncMock, MagicMock + +import pytest +import pytest_asyncio +from sqlalchemy import text +from sqlalchemy.ext.asyncio import AsyncSession, create_async_engine +from sqlalchemy.pool import NullPool + +from app.config import config as app_config +from app.db import ( + Base, + DocumentType, + SearchSourceConnector, + SearchSourceConnectorType, + SearchSpace, + User, +) +from app.indexing_pipeline.connector_document import ConnectorDocument +from tests.conftest import TEST_DATABASE_URL + +_EMBEDDING_DIM = app_config.embedding_model_instance.dimension + + +@pytest_asyncio.fixture(scope="session") +async def async_engine(): + engine = create_async_engine( + TEST_DATABASE_URL, + poolclass=NullPool, + echo=False, + # Required for asyncpg + savepoints: disables prepared statement cache + # to prevent "another operation is in progress" errors during savepoint rollbacks. + connect_args={"prepared_statement_cache_size": 0}, + ) + + async with engine.begin() as conn: + await conn.execute(text("CREATE EXTENSION IF NOT EXISTS vector")) + await conn.run_sync(Base.metadata.create_all) + + yield engine + + # drop_all fails on circular FKs (new_chat_threads ↔ public_chat_snapshots). + # DROP SCHEMA CASCADE handles this without needing topological sort. + async with engine.begin() as conn: + await conn.execute(text("DROP SCHEMA public CASCADE")) + await conn.execute(text("CREATE SCHEMA public")) + + await engine.dispose() + + +@pytest_asyncio.fixture +async def db_session(async_engine) -> AsyncSession: + # Bind the session to a connection that holds an outer transaction. + # join_transaction_mode="create_savepoint" makes session.commit() release + # a SAVEPOINT instead of committing the outer transaction, so the final + # transaction.rollback() undoes everything — including commits made by the + # service under test — leaving the DB clean for the next test. + async with async_engine.connect() as conn: + transaction = await conn.begin() + async with AsyncSession( + bind=conn, + expire_on_commit=False, + join_transaction_mode="create_savepoint", + ) as session: + yield session + await transaction.rollback() + + +@pytest_asyncio.fixture +async def db_user(db_session: AsyncSession) -> User: + user = User( + id=uuid.uuid4(), + email="test@surfsense.net", + hashed_password="hashed", + is_active=True, + is_superuser=False, + is_verified=True, + ) + db_session.add(user) + await db_session.flush() + return user + + +@pytest_asyncio.fixture +async def db_connector( + db_session: AsyncSession, db_user: User, db_search_space: "SearchSpace" +) -> SearchSourceConnector: + connector = SearchSourceConnector( + name="Test Connector", + connector_type=SearchSourceConnectorType.CLICKUP_CONNECTOR, + config={}, + search_space_id=db_search_space.id, + user_id=db_user.id, + ) + db_session.add(connector) + await db_session.flush() + return connector + + +@pytest_asyncio.fixture +async def db_search_space(db_session: AsyncSession, db_user: User) -> SearchSpace: + space = SearchSpace( + name="Test Space", + user_id=db_user.id, + ) + db_session.add(space) + await db_session.flush() + return space + + +@pytest.fixture +def patched_summarize(monkeypatch) -> AsyncMock: + mock = AsyncMock(return_value="Mocked summary.") + monkeypatch.setattr( + "app.indexing_pipeline.indexing_pipeline_service.summarize_document", + mock, + ) + return mock + + +@pytest.fixture +def patched_summarize_raises(monkeypatch) -> AsyncMock: + mock = AsyncMock(side_effect=RuntimeError("LLM unavailable")) + monkeypatch.setattr( + "app.indexing_pipeline.indexing_pipeline_service.summarize_document", + mock, + ) + return mock + + +@pytest.fixture +def patched_embed_text(monkeypatch) -> MagicMock: + mock = MagicMock(return_value=[0.1] * _EMBEDDING_DIM) + monkeypatch.setattr( + "app.indexing_pipeline.indexing_pipeline_service.embed_text", + mock, + ) + return mock + + +@pytest.fixture +def patched_chunk_text(monkeypatch) -> MagicMock: + mock = MagicMock(return_value=["Test chunk content."]) + monkeypatch.setattr( + "app.indexing_pipeline.indexing_pipeline_service.chunk_text", + mock, + ) + return mock + + +@pytest.fixture +def make_connector_document(db_connector, db_user): + """Integration-scoped override: uses real DB connector and user IDs.""" + + def _make(**overrides): + defaults = { + "title": "Test Document", + "source_markdown": "## Heading\n\nSome content.", + "unique_id": "test-id-001", + "document_type": DocumentType.CLICKUP_CONNECTOR, + "search_space_id": db_connector.search_space_id, + "connector_id": db_connector.id, + "created_by_id": str(db_user.id), + } + defaults.update(overrides) + return ConnectorDocument(**defaults) + + return _make diff --git a/surfsense_backend/tests/integration/document_upload/__init__.py b/surfsense_backend/tests/integration/document_upload/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/surfsense_backend/tests/integration/document_upload/conftest.py b/surfsense_backend/tests/integration/document_upload/conftest.py new file mode 100644 index 000000000..41639fc2f --- /dev/null +++ b/surfsense_backend/tests/integration/document_upload/conftest.py @@ -0,0 +1,291 @@ +"""Integration conftest — runs the FastAPI app in-process via ASGITransport. + +Prerequisites: PostgreSQL + pgvector only. + +External system boundaries are mocked: + - LLM summarization, text embedding, text chunking (external APIs) + - Redis heartbeat (external infrastructure) + - Task dispatch is swapped via DI (InlineTaskDispatcher) +""" + +from __future__ import annotations + +import contextlib +from collections.abc import AsyncGenerator +from unittest.mock import AsyncMock, MagicMock + +import asyncpg +import httpx +import pytest +from httpx import ASGITransport +from sqlalchemy import text +from sqlalchemy.ext.asyncio import create_async_engine +from sqlalchemy.pool import NullPool + +from app.app import app, limiter +from app.config import config as app_config +from app.db import Base +from app.services.task_dispatcher import get_task_dispatcher +from tests.integration.conftest import TEST_DATABASE_URL +from tests.utils.helpers import ( + TEST_EMAIL, + auth_headers, + delete_document, + get_auth_token, + get_search_space_id, +) + +limiter.enabled = False + +_EMBEDDING_DIM = app_config.embedding_model_instance.dimension +_ASYNCPG_URL = TEST_DATABASE_URL.replace("postgresql+asyncpg://", "postgresql://") + +pytestmark = pytest.mark.integration + + +# --------------------------------------------------------------------------- +# Inline task dispatcher (replaces Celery via DI — not a mock) +# --------------------------------------------------------------------------- + + +class InlineTaskDispatcher: + """Processes files synchronously in the calling coroutine. + + Swapped in via FastAPI dependency_overrides so the upload endpoint + processes documents inline instead of dispatching to Celery. + + Exceptions are caught to match Celery's fire-and-forget semantics — + the processing function already marks documents as failed internally. + """ + + async def dispatch_file_processing( + self, + *, + document_id: int, + temp_path: str, + filename: str, + search_space_id: int, + user_id: str, + should_summarize: bool = False, + ) -> None: + from app.tasks.celery_tasks.document_tasks import ( + _process_file_with_document, + ) + + with contextlib.suppress(Exception): + await _process_file_with_document( + document_id, + temp_path, + filename, + search_space_id, + user_id, + should_summarize=should_summarize, + ) + + +app.dependency_overrides[get_task_dispatcher] = lambda: InlineTaskDispatcher() + + +# --------------------------------------------------------------------------- +# Database setup (ASGITransport skips the app lifespan) +# --------------------------------------------------------------------------- + + +@pytest.fixture(scope="session") +async def _ensure_tables(): + """Create DB tables and extensions once per session.""" + engine = create_async_engine(TEST_DATABASE_URL, poolclass=NullPool) + async with engine.begin() as conn: + await conn.execute(text("CREATE EXTENSION IF NOT EXISTS vector")) + await conn.execute(text("CREATE EXTENSION IF NOT EXISTS pg_trgm")) + await conn.run_sync(Base.metadata.create_all) + await engine.dispose() + + +# --------------------------------------------------------------------------- +# Auth & search space (session-scoped, via the in-process app) +# --------------------------------------------------------------------------- + + +@pytest.fixture(scope="session") +async def auth_token(_ensure_tables) -> str: + """Authenticate once per session, registering the user if needed.""" + async with httpx.AsyncClient( + transport=ASGITransport(app=app), base_url="http://test", timeout=30.0 + ) as c: + return await get_auth_token(c) + + +@pytest.fixture(scope="session") +async def search_space_id(auth_token: str) -> int: + """Discover the first search space belonging to the test user.""" + async with httpx.AsyncClient( + transport=ASGITransport(app=app), base_url="http://test", timeout=30.0 + ) as c: + return await get_search_space_id(c, auth_token) + + +@pytest.fixture(scope="session") +def headers(auth_token: str) -> dict[str, str]: + return auth_headers(auth_token) + + +# --------------------------------------------------------------------------- +# Per-test HTTP client & cleanup +# --------------------------------------------------------------------------- + + +@pytest.fixture +async def client() -> AsyncGenerator[httpx.AsyncClient]: + """Per-test async HTTP client using ASGITransport (no running server).""" + async with httpx.AsyncClient( + transport=ASGITransport(app=app), base_url="http://test", timeout=180.0 + ) as c: + yield c + + +@pytest.fixture +def cleanup_doc_ids() -> list[int]: + """Accumulator for document IDs that should be deleted after the test.""" + return [] + + +@pytest.fixture(scope="session", autouse=True) +async def _purge_test_search_space(search_space_id: int): + """Delete stale documents from previous runs before the session starts.""" + conn = await asyncpg.connect(_ASYNCPG_URL) + try: + result = await conn.execute( + "DELETE FROM documents WHERE search_space_id = $1", + search_space_id, + ) + deleted = int(result.split()[-1]) + if deleted: + print( + f"\n[purge] Deleted {deleted} stale document(s) " + f"from search space {search_space_id}" + ) + finally: + await conn.close() + yield + + +@pytest.fixture(autouse=True) +async def _cleanup_documents( + client: httpx.AsyncClient, + headers: dict[str, str], + cleanup_doc_ids: list[int], +): + """Delete test documents after every test (API first, DB fallback).""" + yield + + remaining_ids: list[int] = [] + for doc_id in cleanup_doc_ids: + try: + resp = await delete_document(client, headers, doc_id) + if resp.status_code == 409: + remaining_ids.append(doc_id) + except Exception: + remaining_ids.append(doc_id) + + if remaining_ids: + conn = await asyncpg.connect(_ASYNCPG_URL) + try: + await conn.execute( + "DELETE FROM documents WHERE id = ANY($1::int[])", + remaining_ids, + ) + finally: + await conn.close() + + +# --------------------------------------------------------------------------- +# Page-limit helpers (direct DB for setup, API for verification) +# --------------------------------------------------------------------------- + + +async def _get_user_page_usage(email: str) -> tuple[int, int]: + conn = await asyncpg.connect(_ASYNCPG_URL) + try: + row = await conn.fetchrow( + 'SELECT pages_used, pages_limit FROM "user" WHERE email = $1', + email, + ) + assert row is not None, f"User {email!r} not found in database" + return row["pages_used"], row["pages_limit"] + finally: + await conn.close() + + +async def _set_user_page_limits( + email: str, *, pages_used: int, pages_limit: int +) -> None: + conn = await asyncpg.connect(_ASYNCPG_URL) + try: + await conn.execute( + 'UPDATE "user" SET pages_used = $1, pages_limit = $2 WHERE email = $3', + pages_used, + pages_limit, + email, + ) + finally: + await conn.close() + + +@pytest.fixture +async def page_limits(): + """Manipulate the test user's page limits (direct DB for setup only). + + Automatically restores original values after each test. + """ + + class _PageLimits: + async def set(self, *, pages_used: int, pages_limit: int) -> None: + await _set_user_page_limits( + TEST_EMAIL, pages_used=pages_used, pages_limit=pages_limit + ) + + original = await _get_user_page_usage(TEST_EMAIL) + yield _PageLimits() + await _set_user_page_limits( + TEST_EMAIL, pages_used=original[0], pages_limit=original[1] + ) + + +# --------------------------------------------------------------------------- +# Mock external system boundaries +# --------------------------------------------------------------------------- + + +@pytest.fixture(autouse=True) +def _mock_external_apis(monkeypatch): + """Mock LLM, embedding, and chunking — these are external API boundaries.""" + monkeypatch.setattr( + "app.indexing_pipeline.indexing_pipeline_service.summarize_document", + AsyncMock(return_value="Mocked summary."), + ) + monkeypatch.setattr( + "app.indexing_pipeline.indexing_pipeline_service.embed_text", + MagicMock(return_value=[0.1] * _EMBEDDING_DIM), + ) + monkeypatch.setattr( + "app.indexing_pipeline.indexing_pipeline_service.chunk_text", + MagicMock(return_value=["Test chunk content."]), + ) + + +@pytest.fixture(autouse=True) +def _mock_redis_heartbeat(monkeypatch): + """Mock Redis heartbeat — Redis is an external infrastructure boundary.""" + monkeypatch.setattr( + "app.tasks.celery_tasks.document_tasks._start_heartbeat", + lambda notification_id: None, + ) + monkeypatch.setattr( + "app.tasks.celery_tasks.document_tasks._stop_heartbeat", + lambda notification_id: None, + ) + monkeypatch.setattr( + "app.tasks.celery_tasks.document_tasks._run_heartbeat_loop", + AsyncMock(), + ) diff --git a/surfsense_backend/tests/integration/document_upload/test_document_upload.py b/surfsense_backend/tests/integration/document_upload/test_document_upload.py new file mode 100644 index 000000000..13ceae828 --- /dev/null +++ b/surfsense_backend/tests/integration/document_upload/test_document_upload.py @@ -0,0 +1,337 @@ +""" +Integration tests for the document upload HTTP API. + +Covers the API contract, auth, duplicate detection, and error handling. +Pipeline internals are tested in the ``indexing_pipeline`` suite. + +Requires PostgreSQL + pgvector. +""" + +from __future__ import annotations + +import shutil +from pathlib import Path + +import httpx +import pytest + +from tests.utils.helpers import ( + FIXTURES_DIR, + poll_document_status, + upload_file, + upload_multiple_files, +) + +pytestmark = pytest.mark.integration + + +# --------------------------------------------------------------------------- +# Upload smoke tests (one per distinct code-path: direct-read & ETL) +# --------------------------------------------------------------------------- + + +class TestTxtFileUpload: + """Upload a plain-text file (direct-read path) via the HTTP API.""" + + async def test_upload_txt_returns_document_id( + self, + client: httpx.AsyncClient, + headers: dict[str, str], + search_space_id: int, + cleanup_doc_ids: list[int], + ): + resp = await upload_file( + client, headers, "sample.txt", search_space_id=search_space_id + ) + assert resp.status_code == 200 + + body = resp.json() + assert body["pending_files"] >= 1 + assert len(body["document_ids"]) >= 1 + cleanup_doc_ids.extend(body["document_ids"]) + + async def test_txt_processing_reaches_ready( + self, + client: httpx.AsyncClient, + headers: dict[str, str], + search_space_id: int, + cleanup_doc_ids: list[int], + ): + resp = await upload_file( + client, headers, "sample.txt", search_space_id=search_space_id + ) + assert resp.status_code == 200 + doc_ids = resp.json()["document_ids"] + cleanup_doc_ids.extend(doc_ids) + + statuses = await poll_document_status( + client, headers, doc_ids, search_space_id=search_space_id + ) + for did in doc_ids: + assert statuses[did]["status"]["state"] == "ready" + + +class TestPdfFileUpload: + """Upload a PDF (ETL extraction path) via the HTTP API.""" + + async def test_pdf_processing_reaches_ready( + self, + client: httpx.AsyncClient, + headers: dict[str, str], + search_space_id: int, + cleanup_doc_ids: list[int], + ): + resp = await upload_file( + client, headers, "sample.pdf", search_space_id=search_space_id + ) + assert resp.status_code == 200 + doc_ids = resp.json()["document_ids"] + cleanup_doc_ids.extend(doc_ids) + + statuses = await poll_document_status( + client, headers, doc_ids, search_space_id=search_space_id, timeout=300.0 + ) + for did in doc_ids: + assert statuses[did]["status"]["state"] == "ready" + + +# --------------------------------------------------------------------------- +# Test D: Upload multiple files in a single request +# --------------------------------------------------------------------------- + + +class TestMultiFileUpload: + """Upload several files at once and verify the API response contract.""" + + async def test_multi_upload_returns_all_ids( + self, + client: httpx.AsyncClient, + headers: dict[str, str], + search_space_id: int, + cleanup_doc_ids: list[int], + ): + resp = await upload_multiple_files( + client, + headers, + ["sample.txt", "sample.md"], + search_space_id=search_space_id, + ) + assert resp.status_code == 200 + + body = resp.json() + assert body["pending_files"] == 2 + assert len(body["document_ids"]) == 2 + cleanup_doc_ids.extend(body["document_ids"]) + + +# --------------------------------------------------------------------------- +# Test E: Duplicate file upload (same file uploaded twice) +# --------------------------------------------------------------------------- + + +class TestDuplicateFileUpload: + """ + Uploading the exact same file a second time should be detected as a + duplicate via ``unique_identifier_hash``. + """ + + async def test_duplicate_file_is_skipped( + self, + client: httpx.AsyncClient, + headers: dict[str, str], + search_space_id: int, + cleanup_doc_ids: list[int], + ): + resp1 = await upload_file( + client, headers, "sample.txt", search_space_id=search_space_id + ) + assert resp1.status_code == 200 + first_ids = resp1.json()["document_ids"] + cleanup_doc_ids.extend(first_ids) + + await poll_document_status( + client, headers, first_ids, search_space_id=search_space_id + ) + + resp2 = await upload_file( + client, headers, "sample.txt", search_space_id=search_space_id + ) + assert resp2.status_code == 200 + + body2 = resp2.json() + assert body2["skipped_duplicates"] >= 1 + assert len(body2["duplicate_document_ids"]) >= 1 + cleanup_doc_ids.extend(body2.get("document_ids", [])) + + +# --------------------------------------------------------------------------- +# Test F: Duplicate content detection (different name, same content) +# --------------------------------------------------------------------------- + + +class TestDuplicateContentDetection: + """ + Uploading a file with a different name but identical content should be + detected as duplicate content via ``content_hash``. + """ + + async def test_same_content_different_name_detected( + self, + client: httpx.AsyncClient, + headers: dict[str, str], + search_space_id: int, + cleanup_doc_ids: list[int], + tmp_path: Path, + ): + resp1 = await upload_file( + client, headers, "sample.txt", search_space_id=search_space_id + ) + assert resp1.status_code == 200 + first_ids = resp1.json()["document_ids"] + cleanup_doc_ids.extend(first_ids) + await poll_document_status( + client, headers, first_ids, search_space_id=search_space_id + ) + + src = FIXTURES_DIR / "sample.txt" + dest = tmp_path / "renamed_sample.txt" + shutil.copy2(src, dest) + + with open(dest, "rb") as f: + resp2 = await client.post( + "/api/v1/documents/fileupload", + headers=headers, + files={"files": ("renamed_sample.txt", f)}, + data={"search_space_id": str(search_space_id)}, + ) + assert resp2.status_code == 200 + second_ids = resp2.json()["document_ids"] + cleanup_doc_ids.extend(second_ids) + assert second_ids, ( + "Expected at least one document id for renamed duplicate content upload" + ) + + statuses = await poll_document_status( + client, headers, second_ids, search_space_id=search_space_id + ) + for did in second_ids: + assert statuses[did]["status"]["state"] == "failed" + assert "duplicate" in statuses[did]["status"].get("reason", "").lower() + + +# --------------------------------------------------------------------------- +# Test G: Empty / corrupt file handling +# --------------------------------------------------------------------------- + + +class TestEmptyFileUpload: + """An empty file should be processed but ultimately fail gracefully.""" + + async def test_empty_pdf_fails( + self, + client: httpx.AsyncClient, + headers: dict[str, str], + search_space_id: int, + cleanup_doc_ids: list[int], + ): + resp = await upload_file( + client, headers, "empty.pdf", search_space_id=search_space_id + ) + assert resp.status_code == 200 + + doc_ids = resp.json()["document_ids"] + cleanup_doc_ids.extend(doc_ids) + assert doc_ids, "Expected at least one document id for empty PDF upload" + + statuses = await poll_document_status( + client, headers, doc_ids, search_space_id=search_space_id, timeout=120.0 + ) + for did in doc_ids: + assert statuses[did]["status"]["state"] == "failed" + assert statuses[did]["status"].get("reason"), ( + "Failed document should include a reason" + ) + + +# --------------------------------------------------------------------------- +# Test H: Upload without authentication +# --------------------------------------------------------------------------- + + +class TestUnauthenticatedUpload: + """Requests without a valid JWT should be rejected.""" + + async def test_upload_without_auth_returns_401( + self, + client: httpx.AsyncClient, + search_space_id: int, + ): + file_path = FIXTURES_DIR / "sample.txt" + with open(file_path, "rb") as f: + resp = await client.post( + "/api/v1/documents/fileupload", + files={"files": ("sample.txt", f)}, + data={"search_space_id": str(search_space_id)}, + ) + assert resp.status_code == 401 + + +# --------------------------------------------------------------------------- +# Test I: Upload with no files attached +# --------------------------------------------------------------------------- + + +class TestNoFilesUpload: + """Submitting the form with zero files should return a validation error.""" + + async def test_no_files_returns_error( + self, + client: httpx.AsyncClient, + headers: dict[str, str], + search_space_id: int, + ): + resp = await client.post( + "/api/v1/documents/fileupload", + headers=headers, + data={"search_space_id": str(search_space_id)}, + ) + assert resp.status_code in {400, 422} + + +# --------------------------------------------------------------------------- +# Test K: Searchability after upload +# --------------------------------------------------------------------------- + + +class TestDocumentSearchability: + """After upload reaches ready, the document must appear in the title search.""" + + async def test_uploaded_document_appears_in_search( + self, + client: httpx.AsyncClient, + headers: dict[str, str], + search_space_id: int, + cleanup_doc_ids: list[int], + ): + resp = await upload_file( + client, headers, "sample.txt", search_space_id=search_space_id + ) + assert resp.status_code == 200 + doc_ids = resp.json()["document_ids"] + cleanup_doc_ids.extend(doc_ids) + + await poll_document_status( + client, headers, doc_ids, search_space_id=search_space_id + ) + + search_resp = await client.get( + "/api/v1/documents/search", + headers=headers, + params={"title": "sample", "search_space_id": search_space_id}, + ) + assert search_resp.status_code == 200 + + result_ids = [d["id"] for d in search_resp.json()["items"]] + assert doc_ids[0] in result_ids, ( + f"Uploaded document {doc_ids[0]} not found in search results: {result_ids}" + ) diff --git a/surfsense_backend/tests/integration/document_upload/test_page_limits.py b/surfsense_backend/tests/integration/document_upload/test_page_limits.py new file mode 100644 index 000000000..985fd7128 --- /dev/null +++ b/surfsense_backend/tests/integration/document_upload/test_page_limits.py @@ -0,0 +1,332 @@ +""" +Integration tests for page-limit enforcement during document upload. + +These tests manipulate the test user's ``pages_used`` / ``pages_limit`` +columns directly in the database (setup only) and then exercise the upload +pipeline to verify that: + + - Uploads are rejected *before* ETL when the limit is exhausted. + - ``pages_used`` increases after a successful upload (verified via API). + - A ``page_limit_exceeded`` notification is created on rejection. + - ``pages_used`` is not modified when a document fails processing. + +All tests reuse the existing small fixtures (``sample.pdf``, ``sample.txt``) +so no additional processing time is introduced. + +Prerequisites: + - PostgreSQL + pgvector +""" + +from __future__ import annotations + +import httpx +import pytest + +from tests.utils.helpers import ( + get_notifications, + poll_document_status, + upload_file, +) + +pytestmark = pytest.mark.integration + + +# --------------------------------------------------------------------------- +# Helper: read pages_used through the public API +# --------------------------------------------------------------------------- + + +async def _get_pages_used(client: httpx.AsyncClient, headers: dict[str, str]) -> int: + """Fetch the current user's pages_used via the /users/me API.""" + resp = await client.get("/users/me", headers=headers) + assert resp.status_code == 200, ( + f"GET /users/me failed ({resp.status_code}): {resp.text}" + ) + return resp.json()["pages_used"] + + +# --------------------------------------------------------------------------- +# Test A: Successful upload increments pages_used +# --------------------------------------------------------------------------- + + +class TestPageUsageIncrementsOnSuccess: + """After a successful PDF upload the user's ``pages_used`` must grow.""" + + async def test_pages_used_increases_after_pdf_upload( + self, + client: httpx.AsyncClient, + headers: dict[str, str], + search_space_id: int, + cleanup_doc_ids: list[int], + page_limits, + ): + await page_limits.set(pages_used=0, pages_limit=1000) + + resp = await upload_file( + client, headers, "sample.pdf", search_space_id=search_space_id + ) + assert resp.status_code == 200 + doc_ids = resp.json()["document_ids"] + cleanup_doc_ids.extend(doc_ids) + + statuses = await poll_document_status( + client, headers, doc_ids, search_space_id=search_space_id, timeout=300.0 + ) + for did in doc_ids: + assert statuses[did]["status"]["state"] == "ready" + + used = await _get_pages_used(client, headers) + assert used > 0, "pages_used should have increased after successful processing" + + +# --------------------------------------------------------------------------- +# Test B: Upload rejected when page limit is fully exhausted +# --------------------------------------------------------------------------- + + +class TestUploadRejectedWhenLimitExhausted: + """ + When ``pages_used == pages_limit`` (zero remaining) the document + should reach ``failed`` status with a page-limit reason. + """ + + async def test_pdf_fails_when_no_pages_remaining( + self, + client: httpx.AsyncClient, + headers: dict[str, str], + search_space_id: int, + cleanup_doc_ids: list[int], + page_limits, + ): + await page_limits.set(pages_used=100, pages_limit=100) + + resp = await upload_file( + client, headers, "sample.pdf", search_space_id=search_space_id + ) + assert resp.status_code == 200 + doc_ids = resp.json()["document_ids"] + cleanup_doc_ids.extend(doc_ids) + + statuses = await poll_document_status( + client, headers, doc_ids, search_space_id=search_space_id, timeout=300.0 + ) + for did in doc_ids: + assert statuses[did]["status"]["state"] == "failed" + reason = statuses[did]["status"].get("reason", "").lower() + assert "page limit" in reason, ( + f"Expected 'page limit' in failure reason, got: {reason!r}" + ) + + async def test_pages_used_unchanged_after_limit_rejection( + self, + client: httpx.AsyncClient, + headers: dict[str, str], + search_space_id: int, + cleanup_doc_ids: list[int], + page_limits, + ): + await page_limits.set(pages_used=50, pages_limit=50) + + resp = await upload_file( + client, headers, "sample.pdf", search_space_id=search_space_id + ) + assert resp.status_code == 200 + doc_ids = resp.json()["document_ids"] + cleanup_doc_ids.extend(doc_ids) + + await poll_document_status( + client, headers, doc_ids, search_space_id=search_space_id, timeout=300.0 + ) + + used = await _get_pages_used(client, headers) + assert used == 50, ( + f"pages_used should remain 50 after rejected upload, got {used}" + ) + + +# --------------------------------------------------------------------------- +# Test C: Page-limit notification is created on rejection +# --------------------------------------------------------------------------- + + +class TestPageLimitNotification: + """A ``page_limit_exceeded`` notification must be created when upload + is rejected due to the limit.""" + + async def test_page_limit_exceeded_notification_created( + self, + client: httpx.AsyncClient, + headers: dict[str, str], + search_space_id: int, + cleanup_doc_ids: list[int], + page_limits, + ): + await page_limits.set(pages_used=100, pages_limit=100) + + resp = await upload_file( + client, headers, "sample.pdf", search_space_id=search_space_id + ) + assert resp.status_code == 200 + doc_ids = resp.json()["document_ids"] + cleanup_doc_ids.extend(doc_ids) + + await poll_document_status( + client, headers, doc_ids, search_space_id=search_space_id, timeout=300.0 + ) + + notifications = await get_notifications( + client, + headers, + type_filter="page_limit_exceeded", + search_space_id=search_space_id, + ) + assert len(notifications) >= 1, ( + "Expected at least one page_limit_exceeded notification" + ) + + latest = notifications[0] + assert ( + "page limit" in latest["title"].lower() + or "page limit" in latest["message"].lower() + ), ( + f"Notification should mention page limit: title={latest['title']!r}, " + f"message={latest['message']!r}" + ) + + +# --------------------------------------------------------------------------- +# Test D: Successful upload creates a completed document_processing notification +# --------------------------------------------------------------------------- + + +class TestDocumentProcessingNotification: + """A ``document_processing`` notification with ``completed`` status must + exist after a successful upload.""" + + async def test_processing_completed_notification_exists( + self, + client: httpx.AsyncClient, + headers: dict[str, str], + search_space_id: int, + cleanup_doc_ids: list[int], + page_limits, + ): + await page_limits.set(pages_used=0, pages_limit=1000) + + resp = await upload_file( + client, headers, "sample.txt", search_space_id=search_space_id + ) + assert resp.status_code == 200 + doc_ids = resp.json()["document_ids"] + cleanup_doc_ids.extend(doc_ids) + + await poll_document_status( + client, headers, doc_ids, search_space_id=search_space_id + ) + + notifications = await get_notifications( + client, + headers, + type_filter="document_processing", + search_space_id=search_space_id, + ) + completed = [ + n + for n in notifications + if n.get("metadata", {}).get("processing_stage") == "completed" + ] + assert len(completed) >= 1, ( + "Expected at least one document_processing notification with 'completed' stage" + ) + + +# --------------------------------------------------------------------------- +# Test E: pages_used unchanged when a document fails for non-limit reasons +# --------------------------------------------------------------------------- + + +class TestPagesUnchangedOnProcessingFailure: + """If a document fails during ETL (e.g. empty/corrupt file) rather than + a page-limit rejection, ``pages_used`` should remain unchanged.""" + + async def test_pages_used_stable_on_etl_failure( + self, + client: httpx.AsyncClient, + headers: dict[str, str], + search_space_id: int, + cleanup_doc_ids: list[int], + page_limits, + ): + await page_limits.set(pages_used=10, pages_limit=1000) + + resp = await upload_file( + client, headers, "empty.pdf", search_space_id=search_space_id + ) + assert resp.status_code == 200 + doc_ids = resp.json()["document_ids"] + cleanup_doc_ids.extend(doc_ids) + + if doc_ids: + statuses = await poll_document_status( + client, headers, doc_ids, search_space_id=search_space_id, timeout=120.0 + ) + for did in doc_ids: + assert statuses[did]["status"]["state"] == "failed" + + used = await _get_pages_used(client, headers) + assert used == 10, f"pages_used should remain 10 after ETL failure, got {used}" + + +# --------------------------------------------------------------------------- +# Test F: Second upload rejected after first consumes remaining quota +# --------------------------------------------------------------------------- + + +class TestSecondUploadExceedsLimit: + """Upload one PDF successfully, consuming the quota, then verify a + second upload is rejected.""" + + async def test_second_upload_rejected_after_quota_consumed( + self, + client: httpx.AsyncClient, + headers: dict[str, str], + search_space_id: int, + cleanup_doc_ids: list[int], + page_limits, + ): + await page_limits.set(pages_used=0, pages_limit=1) + + resp1 = await upload_file( + client, headers, "sample.pdf", search_space_id=search_space_id + ) + assert resp1.status_code == 200 + first_ids = resp1.json()["document_ids"] + cleanup_doc_ids.extend(first_ids) + + statuses1 = await poll_document_status( + client, headers, first_ids, search_space_id=search_space_id, timeout=300.0 + ) + for did in first_ids: + assert statuses1[did]["status"]["state"] == "ready" + + resp2 = await upload_file( + client, + headers, + "sample.pdf", + search_space_id=search_space_id, + filename_override="sample_copy.pdf", + ) + assert resp2.status_code == 200 + second_ids = resp2.json()["document_ids"] + cleanup_doc_ids.extend(second_ids) + + statuses2 = await poll_document_status( + client, headers, second_ids, search_space_id=search_space_id, timeout=300.0 + ) + for did in second_ids: + assert statuses2[did]["status"]["state"] == "failed" + reason = statuses2[did]["status"].get("reason", "").lower() + assert "page limit" in reason, ( + f"Expected 'page limit' in failure reason, got: {reason!r}" + ) diff --git a/surfsense_backend/tests/integration/document_upload/test_upload_limits.py b/surfsense_backend/tests/integration/document_upload/test_upload_limits.py new file mode 100644 index 000000000..a8dab43f0 --- /dev/null +++ b/surfsense_backend/tests/integration/document_upload/test_upload_limits.py @@ -0,0 +1,145 @@ +""" +Integration tests for backend file upload limit enforcement. + +These tests verify that the API rejects uploads that exceed: + - Max files per upload (10) + - Max per-file size (50 MB) + - Max total upload size (200 MB) + +The limits mirror the frontend's DocumentUploadTab.tsx constants and are +enforced server-side to protect against direct API calls. + +Prerequisites: + - PostgreSQL + pgvector +""" + +from __future__ import annotations + +import io + +import httpx +import pytest + +pytestmark = pytest.mark.integration + + +# --------------------------------------------------------------------------- +# Test A: File count limit +# --------------------------------------------------------------------------- + + +class TestFileCountLimit: + """Uploading more than 10 files in a single request should be rejected.""" + + async def test_11_files_returns_413( + self, + client: httpx.AsyncClient, + headers: dict[str, str], + search_space_id: int, + ): + files = [ + ("files", (f"file_{i}.txt", io.BytesIO(b"test content"), "text/plain")) + for i in range(11) + ] + resp = await client.post( + "/api/v1/documents/fileupload", + headers=headers, + files=files, + data={"search_space_id": str(search_space_id)}, + ) + assert resp.status_code == 413 + assert "too many files" in resp.json()["detail"].lower() + + async def test_10_files_accepted( + self, + client: httpx.AsyncClient, + headers: dict[str, str], + search_space_id: int, + cleanup_doc_ids: list[int], + ): + files = [ + ("files", (f"file_{i}.txt", io.BytesIO(b"test content"), "text/plain")) + for i in range(10) + ] + resp = await client.post( + "/api/v1/documents/fileupload", + headers=headers, + files=files, + data={"search_space_id": str(search_space_id)}, + ) + assert resp.status_code == 200 + cleanup_doc_ids.extend(resp.json().get("document_ids", [])) + + +# --------------------------------------------------------------------------- +# Test B: Per-file size limit +# --------------------------------------------------------------------------- + + +class TestPerFileSizeLimit: + """A single file exceeding 50 MB should be rejected.""" + + async def test_oversized_file_returns_413( + self, + client: httpx.AsyncClient, + headers: dict[str, str], + search_space_id: int, + ): + oversized = io.BytesIO(b"\x00" * (50 * 1024 * 1024 + 1)) + resp = await client.post( + "/api/v1/documents/fileupload", + headers=headers, + files=[("files", ("big.pdf", oversized, "application/pdf"))], + data={"search_space_id": str(search_space_id)}, + ) + assert resp.status_code == 413 + assert "per-file limit" in resp.json()["detail"].lower() + + async def test_file_at_limit_accepted( + self, + client: httpx.AsyncClient, + headers: dict[str, str], + search_space_id: int, + cleanup_doc_ids: list[int], + ): + at_limit = io.BytesIO(b"\x00" * (50 * 1024 * 1024)) + resp = await client.post( + "/api/v1/documents/fileupload", + headers=headers, + files=[("files", ("exact50mb.txt", at_limit, "text/plain"))], + data={"search_space_id": str(search_space_id)}, + ) + assert resp.status_code == 200 + cleanup_doc_ids.extend(resp.json().get("document_ids", [])) + + +# --------------------------------------------------------------------------- +# Test C: Total upload size limit +# --------------------------------------------------------------------------- + + +class TestTotalSizeLimit: + """Multiple files whose combined size exceeds 200 MB should be rejected.""" + + async def test_total_size_over_200mb_returns_413( + self, + client: httpx.AsyncClient, + headers: dict[str, str], + search_space_id: int, + ): + chunk_size = 45 * 1024 * 1024 # 45 MB each + files = [ + ( + "files", + (f"chunk_{i}.txt", io.BytesIO(b"\x00" * chunk_size), "text/plain"), + ) + for i in range(5) # 5 x 45 MB = 225 MB > 200 MB + ] + resp = await client.post( + "/api/v1/documents/fileupload", + headers=headers, + files=files, + data={"search_space_id": str(search_space_id)}, + ) + assert resp.status_code == 413 + assert "total upload size" in resp.json()["detail"].lower() diff --git a/surfsense_backend/tests/integration/indexing_pipeline/__init__.py b/surfsense_backend/tests/integration/indexing_pipeline/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/surfsense_backend/tests/integration/indexing_pipeline/adapters/__init__.py b/surfsense_backend/tests/integration/indexing_pipeline/adapters/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/surfsense_backend/tests/integration/indexing_pipeline/adapters/test_file_upload_adapter.py b/surfsense_backend/tests/integration/indexing_pipeline/adapters/test_file_upload_adapter.py new file mode 100644 index 000000000..fa0fe5787 --- /dev/null +++ b/surfsense_backend/tests/integration/indexing_pipeline/adapters/test_file_upload_adapter.py @@ -0,0 +1,326 @@ +import pytest +from sqlalchemy import select + +from app.db import Chunk, Document, DocumentStatus +from app.indexing_pipeline.adapters.file_upload_adapter import UploadDocumentAdapter + +pytestmark = pytest.mark.integration + + +@pytest.mark.usefixtures( + "patched_summarize", "patched_embed_text", "patched_chunk_text" +) +async def test_sets_status_ready(db_session, db_search_space, db_user, mocker): + """Document status is READY after successful indexing.""" + adapter = UploadDocumentAdapter(db_session) + await adapter.index( + markdown_content="## Hello\n\nSome content.", + filename="test.pdf", + etl_service="UNSTRUCTURED", + search_space_id=db_search_space.id, + user_id=str(db_user.id), + llm=mocker.Mock(), + ) + + result = await db_session.execute( + select(Document).filter(Document.search_space_id == db_search_space.id) + ) + document = result.scalars().first() + + assert DocumentStatus.is_state(document.status, DocumentStatus.READY) + + +@pytest.mark.usefixtures( + "patched_summarize", "patched_embed_text", "patched_chunk_text" +) +async def test_content_is_summary(db_session, db_search_space, db_user, mocker): + """Document content is set to the LLM-generated summary.""" + adapter = UploadDocumentAdapter(db_session) + await adapter.index( + markdown_content="## Hello\n\nSome content.", + filename="test.pdf", + etl_service="UNSTRUCTURED", + search_space_id=db_search_space.id, + user_id=str(db_user.id), + llm=mocker.Mock(), + should_summarize=True, + ) + + result = await db_session.execute( + select(Document).filter(Document.search_space_id == db_search_space.id) + ) + document = result.scalars().first() + + assert document.content == "Mocked summary." + + +@pytest.mark.usefixtures( + "patched_summarize", "patched_embed_text", "patched_chunk_text" +) +async def test_chunks_written_to_db(db_session, db_search_space, db_user, mocker): + """Chunks derived from the source markdown are persisted in the DB.""" + adapter = UploadDocumentAdapter(db_session) + await adapter.index( + markdown_content="## Hello\n\nSome content.", + filename="test.pdf", + etl_service="UNSTRUCTURED", + search_space_id=db_search_space.id, + user_id=str(db_user.id), + llm=mocker.Mock(), + ) + + result = await db_session.execute( + select(Document).filter(Document.search_space_id == db_search_space.id) + ) + document = result.scalars().first() + + chunks_result = await db_session.execute( + select(Chunk).filter(Chunk.document_id == document.id) + ) + chunks = chunks_result.scalars().all() + + assert len(chunks) == 1 + assert chunks[0].content == "Test chunk content." + + +@pytest.mark.usefixtures( + "patched_summarize_raises", "patched_embed_text", "patched_chunk_text" +) +async def test_raises_on_indexing_failure(db_session, db_search_space, db_user, mocker): + """RuntimeError is raised when the indexing step fails so the caller can fire a failure notification.""" + adapter = UploadDocumentAdapter(db_session) + with pytest.raises(RuntimeError, match=r"Embedding failed|Indexing failed"): + await adapter.index( + markdown_content="## Hello\n\nSome content.", + filename="test.pdf", + etl_service="UNSTRUCTURED", + search_space_id=db_search_space.id, + user_id=str(db_user.id), + llm=mocker.Mock(), + should_summarize=True, + ) + + +# --------------------------------------------------------------------------- +# reindex() tests +# --------------------------------------------------------------------------- + + +@pytest.mark.usefixtures( + "patched_summarize", "patched_embed_text", "patched_chunk_text" +) +async def test_reindex_updates_content(db_session, db_search_space, db_user, mocker): + """Document content is updated to the new summary after reindexing.""" + adapter = UploadDocumentAdapter(db_session) + await adapter.index( + markdown_content="## Original\n\nOriginal content.", + filename="test.pdf", + etl_service="UNSTRUCTURED", + search_space_id=db_search_space.id, + user_id=str(db_user.id), + llm=mocker.Mock(), + ) + + result = await db_session.execute( + select(Document).filter(Document.search_space_id == db_search_space.id) + ) + document = result.scalars().first() + + document.source_markdown = "## Edited\n\nNew content after user edit." + await db_session.flush() + + await adapter.reindex(document=document, llm=mocker.Mock()) + + await db_session.refresh(document) + assert document.content == "Mocked summary." + + +@pytest.mark.usefixtures( + "patched_summarize", "patched_embed_text", "patched_chunk_text" +) +async def test_reindex_updates_content_hash( + db_session, db_search_space, db_user, mocker +): + """Content hash is recomputed after reindexing with new source markdown.""" + adapter = UploadDocumentAdapter(db_session) + await adapter.index( + markdown_content="## Original\n\nOriginal content.", + filename="test.pdf", + etl_service="UNSTRUCTURED", + search_space_id=db_search_space.id, + user_id=str(db_user.id), + llm=mocker.Mock(), + ) + + result = await db_session.execute( + select(Document).filter(Document.search_space_id == db_search_space.id) + ) + document = result.scalars().first() + original_hash = document.content_hash + + document.source_markdown = "## Edited\n\nNew content after user edit." + await db_session.flush() + + await adapter.reindex(document=document, llm=mocker.Mock()) + + await db_session.refresh(document) + assert document.content_hash != original_hash + + +@pytest.mark.usefixtures( + "patched_summarize", "patched_embed_text", "patched_chunk_text" +) +async def test_reindex_sets_status_ready(db_session, db_search_space, db_user, mocker): + """Document status is READY after successful reindexing.""" + adapter = UploadDocumentAdapter(db_session) + await adapter.index( + markdown_content="## Original\n\nOriginal content.", + filename="test.pdf", + etl_service="UNSTRUCTURED", + search_space_id=db_search_space.id, + user_id=str(db_user.id), + llm=mocker.Mock(), + ) + + result = await db_session.execute( + select(Document).filter(Document.search_space_id == db_search_space.id) + ) + document = result.scalars().first() + + document.source_markdown = "## Edited\n\nNew content after user edit." + await db_session.flush() + + await adapter.reindex(document=document, llm=mocker.Mock()) + + await db_session.refresh(document) + assert DocumentStatus.is_state(document.status, DocumentStatus.READY) + + +@pytest.mark.usefixtures("patched_summarize", "patched_embed_text") +async def test_reindex_replaces_chunks(db_session, db_search_space, db_user, mocker): + """Reindexing replaces old chunks with new content rather than appending.""" + mocker.patch( + "app.indexing_pipeline.indexing_pipeline_service.chunk_text", + side_effect=[["Original chunk."], ["Updated chunk."]], + ) + + adapter = UploadDocumentAdapter(db_session) + await adapter.index( + markdown_content="## Original\n\nOriginal content.", + filename="test.pdf", + etl_service="UNSTRUCTURED", + search_space_id=db_search_space.id, + user_id=str(db_user.id), + llm=mocker.Mock(), + ) + + result = await db_session.execute( + select(Document).filter(Document.search_space_id == db_search_space.id) + ) + document = result.scalars().first() + document_id = document.id + + document.source_markdown = "## Edited\n\nNew content after user edit." + await db_session.flush() + + await adapter.reindex(document=document, llm=mocker.Mock()) + + chunks_result = await db_session.execute( + select(Chunk).filter(Chunk.document_id == document_id) + ) + chunks = chunks_result.scalars().all() + + assert len(chunks) == 1 + assert chunks[0].content == "Updated chunk." + + +@pytest.mark.usefixtures( + "patched_summarize", "patched_embed_text", "patched_chunk_text" +) +async def test_reindex_clears_reindexing_flag( + db_session, db_search_space, db_user, mocker +): + """After successful reindex, content_needs_reindexing is False.""" + adapter = UploadDocumentAdapter(db_session) + await adapter.index( + markdown_content="## Original\n\nOriginal content.", + filename="test.pdf", + etl_service="UNSTRUCTURED", + search_space_id=db_search_space.id, + user_id=str(db_user.id), + llm=mocker.Mock(), + ) + + result = await db_session.execute( + select(Document).filter(Document.search_space_id == db_search_space.id) + ) + document = result.scalars().first() + + document.source_markdown = "## Edited\n\nNew content after user edit." + document.content_needs_reindexing = True + await db_session.flush() + + await adapter.reindex(document=document, llm=mocker.Mock()) + + await db_session.refresh(document) + assert document.content_needs_reindexing is False + + +@pytest.mark.usefixtures("patched_embed_text", "patched_chunk_text") +async def test_reindex_raises_on_failure(db_session, db_search_space, db_user, mocker): + """RuntimeError is raised when reindexing fails so the caller can handle it.""" + mocker.patch( + "app.indexing_pipeline.indexing_pipeline_service.summarize_document", + return_value="Mocked summary.", + ) + + adapter = UploadDocumentAdapter(db_session) + await adapter.index( + markdown_content="## Original\n\nOriginal content.", + filename="test.pdf", + etl_service="UNSTRUCTURED", + search_space_id=db_search_space.id, + user_id=str(db_user.id), + llm=mocker.Mock(), + ) + + result = await db_session.execute( + select(Document).filter(Document.search_space_id == db_search_space.id) + ) + document = result.scalars().first() + + document.source_markdown = "## Edited\n\nNew content after user edit." + await db_session.flush() + + mocker.patch( + "app.indexing_pipeline.indexing_pipeline_service.summarize_document", + side_effect=RuntimeError("LLM unavailable"), + ) + + with pytest.raises(RuntimeError, match=r"Embedding failed|Reindexing failed"): + await adapter.reindex(document=document, llm=mocker.Mock()) + + +async def test_reindex_raises_on_empty_source_markdown( + db_session, db_search_space, db_user, mocker +): + """Reindexing a document with no source_markdown raises immediately.""" + from app.db import DocumentType + + document = Document( + title="empty.pdf", + document_type=DocumentType.FILE, + content="placeholder", + content_hash="abc123", + unique_identifier_hash="def456", + source_markdown="", + search_space_id=db_search_space.id, + created_by_id=str(db_user.id), + ) + db_session.add(document) + await db_session.flush() + + adapter = UploadDocumentAdapter(db_session) + + with pytest.raises(RuntimeError, match="no source_markdown"): + await adapter.reindex(document=document, llm=mocker.Mock()) diff --git a/surfsense_backend/tests/integration/indexing_pipeline/test_index_document.py b/surfsense_backend/tests/integration/indexing_pipeline/test_index_document.py new file mode 100644 index 000000000..2e8ee4d92 --- /dev/null +++ b/surfsense_backend/tests/integration/indexing_pipeline/test_index_document.py @@ -0,0 +1,341 @@ +import pytest +from sqlalchemy import select + +from app.config import config as app_config +from app.db import Chunk, Document, DocumentStatus +from app.indexing_pipeline.indexing_pipeline_service import IndexingPipelineService + +_EMBEDDING_DIM = app_config.embedding_model_instance.dimension + +pytestmark = pytest.mark.integration + + +@pytest.mark.usefixtures( + "patched_summarize", "patched_embed_text", "patched_chunk_text" +) +async def test_sets_status_ready( + db_session, + db_search_space, + make_connector_document, + mocker, +): + """Document status is READY after successful indexing.""" + connector_doc = make_connector_document(search_space_id=db_search_space.id) + service = IndexingPipelineService(session=db_session) + + prepared = await service.prepare_for_indexing([connector_doc]) + document = prepared[0] + document_id = document.id + + await service.index(document, connector_doc, llm=mocker.Mock()) + + result = await db_session.execute( + select(Document).filter(Document.id == document_id) + ) + reloaded = result.scalars().first() + + assert DocumentStatus.is_state(reloaded.status, DocumentStatus.READY) + + +@pytest.mark.usefixtures( + "patched_summarize", "patched_embed_text", "patched_chunk_text" +) +async def test_content_is_summary_when_should_summarize_true( + db_session, + db_search_space, + make_connector_document, + mocker, +): + """Document content is set to the LLM-generated summary when should_summarize=True.""" + connector_doc = make_connector_document(search_space_id=db_search_space.id) + service = IndexingPipelineService(session=db_session) + + prepared = await service.prepare_for_indexing([connector_doc]) + document = prepared[0] + document_id = document.id + + await service.index(document, connector_doc, llm=mocker.Mock()) + + result = await db_session.execute( + select(Document).filter(Document.id == document_id) + ) + reloaded = result.scalars().first() + + assert reloaded.content == "Mocked summary." + + +@pytest.mark.usefixtures( + "patched_summarize", "patched_embed_text", "patched_chunk_text" +) +async def test_content_is_source_markdown_when_should_summarize_false( + db_session, + db_search_space, + make_connector_document, +): + """Document content is set to source_markdown verbatim when should_summarize=False.""" + connector_doc = make_connector_document( + search_space_id=db_search_space.id, + should_summarize=False, + source_markdown="## Raw content", + ) + service = IndexingPipelineService(session=db_session) + + prepared = await service.prepare_for_indexing([connector_doc]) + document = prepared[0] + document_id = document.id + + await service.index(document, connector_doc, llm=None) + + result = await db_session.execute( + select(Document).filter(Document.id == document_id) + ) + reloaded = result.scalars().first() + + assert reloaded.content == "## Raw content" + + +@pytest.mark.usefixtures( + "patched_summarize", "patched_embed_text", "patched_chunk_text" +) +async def test_chunks_written_to_db( + db_session, + db_search_space, + make_connector_document, + mocker, +): + """Chunks derived from source_markdown are persisted in the DB.""" + connector_doc = make_connector_document(search_space_id=db_search_space.id) + service = IndexingPipelineService(session=db_session) + + prepared = await service.prepare_for_indexing([connector_doc]) + document = prepared[0] + document_id = document.id + + await service.index(document, connector_doc, llm=mocker.Mock()) + + result = await db_session.execute( + select(Chunk).filter(Chunk.document_id == document_id) + ) + chunks = result.scalars().all() + + assert len(chunks) == 1 + assert chunks[0].content == "Test chunk content." + + +@pytest.mark.usefixtures( + "patched_summarize", "patched_embed_text", "patched_chunk_text" +) +async def test_embedding_written_to_db( + db_session, + db_search_space, + make_connector_document, + mocker, +): + """Document embedding vector is persisted in the DB after indexing.""" + connector_doc = make_connector_document(search_space_id=db_search_space.id) + service = IndexingPipelineService(session=db_session) + + prepared = await service.prepare_for_indexing([connector_doc]) + document = prepared[0] + document_id = document.id + + await service.index(document, connector_doc, llm=mocker.Mock()) + + result = await db_session.execute( + select(Document).filter(Document.id == document_id) + ) + reloaded = result.scalars().first() + + assert reloaded.embedding is not None + assert len(reloaded.embedding) == _EMBEDDING_DIM + + +@pytest.mark.usefixtures( + "patched_summarize", "patched_embed_text", "patched_chunk_text" +) +async def test_updated_at_advances_after_indexing( + db_session, + db_search_space, + make_connector_document, + mocker, +): + """updated_at timestamp is later after indexing than it was at prepare time.""" + connector_doc = make_connector_document(search_space_id=db_search_space.id) + service = IndexingPipelineService(session=db_session) + + prepared = await service.prepare_for_indexing([connector_doc]) + document = prepared[0] + document_id = document.id + + result = await db_session.execute( + select(Document).filter(Document.id == document_id) + ) + updated_at_pending = result.scalars().first().updated_at + + await service.index(document, connector_doc, llm=mocker.Mock()) + + result = await db_session.execute( + select(Document).filter(Document.id == document_id) + ) + updated_at_ready = result.scalars().first().updated_at + + assert updated_at_ready > updated_at_pending + + +@pytest.mark.usefixtures( + "patched_summarize", "patched_embed_text", "patched_chunk_text" +) +async def test_no_llm_falls_back_to_source_markdown( + db_session, + db_search_space, + make_connector_document, +): + """When llm=None and no fallback_summary, content falls back to source_markdown.""" + connector_doc = make_connector_document( + search_space_id=db_search_space.id, + should_summarize=True, + source_markdown="## Fallback content", + ) + service = IndexingPipelineService(session=db_session) + + prepared = await service.prepare_for_indexing([connector_doc]) + document = prepared[0] + document_id = document.id + + await service.index(document, connector_doc, llm=None) + + result = await db_session.execute( + select(Document).filter(Document.id == document_id) + ) + reloaded = result.scalars().first() + + assert DocumentStatus.is_state(reloaded.status, DocumentStatus.READY) + assert reloaded.content == "## Fallback content" + + +@pytest.mark.usefixtures( + "patched_summarize", "patched_embed_text", "patched_chunk_text" +) +async def test_fallback_summary_used_when_llm_unavailable( + db_session, + db_search_space, + make_connector_document, +): + """fallback_summary is used as content when llm=None and should_summarize=True.""" + connector_doc = make_connector_document( + search_space_id=db_search_space.id, + should_summarize=True, + source_markdown="## Full raw content", + fallback_summary="Short pre-built summary.", + ) + service = IndexingPipelineService(session=db_session) + + prepared = await service.prepare_for_indexing([connector_doc]) + document_id = prepared[0].id + + await service.index(prepared[0], connector_doc, llm=None) + + result = await db_session.execute( + select(Document).filter(Document.id == document_id) + ) + reloaded = result.scalars().first() + + assert DocumentStatus.is_state(reloaded.status, DocumentStatus.READY) + assert reloaded.content == "Short pre-built summary." + + +@pytest.mark.usefixtures( + "patched_summarize", "patched_embed_text", "patched_chunk_text" +) +async def test_reindex_replaces_old_chunks( + db_session, + db_search_space, + make_connector_document, + mocker, +): + """Re-indexing a document replaces its old chunks rather than appending.""" + connector_doc = make_connector_document( + search_space_id=db_search_space.id, + source_markdown="## v1", + ) + service = IndexingPipelineService(session=db_session) + + prepared = await service.prepare_for_indexing([connector_doc]) + document = prepared[0] + document_id = document.id + + await service.index(document, connector_doc, llm=mocker.Mock()) + + updated_doc = make_connector_document( + search_space_id=db_search_space.id, + source_markdown="## v2", + ) + re_prepared = await service.prepare_for_indexing([updated_doc]) + await service.index(re_prepared[0], updated_doc, llm=mocker.Mock()) + + result = await db_session.execute( + select(Chunk).filter(Chunk.document_id == document_id) + ) + chunks = result.scalars().all() + + assert len(chunks) == 1 + + +@pytest.mark.usefixtures( + "patched_summarize_raises", "patched_embed_text", "patched_chunk_text" +) +async def test_llm_error_sets_status_failed( + db_session, + db_search_space, + make_connector_document, + mocker, +): + """Document status is FAILED when the LLM raises during indexing.""" + connector_doc = make_connector_document(search_space_id=db_search_space.id) + service = IndexingPipelineService(session=db_session) + + prepared = await service.prepare_for_indexing([connector_doc]) + document = prepared[0] + document_id = document.id + + await service.index(document, connector_doc, llm=mocker.Mock()) + + result = await db_session.execute( + select(Document).filter(Document.id == document_id) + ) + reloaded = result.scalars().first() + + assert DocumentStatus.is_state(reloaded.status, DocumentStatus.FAILED) + + +@pytest.mark.usefixtures( + "patched_summarize_raises", "patched_embed_text", "patched_chunk_text" +) +async def test_llm_error_leaves_no_partial_data( + db_session, + db_search_space, + make_connector_document, + mocker, +): + """A failed indexing attempt leaves no partial embedding or chunks in the DB.""" + connector_doc = make_connector_document(search_space_id=db_search_space.id) + service = IndexingPipelineService(session=db_session) + + prepared = await service.prepare_for_indexing([connector_doc]) + document = prepared[0] + document_id = document.id + + await service.index(document, connector_doc, llm=mocker.Mock()) + + result = await db_session.execute( + select(Document).filter(Document.id == document_id) + ) + reloaded = result.scalars().first() + + assert reloaded.embedding is None + assert reloaded.content == "Pending..." + + chunks_result = await db_session.execute( + select(Chunk).filter(Chunk.document_id == document_id) + ) + assert chunks_result.scalars().all() == [] diff --git a/surfsense_backend/tests/integration/indexing_pipeline/test_prepare_for_indexing.py b/surfsense_backend/tests/integration/indexing_pipeline/test_prepare_for_indexing.py new file mode 100644 index 000000000..837b02c9f --- /dev/null +++ b/surfsense_backend/tests/integration/indexing_pipeline/test_prepare_for_indexing.py @@ -0,0 +1,459 @@ +import pytest +from sqlalchemy import select + +from app.db import Document, DocumentStatus +from app.indexing_pipeline.document_hashing import ( + compute_content_hash as real_compute_content_hash, +) +from app.indexing_pipeline.indexing_pipeline_service import IndexingPipelineService + +pytestmark = pytest.mark.integration + + +async def test_new_document_is_persisted_with_pending_status( + db_session, db_search_space, make_connector_document +): + """A new document is created in the DB with PENDING status and correct markdown.""" + doc = make_connector_document(search_space_id=db_search_space.id) + service = IndexingPipelineService(session=db_session) + + results = await service.prepare_for_indexing([doc]) + + assert len(results) == 1 + document_id = results[0].id + + result = await db_session.execute( + select(Document).filter(Document.id == document_id) + ) + reloaded = result.scalars().first() + + assert reloaded is not None + assert DocumentStatus.is_state(reloaded.status, DocumentStatus.PENDING) + assert reloaded.source_markdown == doc.source_markdown + + +@pytest.mark.usefixtures( + "patched_summarize", "patched_embed_text", "patched_chunk_text" +) +async def test_unchanged_ready_document_is_skipped( + db_session, + db_search_space, + make_connector_document, + mocker, +): + """A READY document with unchanged content is not returned for re-indexing.""" + doc = make_connector_document(search_space_id=db_search_space.id) + service = IndexingPipelineService(session=db_session) + + # Index fully so the document reaches ready state + prepared = await service.prepare_for_indexing([doc]) + await service.index(prepared[0], doc, llm=mocker.Mock()) + + # Same content on the next run — a ready document must be skipped + results = await service.prepare_for_indexing([doc]) + + assert results == [] + + +@pytest.mark.usefixtures( + "patched_summarize", "patched_embed_text", "patched_chunk_text" +) +async def test_title_only_change_updates_title_in_db( + db_session, + db_search_space, + make_connector_document, + mocker, +): + """A title-only change updates the DB title without re-queuing the document.""" + original = make_connector_document( + search_space_id=db_search_space.id, title="Original Title" + ) + service = IndexingPipelineService(session=db_session) + + prepared = await service.prepare_for_indexing([original]) + document_id = prepared[0].id + await service.index(prepared[0], original, llm=mocker.Mock()) + + renamed = make_connector_document( + search_space_id=db_search_space.id, title="Updated Title" + ) + results = await service.prepare_for_indexing([renamed]) + + assert results == [] + + result = await db_session.execute( + select(Document).filter(Document.id == document_id) + ) + reloaded = result.scalars().first() + + assert reloaded.title == "Updated Title" + + +async def test_changed_content_is_returned_for_reprocessing( + db_session, db_search_space, make_connector_document +): + """A document with changed content is returned for re-indexing with updated markdown.""" + original = make_connector_document( + search_space_id=db_search_space.id, source_markdown="## v1" + ) + service = IndexingPipelineService(session=db_session) + + first = await service.prepare_for_indexing([original]) + original_id = first[0].id + + updated = make_connector_document( + search_space_id=db_search_space.id, source_markdown="## v2" + ) + results = await service.prepare_for_indexing([updated]) + + assert len(results) == 1 + assert results[0].id == original_id + + result = await db_session.execute( + select(Document).filter(Document.id == original_id) + ) + reloaded = result.scalars().first() + + assert reloaded.source_markdown == "## v2" + assert DocumentStatus.is_state(reloaded.status, DocumentStatus.PENDING) + + +async def test_all_documents_in_batch_are_persisted( + db_session, db_search_space, make_connector_document +): + """All documents in a batch are persisted and returned.""" + docs = [ + make_connector_document( + search_space_id=db_search_space.id, + unique_id="id-1", + title="Doc 1", + source_markdown="## Content 1", + ), + make_connector_document( + search_space_id=db_search_space.id, + unique_id="id-2", + title="Doc 2", + source_markdown="## Content 2", + ), + make_connector_document( + search_space_id=db_search_space.id, + unique_id="id-3", + title="Doc 3", + source_markdown="## Content 3", + ), + ] + service = IndexingPipelineService(session=db_session) + + results = await service.prepare_for_indexing(docs) + + assert len(results) == 3 + + result = await db_session.execute( + select(Document).filter(Document.search_space_id == db_search_space.id) + ) + rows = result.scalars().all() + + assert len(rows) == 3 + + +async def test_duplicate_in_batch_is_persisted_once( + db_session, db_search_space, make_connector_document +): + """The same document passed twice in a batch is only persisted once.""" + doc = make_connector_document(search_space_id=db_search_space.id) + service = IndexingPipelineService(session=db_session) + + results = await service.prepare_for_indexing([doc, doc]) + + assert len(results) == 1 + + result = await db_session.execute( + select(Document).filter(Document.search_space_id == db_search_space.id) + ) + rows = result.scalars().all() + + assert len(rows) == 1 + + +async def test_created_by_id_is_persisted( + db_session, db_user, db_search_space, make_connector_document +): + """created_by_id from the connector document is persisted on the DB row.""" + doc = make_connector_document( + search_space_id=db_search_space.id, + created_by_id=str(db_user.id), + ) + service = IndexingPipelineService(session=db_session) + + results = await service.prepare_for_indexing([doc]) + document_id = results[0].id + + result = await db_session.execute( + select(Document).filter(Document.id == document_id) + ) + reloaded = result.scalars().first() + + assert str(reloaded.created_by_id) == str(db_user.id) + + +async def test_metadata_is_updated_when_content_changes( + db_session, db_search_space, make_connector_document +): + """document_metadata is overwritten with the latest metadata when content changes.""" + original = make_connector_document( + search_space_id=db_search_space.id, + source_markdown="## v1", + metadata={"status": "in_progress"}, + ) + service = IndexingPipelineService(session=db_session) + + first = await service.prepare_for_indexing([original]) + document_id = first[0].id + + updated = make_connector_document( + search_space_id=db_search_space.id, + source_markdown="## v2", + metadata={"status": "done"}, + ) + await service.prepare_for_indexing([updated]) + + result = await db_session.execute( + select(Document).filter(Document.id == document_id) + ) + reloaded = result.scalars().first() + + assert reloaded.document_metadata == {"status": "done"} + + +async def test_updated_at_advances_when_title_only_changes( + db_session, db_search_space, make_connector_document +): + """updated_at advances even when only the title changes.""" + original = make_connector_document( + search_space_id=db_search_space.id, title="Old Title" + ) + service = IndexingPipelineService(session=db_session) + + first = await service.prepare_for_indexing([original]) + document_id = first[0].id + + result = await db_session.execute( + select(Document).filter(Document.id == document_id) + ) + updated_at_v1 = result.scalars().first().updated_at + + renamed = make_connector_document( + search_space_id=db_search_space.id, title="New Title" + ) + await service.prepare_for_indexing([renamed]) + + result = await db_session.execute( + select(Document).filter(Document.id == document_id) + ) + updated_at_v2 = result.scalars().first().updated_at + + assert updated_at_v2 > updated_at_v1 + + +async def test_updated_at_advances_when_content_changes( + db_session, db_search_space, make_connector_document +): + """updated_at advances when document content changes.""" + original = make_connector_document( + search_space_id=db_search_space.id, source_markdown="## v1" + ) + service = IndexingPipelineService(session=db_session) + + first = await service.prepare_for_indexing([original]) + document_id = first[0].id + + result = await db_session.execute( + select(Document).filter(Document.id == document_id) + ) + updated_at_v1 = result.scalars().first().updated_at + + updated = make_connector_document( + search_space_id=db_search_space.id, source_markdown="## v2" + ) + await service.prepare_for_indexing([updated]) + + result = await db_session.execute( + select(Document).filter(Document.id == document_id) + ) + updated_at_v2 = result.scalars().first().updated_at + + assert updated_at_v2 > updated_at_v1 + + +async def test_same_content_from_different_source_skipped_in_single_batch( + db_session, db_search_space, make_connector_document +): + """Two documents with identical content in the same batch result in only one being persisted.""" + first = make_connector_document( + search_space_id=db_search_space.id, + unique_id="source-a", + source_markdown="## Shared content", + ) + second = make_connector_document( + search_space_id=db_search_space.id, + unique_id="source-b", + source_markdown="## Shared content", + ) + service = IndexingPipelineService(session=db_session) + + results = await service.prepare_for_indexing([first, second]) + + assert len(results) == 1 + + result = await db_session.execute( + select(Document).filter(Document.search_space_id == db_search_space.id) + ) + assert len(result.scalars().all()) == 1 + + +async def test_same_content_from_different_source_is_skipped( + db_session, db_search_space, make_connector_document +): + """A document with content identical to an already-indexed document is skipped.""" + first = make_connector_document( + search_space_id=db_search_space.id, + unique_id="source-a", + source_markdown="## Shared content", + ) + second = make_connector_document( + search_space_id=db_search_space.id, + unique_id="source-b", + source_markdown="## Shared content", + ) + service = IndexingPipelineService(session=db_session) + + await service.prepare_for_indexing([first]) + results = await service.prepare_for_indexing([second]) + + assert results == [] + + result = await db_session.execute( + select(Document).filter(Document.search_space_id == db_search_space.id) + ) + assert len(result.scalars().all()) == 1 + + +@pytest.mark.usefixtures( + "patched_summarize_raises", "patched_embed_text", "patched_chunk_text" +) +async def test_failed_document_with_unchanged_content_is_requeued( + db_session, + db_search_space, + make_connector_document, + mocker, +): + """A FAILED document with unchanged content is re-queued as PENDING on the next run.""" + doc = make_connector_document(search_space_id=db_search_space.id) + service = IndexingPipelineService(session=db_session) + + # First run: document is created and indexing crashes → status = failed + prepared = await service.prepare_for_indexing([doc]) + document_id = prepared[0].id + await service.index(prepared[0], doc, llm=mocker.Mock()) + + result = await db_session.execute( + select(Document).filter(Document.id == document_id) + ) + assert DocumentStatus.is_state( + result.scalars().first().status, DocumentStatus.FAILED + ) + + # Next run: same content, pipeline must re-queue the failed document + results = await service.prepare_for_indexing([doc]) + + assert len(results) == 1 + assert results[0].id == document_id + + result = await db_session.execute( + select(Document).filter(Document.id == document_id) + ) + assert DocumentStatus.is_state( + result.scalars().first().status, DocumentStatus.PENDING + ) + + +async def test_title_and_content_change_updates_both_and_returns_document( + db_session, db_search_space, make_connector_document +): + """When both title and content change, both are updated and the document is returned for re-indexing.""" + original = make_connector_document( + search_space_id=db_search_space.id, + title="Original Title", + source_markdown="## v1", + ) + service = IndexingPipelineService(session=db_session) + + first = await service.prepare_for_indexing([original]) + original_id = first[0].id + + updated = make_connector_document( + search_space_id=db_search_space.id, + title="Updated Title", + source_markdown="## v2", + ) + results = await service.prepare_for_indexing([updated]) + + assert len(results) == 1 + assert results[0].id == original_id + + result = await db_session.execute( + select(Document).filter(Document.id == original_id) + ) + reloaded = result.scalars().first() + + assert reloaded.title == "Updated Title" + assert reloaded.source_markdown == "## v2" + + +async def test_one_bad_document_in_batch_does_not_prevent_others_from_being_persisted( + db_session, + db_search_space, + make_connector_document, + monkeypatch, +): + """ + A per-document error during prepare_for_indexing must be isolated. + The two valid documents around the failing one must still be persisted. + """ + docs = [ + make_connector_document( + search_space_id=db_search_space.id, + unique_id="good-1", + source_markdown="## Good doc 1", + ), + make_connector_document( + search_space_id=db_search_space.id, + unique_id="will-fail", + source_markdown="## Bad doc", + ), + make_connector_document( + search_space_id=db_search_space.id, + unique_id="good-2", + source_markdown="## Good doc 2", + ), + ] + + def compute_content_hash_with_error(doc): + if doc.unique_id == "will-fail": + raise RuntimeError("Simulated per-document failure") + return real_compute_content_hash(doc) + + monkeypatch.setattr( + "app.indexing_pipeline.indexing_pipeline_service.compute_content_hash", + compute_content_hash_with_error, + ) + + service = IndexingPipelineService(session=db_session) + results = await service.prepare_for_indexing(docs) + + assert len(results) == 2 + + result = await db_session.execute( + select(Document).filter(Document.search_space_id == db_search_space.id) + ) + assert len(result.scalars().all()) == 2 diff --git a/surfsense_backend/tests/unit/__init__.py b/surfsense_backend/tests/unit/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/surfsense_backend/tests/unit/adapters/__init__.py b/surfsense_backend/tests/unit/adapters/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/surfsense_backend/tests/unit/indexing_pipeline/__init__.py b/surfsense_backend/tests/unit/indexing_pipeline/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/surfsense_backend/tests/unit/indexing_pipeline/conftest.py b/surfsense_backend/tests/unit/indexing_pipeline/conftest.py new file mode 100644 index 000000000..11f84dce5 --- /dev/null +++ b/surfsense_backend/tests/unit/indexing_pipeline/conftest.py @@ -0,0 +1,38 @@ +from unittest.mock import AsyncMock, MagicMock + +import pytest + + +@pytest.fixture +def patched_summarizer_chain(monkeypatch): + chain = MagicMock() + chain.ainvoke = AsyncMock(return_value=MagicMock(content="The summary.")) + + template = MagicMock() + template.__or__ = MagicMock(return_value=chain) + + monkeypatch.setattr( + "app.indexing_pipeline.document_summarizer.SUMMARY_PROMPT_TEMPLATE", + template, + ) + return chain + + +@pytest.fixture +def patched_chunker_instance(monkeypatch): + mock = MagicMock() + mock.chunk.return_value = [MagicMock(text="prose chunk")] + monkeypatch.setattr( + "app.indexing_pipeline.document_chunker.config.chunker_instance", mock + ) + return mock + + +@pytest.fixture +def patched_code_chunker_instance(monkeypatch): + mock = MagicMock() + mock.chunk.return_value = [MagicMock(text="code chunk")] + monkeypatch.setattr( + "app.indexing_pipeline.document_chunker.config.code_chunker_instance", mock + ) + return mock diff --git a/surfsense_backend/tests/unit/indexing_pipeline/test_connector_document.py b/surfsense_backend/tests/unit/indexing_pipeline/test_connector_document.py new file mode 100644 index 000000000..2136f2152 --- /dev/null +++ b/surfsense_backend/tests/unit/indexing_pipeline/test_connector_document.py @@ -0,0 +1,114 @@ +import pytest +from pydantic import ValidationError + +from app.db import DocumentType +from app.indexing_pipeline.connector_document import ConnectorDocument + +pytestmark = pytest.mark.unit + + +def test_valid_document_created_with_required_fields(): + """All optional fields default correctly when only required fields are supplied.""" + doc = ConnectorDocument( + title="Task", + source_markdown="## Task\n\nSome content.", + unique_id="task-1", + document_type=DocumentType.CLICKUP_CONNECTOR, + search_space_id=1, + connector_id=42, + created_by_id="00000000-0000-0000-0000-000000000001", + ) + assert doc.should_summarize is True + assert doc.should_use_code_chunker is False + assert doc.metadata == {} + assert doc.connector_id == 42 + assert doc.created_by_id == "00000000-0000-0000-0000-000000000001" + + +def test_omitting_created_by_id_raises(): + """Omitting created_by_id raises a validation error.""" + with pytest.raises(ValidationError): + ConnectorDocument( + title="Task", + source_markdown="## Content", + unique_id="task-1", + document_type=DocumentType.CLICKUP_CONNECTOR, + search_space_id=1, + connector_id=42, + ) + + +def test_empty_source_markdown_raises(): + """Empty source_markdown raises a validation error.""" + with pytest.raises(ValidationError): + ConnectorDocument( + title="Task", + source_markdown="", + unique_id="task-1", + document_type=DocumentType.CLICKUP_CONNECTOR, + search_space_id=1, + ) + + +def test_whitespace_only_source_markdown_raises(): + """Whitespace-only source_markdown raises a validation error.""" + with pytest.raises(ValidationError): + ConnectorDocument( + title="Task", + source_markdown=" \n\t ", + unique_id="task-1", + document_type=DocumentType.CLICKUP_CONNECTOR, + search_space_id=1, + ) + + +def test_empty_title_raises(): + """Empty title raises a validation error.""" + with pytest.raises(ValidationError): + ConnectorDocument( + title="", + source_markdown="## Content", + unique_id="task-1", + document_type=DocumentType.CLICKUP_CONNECTOR, + search_space_id=1, + ) + + +def test_empty_created_by_id_raises(): + """Empty created_by_id raises a validation error.""" + with pytest.raises(ValidationError): + ConnectorDocument( + title="Task", + source_markdown="## Content", + unique_id="task-1", + document_type=DocumentType.CLICKUP_CONNECTOR, + search_space_id=1, + connector_id=42, + created_by_id="", + ) + + +def test_zero_search_space_id_raises(): + """search_space_id of zero raises a validation error.""" + with pytest.raises(ValidationError): + ConnectorDocument( + title="Task", + source_markdown="## Content", + unique_id="task-1", + document_type=DocumentType.CLICKUP_CONNECTOR, + search_space_id=0, + connector_id=42, + created_by_id="00000000-0000-0000-0000-000000000001", + ) + + +def test_empty_unique_id_raises(): + """Empty unique_id raises a validation error.""" + with pytest.raises(ValidationError): + ConnectorDocument( + title="Task", + source_markdown="## Content", + unique_id="", + document_type=DocumentType.CLICKUP_CONNECTOR, + search_space_id=1, + ) diff --git a/surfsense_backend/tests/unit/indexing_pipeline/test_document_chunker.py b/surfsense_backend/tests/unit/indexing_pipeline/test_document_chunker.py new file mode 100644 index 000000000..9c52d503d --- /dev/null +++ b/surfsense_backend/tests/unit/indexing_pipeline/test_document_chunker.py @@ -0,0 +1,21 @@ +import pytest + +from app.indexing_pipeline.document_chunker import chunk_text + +pytestmark = pytest.mark.unit + + +@pytest.mark.usefixtures("patched_chunker_instance", "patched_code_chunker_instance") +def test_uses_code_chunker_when_flag_is_true(): + """Code chunker is selected when use_code_chunker=True.""" + result = chunk_text("def foo(): pass", use_code_chunker=True) + + assert result == ["code chunk"] + + +@pytest.mark.usefixtures("patched_chunker_instance", "patched_code_chunker_instance") +def test_uses_default_chunker_when_flag_is_false(): + """Default prose chunker is selected when use_code_chunker=False.""" + result = chunk_text("Some prose text.", use_code_chunker=False) + + assert result == ["prose chunk"] diff --git a/surfsense_backend/tests/unit/indexing_pipeline/test_document_hashing.py b/surfsense_backend/tests/unit/indexing_pipeline/test_document_hashing.py new file mode 100644 index 000000000..fe536b066 --- /dev/null +++ b/surfsense_backend/tests/unit/indexing_pipeline/test_document_hashing.py @@ -0,0 +1,63 @@ +import pytest + +from app.db import DocumentType +from app.indexing_pipeline.document_hashing import ( + compute_content_hash, + compute_unique_identifier_hash, +) + +pytestmark = pytest.mark.unit + + +def test_different_unique_id_produces_different_hash(make_connector_document): + """Two documents with different unique_ids produce different identifier hashes.""" + doc_a = make_connector_document(unique_id="id-001") + doc_b = make_connector_document(unique_id="id-002") + assert compute_unique_identifier_hash(doc_a) != compute_unique_identifier_hash( + doc_b + ) + + +def test_different_search_space_produces_different_identifier_hash( + make_connector_document, +): + """Same document in different search spaces produces different identifier hashes.""" + doc_a = make_connector_document(search_space_id=1) + doc_b = make_connector_document(search_space_id=2) + assert compute_unique_identifier_hash(doc_a) != compute_unique_identifier_hash( + doc_b + ) + + +def test_different_document_type_produces_different_identifier_hash( + make_connector_document, +): + """Same unique_id with different document types produces different identifier hashes.""" + doc_a = make_connector_document(document_type=DocumentType.CLICKUP_CONNECTOR) + doc_b = make_connector_document(document_type=DocumentType.NOTION_CONNECTOR) + assert compute_unique_identifier_hash(doc_a) != compute_unique_identifier_hash( + doc_b + ) + + +def test_same_content_same_space_produces_same_content_hash(make_connector_document): + """Identical content in the same search space always produces the same content hash.""" + doc_a = make_connector_document(source_markdown="Hello world", search_space_id=1) + doc_b = make_connector_document(source_markdown="Hello world", search_space_id=1) + assert compute_content_hash(doc_a) == compute_content_hash(doc_b) + + +def test_same_content_different_space_produces_different_content_hash( + make_connector_document, +): + """Identical content in different search spaces produces different content hashes.""" + doc_a = make_connector_document(source_markdown="Hello world", search_space_id=1) + doc_b = make_connector_document(source_markdown="Hello world", search_space_id=2) + assert compute_content_hash(doc_a) != compute_content_hash(doc_b) + + +def test_different_content_produces_different_content_hash(make_connector_document): + """Different source markdown produces different content hashes.""" + doc_a = make_connector_document(source_markdown="Original content") + doc_b = make_connector_document(source_markdown="Updated content") + assert compute_content_hash(doc_a) != compute_content_hash(doc_b) diff --git a/surfsense_backend/tests/unit/indexing_pipeline/test_document_summarizer.py b/surfsense_backend/tests/unit/indexing_pipeline/test_document_summarizer.py new file mode 100644 index 000000000..eee32357f --- /dev/null +++ b/surfsense_backend/tests/unit/indexing_pipeline/test_document_summarizer.py @@ -0,0 +1,41 @@ +from unittest.mock import MagicMock + +import pytest + +from app.indexing_pipeline.document_summarizer import summarize_document + +pytestmark = pytest.mark.unit + + +@pytest.mark.usefixtures("patched_summarizer_chain") +async def test_without_metadata_returns_raw_summary(): + """Summarizer returns the LLM output directly when no metadata is provided.""" + result = await summarize_document("# Content", llm=MagicMock(model="gpt-4")) + + assert result == "The summary." + + +@pytest.mark.usefixtures("patched_summarizer_chain") +async def test_with_metadata_includes_metadata_values_in_output(): + """Non-empty metadata values are prepended to the summary output.""" + result = await summarize_document( + "# Content", + llm=MagicMock(model="gpt-4"), + metadata={"author": "Alice", "source": "Notion"}, + ) + + assert "Alice" in result + assert "Notion" in result + + +@pytest.mark.usefixtures("patched_summarizer_chain") +async def test_with_metadata_omits_empty_fields_from_output(): + """Empty metadata fields are omitted from the summary output.""" + result = await summarize_document( + "# Content", + llm=MagicMock(model="gpt-4"), + metadata={"author": "Alice", "description": ""}, + ) + + assert "Alice" in result + assert "description" not in result.lower() diff --git a/surfsense_backend/tests/utils/__init__.py b/surfsense_backend/tests/utils/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/surfsense_backend/tests/utils/helpers.py b/surfsense_backend/tests/utils/helpers.py new file mode 100644 index 000000000..c5719a253 --- /dev/null +++ b/surfsense_backend/tests/utils/helpers.py @@ -0,0 +1,222 @@ +"""Shared test helpers for authentication, polling, and cleanup.""" + +from __future__ import annotations + +import asyncio +from pathlib import Path + +import httpx + +FIXTURES_DIR = Path(__file__).resolve().parent.parent / "fixtures" + +TEST_EMAIL = "testuser@surfsense.com" +TEST_PASSWORD = "testpassword123" + + +async def get_auth_token(client: httpx.AsyncClient) -> str: + """Log in and return a Bearer JWT token, registering the user first if needed.""" + response = await client.post( + "/auth/jwt/login", + data={"username": TEST_EMAIL, "password": TEST_PASSWORD}, + headers={"Content-Type": "application/x-www-form-urlencoded"}, + ) + if response.status_code == 200: + return response.json()["access_token"] + + reg_response = await client.post( + "/auth/register", + json={"email": TEST_EMAIL, "password": TEST_PASSWORD}, + ) + assert reg_response.status_code == 201, ( + f"Registration failed ({reg_response.status_code}): {reg_response.text}" + ) + + response = await client.post( + "/auth/jwt/login", + data={"username": TEST_EMAIL, "password": TEST_PASSWORD}, + headers={"Content-Type": "application/x-www-form-urlencoded"}, + ) + assert response.status_code == 200, ( + f"Login after registration failed ({response.status_code}): {response.text}" + ) + return response.json()["access_token"] + + +async def get_search_space_id(client: httpx.AsyncClient, token: str) -> int: + """Fetch the first search space owned by the test user.""" + resp = await client.get( + "/api/v1/searchspaces", + headers=auth_headers(token), + ) + assert resp.status_code == 200, ( + f"Failed to list search spaces ({resp.status_code}): {resp.text}" + ) + spaces = resp.json() + assert len(spaces) > 0, "No search spaces found for test user" + return spaces[0]["id"] + + +def auth_headers(token: str) -> dict[str, str]: + """Return Authorization header dict for a Bearer token.""" + return {"Authorization": f"Bearer {token}"} + + +async def upload_file( + client: httpx.AsyncClient, + headers: dict[str, str], + fixture_name: str, + *, + search_space_id: int, + filename_override: str | None = None, +) -> httpx.Response: + """Upload a single fixture file and return the raw response.""" + file_path = FIXTURES_DIR / fixture_name + upload_name = filename_override or fixture_name + with open(file_path, "rb") as f: + return await client.post( + "/api/v1/documents/fileupload", + headers=headers, + files={"files": (upload_name, f)}, + data={"search_space_id": str(search_space_id)}, + ) + + +async def upload_multiple_files( + client: httpx.AsyncClient, + headers: dict[str, str], + fixture_names: list[str], + *, + search_space_id: int, +) -> httpx.Response: + """Upload multiple fixture files in a single request.""" + files = [] + open_handles = [] + try: + for name in fixture_names: + fh = open(FIXTURES_DIR / name, "rb") # noqa: SIM115 + open_handles.append(fh) + files.append(("files", (name, fh))) + + return await client.post( + "/api/v1/documents/fileupload", + headers=headers, + files=files, + data={"search_space_id": str(search_space_id)}, + ) + finally: + for fh in open_handles: + fh.close() + + +async def poll_document_status( + client: httpx.AsyncClient, + headers: dict[str, str], + document_ids: list[int], + *, + search_space_id: int, + timeout: float = 180.0, + interval: float = 3.0, +) -> dict[int, dict]: + """ + Poll ``GET /api/v1/documents/status`` until every document reaches a + terminal state (``ready`` or ``failed``) or *timeout* seconds elapse. + + Returns a mapping of ``{document_id: status_item_dict}``. + + Retries on transient transport errors until timeout. + """ + ids_param = ",".join(str(d) for d in document_ids) + terminal_states = {"ready", "failed"} + elapsed = 0.0 + items: dict[int, dict] = {} + last_transport_error: Exception | None = None + + while elapsed < timeout: + try: + resp = await client.get( + "/api/v1/documents/status", + headers=headers, + params={ + "search_space_id": search_space_id, + "document_ids": ids_param, + }, + ) + except (httpx.ReadError, httpx.ConnectError, httpx.TimeoutException) as exc: + last_transport_error = exc + await asyncio.sleep(interval) + elapsed += interval + continue + + assert resp.status_code == 200, ( + f"Status poll failed ({resp.status_code}): {resp.text}" + ) + + items = {item["id"]: item for item in resp.json()["items"]} + if all( + items.get(did, {}).get("status", {}).get("state") in terminal_states + for did in document_ids + ): + return items + + await asyncio.sleep(interval) + elapsed += interval + + raise TimeoutError( + f"Documents {document_ids} did not reach terminal state within {timeout}s. " + f"Last status: {items}. " + f"Last transport error: {last_transport_error!r}" + ) + + +async def get_document( + client: httpx.AsyncClient, + headers: dict[str, str], + document_id: int, +) -> dict: + """Fetch a single document by ID.""" + resp = await client.get( + f"/api/v1/documents/{document_id}", + headers=headers, + ) + assert resp.status_code == 200, ( + f"GET document {document_id} failed ({resp.status_code}): {resp.text}" + ) + return resp.json() + + +async def delete_document( + client: httpx.AsyncClient, + headers: dict[str, str], + document_id: int, +) -> httpx.Response: + """Delete a document by ID, returning the raw response.""" + return await client.delete( + f"/api/v1/documents/{document_id}", + headers=headers, + ) + + +async def get_notifications( + client: httpx.AsyncClient, + headers: dict[str, str], + *, + type_filter: str | None = None, + search_space_id: int | None = None, + limit: int = 50, +) -> list[dict]: + """Fetch notifications for the authenticated user, optionally filtered by type.""" + params: dict[str, str | int] = {"limit": limit} + if type_filter: + params["type"] = type_filter + if search_space_id is not None: + params["search_space_id"] = search_space_id + + resp = await client.get( + "/api/v1/notifications", + headers=headers, + params=params, + ) + assert resp.status_code == 200, ( + f"GET notifications failed ({resp.status_code}): {resp.text}" + ) + return resp.json()["items"] diff --git a/surfsense_backend/uv.lock b/surfsense_backend/uv.lock index 1731944a0..f63623a2b 100644 --- a/surfsense_backend/uv.lock +++ b/surfsense_backend/uv.lock @@ -1,28 +1,16 @@ version = 1 -revision = 1 +revision = 3 requires-python = ">=3.12" resolution-markers = [ - "python_full_version >= '3.14' and sys_platform == 'darwin'", - "python_full_version == '3.13.*' and sys_platform == 'darwin'", - "python_full_version >= '3.14' and platform_machine == 'aarch64' and sys_platform == 'linux'", - "python_full_version == '3.13.*' and platform_machine == 'aarch64' and 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"../tailwind.css"; +import "~tailwind.css"; export const Routing = () => ( diff --git a/surfsense_browser_extension/routes/pages/ApiKeyForm.tsx b/surfsense_browser_extension/routes/pages/ApiKeyForm.tsx index b6deb1c05..537eba3da 100644 --- a/surfsense_browser_extension/routes/pages/ApiKeyForm.tsx +++ b/surfsense_browser_extension/routes/pages/ApiKeyForm.tsx @@ -4,6 +4,8 @@ import { ReloadIcon } from "@radix-ui/react-icons"; import { useState } from "react"; import { useNavigate } from "react-router-dom"; import { Button } from "~/routes/ui/button"; +import { ConnectionSettingsButton } from "~/routes/ui/connection-settings-button"; +import { buildBackendUrl } from "~utils/backend-url"; const ApiKeyForm = () => { const navigation = useNavigate(); @@ -27,8 +29,7 @@ const ApiKeyForm = () => { setLoading(true); try { - // Verify token is valid by making a request to the API - const response = await fetch(`${process.env.PLASMO_PUBLIC_BACKEND_URL}/verify-token`, { + const response = await fetch(await buildBackendUrl("/verify-token"), { method: "GET", headers: { Authorization: `Bearer ${apiKey}`, @@ -53,6 +54,10 @@ const ApiKeyForm = () => { return (
+
+ +
+
SurfSense diff --git a/surfsense_browser_extension/routes/pages/HomePage.tsx b/surfsense_browser_extension/routes/pages/HomePage.tsx index 362c64056..9d8787d29 100644 --- a/surfsense_browser_extension/routes/pages/HomePage.tsx +++ b/surfsense_browser_extension/routes/pages/HomePage.tsx @@ -16,6 +16,7 @@ import React, { useEffect, useState } from "react"; import { useNavigate } from "react-router-dom"; import { cn } from "~/lib/utils"; import { Button } from "~/routes/ui/button"; +import { ConnectionSettingsButton } from "~/routes/ui/connection-settings-button"; import { Command, CommandEmpty, @@ -27,6 +28,7 @@ import { import { Popover, PopoverContent, PopoverTrigger } from "~/routes/ui/popover"; import { Label } from "~routes/ui/label"; import { useToast } from "~routes/ui/use-toast"; +import { buildBackendUrl } from "~utils/backend-url"; import { getRenderedHtml } from "~utils/commons"; import type { WebHistory } from "~utils/interfaces"; import Loading from "./Loading"; @@ -45,15 +47,19 @@ const HomePage = () => { const checkSearchSpaces = async () => { const storage = new Storage({ area: "local" }); const token = await storage.get("token"); + + if (!token) { + setLoading(false); + navigation("/login"); + return; + } + try { - const response = await fetch( - `${process.env.PLASMO_PUBLIC_BACKEND_URL}/api/v1/searchspaces`, - { - headers: { - Authorization: `Bearer ${token}`, - }, + const response = await fetch(await buildBackendUrl("/api/v1/searchspaces"), { + headers: { + Authorization: `Bearer ${token}`, } - ); + }); if (!response.ok) { throw new Error("Token verification failed"); @@ -66,11 +72,12 @@ const HomePage = () => { await storage.remove("token"); await storage.remove("showShadowDom"); navigation("/login"); + } finally { + setLoading(false); } }; checkSearchSpaces(); - setLoading(false); }, []); useEffect(() => { @@ -304,6 +311,19 @@ const HomePage = () => { navigation("/login"); } + async function handleConnectionSaved(changed: boolean): Promise { + if (!changed) { + return; + } + + const storage = new Storage({ area: "local" }); + await storage.remove("token"); + await storage.remove("showShadowDom"); + await storage.remove("search_space"); + await storage.remove("search_space_id"); + navigation("/login"); + } + if (loading) { return ; } else { @@ -344,15 +364,18 @@ const HomePage = () => {

SurfSense

- +
+ + +
diff --git a/surfsense_browser_extension/routes/ui/connection-settings-button.tsx b/surfsense_browser_extension/routes/ui/connection-settings-button.tsx new file mode 100644 index 000000000..f68f252a5 --- /dev/null +++ b/surfsense_browser_extension/routes/ui/connection-settings-button.tsx @@ -0,0 +1,114 @@ +import { GearIcon } from "@radix-ui/react-icons"; +import { useEffect, useState } from "react"; +import { Button } from "~/routes/ui/button"; +import { + Dialog, + DialogContent, + DialogDescription, + DialogFooter, + DialogHeader, + DialogTitle, +} from "~/routes/ui/dialog"; +import { Label } from "~/routes/ui/label"; +import { + DEFAULT_BACKEND_BASE_URL, + getCustomBackendBaseUrl, + normalizeBackendBaseUrl, + setCustomBackendBaseUrl, +} from "~utils/backend-url"; + +type ConnectionSettingsButtonProps = { + onSaved?: (changed: boolean) => void | Promise; +}; + +export function ConnectionSettingsButton({ onSaved }: ConnectionSettingsButtonProps) { + const [open, setOpen] = useState(false); + const [customUrl, setCustomUrl] = useState(""); + const [savedUrl, setSavedUrl] = useState(""); + + useEffect(() => { + if (!open) { + return; + } + + const loadSettings = async () => { + const normalized = await getCustomBackendBaseUrl(); + setCustomUrl(normalized || DEFAULT_BACKEND_BASE_URL); + setSavedUrl(normalized); + }; + + loadSettings(); + }, [open]); + + const handleSave = async () => { + const normalizedUrl = normalizeBackendBaseUrl(customUrl); + const nextUrl = await setCustomBackendBaseUrl( + normalizedUrl === DEFAULT_BACKEND_BASE_URL ? "" : normalizedUrl + ); + const changed = nextUrl !== savedUrl; + setSavedUrl(nextUrl); + setCustomUrl(nextUrl || DEFAULT_BACKEND_BASE_URL); + setOpen(false); + + if (onSaved) { + await onSaved(changed); + } + }; + + return ( + <> + + + + + Connection Settings + + Leave blank to use the default SurfSense backend URL. + + + +
+ + setCustomUrl(event.target.value)} + placeholder={DEFAULT_BACKEND_BASE_URL} + className="w-full rounded-md border border-gray-700 bg-gray-900 px-3 py-2 text-white placeholder:text-gray-500 focus:outline-none focus:ring-2 focus:ring-teal-500" + /> +

Default: {DEFAULT_BACKEND_BASE_URL}

+
+ + + + + + + + + ); +} diff --git a/surfsense_browser_extension/utils/backend-url.ts b/surfsense_browser_extension/utils/backend-url.ts new file mode 100644 index 000000000..b295bf963 --- /dev/null +++ b/surfsense_browser_extension/utils/backend-url.ts @@ -0,0 +1,41 @@ +import { Storage } from "@plasmohq/storage"; + +export const BACKEND_URL_STORAGE_KEY = "backend_base_url"; +export const FALLBACK_BACKEND_BASE_URL = "https://www.surfsense.com"; + +const storage = new Storage({ area: "local" }); + +export function normalizeBackendBaseUrl(url: string) { + return url.trim().replace(/\/+$/, ""); +} + +export const DEFAULT_BACKEND_BASE_URL = normalizeBackendBaseUrl( + process.env.PLASMO_PUBLIC_BACKEND_URL || FALLBACK_BACKEND_BASE_URL +); + +export async function getCustomBackendBaseUrl() { + const value = await storage.get(BACKEND_URL_STORAGE_KEY); + return typeof value === "string" ? normalizeBackendBaseUrl(value) : ""; +} + +export async function setCustomBackendBaseUrl(url: string) { + const normalized = normalizeBackendBaseUrl(url); + + if (normalized) { + await storage.set(BACKEND_URL_STORAGE_KEY, normalized); + return normalized; + } + + await storage.remove(BACKEND_URL_STORAGE_KEY); + return ""; +} + +export async function getBackendBaseUrl() { + return (await getCustomBackendBaseUrl()) || DEFAULT_BACKEND_BASE_URL; +} + +export async function buildBackendUrl(path: string) { + const baseUrl = await getBackendBaseUrl(); + const normalizedPath = path.startsWith("/") ? path : `/${path}`; + return `${baseUrl}${normalizedPath}`; +} diff --git a/surfsense_web/Dockerfile b/surfsense_web/Dockerfile index e0ecb1225..51f65da5e 100644 --- a/surfsense_web/Dockerfile +++ b/surfsense_web/Dockerfile @@ -29,15 +29,22 @@ WORKDIR /app # Enable pnpm RUN corepack enable pnpm -# Accept build arguments for Next.js public env vars -ARG NEXT_PUBLIC_FASTAPI_BACKEND_URL -ARG NEXT_PUBLIC_FASTAPI_BACKEND_AUTH_TYPE -ARG NEXT_PUBLIC_ETL_SERVICE +# Build with placeholder values for NEXT_PUBLIC_* variables. +# These are replaced at container startup by docker-entrypoint.js +# with real values from the container's environment variables. +ARG NEXT_PUBLIC_FASTAPI_BACKEND_URL=__NEXT_PUBLIC_FASTAPI_BACKEND_URL__ +ARG NEXT_PUBLIC_FASTAPI_BACKEND_AUTH_TYPE=__NEXT_PUBLIC_FASTAPI_BACKEND_AUTH_TYPE__ +ARG NEXT_PUBLIC_ETL_SERVICE=__NEXT_PUBLIC_ETL_SERVICE__ +ARG NEXT_PUBLIC_ELECTRIC_URL=__NEXT_PUBLIC_ELECTRIC_URL__ +ARG NEXT_PUBLIC_ELECTRIC_AUTH_MODE=__NEXT_PUBLIC_ELECTRIC_AUTH_MODE__ +ARG NEXT_PUBLIC_DEPLOYMENT_MODE=__NEXT_PUBLIC_DEPLOYMENT_MODE__ -# Set them as environment variables for the build ENV NEXT_PUBLIC_FASTAPI_BACKEND_URL=$NEXT_PUBLIC_FASTAPI_BACKEND_URL ENV NEXT_PUBLIC_FASTAPI_BACKEND_AUTH_TYPE=$NEXT_PUBLIC_FASTAPI_BACKEND_AUTH_TYPE ENV NEXT_PUBLIC_ETL_SERVICE=$NEXT_PUBLIC_ETL_SERVICE +ENV NEXT_PUBLIC_ELECTRIC_URL=$NEXT_PUBLIC_ELECTRIC_URL +ENV NEXT_PUBLIC_ELECTRIC_AUTH_MODE=$NEXT_PUBLIC_ELECTRIC_AUTH_MODE +ENV NEXT_PUBLIC_DEPLOYMENT_MODE=$NEXT_PUBLIC_DEPLOYMENT_MODE COPY --from=deps /app/node_modules ./node_modules COPY . . @@ -67,6 +74,10 @@ COPY --from=builder /app/public ./public COPY --from=builder --chown=nextjs:nodejs /app/.next/standalone ./ COPY --from=builder --chown=nextjs:nodejs /app/.next/static ./.next/static +# Entrypoint scripts for runtime env var substitution +COPY --chown=nextjs:nodejs docker-entrypoint.js ./docker-entrypoint.js +COPY --chown=nextjs:nodejs --chmod=755 docker-entrypoint.sh ./docker-entrypoint.sh + USER nextjs EXPOSE 3000 @@ -76,4 +87,4 @@ ENV PORT=3000 # server.js is created by next build from the standalone output # https://nextjs.org/docs/pages/api-reference/config/next-config-js/output ENV HOSTNAME="0.0.0.0" -CMD ["node", "server.js"] \ No newline at end of file +ENTRYPOINT ["/bin/sh", "./docker-entrypoint.sh"] \ No newline at end of file diff --git a/surfsense_web/app/(home)/announcements/page.tsx b/surfsense_web/app/(home)/announcements/page.tsx index bfc883dfc..966c09f77 100644 --- a/surfsense_web/app/(home)/announcements/page.tsx +++ b/surfsense_web/app/(home)/announcements/page.tsx @@ -1,147 +1,9 @@ "use client"; -import { - Bell, - BellOff, - ExternalLink, - Info, - type Megaphone, - Rocket, - Wrench, - Zap, -} from "lucide-react"; -import Link from "next/link"; import { useEffect } from "react"; -import { Badge } from "@/components/ui/badge"; -import { Button } from "@/components/ui/button"; -import { - Card, - CardContent, - CardDescription, - CardFooter, - CardHeader, - CardTitle, -} from "@/components/ui/card"; -import type { AnnouncementCategory } from "@/contracts/types/announcement.types"; -import { type AnnouncementWithState, useAnnouncements } from "@/hooks/use-announcements"; -import { formatRelativeDate } from "@/lib/format-date"; - -// --------------------------------------------------------------------------- -// Category configuration -// --------------------------------------------------------------------------- - -const categoryConfig: Record< - AnnouncementCategory, - { - label: string; - icon: typeof Megaphone; - color: string; - badgeVariant: "default" | "secondary" | "destructive" | "outline"; - } -> = { - feature: { - label: "Feature", - icon: Rocket, - color: "text-emerald-500", - badgeVariant: "default", - }, - update: { - label: "Update", - icon: Zap, - color: "text-blue-500", - badgeVariant: "secondary", - }, - maintenance: { - label: "Maintenance", - icon: Wrench, - color: "text-amber-500", - badgeVariant: "outline", - }, - info: { - label: "Info", - icon: Info, - color: "text-muted-foreground", - badgeVariant: "secondary", - }, -}; - -// --------------------------------------------------------------------------- -// Announcement card -// --------------------------------------------------------------------------- - -function AnnouncementCard({ announcement }: { announcement: AnnouncementWithState }) { - const config = categoryConfig[announcement.category] ?? categoryConfig.info; - const Icon = config.icon; - - return ( - - -
-
-
- -
-
-
- {announcement.title} - - {config.label} - - {announcement.isImportant && ( - - - Important - - )} -
- - {formatRelativeDate(announcement.date)} - -
-
-
- - - -

{announcement.description}

- - - {announcement.link && ( - - - - )} - - ); -} - -// --------------------------------------------------------------------------- -// Empty state -// --------------------------------------------------------------------------- - -function EmptyState() { - return ( -
-
- -
-

No announcements

-

- You're all caught up! New announcements will appear here. -

-
- ); -} +import { AnnouncementCard } from "@/components/announcements/AnnouncementCard"; +import { AnnouncementsEmptyState } from "@/components/announcements/AnnouncementsEmptyState"; +import { useAnnouncements } from "@/hooks/use-announcements"; // --------------------------------------------------------------------------- // Page @@ -171,7 +33,7 @@ export default function AnnouncementsPage() { {/* Content */}
{announcements.length === 0 ? ( - + ) : (
{announcements.map((announcement) => ( diff --git a/surfsense_web/app/dashboard/[search_space_id]/more-pages/page.tsx b/surfsense_web/app/dashboard/[search_space_id]/more-pages/page.tsx index f2e9fb731..77ca38c38 100644 --- a/surfsense_web/app/dashboard/[search_space_id]/more-pages/page.tsx +++ b/surfsense_web/app/dashboard/[search_space_id]/more-pages/page.tsx @@ -181,7 +181,7 @@ export default function MorePagesPage() {
- eric@surfsense.com + rohan@surfsense.com
diff --git a/surfsense_web/app/dashboard/[search_space_id]/new-chat/[[...chat_id]]/page.tsx b/surfsense_web/app/dashboard/[search_space_id]/new-chat/[[...chat_id]]/page.tsx index 66d7b4f04..1df9ef06c 100644 --- a/surfsense_web/app/dashboard/[search_space_id]/new-chat/[[...chat_id]]/page.tsx +++ b/surfsense_web/app/dashboard/[search_space_id]/new-chat/[[...chat_id]]/page.tsx @@ -26,7 +26,6 @@ import { import { clearPlanOwnerRegistry, // extractWriteTodosFromContent, - hydratePlanStateAtom, } from "@/atoms/chat/plan-state.atom"; import { closeReportPanelAtom } from "@/atoms/chat/report-panel.atom"; import { membersAtom } from "@/atoms/members/members-query.atoms"; @@ -53,6 +52,7 @@ import { DeleteNotionPageToolUI, UpdateNotionPageToolUI, } from "@/components/tool-ui/notion"; +import { SandboxExecuteToolUI } from "@/components/tool-ui/sandbox-execute"; import { ScrapeWebpageToolUI } from "@/components/tool-ui/scrape-webpage"; import { RecallMemoryToolUI, SaveMemoryToolUI } from "@/components/tool-ui/user-memory"; import { Skeleton } from "@/components/ui/skeleton"; @@ -72,7 +72,6 @@ import { appendText, buildContentForPersistence, buildContentForUI, - type ContentPart, type ContentPartsState, readSSEStream, type ThinkingStepData, @@ -157,6 +156,7 @@ const TOOLS_WITH_UI = new Set([ "delete_linear_issue", "create_google_drive_file", "delete_google_drive_file", + "execute", // "write_todos", // Disabled for now ]); @@ -186,7 +186,6 @@ export default function NewChatPage() { const setMentionedDocumentIds = useSetAtom(mentionedDocumentIdsAtom); const setMentionedDocuments = useSetAtom(mentionedDocumentsAtom); const setMessageDocumentsMap = useSetAtom(messageDocumentsMapAtom); - const hydratePlanState = useSetAtom(hydratePlanStateAtom); const setCurrentThreadState = useSetAtom(currentThreadAtom); const setTargetCommentId = useSetAtom(setTargetCommentIdAtom); const clearTargetCommentId = useSetAtom(clearTargetCommentIdAtom); @@ -348,7 +347,6 @@ export default function NewChatPage() { setMessageDocumentsMap, setMentionedDocumentIds, setMentionedDocuments, - hydratePlanState, closeReportPanel, ]); @@ -1672,6 +1670,7 @@ export default function NewChatPage() { + {/* Disabled for now */}
diff --git a/surfsense_web/app/dashboard/[search_space_id]/team/page.tsx b/surfsense_web/app/dashboard/[search_space_id]/team/page.tsx index f8a9cecd0..c33c2e341 100644 --- a/surfsense_web/app/dashboard/[search_space_id]/team/page.tsx +++ b/surfsense_web/app/dashboard/[search_space_id]/team/page.tsx @@ -16,8 +16,8 @@ import { Link2, ShieldUser, Trash2, - UserPlus, User, + UserPlus, Users, } from "lucide-react"; import { motion } from "motion/react"; diff --git a/surfsense_web/app/docs/layout.tsx b/surfsense_web/app/docs/layout.tsx index 27dd5de7a..9311a45b4 100644 --- a/surfsense_web/app/docs/layout.tsx +++ b/surfsense_web/app/docs/layout.tsx @@ -2,10 +2,24 @@ import { DocsLayout } from "fumadocs-ui/layouts/docs"; import type { ReactNode } from "react"; import { baseOptions } from "@/app/layout.config"; import { source } from "@/lib/source"; +import { SidebarSeparator } from "./sidebar-separator"; + +const gridTemplate = `"sidebar header toc" +"sidebar toc-popover toc" +"sidebar main toc" 1fr / var(--fd-sidebar-col) minmax(0, 1fr) min-content`; export default function Layout({ children }: { children: ReactNode }) { return ( - + {children} ); diff --git a/surfsense_web/app/docs/sidebar-separator.tsx b/surfsense_web/app/docs/sidebar-separator.tsx new file mode 100644 index 000000000..36fff09a4 --- /dev/null +++ b/surfsense_web/app/docs/sidebar-separator.tsx @@ -0,0 +1,12 @@ +"use client"; + +import type { Separator } from "fumadocs-core/page-tree"; + +export function SidebarSeparator({ item }: { item: Separator }) { + return ( +

+ {item.icon} + {item.name} +

+ ); +} diff --git a/surfsense_web/app/layout.config.tsx b/surfsense_web/app/layout.config.tsx index b1b07fd02..214c5b940 100644 --- a/surfsense_web/app/layout.config.tsx +++ b/surfsense_web/app/layout.config.tsx @@ -1,7 +1,7 @@ import type { BaseLayoutProps } from "fumadocs-ui/layouts/shared"; - export const baseOptions: BaseLayoutProps = { nav: { - title: "SurfSense Documentation", + title: "SurfSense Docs", }, + githubUrl: "https://github.com/MODSetter/SurfSense", }; diff --git a/surfsense_web/app/verify-token/route.ts b/surfsense_web/app/verify-token/route.ts new file mode 100644 index 000000000..1c11d6ce0 --- /dev/null +++ b/surfsense_web/app/verify-token/route.ts @@ -0,0 +1,25 @@ +import { NextRequest, NextResponse } from "next/server"; + +const backendBaseUrl = (process.env.INTERNAL_FASTAPI_BACKEND_URL || "http://backend:8000").replace( + /\/+$/, + "" +); + +export async function GET(request: NextRequest) { + const response = await fetch(`${backendBaseUrl}/verify-token`, { + method: "GET", + headers: { + Authorization: request.headers.get("authorization") || "", + "X-API-Key": request.headers.get("x-api-key") || "", + }, + cache: "no-store", + }); + + return new NextResponse(response.body, { + status: response.status, + headers: { + "content-type": response.headers.get("content-type") || "application/json", + "cache-control": "no-store", + }, + }); +} diff --git a/surfsense_web/components/announcements/AnnouncementCard.tsx b/surfsense_web/components/announcements/AnnouncementCard.tsx new file mode 100644 index 000000000..daaecee07 --- /dev/null +++ b/surfsense_web/components/announcements/AnnouncementCard.tsx @@ -0,0 +1,117 @@ +"use client"; + +import { + Bell, + ExternalLink, + Info, + type LucideIcon, + Rocket, + Wrench, + Zap, +} from "lucide-react"; +import Link from "next/link"; +import { Badge } from "@/components/ui/badge"; +import { Button } from "@/components/ui/button"; +import { + Card, + CardContent, + CardDescription, + CardFooter, + CardHeader, + CardTitle, +} from "@/components/ui/card"; +import type { AnnouncementCategory } from "@/contracts/types/announcement.types"; +import type { AnnouncementWithState } from "@/hooks/use-announcements"; +import { formatRelativeDate } from "@/lib/format-date"; + +const categoryConfig: Record< + AnnouncementCategory, + { + label: string; + icon: LucideIcon; + color: string; + badgeVariant: "default" | "secondary" | "destructive" | "outline"; + } +> = { + feature: { + label: "Feature", + icon: Rocket, + color: "text-emerald-500", + badgeVariant: "default", + }, + update: { + label: "Update", + icon: Zap, + color: "text-blue-500", + badgeVariant: "secondary", + }, + maintenance: { + label: "Maintenance", + icon: Wrench, + color: "text-amber-500", + badgeVariant: "outline", + }, + info: { + label: "Info", + icon: Info, + color: "text-muted-foreground", + badgeVariant: "secondary", + }, +}; + +export function AnnouncementCard({ announcement }: { announcement: AnnouncementWithState }) { + const config = categoryConfig[announcement.category] ?? categoryConfig.info; + const Icon = config.icon; + + return ( + + +
+
+
+ +
+
+
+ {announcement.title} + + {config.label} + + {announcement.isImportant && ( + + + Important + + )} +
+ + {formatRelativeDate(announcement.date)} + +
+
+
+ + + +

{announcement.description}

+ + + {announcement.link && ( + + + + )} + + ); +} + diff --git a/surfsense_web/components/announcements/AnnouncementsEmptyState.tsx b/surfsense_web/components/announcements/AnnouncementsEmptyState.tsx new file mode 100644 index 000000000..2ae926b1f --- /dev/null +++ b/surfsense_web/components/announcements/AnnouncementsEmptyState.tsx @@ -0,0 +1,18 @@ +"use client"; + +import { BellOff } from "lucide-react"; + +export function AnnouncementsEmptyState() { + return ( +
+
+ +
+

No announcements

+

+ You're all caught up! New announcements will appear here. +

+
+ ); +} + diff --git a/surfsense_web/components/assistant-ui/connector-popup.tsx b/surfsense_web/components/assistant-ui/connector-popup.tsx index bac5c44a3..332694676 100644 --- a/surfsense_web/components/assistant-ui/connector-popup.tsx +++ b/surfsense_web/components/assistant-ui/connector-popup.tsx @@ -5,6 +5,7 @@ import { AlertTriangle, Cable, Settings } from "lucide-react"; import Link from "next/link"; import { useSearchParams } from "next/navigation"; import type { FC } from "react"; +import { documentTypeCountsAtom } from "@/atoms/documents/document-query.atoms"; import { globalNewLLMConfigsAtom, llmPreferencesAtom, @@ -19,7 +20,6 @@ import { Spinner } from "@/components/ui/spinner"; import { Tabs, TabsContent } from "@/components/ui/tabs"; import type { SearchSourceConnector } from "@/contracts/types/connector.types"; import { useConnectorsElectric } from "@/hooks/use-connectors-electric"; -import { useDocuments } from "@/hooks/use-documents"; import { useInbox } from "@/hooks/use-inbox"; import { cn } from "@/lib/utils"; import { ConnectorDialogHeader } from "./connector-popup/components/connector-dialog-header"; @@ -62,10 +62,9 @@ export const ConnectorIndicator: FC<{ hideTrigger?: boolean }> = ({ hideTrigger const llmConfigLoading = preferencesLoading || globalConfigsLoading; - // Fetch document type counts using Electric SQL + PGlite for real-time updates - const { typeCounts: documentTypeCounts, loading: documentTypesLoading } = useDocuments( - searchSpaceId ? Number(searchSpaceId) : null - ); + // Fetch document type counts via the lightweight /type-counts endpoint (cached 10 min) + const { data: documentTypeCounts, isFetching: documentTypesLoading } = + useAtomValue(documentTypeCountsAtom); // Fetch notifications to detect indexing failures const { inboxItems = [] } = useInbox( @@ -97,6 +96,7 @@ export const ConnectorIndicator: FC<{ hideTrigger?: boolean }> = ({ hideTrigger isDisconnecting, periodicEnabled, frequencyMinutes, + enableSummary, allConnectors, viewingAccountsType, viewingMCPList, @@ -105,6 +105,7 @@ export const ConnectorIndicator: FC<{ hideTrigger?: boolean }> = ({ hideTrigger setEndDate, setPeriodicEnabled, setFrequencyMinutes, + setEnableSummary, handleOpenChange, handleTabChange, handleScroll, @@ -282,6 +283,7 @@ export const ConnectorIndicator: FC<{ hideTrigger?: boolean }> = ({ hideTrigger endDate={endDate} periodicEnabled={periodicEnabled} frequencyMinutes={frequencyMinutes} + enableSummary={enableSummary} isSaving={isSaving} isDisconnecting={isDisconnecting} isIndexing={indexingConnectorIds.has(editingConnector.id)} @@ -290,6 +292,7 @@ export const ConnectorIndicator: FC<{ hideTrigger?: boolean }> = ({ hideTrigger onEndDateChange={setEndDate} onPeriodicEnabledChange={setPeriodicEnabled} onFrequencyChange={setFrequencyMinutes} + onEnableSummaryChange={setEnableSummary} onSave={() => { startIndexing(editingConnector.id); handleSaveConnector(() => refreshConnectors()); @@ -328,11 +331,13 @@ export const ConnectorIndicator: FC<{ hideTrigger?: boolean }> = ({ hideTrigger endDate={endDate} periodicEnabled={periodicEnabled} frequencyMinutes={frequencyMinutes} + enableSummary={enableSummary} isStartingIndexing={isStartingIndexing} onStartDateChange={setStartDate} onEndDateChange={setEndDate} onPeriodicEnabledChange={setPeriodicEnabled} onFrequencyChange={setFrequencyMinutes} + onEnableSummaryChange={setEnableSummary} onConfigChange={setIndexingConnectorConfig} onStartIndexing={() => { if (indexingConfig.connectorId) { diff --git a/surfsense_web/components/assistant-ui/connector-popup/components/summary-config.tsx b/surfsense_web/components/assistant-ui/connector-popup/components/summary-config.tsx new file mode 100644 index 000000000..b9ff69f5f --- /dev/null +++ b/surfsense_web/components/assistant-ui/connector-popup/components/summary-config.tsx @@ -0,0 +1,25 @@ +"use client"; + +import type { FC } from "react"; +import { Switch } from "@/components/ui/switch"; + +interface SummaryConfigProps { + enabled: boolean; + onEnabledChange: (enabled: boolean) => void; +} + +export const SummaryConfig: FC = ({ enabled, onEnabledChange }) => { + return ( +
+
+
+

Enable AI Summary

+

+ Improves search quality but adds latency during indexing +

+
+ +
+
+ ); +}; diff --git a/surfsense_web/components/assistant-ui/connector-popup/connector-configs/views/connector-edit-view.tsx b/surfsense_web/components/assistant-ui/connector-popup/connector-configs/views/connector-edit-view.tsx index cfdebee60..536044df4 100644 --- a/surfsense_web/components/assistant-ui/connector-popup/connector-configs/views/connector-edit-view.tsx +++ b/surfsense_web/components/assistant-ui/connector-popup/connector-configs/views/connector-edit-view.tsx @@ -9,6 +9,7 @@ import type { SearchSourceConnector } from "@/contracts/types/connector.types"; import { cn } from "@/lib/utils"; import { DateRangeSelector } from "../../components/date-range-selector"; import { PeriodicSyncConfig } from "../../components/periodic-sync-config"; +import { SummaryConfig } from "../../components/summary-config"; import { getConnectorDisplayName } from "../../tabs/all-connectors-tab"; import { getConnectorConfigComponent } from "../index"; @@ -18,6 +19,7 @@ interface ConnectorEditViewProps { endDate: Date | undefined; periodicEnabled: boolean; frequencyMinutes: string; + enableSummary: boolean; isSaving: boolean; isDisconnecting: boolean; isIndexing?: boolean; @@ -26,6 +28,7 @@ interface ConnectorEditViewProps { onEndDateChange: (date: Date | undefined) => void; onPeriodicEnabledChange: (enabled: boolean) => void; onFrequencyChange: (frequency: string) => void; + onEnableSummaryChange: (enabled: boolean) => void; onSave: () => void; onDisconnect: () => void; onBack: () => void; @@ -40,6 +43,7 @@ export const ConnectorEditView: FC = ({ endDate, periodicEnabled, frequencyMinutes, + enableSummary, isSaving, isDisconnecting, isIndexing = false, @@ -48,6 +52,7 @@ export const ConnectorEditView: FC = ({ onEndDateChange, onPeriodicEnabledChange, onFrequencyChange, + onEnableSummaryChange, onSave, onDisconnect, onBack, @@ -209,9 +214,12 @@ export const ConnectorEditView: FC = ({ /> )} - {/* Date range selector and periodic sync - only shown for indexable connectors */} + {/* Summary and sync settings - only shown for indexable connectors */} {connector.is_indexable && ( <> + {/* AI Summary toggle */} + + {/* Date range selector - not shown for Google Drive (regular and Composio), Webcrawler, or GitHub (indexes full repo snapshots) */} {connector.connector_type !== "GOOGLE_DRIVE_CONNECTOR" && connector.connector_type !== "COMPOSIO_GOOGLE_DRIVE_CONNECTOR" && diff --git a/surfsense_web/components/assistant-ui/connector-popup/connector-configs/views/indexing-configuration-view.tsx b/surfsense_web/components/assistant-ui/connector-popup/connector-configs/views/indexing-configuration-view.tsx index 11760bb30..69d5c8e28 100644 --- a/surfsense_web/components/assistant-ui/connector-popup/connector-configs/views/indexing-configuration-view.tsx +++ b/surfsense_web/components/assistant-ui/connector-popup/connector-configs/views/indexing-configuration-view.tsx @@ -10,6 +10,7 @@ import { getConnectorTypeDisplay } from "@/lib/connectors/utils"; import { cn } from "@/lib/utils"; import { DateRangeSelector } from "../../components/date-range-selector"; import { PeriodicSyncConfig } from "../../components/periodic-sync-config"; +import { SummaryConfig } from "../../components/summary-config"; import type { IndexingConfigState } from "../../constants/connector-constants"; import { getConnectorDisplayName } from "../../tabs/all-connectors-tab"; import { getConnectorConfigComponent } from "../index"; @@ -21,11 +22,13 @@ interface IndexingConfigurationViewProps { endDate: Date | undefined; periodicEnabled: boolean; frequencyMinutes: string; + enableSummary: boolean; isStartingIndexing: boolean; onStartDateChange: (date: Date | undefined) => void; onEndDateChange: (date: Date | undefined) => void; onPeriodicEnabledChange: (enabled: boolean) => void; onFrequencyChange: (frequency: string) => void; + onEnableSummaryChange: (enabled: boolean) => void; onConfigChange?: (config: Record) => void; onStartIndexing: () => void; onSkip: () => void; @@ -38,11 +41,13 @@ export const IndexingConfigurationView: FC = ({ endDate, periodicEnabled, frequencyMinutes, + enableSummary, isStartingIndexing, onStartDateChange, onEndDateChange, onPeriodicEnabledChange, onFrequencyChange, + onEnableSummaryChange, onConfigChange, onStartIndexing, onSkip, @@ -149,9 +154,12 @@ export const IndexingConfigurationView: FC = ({ )} - {/* Date range selector and periodic sync - only shown for indexable connectors */} + {/* Summary and sync settings - only shown for indexable connectors */} {connector?.is_indexable && ( <> + {/* AI Summary toggle */} + + {/* Date range selector - not shown for Google Drive (regular and Composio), Webcrawler, or GitHub (indexes full repo snapshots) */} {config.connectorType !== "GOOGLE_DRIVE_CONNECTOR" && config.connectorType !== "COMPOSIO_GOOGLE_DRIVE_CONNECTOR" && diff --git a/surfsense_web/components/assistant-ui/connector-popup/constants/connector-constants.ts b/surfsense_web/components/assistant-ui/connector-popup/constants/connector-constants.ts index a3e8ae272..5deee8360 100644 --- a/surfsense_web/components/assistant-ui/connector-popup/constants/connector-constants.ts +++ b/surfsense_web/components/assistant-ui/connector-popup/constants/connector-constants.ts @@ -2,27 +2,28 @@ import { EnumConnectorName } from "@/contracts/enums/connector"; // OAuth Connectors (Quick Connect) export const OAUTH_CONNECTORS = [ - { - id: "google-drive-connector", - title: "Google Drive", - description: "Search your Drive files", - connectorType: EnumConnectorName.GOOGLE_DRIVE_CONNECTOR, - authEndpoint: "/api/v1/auth/google/drive/connector/add/", - }, - { - id: "google-gmail-connector", - title: "Gmail", - description: "Search through your emails", - connectorType: EnumConnectorName.GOOGLE_GMAIL_CONNECTOR, - authEndpoint: "/api/v1/auth/google/gmail/connector/add/", - }, - { - id: "google-calendar-connector", - title: "Google Calendar", - description: "Search through your events", - connectorType: EnumConnectorName.GOOGLE_CALENDAR_CONNECTOR, - authEndpoint: "/api/v1/auth/google/calendar/connector/add/", - }, + // // Uncomment for managed Google Connections + // { + // id: "google-drive-connector", + // title: "Google Drive", + // description: "Search your Drive files", + // connectorType: EnumConnectorName.GOOGLE_DRIVE_CONNECTOR, + // authEndpoint: "/api/v1/auth/google/drive/connector/add/", + // }, + // { + // id: "google-gmail-connector", + // title: "Gmail", + // description: "Search through your emails", + // connectorType: EnumConnectorName.GOOGLE_GMAIL_CONNECTOR, + // authEndpoint: "/api/v1/auth/google/gmail/connector/add/", + // }, + // { + // id: "google-calendar-connector", + // title: "Google Calendar", + // description: "Search through your events", + // connectorType: EnumConnectorName.GOOGLE_CALENDAR_CONNECTOR, + // authEndpoint: "/api/v1/auth/google/calendar/connector/add/", + // }, { id: "airtable-connector", title: "Airtable", diff --git a/surfsense_web/components/assistant-ui/connector-popup/hooks/use-connector-dialog.ts b/surfsense_web/components/assistant-ui/connector-popup/hooks/use-connector-dialog.ts index 916d0dca3..4585057ff 100644 --- a/surfsense_web/components/assistant-ui/connector-popup/hooks/use-connector-dialog.ts +++ b/surfsense_web/components/assistant-ui/connector-popup/hooks/use-connector-dialog.ts @@ -67,6 +67,7 @@ export const useConnectorDialog = () => { const [isStartingIndexing, setIsStartingIndexing] = useState(false); const [periodicEnabled, setPeriodicEnabled] = useState(false); const [frequencyMinutes, setFrequencyMinutes] = useState("1440"); + const [enableSummary, setEnableSummary] = useState(false); // Edit mode state const [editingConnector, setEditingConnector] = useState(null); @@ -240,6 +241,7 @@ export const useConnectorDialog = () => { !connector.is_indexable ? false : connector.periodic_indexing_enabled ); setFrequencyMinutes(connector.indexing_frequency_minutes?.toString() || "1440"); + setEnableSummary(connector.enable_summary ?? false); // Reset dates - user can set new ones for re-indexing setStartDate(undefined); setEndDate(undefined); @@ -257,6 +259,7 @@ export const useConnectorDialog = () => { setEndDate(undefined); setPeriodicEnabled(false); setFrequencyMinutes("1440"); + setEnableSummary(false); setIsScrolled(false); setSearchQuery(""); } @@ -269,6 +272,7 @@ export const useConnectorDialog = () => { setEndDate(undefined); setPeriodicEnabled(false); setFrequencyMinutes("1440"); + setEnableSummary(false); setIsScrolled(false); setSearchQuery(""); } @@ -722,6 +726,7 @@ export const useConnectorDialog = () => { setConnectorConfig(connector.config || {}); setPeriodicEnabled(false); setFrequencyMinutes("1440"); + setEnableSummary(connector.enable_summary ?? false); setStartDate(undefined); setEndDate(undefined); @@ -909,12 +914,13 @@ export const useConnectorDialog = () => { const startDateStr = startDate ? format(startDate, "yyyy-MM-dd") : undefined; const endDateStr = endDate ? format(endDate, "yyyy-MM-dd") : undefined; - // Update connector with periodic sync settings and config changes - if (periodicEnabled || indexingConnectorConfig) { + // Update connector with summary, periodic sync settings, and config changes + if (enableSummary || periodicEnabled || indexingConnectorConfig) { const frequency = periodicEnabled ? parseInt(frequencyMinutes, 10) : undefined; await updateConnector({ id: indexingConfig.connectorId, data: { + enable_summary: enableSummary, ...(periodicEnabled && { periodic_indexing_enabled: true, indexing_frequency_minutes: frequency, @@ -1042,6 +1048,7 @@ export const useConnectorDialog = () => { updateConnector, periodicEnabled, frequencyMinutes, + enableSummary, router, indexingConnectorConfig, ] @@ -1108,6 +1115,7 @@ export const useConnectorDialog = () => { // Load existing periodic sync settings (disabled for non-indexable connectors) setPeriodicEnabled(!connector.is_indexable ? false : connector.periodic_indexing_enabled); setFrequencyMinutes(connector.indexing_frequency_minutes?.toString() || "1440"); + setEnableSummary(connector.enable_summary ?? false); // Reset dates - user can set new ones for re-indexing setStartDate(undefined); setEndDate(undefined); @@ -1189,6 +1197,7 @@ export const useConnectorDialog = () => { id: editingConnector.id, data: { name: connectorName || editingConnector.name, + enable_summary: enableSummary, periodic_indexing_enabled: !editingConnector.is_indexable ? false : periodicEnabled, indexing_frequency_minutes: !editingConnector.is_indexable ? null : frequency, config: connectorConfig || editingConnector.config, @@ -1326,6 +1335,7 @@ export const useConnectorDialog = () => { updateConnector, periodicEnabled, frequencyMinutes, + enableSummary, getFrequencyLabel, router, connectorConfig, @@ -1518,6 +1528,7 @@ export const useConnectorDialog = () => { setEndDate(undefined); setPeriodicEnabled(false); setFrequencyMinutes("1440"); + setEnableSummary(false); } } }, @@ -1557,6 +1568,7 @@ export const useConnectorDialog = () => { isDisconnecting, periodicEnabled, frequencyMinutes, + enableSummary, searchSpaceId, allConnectors, viewingAccountsType, @@ -1568,6 +1580,7 @@ export const useConnectorDialog = () => { setEndDate, setPeriodicEnabled, setFrequencyMinutes, + setEnableSummary, setConnectorName, // Handlers diff --git a/surfsense_web/components/assistant-ui/thread.tsx b/surfsense_web/components/assistant-ui/thread.tsx index 91de2bb90..98fa5b436 100644 --- a/surfsense_web/components/assistant-ui/thread.tsx +++ b/surfsense_web/components/assistant-ui/thread.tsx @@ -65,6 +65,7 @@ import type { ThinkingStep } from "@/components/tool-ui/deepagent-thinking"; import { Button } from "@/components/ui/button"; import { Spinner } from "@/components/ui/spinner"; import type { Document } from "@/contracts/types/document.types"; +import { useBatchCommentsPreload } from "@/hooks/use-comments"; import { useCommentsElectric } from "@/hooks/use-comments-electric"; import { documentsApiService } from "@/lib/apis/documents-api.service"; import { cn } from "@/lib/utils"; @@ -82,6 +83,10 @@ const CYCLING_PLACEHOLDERS = [ const CHAT_UPLOAD_ACCEPT = ".pdf,.doc,.docx,.txt,.md,.markdown,.ppt,.pptx,.xls,.xlsx,.xlsm,.xlsb,.csv,.html,.htm,.xml,.rtf,.epub,.jpg,.jpeg,.png,.bmp,.webp,.tiff,.tif,.mp3,.mp4,.mpeg,.mpga,.m4a,.wav,.webm"; +const CHAT_MAX_FILES = 10; +const CHAT_MAX_FILE_SIZE_BYTES = 50 * 1024 * 1024; // 50 MB per file +const CHAT_MAX_TOTAL_SIZE_BYTES = 200 * 1024 * 1024; // 200 MB total + type UploadState = "pending" | "processing" | "ready" | "failed"; interface UploadedMentionDoc { @@ -305,6 +310,22 @@ const Composer: FC = () => { // Sync comments for the entire thread via Electric SQL (one subscription per thread) useCommentsElectric(threadId); + // Batch-prefetch comments for all assistant messages so individual useComments + // hooks never fire their own network requests (eliminates N+1 API calls). + // Return a primitive string from the selector so useSyncExternalStore can + // compare snapshots by value and avoid infinite re-render loops. + const assistantIdsKey = useAssistantState(({ thread }) => + thread.messages + .filter((m) => m.role === "assistant" && m.id?.startsWith("msg-")) + .map((m) => m.id!.replace("msg-", "")) + .join(",") + ); + const assistantDbMessageIds = useMemo( + () => (assistantIdsKey ? assistantIdsKey.split(",").map(Number) : []), + [assistantIdsKey] + ); + useBatchCommentsPreload(assistantDbMessageIds); + // Auto-focus editor on new chat page after mount useEffect(() => { if (isThreadEmpty && !hasAutoFocusedRef.current && editorRef.current) { @@ -534,6 +555,28 @@ const Composer: FC = () => { event.target.value = ""; if (files.length === 0 || !search_space_id) return; + if (files.length > CHAT_MAX_FILES) { + toast.error(`Too many files. Maximum ${CHAT_MAX_FILES} files per upload.`); + return; + } + + let totalSize = 0; + for (const file of files) { + if (file.size > CHAT_MAX_FILE_SIZE_BYTES) { + toast.error( + `File "${file.name}" (${(file.size / (1024 * 1024)).toFixed(1)} MB) exceeds the ${CHAT_MAX_FILE_SIZE_BYTES / (1024 * 1024)} MB per-file limit.` + ); + return; + } + totalSize += file.size; + } + if (totalSize > CHAT_MAX_TOTAL_SIZE_BYTES) { + toast.error( + `Total upload size (${(totalSize / (1024 * 1024)).toFixed(1)} MB) exceeds the ${CHAT_MAX_TOTAL_SIZE_BYTES / (1024 * 1024)} MB limit.` + ); + return; + } + setIsUploadingDocs(true); try { const uploadResponse = await documentsApiService.uploadDocument({ diff --git a/surfsense_web/components/assistant-ui/tooltip-icon-button.tsx b/surfsense_web/components/assistant-ui/tooltip-icon-button.tsx index 55f7c6a2e..0ca96e912 100644 --- a/surfsense_web/components/assistant-ui/tooltip-icon-button.tsx +++ b/surfsense_web/components/assistant-ui/tooltip-icon-button.tsx @@ -1,7 +1,7 @@ "use client"; import { Slottable } from "@radix-ui/react-slot"; -import { type ComponentPropsWithRef, type ReactNode, forwardRef } from "react"; +import { type ComponentPropsWithRef, forwardRef, type ReactNode } from "react"; import { Button } from "@/components/ui/button"; import { Tooltip, TooltipContent, TooltipTrigger } from "@/components/ui/tooltip"; import { cn } from "@/lib/utils"; diff --git a/surfsense_web/components/contact/contact-form.tsx b/surfsense_web/components/contact/contact-form.tsx index 6f6e9f5b4..967c1c524 100644 --- a/surfsense_web/components/contact/contact-form.tsx +++ b/surfsense_web/components/contact/contact-form.tsx @@ -23,12 +23,12 @@ export function ContactFormGridWithDetails() { We'd love to hear from you!

- Schedule a meeting with our Head of Product, Eric Lammertsma, or send us an email. + Schedule a meeting with us, or send us an email.

- eric@surfsense.com + rohan@surfsense.com
diff --git a/surfsense_web/components/homepage/hero-section.tsx b/surfsense_web/components/homepage/hero-section.tsx index 00226517c..a1aa5ac4a 100644 --- a/surfsense_web/components/homepage/hero-section.tsx +++ b/surfsense_web/components/homepage/hero-section.tsx @@ -96,12 +96,9 @@ export function HeroSection() {
)} - {/* // TODO:aCTUAL DESCRITION */} -

- Connect any AI to your documents, Drive, Notion and more, -

-

- then chat with it, generate podcasts and reports, or even invite your team. +

+ Connect any LLM to your internal knowledge sources and chat with it in real time alongside + your team.

diff --git a/surfsense_web/components/homepage/navbar.tsx b/surfsense_web/components/homepage/navbar.tsx index 2b0d60546..ddf43e7eb 100644 --- a/surfsense_web/components/homepage/navbar.tsx +++ b/surfsense_web/components/homepage/navbar.tsx @@ -4,7 +4,6 @@ import { IconBrandGithub, IconBrandReddit, IconMenu2, - IconSpeakerphone, IconX, } from "@tabler/icons-react"; import { AnimatePresence, motion } from "motion/react"; @@ -13,7 +12,6 @@ import { useEffect, useState } from "react"; import { SignInButton } from "@/components/auth/sign-in-button"; import { Logo } from "@/components/Logo"; import { ThemeTogglerComponent } from "@/components/theme/theme-toggle"; -import { useAnnouncements } from "@/hooks/use-announcements"; import { useGithubStars } from "@/hooks/use-github-stars"; import { cn } from "@/lib/utils"; @@ -49,11 +47,7 @@ export const Navbar = () => { const DesktopNav = ({ navItems, isScrolled }: any) => { const [hovered, setHovered] = useState(null); - const [mounted, setMounted] = useState(false); const { compactFormat: githubStars, loading: loadingGithubStars } = useGithubStars(); - const { unreadCount } = useAnnouncements(); - - useEffect(() => setMounted(true), []); return ( { @@ -124,17 +118,6 @@ const DesktopNav = ({ navItems, isScrolled }: any) => { )} - - - {mounted && unreadCount > 0 && ( - - {unreadCount > 99 ? "99+" : unreadCount} - - )} -
@@ -144,11 +127,7 @@ const DesktopNav = ({ navItems, isScrolled }: any) => { const MobileNav = ({ navItems, isScrolled }: any) => { const [open, setOpen] = useState(false); - const [mounted, setMounted] = useState(false); const { compactFormat: githubStars, loading: loadingGithubStars } = useGithubStars(); - const { unreadCount } = useAnnouncements(); - - useEffect(() => setMounted(true), []); return ( { )} - - - {mounted && unreadCount > 0 && ( - - {unreadCount > 99 ? "99+" : unreadCount} - - )} -
diff --git a/surfsense_web/components/layout/providers/LayoutDataProvider.tsx b/surfsense_web/components/layout/providers/LayoutDataProvider.tsx index 0f6aaaf0d..f378990a5 100644 --- a/surfsense_web/components/layout/providers/LayoutDataProvider.tsx +++ b/surfsense_web/components/layout/providers/LayoutDataProvider.tsx @@ -114,6 +114,9 @@ export function LayoutDataProvider({ const [isInboxSidebarOpen, setIsInboxSidebarOpen] = useState(false); const [isInboxDocked, setIsInboxDocked] = useState(false); + // Announcements sidebar state + const [isAnnouncementsSidebarOpen, setIsAnnouncementsSidebarOpen] = useState(false); + // Search space dialog state const [isCreateSearchSpaceDialogOpen, setIsCreateSearchSpaceDialogOpen] = useState(false); @@ -292,6 +295,12 @@ export function LayoutDataProvider({ // Navigation items const navItems: NavItem[] = useMemo( () => [ + { + title: "Documents", + url: `/dashboard/${searchSpaceId}/documents`, + icon: SquareLibrary, + isActive: pathname?.includes("/documents"), + }, { title: "Inbox", url: "#inbox", // Special URL to indicate this is handled differently @@ -299,21 +308,22 @@ export function LayoutDataProvider({ isActive: isInboxSidebarOpen, badge: totalUnreadCount > 0 ? formatInboxCount(totalUnreadCount) : undefined, }, - { - title: "Documents", - url: `/dashboard/${searchSpaceId}/documents`, - icon: SquareLibrary, - isActive: pathname?.includes("/documents"), - }, { title: "Announcements", - url: "/announcements", + url: "#announcements", // Special URL to indicate this is handled differently icon: Megaphone, - isActive: pathname?.includes("/announcements"), + isActive: isAnnouncementsSidebarOpen, badge: announcementUnreadCount > 0 ? formatInboxCount(announcementUnreadCount) : undefined, }, ], - [searchSpaceId, pathname, isInboxSidebarOpen, totalUnreadCount, announcementUnreadCount] + [ + searchSpaceId, + pathname, + isInboxSidebarOpen, + totalUnreadCount, + isAnnouncementsSidebarOpen, + announcementUnreadCount, + ] ); // Handlers @@ -411,6 +421,19 @@ export function LayoutDataProvider({ if (!prev) { setIsAllSharedChatsSidebarOpen(false); setIsAllPrivateChatsSidebarOpen(false); + setIsAnnouncementsSidebarOpen(false); + } + return !prev; + }); + return; + } + // Handle announcements specially - toggle sidebar instead of navigating + if (item.url === "#announcements") { + setIsAnnouncementsSidebarOpen((prev) => { + if (!prev) { + setIsInboxSidebarOpen(false); + setIsAllSharedChatsSidebarOpen(false); + setIsAllPrivateChatsSidebarOpen(false); } return !prev; }); @@ -418,7 +441,13 @@ export function LayoutDataProvider({ } router.push(item.url); }, - [router] + [ + router, + setIsAllPrivateChatsSidebarOpen, + setIsAllSharedChatsSidebarOpen, + setIsAnnouncementsSidebarOpen, + setIsInboxSidebarOpen, + ] ); const handleNewChat = useCallback(() => { @@ -515,12 +544,14 @@ export function LayoutDataProvider({ setIsAllSharedChatsSidebarOpen(true); setIsAllPrivateChatsSidebarOpen(false); setIsInboxSidebarOpen(false); + setIsAnnouncementsSidebarOpen(false); }, []); const handleViewAllPrivateChats = useCallback(() => { setIsAllPrivateChatsSidebarOpen(true); setIsAllSharedChatsSidebarOpen(false); setIsInboxSidebarOpen(false); + setIsAnnouncementsSidebarOpen(false); }, []); // Delete handlers @@ -641,6 +672,10 @@ export function LayoutDataProvider({ isDocked: isInboxDocked, onDockedChange: setIsInboxDocked, }} + announcementsPanel={{ + open: isAnnouncementsSidebarOpen, + onOpenChange: setIsAnnouncementsSidebarOpen, + }} allSharedChatsPanel={{ open: isAllSharedChatsSidebarOpen, onOpenChange: setIsAllSharedChatsSidebarOpen, diff --git a/surfsense_web/components/layout/ui/shell/LayoutShell.tsx b/surfsense_web/components/layout/ui/shell/LayoutShell.tsx index 107e15d2b..03628d0ac 100644 --- a/surfsense_web/components/layout/ui/shell/LayoutShell.tsx +++ b/surfsense_web/components/layout/ui/shell/LayoutShell.tsx @@ -13,6 +13,7 @@ import { IconRail } from "../icon-rail"; import { AllPrivateChatsSidebar, AllSharedChatsSidebar, + AnnouncementsSidebar, InboxSidebar, MobileSidebar, MobileSidebarTrigger, @@ -82,6 +83,10 @@ interface LayoutShellProps { className?: string; // Inbox props inbox?: InboxProps; + announcementsPanel?: { + open: boolean; + onOpenChange: (open: boolean) => void; + }; isLoadingChats?: boolean; // All chats panel props allSharedChatsPanel?: { @@ -130,6 +135,7 @@ export function LayoutShell({ children, className, inbox, + announcementsPanel, isLoadingChats = false, allSharedChatsPanel, allPrivateChatsPanel, @@ -211,6 +217,15 @@ export function LayoutShell({ /> )} + {/* Mobile Announcements Sidebar - only render when open to avoid scroll blocking */} + {announcementsPanel?.open && ( + setMobileMenuOpen(false)} + /> + )} + {/* Mobile All Shared Chats - slide-out panel */} {allSharedChatsPanel && ( )} + {/* Announcements Sidebar - positioned absolutely on top of content */} + {announcementsPanel && ( + + )} + {/* All Shared Chats - slide-out panel */} {allSharedChatsPanel && ( void; + onCloseMobileSidebar?: () => void; +} + +export function AnnouncementsSidebar({ + open, + onOpenChange, + onCloseMobileSidebar, +}: AnnouncementsSidebarProps) { + const isMobile = !useMediaQuery("(min-width: 640px)"); + const { announcements, markAllRead } = useAnnouncements(); + + useEffect(() => { + if (!open) return; + markAllRead(); + }, [open, markAllRead]); + + const body = ( +
+
+
+
+ {isMobile && ( + + )} +

Announcements

+
+
+
+ +
+ {announcements.length === 0 ? ( + + ) : ( +
+ {announcements.map((announcement) => ( + + ))} +
+ )} +
+
+ ); + + return ( + + {body} + + ); +} + diff --git a/surfsense_web/components/layout/ui/sidebar/index.ts b/surfsense_web/components/layout/ui/sidebar/index.ts index d9c5edee5..e7590b2d7 100644 --- a/surfsense_web/components/layout/ui/sidebar/index.ts +++ b/surfsense_web/components/layout/ui/sidebar/index.ts @@ -1,5 +1,6 @@ export { AllPrivateChatsSidebar } from "./AllPrivateChatsSidebar"; export { AllSharedChatsSidebar } from "./AllSharedChatsSidebar"; +export { AnnouncementsSidebar } from "./AnnouncementsSidebar"; export { ChatListItem } from "./ChatListItem"; export { InboxSidebar } from "./InboxSidebar"; export { MobileSidebar, MobileSidebarTrigger } from "./MobileSidebar"; diff --git a/surfsense_web/components/pricing/pricing-section.tsx b/surfsense_web/components/pricing/pricing-section.tsx index 7528aeb0b..ce7b06da6 100644 --- a/surfsense_web/components/pricing/pricing-section.tsx +++ b/surfsense_web/components/pricing/pricing-section.tsx @@ -8,43 +8,34 @@ const demoPlans = [ price: "0", yearlyPrice: "0", period: "", - billingText: "Includes 30 day PRO trial", + billingText: "", features: [ - "Open source on GitHub", + "Self Hostable", "Upload and chat with 300+ pages of content", - "Connects with 8 popular sources, like Drive and Notion", - "Includes limited access to ChatGPT, Claude, and DeepSeek models", - "Supports 100+ more LLMs, including Gemini, Llama and many more", - "50+ File extensions supported", - "Generate podcasts in seconds", - "Cross-Browser Extension for dynamic webpages including authenticated content", + "Includes access to ChatGPT text and audio models", + "Realtime Collaborative Group Chats with teammates", "Community support on Discord", ], - description: "Powerful features with some limitations", + description: "", buttonText: "Get Started", - href: "/", + href: "/login", isPopular: false, }, { name: "PRO", - price: "10", - yearlyPrice: "10", - period: "user / month", - billingText: "billed annually", + price: "0", + yearlyPrice: "0", + period: "", + billingText: "Free during beta", features: [ "Everything in Free", - "Upload and chat with 5,000+ pages of content per user", - "Connects with 15+ external sources, like Slack and Airtable", - "Includes extended access to ChatGPT, Claude, and DeepSeek models", - "Collaboration and commenting features", - "Shared BYOK (Bring Your Own Key)", - "Team and role management", - "Planned: Centralized billing", - "Priority support", + "Includes 6000+ pages of content", + "Access to more models and providers", + "Priority support on Discord", ], - description: "The AI knowledge base for individuals and teams", - buttonText: "Upgrade", - href: "/contact", + description: "", + buttonText: "Get Started", + href: "/login", isPopular: true, }, { @@ -55,12 +46,9 @@ const demoPlans = [ billingText: "", features: [ "Everything in Pro", - "Connect and chat with virtually unlimited pages of content", - "Limit models and/or providers", "On-prem or VPC deployment", - "Planned: Audit logs and compliance", - "Planned: SSO, OIDC & SAML", - "Planned: Role-based access control (RBAC)", + "Audit logs and compliance", + "SSO, OIDC & SAML", "White-glove setup and deployment", "Monthly managed updates and maintenance", "SLA commitments", diff --git a/surfsense_web/components/settings/roles-manager.tsx b/surfsense_web/components/settings/roles-manager.tsx index 96ab2551f..820fd11e5 100644 --- a/surfsense_web/components/settings/roles-manager.tsx +++ b/surfsense_web/components/settings/roles-manager.tsx @@ -7,6 +7,7 @@ import { Edit2, FileText, Globe, + Logs, type LucideIcon, MessageCircle, MessageSquare, @@ -14,7 +15,6 @@ import { MoreHorizontal, Plug, Plus, - Logs, Settings, Shield, Trash2, @@ -23,13 +23,13 @@ import { import { motion } from "motion/react"; import { useCallback, useEffect, useMemo, useState } from "react"; import { toast } from "sonner"; +import { myAccessAtom } from "@/atoms/members/members-query.atoms"; +import { permissionsAtom } from "@/atoms/permissions/permissions-query.atoms"; import { createRoleMutationAtom, deleteRoleMutationAtom, updateRoleMutationAtom, } from "@/atoms/roles/roles-mutation.atoms"; -import { permissionsAtom } from "@/atoms/permissions/permissions-query.atoms"; -import { myAccessAtom } from "@/atoms/members/members-query.atoms"; import { AlertDialog, AlertDialogAction, diff --git a/surfsense_web/components/sources/DocumentUploadTab.tsx b/surfsense_web/components/sources/DocumentUploadTab.tsx index 94ba187d6..cae78f7b7 100644 --- a/surfsense_web/components/sources/DocumentUploadTab.tsx +++ b/surfsense_web/components/sources/DocumentUploadTab.tsx @@ -8,6 +8,7 @@ import { useCallback, useMemo, useRef, useState } from "react"; import { useDropzone } from "react-dropzone"; import { toast } from "sonner"; import { uploadDocumentMutationAtom } from "@/atoms/documents/document-mutation.atoms"; +import { SummaryConfig } from "@/components/assistant-ui/connector-popup/components/summary-config"; import { Accordion, AccordionContent, @@ -110,8 +111,8 @@ const FILE_TYPE_CONFIG: Record> = { const cardClass = "border border-border bg-slate-400/5 dark:bg-white/5"; -// Upload limits -const MAX_FILES = 10; +// Upload limits — files are sent in batches of 5 to avoid proxy timeouts +const MAX_FILES = 50; const MAX_TOTAL_SIZE_MB = 200; const MAX_TOTAL_SIZE_BYTES = MAX_TOTAL_SIZE_MB * 1024 * 1024; @@ -124,6 +125,7 @@ export function DocumentUploadTab({ const [files, setFiles] = useState([]); const [uploadProgress, setUploadProgress] = useState(0); const [accordionValue, setAccordionValue] = useState(""); + const [shouldSummarize, setShouldSummarize] = useState(false); const [uploadDocumentMutation] = useAtom(uploadDocumentMutationAtom); const { mutate: uploadDocuments, isPending: isUploading } = uploadDocumentMutation; const fileInputRef = useRef(null); @@ -216,7 +218,7 @@ export function DocumentUploadTab({ }, 200); uploadDocuments( - { files, search_space_id: Number(searchSpaceId) }, + { files, search_space_id: Number(searchSpaceId), should_summarize: shouldSummarize }, { onSuccess: () => { clearInterval(progressInterval); @@ -413,6 +415,10 @@ export function DocumentUploadTab({ )} +
+ +
+ )} - {/* Display mode */} - {!isEditing && ( -
-
-

Name

-

{committedArgs?.name ?? args.name}

-
-
-

Type

-

- {FILE_TYPE_LABELS[committedArgs?.file_type ?? args.file_type] ?? committedArgs?.file_type ?? args.file_type} -

-
- {(committedArgs?.content ?? args.content) && ( + {/* Display mode */} + {!isEditing && ( +
-

Content

-

- {committedArgs?.content ?? args.content} +

Name

+

{committedArgs?.name ?? args.name}

+
+
+

Type

+

+ {FILE_TYPE_LABELS[committedArgs?.file_type ?? args.file_type] ?? + committedArgs?.file_type ?? + args.file_type}

- )} -
- )} + {(committedArgs?.content ?? args.content) && ( +
+

Content

+

+ {committedArgs?.content ?? args.content} +

+
+ )} +
+ )} {/* Edit mode */} {isEditing && !decided && ( @@ -341,26 +343,26 @@ function ApprovalCard({

) : isEditing ? ( <> - + + )} {canEdit && (
- {result.message && ( -

{result.message}

- )} + {result.message &&

{result.message}

}

{result.warning}

diff --git a/surfsense_web/components/tool-ui/index.ts b/surfsense_web/components/tool-ui/index.ts index c04dd5ccc..b6462f80a 100644 --- a/surfsense_web/components/tool-ui/index.ts +++ b/surfsense_web/components/tool-ui/index.ts @@ -78,6 +78,13 @@ export { type SerializablePlan, type TodoStatus, } from "./plan"; +export { + type ExecuteArgs, + ExecuteArgsSchema, + type ExecuteResult, + ExecuteResultSchema, + SandboxExecuteToolUI, +} from "./sandbox-execute"; export { type ScrapeWebpageArgs, ScrapeWebpageArgsSchema, diff --git a/surfsense_web/components/tool-ui/sandbox-execute.tsx b/surfsense_web/components/tool-ui/sandbox-execute.tsx new file mode 100644 index 000000000..d4e60de9e --- /dev/null +++ b/surfsense_web/components/tool-ui/sandbox-execute.tsx @@ -0,0 +1,420 @@ +"use client"; + +import { makeAssistantToolUI } from "@assistant-ui/react"; +import { + AlertCircleIcon, + CheckCircle2Icon, + ChevronRightIcon, + DownloadIcon, + FileIcon, + Loader2Icon, + TerminalIcon, + XCircleIcon, +} from "lucide-react"; +import { useCallback, useMemo, useState } from "react"; +import { z } from "zod"; +import { Badge } from "@/components/ui/badge"; +import { Button } from "@/components/ui/button"; +import { Collapsible, CollapsibleContent, CollapsibleTrigger } from "@/components/ui/collapsible"; +import { getBearerToken } from "@/lib/auth-utils"; +import { BACKEND_URL } from "@/lib/env-config"; +import { cn } from "@/lib/utils"; + +// ============================================================================ +// Zod Schemas +// ============================================================================ + +const ExecuteArgsSchema = z.object({ + command: z.string(), + timeout: z.number().nullish(), +}); + +const ExecuteResultSchema = z.object({ + result: z.string().nullish(), + exit_code: z.number().nullish(), + output: z.string().nullish(), + error: z.string().nullish(), + status: z.string().nullish(), + thread_id: z.string().nullish(), +}); + +// ============================================================================ +// Types +// ============================================================================ + +type ExecuteArgs = z.infer; +type ExecuteResult = z.infer; + +interface SandboxFile { + path: string; + name: string; +} + +interface ParsedOutput { + exitCode: number | null; + output: string; + displayOutput: string; + truncated: boolean; + isError: boolean; + files: SandboxFile[]; +} + +// ============================================================================ +// Helpers +// ============================================================================ + +const SANDBOX_FILE_RE = /^SANDBOX_FILE:\s*(.+)$/gm; + +function extractSandboxFiles(text: string): SandboxFile[] { + const files: SandboxFile[] = []; + let match: RegExpExecArray | null; + while ((match = SANDBOX_FILE_RE.exec(text)) !== null) { + const filePath = match[1].trim(); + if (filePath) { + const name = filePath.includes("/") ? filePath.split("/").pop() || filePath : filePath; + files.push({ path: filePath, name }); + } + } + SANDBOX_FILE_RE.lastIndex = 0; + return files; +} + +function stripSandboxFileLines(text: string): string { + return text + .replace(/^SANDBOX_FILE:\s*.+$/gm, "") + .replace(/\n{3,}/g, "\n\n") + .trim(); +} + +function parseExecuteResult(result: ExecuteResult): ParsedOutput { + const raw = result.result || result.output || ""; + + if (result.error) { + return { + exitCode: null, + output: result.error, + displayOutput: result.error, + truncated: false, + isError: true, + files: [], + }; + } + + if (result.exit_code !== undefined && result.exit_code !== null) { + const files = extractSandboxFiles(raw); + const displayOutput = stripSandboxFileLines(raw); + return { + exitCode: result.exit_code, + output: raw, + displayOutput, + truncated: raw.includes("[Output was truncated"), + isError: result.exit_code !== 0, + files, + }; + } + + const exitMatch = raw.match(/^Exit code:\s*(\d+)/); + if (exitMatch) { + const exitCode = parseInt(exitMatch[1], 10); + const outputMatch = raw.match(/\nOutput:\n([\s\S]*)/); + const output = outputMatch ? outputMatch[1] : ""; + const files = extractSandboxFiles(output); + const displayOutput = stripSandboxFileLines(output); + return { + exitCode, + output, + displayOutput, + truncated: raw.includes("[Output was truncated"), + isError: exitCode !== 0, + files, + }; + } + + if (raw.startsWith("Error:")) { + return { + exitCode: null, + output: raw, + displayOutput: raw, + truncated: false, + isError: true, + files: [], + }; + } + + const files = extractSandboxFiles(raw); + const displayOutput = stripSandboxFileLines(raw); + return { exitCode: null, output: raw, displayOutput, truncated: false, isError: false, files }; +} + +function truncateCommand(command: string, maxLen = 80): string { + if (command.length <= maxLen) return command; + return command.slice(0, maxLen) + "…"; +} + +// ============================================================================ +// Download helper +// ============================================================================ + +async function downloadSandboxFile(threadId: string, filePath: string, fileName: string) { + const token = getBearerToken(); + const url = `${BACKEND_URL}/api/v1/threads/${threadId}/sandbox/download?path=${encodeURIComponent(filePath)}`; + const res = await fetch(url, { + headers: { Authorization: `Bearer ${token || ""}` }, + }); + if (!res.ok) { + throw new Error(`Download failed: ${res.statusText}`); + } + const blob = await res.blob(); + const blobUrl = URL.createObjectURL(blob); + const a = document.createElement("a"); + a.href = blobUrl; + a.download = fileName; + document.body.appendChild(a); + a.click(); + a.remove(); + URL.revokeObjectURL(blobUrl); +} + +// ============================================================================ +// Sub-Components +// ============================================================================ + +function ExecuteLoading({ command }: { command: string }) { + return ( +
+ + + {truncateCommand(command)} + +
+ ); +} + +function ExecuteErrorState({ command, error }: { command: string; error: string }) { + return ( +
+
+
+ +
+
+

Execution failed

+ + $ {command} + +

{error}

+
+
+
+ ); +} + +function ExecuteCancelledState({ command }: { command: string }) { + return ( +
+

+ + $ {command} +

+
+ ); +} + +function SandboxFileDownload({ file, threadId }: { file: SandboxFile; threadId: string }) { + const [downloading, setDownloading] = useState(false); + const [error, setError] = useState(null); + + const handleDownload = useCallback(async () => { + setDownloading(true); + setError(null); + try { + await downloadSandboxFile(threadId, file.path, file.name); + } catch (e) { + setError(e instanceof Error ? e.message : "Download failed"); + } finally { + setDownloading(false); + } + }, [threadId, file.path, file.name]); + + return ( + + ); +} + +function ExecuteCompleted({ + command, + parsed, + threadId, +}: { + command: string; + parsed: ParsedOutput; + threadId: string | null; +}) { + const [open, setOpen] = useState(false); + const isLongCommand = command.length > 80 || command.includes("\n"); + const hasTextContent = parsed.displayOutput.trim().length > 0 || isLongCommand; + const hasFiles = parsed.files.length > 0 && !!threadId; + const hasContent = hasTextContent || hasFiles; + + const exitBadge = useMemo(() => { + if (parsed.exitCode === null) return null; + const success = parsed.exitCode === 0; + return ( + + {success ? : } + {parsed.exitCode} + + ); + }, [parsed.exitCode]); + + return ( +
+ + + + + + {truncateCommand(command)} + + {hasFiles && !open && ( + + + {parsed.files.length} + + )} + {exitBadge} + + + +
+ {isLongCommand && ( +
+

+ Command +

+ 
+									{command}
+
+
+ )} + {parsed.displayOutput.trim().length > 0 && ( +
+ {(isLongCommand || hasFiles) && ( +

+ Output +

+ )} + 
+									{parsed.displayOutput}
+
+
+ )} + {parsed.truncated && ( +

+ Output was truncated due to size limits +

+ )} + {hasFiles && threadId && ( +
+

+ Files +

+
+ {parsed.files.map((file) => ( + + ))} +
+
+ )} +
+ + +
+ ); +} + +// ============================================================================ +// Tool UI +// ============================================================================ + +export const SandboxExecuteToolUI = makeAssistantToolUI({ + toolName: "execute", + render: function SandboxExecuteUI({ args, result, status }) { + const command = args.command || "…"; + + if (status.type === "running" || status.type === "requires-action") { + return ; + } + + if (status.type === "incomplete") { + if (status.reason === "cancelled") { + return ; + } + if (status.reason === "error") { + return ( + + ); + } + } + + if (!result) { + return ; + } + + if (result.error && !result.result && !result.output) { + return ; + } + + const parsed = parseExecuteResult(result); + const threadId = result.thread_id || null; + return ; + }, +}); + +export { ExecuteArgsSchema, ExecuteResultSchema, type ExecuteArgs, type ExecuteResult }; diff --git a/surfsense_web/components/ui/expanded-gif-overlay.tsx b/surfsense_web/components/ui/expanded-gif-overlay.tsx index 1e4f622ba..c53dbcdc4 100644 --- a/surfsense_web/components/ui/expanded-gif-overlay.tsx +++ b/surfsense_web/components/ui/expanded-gif-overlay.tsx @@ -40,7 +40,7 @@ function ExpandedGifOverlay({ className="max-h-[90vh] max-w-[90vw] cursor-pointer rounded-2xl shadow-2xl" /> , - document.body, + document.body ); } diff --git a/surfsense_web/components/ui/hero-carousel.tsx b/surfsense_web/components/ui/hero-carousel.tsx index c623aa525..141583d67 100644 --- a/surfsense_web/components/ui/hero-carousel.tsx +++ b/surfsense_web/components/ui/hero-carousel.tsx @@ -18,8 +18,7 @@ const carouselItems = [ }, { title: "Search & Citation", - description: - "Ask questions and get cited responses from your knowledge base.", + description: "Ask questions and get cited responses from your knowledge base.", src: "/homepage/hero_tutorial/BSNCGif.gif", }, { @@ -121,9 +120,7 @@ function HeroCarouselCard({

{title}

-

- {description} -

+

{description}

) : frozenFrame ? ( - {title} + {title} ) : (
)} @@ -174,7 +167,7 @@ function HeroCarousel() { directionRef.current = newIndex >= activeIndex ? "forward" : "backward"; setActiveIndex(newIndex); }, - [activeIndex], + [activeIndex] ); useEffect(() => { @@ -246,7 +239,7 @@ function HeroCarousel() { blur: t * 6, }; }, - [activeIndex, cardWidth, baseOffset, stackGap], + [activeIndex, cardWidth, baseOffset, stackGap] ); return ( @@ -287,18 +280,18 @@ function HeroCarousel() { transition={{ duration: 0.7, ease: [0.32, 0.72, 0, 1] }} > - - + animate={{ filter: `blur(${style.blur}px)` }} + transition={{ duration: 0.7, ease: [0.32, 0.72, 0, 1] }} + > + + -The all-in-one Docker image bundles PostgreSQL (with pgvector), Redis, and all SurfSense services. Perfect for quick evaluation and development. - +**Prerequisites:** [Docker Desktop](https://www.docker.com/products/docker-desktop/) must be installed and running. - -Make sure to include the `-v surfsense-data:/data` in your Docker command. This ensures your database and files are properly persisted. - - -### One-Line Installation - -**Linux/macOS:** +#### For Linux/macOS users: ```bash -docker run -d -p 3000:3000 -p 8000:8000 -p 5133:5133 \ - -v surfsense-data:/data \ - --name surfsense \ - --restart unless-stopped \ - ghcr.io/modsetter/surfsense:latest +curl -fsSL https://raw.githubusercontent.com/MODSetter/SurfSense/main/docker/scripts/install.sh | bash ``` -**Windows (PowerShell):** +#### For Windows users (PowerShell): ```powershell -docker run -d -p 3000:3000 -p 8000:8000 -p 5133:5133 ` - -v surfsense-data:/data ` - --name surfsense ` - --restart unless-stopped ` - ghcr.io/modsetter/surfsense:latest +irm https://raw.githubusercontent.com/MODSetter/SurfSense/main/docker/scripts/install.ps1 | iex ``` -> **Note:** A secure `SECRET_KEY` is automatically generated and persisted in the data volume on first run. +This creates a `./surfsense/` directory with `docker-compose.yml` and `.env`, then runs `docker compose up -d`. -### With Custom Configuration - -You can pass any [environment variable](/docs/manual-installation#backend-environment-variables) using `-e` flags: +To skip Watchtower (e.g. in production where you manage updates yourself): ```bash -docker run -d -p 3000:3000 -p 8000:8000 -p 5133:5133 \ - -v surfsense-data:/data \ - -e EMBEDDING_MODEL=openai://text-embedding-ada-002 \ - -e OPENAI_API_KEY=your_openai_api_key \ - -e AUTH_TYPE=GOOGLE \ - -e GOOGLE_OAUTH_CLIENT_ID=your_google_client_id \ - -e GOOGLE_OAUTH_CLIENT_SECRET=your_google_client_secret \ - -e ETL_SERVICE=LLAMACLOUD \ - -e LLAMA_CLOUD_API_KEY=your_llama_cloud_key \ - --name surfsense \ - --restart unless-stopped \ - ghcr.io/modsetter/surfsense:latest +curl -fsSL https://raw.githubusercontent.com/MODSetter/SurfSense/main/docker/scripts/install.sh | bash -s -- --no-watchtower ``` - -- For Google OAuth, create credentials in the [Google Cloud Console](https://console.cloud.google.com/apis/credentials) -- For Airtable connector, create an OAuth integration in the [Airtable Developer Hub](https://airtable.com/create/oauth) -- If deploying behind a reverse proxy with HTTPS, add `-e BACKEND_URL=https://api.yourdomain.com` - +To customise the check interval (default 24h), use `--watchtower-interval=SECONDS`. -### Quick Start with Docker Compose - -For easier management with environment files: +### Option 2 — Manual Docker Compose ```bash -# Download the quick start compose file -curl -o docker-compose.yml https://raw.githubusercontent.com/MODSetter/SurfSense/main/docker-compose.quickstart.yml - -# Create .env file (optional - for custom configuration) -cat > .env << EOF -# EMBEDDING_MODEL=sentence-transformers/all-MiniLM-L6-v2 -# ETL_SERVICE=DOCLING -# SECRET_KEY=your_custom_secret_key # Auto-generated if not set -EOF - -# Start SurfSense +git clone https://github.com/MODSetter/SurfSense.git +cd SurfSense/docker +cp .env.example .env +# Edit .env — at minimum set SECRET_KEY docker compose up -d ``` After starting, access SurfSense at: + - **Frontend**: [http://localhost:3000](http://localhost:3000) - **Backend API**: [http://localhost:8000](http://localhost:8000) - **API Docs**: [http://localhost:8000/docs](http://localhost:8000/docs) -- **Electric-SQL**: [http://localhost:5133](http://localhost:5133) +- **Electric SQL**: [http://localhost:5133](http://localhost:5133) -### Quick Start Environment Variables +--- -| Variable | Description | Default | -|----------|-------------|---------| -| SECRET_KEY | JWT secret key (auto-generated if not set) | Auto-generated | -| AUTH_TYPE | Authentication: `LOCAL` or `GOOGLE` | LOCAL | -| EMBEDDING_MODEL | Model for embeddings | sentence-transformers/all-MiniLM-L6-v2 | -| ETL_SERVICE | Document parser: `DOCLING`, `UNSTRUCTURED`, `LLAMACLOUD` | DOCLING | -| TTS_SERVICE | Text-to-speech for podcasts | local/kokoro | -| STT_SERVICE | Speech-to-text for audio (model size: tiny, base, small, medium, large) | local/base | -| REGISTRATION_ENABLED | Allow new user registration | TRUE | +## Updating -### Useful Commands +**Option 1 — Watchtower daemon (recommended, auto-updates every 24 h):** + +If you used the install script (Option 1 above), Watchtower is already running. No extra setup needed. + +For manual Docker Compose installs (Option 2), start Watchtower separately: ```bash -# View logs -docker logs -f surfsense - -# Stop SurfSense -docker stop surfsense - -# Start SurfSense -docker start surfsense - -# Remove container (data preserved in volume) -docker rm surfsense - -# Remove container AND data -docker rm surfsense && docker volume rm surfsense-data -``` - -### Updating - -To update SurfSense to the latest version, you can use either of the following methods: - - -Your data is safe! The `surfsense-data` volume persists across updates, and database migrations are applied automatically on every startup. - - -**Option 1: Using Watchtower (one-time auto-update)** - -[Watchtower](https://github.com/nicholas-fedor/watchtower) can automatically pull the latest image, stop the old container, and restart it with the same options: - -```bash -docker run --rm \ +docker run -d --name watchtower \ + --restart unless-stopped \ -v /var/run/docker.sock:/var/run/docker.sock \ nickfedor/watchtower \ - --run-once surfsense + --label-enable \ + --interval 86400 +``` + +**Option 2 — Watchtower one-time update:** + +```bash +docker run --rm -v /var/run/docker.sock:/var/run/docker.sock \ + nickfedor/watchtower --run-once \ + --label-filter "com.docker.compose.project=surfsense" ``` -Use the `nickfedor/watchtower` fork. The original `containrrr/watchtower` is no longer maintained and may fail with newer Docker versions. +Use `nickfedor/watchtower`. The original `containrrr/watchtower` is no longer maintained and may fail with newer Docker versions. -**Option 2: Manual Update** +**Option 3 — Manual:** ```bash -# Stop and remove the current container -docker rm -f surfsense - -# Pull the latest image -docker pull ghcr.io/modsetter/surfsense:latest - -# Start with the new image -docker run -d -p 3000:3000 -p 8000:8000 -p 5133:5133 \ - -v surfsense-data:/data \ - --name surfsense \ - --restart unless-stopped \ - ghcr.io/modsetter/surfsense:latest +cd surfsense # or SurfSense/docker if you cloned manually +docker compose pull && docker compose up -d ``` -If you used Docker Compose for the quick start, updating is simpler: +Database migrations are applied automatically on every startup. + +--- + +## Configuration + +All configuration lives in a single `docker/.env` file (or `surfsense/.env` if you used the install script). Copy `.env.example` to `.env` and edit the values you need. + +### Required + +| Variable | Description | +|----------|-------------| +| `SECRET_KEY` | JWT secret key. Generate with: `openssl rand -base64 32`. Auto-generated by the install script. | + +### Core Settings + +| Variable | Description | Default | +|----------|-------------|---------| +| `SURFSENSE_VERSION` | Image tag to deploy. Use `latest`, a clean version (e.g. `0.0.14`), or a specific build (e.g. `0.0.14.1`) | `latest` | +| `AUTH_TYPE` | Authentication method: `LOCAL` (email/password) or `GOOGLE` (OAuth) | `LOCAL` | +| `ETL_SERVICE` | Document parsing: `DOCLING` (local), `UNSTRUCTURED`, or `LLAMACLOUD` | `DOCLING` | +| `EMBEDDING_MODEL` | Embedding model for vector search | `sentence-transformers/all-MiniLM-L6-v2` | +| `TTS_SERVICE` | Text-to-speech provider for podcasts | `local/kokoro` | +| `STT_SERVICE` | Speech-to-text provider for audio files | `local/base` | +| `REGISTRATION_ENABLED` | Allow new user registrations | `TRUE` | + +### Ports + +| Variable | Description | Default | +|----------|-------------|---------| +| `FRONTEND_PORT` | Frontend service port | `3000` | +| `BACKEND_PORT` | Backend API service port | `8000` | +| `ELECTRIC_PORT` | Electric SQL service port | `5133` | + +### Custom Domain / Reverse Proxy + +Only set these if serving SurfSense on a real domain via a reverse proxy (Caddy, Nginx, Cloudflare Tunnel, etc.). Leave commented out for standard localhost deployments. + +| Variable | Description | +|----------|-------------| +| `NEXT_FRONTEND_URL` | Public frontend URL (e.g. `https://app.yourdomain.com`) | +| `BACKEND_URL` | Public backend URL for OAuth callbacks (e.g. `https://api.yourdomain.com`) | +| `NEXT_PUBLIC_FASTAPI_BACKEND_URL` | Backend URL used by the frontend (e.g. `https://api.yourdomain.com`) | +| `NEXT_PUBLIC_ELECTRIC_URL` | Electric SQL URL used by the frontend (e.g. `https://electric.yourdomain.com`) | + +### Database + +Defaults work out of the box. Change for security in production. + +| Variable | Description | Default | +|----------|-------------|---------| +| `DB_USER` | PostgreSQL username | `surfsense` | +| `DB_PASSWORD` | PostgreSQL password | `surfsense` | +| `DB_NAME` | PostgreSQL database name | `surfsense` | +| `DB_HOST` | PostgreSQL host | `db` | +| `DB_PORT` | PostgreSQL port | `5432` | +| `DB_SSLMODE` | SSL mode: `disable`, `require`, `verify-ca`, `verify-full` | `disable` | +| `DATABASE_URL` | Full connection URL override. Use for managed databases (RDS, Supabase, etc.) | *(built from above)* | + +### Electric SQL + +| Variable | Description | Default | +|----------|-------------|---------| +| `ELECTRIC_DB_USER` | Replication user for Electric SQL | `electric` | +| `ELECTRIC_DB_PASSWORD` | Replication password for Electric SQL | `electric_password` | +| `ELECTRIC_DATABASE_URL` | Full connection URL override for Electric. Set to `host.docker.internal` when pointing at a local Postgres instance | *(built from above)* | + +### Authentication + +| Variable | Description | +|----------|-------------| +| `GOOGLE_OAUTH_CLIENT_ID` | Google OAuth client ID (required if `AUTH_TYPE=GOOGLE`) | +| `GOOGLE_OAUTH_CLIENT_SECRET` | Google OAuth client secret (required if `AUTH_TYPE=GOOGLE`) | + +Create credentials at the [Google Cloud Console](https://console.cloud.google.com/apis/credentials). + +### External API Keys + +| Variable | Description | +|----------|-------------| +| `FIRECRAWL_API_KEY` | Firecrawl API key for web crawling | +| `UNSTRUCTURED_API_KEY` | Unstructured.io API key (required if `ETL_SERVICE=UNSTRUCTURED`) | +| `LLAMA_CLOUD_API_KEY` | LlamaCloud API key (required if `ETL_SERVICE=LLAMACLOUD`) | + +### Connector OAuth Keys + +Uncomment the connectors you want to use. Redirect URIs follow the pattern `http://localhost:8000/api/v1/auth//connector/callback`. + +| Connector | Variables | +|-----------|-----------| +| Google Drive / Gmail / Calendar | `GOOGLE_DRIVE_REDIRECT_URI`, `GOOGLE_GMAIL_REDIRECT_URI`, `GOOGLE_CALENDAR_REDIRECT_URI` | +| Notion | `NOTION_CLIENT_ID`, `NOTION_CLIENT_SECRET`, `NOTION_REDIRECT_URI` | +| Slack | `SLACK_CLIENT_ID`, `SLACK_CLIENT_SECRET`, `SLACK_REDIRECT_URI` | +| Discord | `DISCORD_CLIENT_ID`, `DISCORD_CLIENT_SECRET`, `DISCORD_BOT_TOKEN`, `DISCORD_REDIRECT_URI` | +| Jira & Confluence | `ATLASSIAN_CLIENT_ID`, `ATLASSIAN_CLIENT_SECRET`, `JIRA_REDIRECT_URI`, `CONFLUENCE_REDIRECT_URI` | +| Linear | `LINEAR_CLIENT_ID`, `LINEAR_CLIENT_SECRET`, `LINEAR_REDIRECT_URI` | +| ClickUp | `CLICKUP_CLIENT_ID`, `CLICKUP_CLIENT_SECRET`, `CLICKUP_REDIRECT_URI` | +| Airtable | `AIRTABLE_CLIENT_ID`, `AIRTABLE_CLIENT_SECRET`, `AIRTABLE_REDIRECT_URI` | +| Microsoft Teams | `TEAMS_CLIENT_ID`, `TEAMS_CLIENT_SECRET`, `TEAMS_REDIRECT_URI` | + +For Airtable, create an OAuth integration at the [Airtable Developer Hub](https://airtable.com/create/oauth). + +### Observability (optional) + +| Variable | Description | +|----------|-------------| +| `LANGSMITH_TRACING` | Enable LangSmith tracing (`true` / `false`) | +| `LANGSMITH_ENDPOINT` | LangSmith API endpoint | +| `LANGSMITH_API_KEY` | LangSmith API key | +| `LANGSMITH_PROJECT` | LangSmith project name | + +### Advanced (optional) + +| Variable | Description | Default | +|----------|-------------|---------| +| `SCHEDULE_CHECKER_INTERVAL` | How often to check for scheduled connector tasks (e.g. `5m`, `1h`) | `5m` | +| `RERANKERS_ENABLED` | Enable document reranking for improved search | `FALSE` | +| `RERANKERS_MODEL_NAME` | Reranker model name (e.g. `ms-marco-MiniLM-L-12-v2`) | | +| `RERANKERS_MODEL_TYPE` | Reranker model type (e.g. `flashrank`) | | +| `PAGES_LIMIT` | Max pages per user for ETL services | unlimited | + +--- + +## Docker Services + +| Service | Description | +|---------|-------------| +| `db` | PostgreSQL with pgvector extension | +| `redis` | Message broker for Celery | +| `backend` | FastAPI application server | +| `celery_worker` | Background task processing (document indexing, etc.) | +| `celery_beat` | Periodic task scheduler (connector sync) | +| `electric` | Electric SQL — real-time sync for the frontend | +| `frontend` | Next.js web application | + +All services start automatically with `docker compose up -d`. + +The backend includes a health check — dependent services (workers, frontend) wait until the API is fully ready before starting. You can monitor startup progress with `docker compose ps` (look for `(health: starting)` → `(healthy)`). + +--- + +## Development Compose File + +If you're contributing to SurfSense and want to build from source, use `docker-compose.dev.yml` instead: ```bash -docker compose -f docker-compose.quickstart.yml pull -docker compose -f docker-compose.quickstart.yml up -d +cd SurfSense/docker +docker compose -f docker-compose.dev.yml up --build +``` + +This file builds the backend and frontend from your local source code (instead of pulling prebuilt images) and includes pgAdmin for database inspection at [http://localhost:5050](http://localhost:5050). Use the production `docker-compose.yml` for all other cases. + +The following `.env` variables are **only used by the dev compose file** (they have no effect on the production `docker-compose.yml`): + +| Variable | Description | Default | +|----------|-------------|---------| +| `PGADMIN_PORT` | pgAdmin web UI port | `5050` | +| `PGADMIN_DEFAULT_EMAIL` | pgAdmin login email | `admin@surfsense.com` | +| `PGADMIN_DEFAULT_PASSWORD` | pgAdmin login password | `surfsense` | +| `REDIS_PORT` | Exposed Redis port (internal-only in prod) | `6379` | +| `NEXT_PUBLIC_FASTAPI_BACKEND_AUTH_TYPE` | Frontend build arg for auth type | `LOCAL` | +| `NEXT_PUBLIC_ETL_SERVICE` | Frontend build arg for ETL service | `DOCLING` | +| `NEXT_PUBLIC_DEPLOYMENT_MODE` | Frontend build arg for deployment mode | `self-hosted` | +| `NEXT_PUBLIC_ELECTRIC_AUTH_MODE` | Frontend build arg for Electric auth | `insecure` | + +In the production compose file, the `NEXT_PUBLIC_*` frontend variables are automatically derived from `AUTH_TYPE`, `ETL_SERVICE`, and the port settings. In the dev compose file, they are passed as build args since the frontend is built from source. + +--- + +## Migrating from the All-in-One Container + + +If you were previously using `docker-compose.quickstart.yml` (the legacy all-in-one `surfsense` container), your data lives in a `surfsense-data` volume and requires a **one-time migration** before switching to the current setup. PostgreSQL has been upgraded from version 14 to 17, so a simple volume swap will not work. + +See the full step-by-step guide: [Migrate from the All-in-One Container](/docs/how-to/migrate-from-allinone). + + +--- + +## Useful Commands + +```bash +# View logs (all services) +docker compose logs -f + +# View logs for a specific service +docker compose logs -f backend +docker compose logs -f electric + +# Stop all services +docker compose down + +# Restart a specific service +docker compose restart backend + +# Stop and remove all containers + volumes (destructive!) +docker compose down -v ``` --- -## Full Docker Compose Setup (Production) - -For production deployments with separate services and more control, use the full Docker Compose setup below. - -## Prerequisites - -Before you begin, ensure you have: - -- [Docker](https://docs.docker.com/get-docker/) and [Docker Compose](https://docs.docker.com/compose/install/) installed on your machine -- [Git](https://git-scm.com/downloads) (to clone the repository) -- Completed all the [prerequisite setup steps](/docs) including: - - Auth setup - - **File Processing ETL Service** (choose one): - - Unstructured.io API key (Supports 34+ formats) - - LlamaIndex API key (enhanced parsing, supports 50+ formats) - - Docling (local processing, no API key required, supports PDF, Office docs, images, HTML, CSV) - - Other required API keys - -## Installation Steps - -1. **Configure Environment Variables** - Set up the necessary environment variables: - - **Linux/macOS:** - - ```bash - # Copy example environment files - cp surfsense_backend/.env.example surfsense_backend/.env - cp surfsense_web/.env.example surfsense_web/.env - cp .env.example .env # For Docker-specific settings - ``` - - **Windows (Command Prompt):** - - ```cmd - copy surfsense_backend\.env.example surfsense_backend\.env - copy surfsense_web\.env.example surfsense_web\.env - copy .env.example .env - ``` - - **Windows (PowerShell):** - - ```powershell - Copy-Item -Path surfsense_backend\.env.example -Destination surfsense_backend\.env - Copy-Item -Path surfsense_web\.env.example -Destination surfsense_web\.env - Copy-Item -Path .env.example -Destination .env - ``` - - Edit all `.env` files and fill in the required values: - -### Docker-Specific Environment Variables (Optional) - -| ENV VARIABLE | DESCRIPTION | DEFAULT VALUE | -|----------------------------|-----------------------------------------------------------------------------|---------------------| -| FRONTEND_PORT | Port for the frontend service | 3000 | -| BACKEND_PORT | Port for the backend API service | 8000 | -| POSTGRES_PORT | Port for the PostgreSQL database | 5432 | -| PGADMIN_PORT | Port for pgAdmin web interface | 5050 | -| REDIS_PORT | Port for Redis (used by Celery) | 6379 | -| FLOWER_PORT | Port for Flower (Celery monitoring tool) | 5555 | -| POSTGRES_USER | PostgreSQL username | postgres | -| POSTGRES_PASSWORD | PostgreSQL password | postgres | -| POSTGRES_DB | PostgreSQL database name | surfsense | -| PGADMIN_DEFAULT_EMAIL | Email for pgAdmin login | admin@surfsense.com | -| PGADMIN_DEFAULT_PASSWORD | Password for pgAdmin login | surfsense | -| NEXT_PUBLIC_FASTAPI_BACKEND_URL | URL of the backend API (used by frontend during build and runtime) | http://localhost:8000 | -| NEXT_PUBLIC_FASTAPI_BACKEND_AUTH_TYPE | Authentication method for frontend: `LOCAL` or `GOOGLE` | LOCAL | -| NEXT_PUBLIC_ETL_SERVICE | Document parsing service for frontend UI: `UNSTRUCTURED`, `LLAMACLOUD`, or `DOCLING` | DOCLING | -| ELECTRIC_PORT | Port for Electric-SQL service | 5133 | -| POSTGRES_HOST | PostgreSQL host for Electric connection (`db` for Docker PostgreSQL, `host.docker.internal` for local PostgreSQL) | db | -| ELECTRIC_DB_USER | PostgreSQL username for Electric connection | electric | -| ELECTRIC_DB_PASSWORD | PostgreSQL password for Electric connection | electric_password | -| NEXT_PUBLIC_ELECTRIC_URL | URL for Electric-SQL service (used by frontend) | http://localhost:5133 | - -**Note:** Frontend environment variables with the `NEXT_PUBLIC_` prefix are embedded into the Next.js production build at build time. Since the frontend now runs as a production build in Docker, these variables must be set in the root `.env` file (Docker-specific configuration) and will be passed as build arguments during the Docker build process. - -**Backend Environment Variables:** - -| ENV VARIABLE | DESCRIPTION | -| -------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| DATABASE_URL | PostgreSQL connection string (e.g., `postgresql+asyncpg://postgres:postgres@localhost:5432/surfsense`) | -| SECRET_KEY | JWT Secret key for authentication (should be a secure random string) | -| NEXT_FRONTEND_URL | URL where your frontend application is hosted (e.g., `http://localhost:3000`) | -| BACKEND_URL | (Optional) Public URL of the backend for OAuth callbacks (e.g., `https://api.yourdomain.com`). Required when running behind a reverse proxy with HTTPS. Used to set correct OAuth redirect URLs and secure cookies. | -| AUTH_TYPE | Authentication method: `GOOGLE` for OAuth with Google, `LOCAL` for email/password authentication | -| GOOGLE_OAUTH_CLIENT_ID | (Optional) Client ID from Google Cloud Console (required if AUTH_TYPE=GOOGLE) | -| GOOGLE_OAUTH_CLIENT_SECRET | (Optional) Client secret from Google Cloud Console (required if AUTH_TYPE=GOOGLE) | -| ELECTRIC_DB_USER | (Optional) PostgreSQL username for Electric-SQL connection (default: `electric`) | -| ELECTRIC_DB_PASSWORD | (Optional) PostgreSQL password for Electric-SQL connection (default: `electric_password`) | -| EMBEDDING_MODEL | Name of the embedding model (e.g., `sentence-transformers/all-MiniLM-L6-v2`, `openai://text-embedding-ada-002`) | -| RERANKERS_ENABLED | (Optional) Enable or disable document reranking for improved search results (e.g., `TRUE` or `FALSE`, default: `FALSE`) | -| RERANKERS_MODEL_NAME | Name of the reranker model (e.g., `ms-marco-MiniLM-L-12-v2`) (required if RERANKERS_ENABLED=TRUE) | -| RERANKERS_MODEL_TYPE | Type of reranker model (e.g., `flashrank`) (required if RERANKERS_ENABLED=TRUE) | -| TTS_SERVICE | Text-to-Speech API provider for Podcasts (e.g., `local/kokoro`, `openai/tts-1`). See [supported providers](https://docs.litellm.ai/docs/text_to_speech#supported-providers) | -| TTS_SERVICE_API_KEY | (Optional if local) API key for the Text-to-Speech service | -| TTS_SERVICE_API_BASE | (Optional) Custom API base URL for the Text-to-Speech service | -| STT_SERVICE | Speech-to-Text API provider for Audio Files (e.g., `local/base`, `openai/whisper-1`). See [supported providers](https://docs.litellm.ai/docs/audio_transcription#supported-providers) | -| STT_SERVICE_API_KEY | (Optional if local) API key for the Speech-to-Text service | -| STT_SERVICE_API_BASE | (Optional) Custom API base URL for the Speech-to-Text service | -| FIRECRAWL_API_KEY | API key for Firecrawl service for web crawling | -| ETL_SERVICE | Document parsing service: `UNSTRUCTURED` (supports 34+ formats), `LLAMACLOUD` (supports 50+ formats including legacy document types), or `DOCLING` (local processing, supports PDF, Office docs, images, HTML, CSV) | -| UNSTRUCTURED_API_KEY | API key for Unstructured.io service for document parsing (required if ETL_SERVICE=UNSTRUCTURED) | -| LLAMA_CLOUD_API_KEY | API key for LlamaCloud service for document parsing (required if ETL_SERVICE=LLAMACLOUD) | -| CELERY_BROKER_URL | Redis connection URL for Celery broker (e.g., `redis://localhost:6379/0`) | -| CELERY_RESULT_BACKEND | Redis connection URL for Celery result backend (e.g., `redis://localhost:6379/0`) | -| SCHEDULE_CHECKER_INTERVAL | (Optional) How often to check for scheduled connector tasks. Format: `` where unit is `m` (minutes) or `h` (hours). Examples: `1m`, `5m`, `1h`, `2h` (default: `1m`) | -| REGISTRATION_ENABLED | (Optional) Enable or disable new user registration (e.g., `TRUE` or `FALSE`, default: `TRUE`) | -| PAGES_LIMIT | (Optional) Maximum pages limit per user for ETL services (default: `999999999` for unlimited in OSS version) | - -**Google Connector OAuth Configuration:** -| ENV VARIABLE | DESCRIPTION | -| -------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| GOOGLE_CALENDAR_REDIRECT_URI | (Optional) Redirect URI for Google Calendar connector OAuth callback (e.g., `http://localhost:8000/api/v1/auth/google/calendar/connector/callback`) | -| GOOGLE_GMAIL_REDIRECT_URI | (Optional) Redirect URI for Gmail connector OAuth callback (e.g., `http://localhost:8000/api/v1/auth/google/gmail/connector/callback`) | -| GOOGLE_DRIVE_REDIRECT_URI | (Optional) Redirect URI for Google Drive connector OAuth callback (e.g., `http://localhost:8000/api/v1/auth/google/drive/connector/callback`) | - -**Connector OAuth Configurations (Optional):** - -| ENV VARIABLE | DESCRIPTION | -| -------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| AIRTABLE_CLIENT_ID | (Optional) Airtable OAuth client ID from [Airtable Developer Hub](https://airtable.com/create/oauth) | -| AIRTABLE_CLIENT_SECRET | (Optional) Airtable OAuth client secret | -| AIRTABLE_REDIRECT_URI | (Optional) Redirect URI for Airtable connector OAuth callback (e.g., `http://localhost:8000/api/v1/auth/airtable/connector/callback`) | -| CLICKUP_CLIENT_ID | (Optional) ClickUp OAuth client ID | -| CLICKUP_CLIENT_SECRET | (Optional) ClickUp OAuth client secret | -| CLICKUP_REDIRECT_URI | (Optional) Redirect URI for ClickUp connector OAuth callback (e.g., `http://localhost:8000/api/v1/auth/clickup/connector/callback`) | -| DISCORD_CLIENT_ID | (Optional) Discord OAuth client ID | -| DISCORD_CLIENT_SECRET | (Optional) Discord OAuth client secret | -| DISCORD_REDIRECT_URI | (Optional) Redirect URI for Discord connector OAuth callback (e.g., `http://localhost:8000/api/v1/auth/discord/connector/callback`) | -| DISCORD_BOT_TOKEN | (Optional) Discord bot token from Developer Portal | -| ATLASSIAN_CLIENT_ID | (Optional) Atlassian OAuth client ID (for Jira and Confluence) | -| ATLASSIAN_CLIENT_SECRET | (Optional) Atlassian OAuth client secret | -| JIRA_REDIRECT_URI | (Optional) Redirect URI for Jira connector OAuth callback (e.g., `http://localhost:8000/api/v1/auth/jira/connector/callback`) | -| CONFLUENCE_REDIRECT_URI | (Optional) Redirect URI for Confluence connector OAuth callback (e.g., `http://localhost:8000/api/v1/auth/confluence/connector/callback`) | -| LINEAR_CLIENT_ID | (Optional) Linear OAuth client ID | -| LINEAR_CLIENT_SECRET | (Optional) Linear OAuth client secret | -| LINEAR_REDIRECT_URI | (Optional) Redirect URI for Linear connector OAuth callback (e.g., `http://localhost:8000/api/v1/auth/linear/connector/callback`) | -| NOTION_CLIENT_ID | (Optional) Notion OAuth client ID | -| NOTION_CLIENT_SECRET | (Optional) Notion OAuth client secret | -| NOTION_REDIRECT_URI | (Optional) Redirect URI for Notion connector OAuth callback (e.g., `http://localhost:8000/api/v1/auth/notion/connector/callback`) | -| SLACK_CLIENT_ID | (Optional) Slack OAuth client ID | -| SLACK_CLIENT_SECRET | (Optional) Slack OAuth client secret | -| SLACK_REDIRECT_URI | (Optional) Redirect URI for Slack connector OAuth callback (e.g., `http://localhost:8000/api/v1/auth/slack/connector/callback`) | -| TEAMS_CLIENT_ID | (Optional) Microsoft Teams OAuth client ID | -| TEAMS_CLIENT_SECRET | (Optional) Microsoft Teams OAuth client secret | -| TEAMS_REDIRECT_URI | (Optional) Redirect URI for Teams connector OAuth callback (e.g., `http://localhost:8000/api/v1/auth/teams/connector/callback`) | - - -**Optional Backend LangSmith Observability:** -| ENV VARIABLE | DESCRIPTION | -|--------------|-------------| -| LANGSMITH_TRACING | Enable LangSmith tracing (e.g., `true`) | -| LANGSMITH_ENDPOINT | LangSmith API endpoint (e.g., `https://api.smith.langchain.com`) | -| LANGSMITH_API_KEY | Your LangSmith API key | -| LANGSMITH_PROJECT | LangSmith project name (e.g., `surfsense`) | - -**Backend Uvicorn Server Configuration:** -| ENV VARIABLE | DESCRIPTION | DEFAULT VALUE | -|------------------------------|---------------------------------------------|---------------| -| UVICORN_HOST | Host address to bind the server | 0.0.0.0 | -| UVICORN_PORT | Port to run the backend API | 8000 | -| UVICORN_LOG_LEVEL | Logging level (e.g., info, debug, warning) | info | -| UVICORN_PROXY_HEADERS | Enable/disable proxy headers | false | -| UVICORN_FORWARDED_ALLOW_IPS | Comma-separated list of allowed IPs | 127.0.0.1 | -| UVICORN_WORKERS | Number of worker processes | 1 | -| UVICORN_ACCESS_LOG | Enable/disable access log (true/false) | true | -| UVICORN_LOOP | Event loop implementation | auto | -| UVICORN_HTTP | HTTP protocol implementation | auto | -| UVICORN_WS | WebSocket protocol implementation | auto | -| UVICORN_LIFESPAN | Lifespan implementation | auto | -| UVICORN_LOG_CONFIG | Path to logging config file or empty string | | -| UVICORN_SERVER_HEADER | Enable/disable Server header | true | -| UVICORN_DATE_HEADER | Enable/disable Date header | true | -| UVICORN_LIMIT_CONCURRENCY | Max concurrent connections | | -| UVICORN_LIMIT_MAX_REQUESTS | Max requests before worker restart | | -| UVICORN_TIMEOUT_KEEP_ALIVE | Keep-alive timeout (seconds) | 5 | -| UVICORN_TIMEOUT_NOTIFY | Worker shutdown notification timeout (sec) | 30 | -| UVICORN_SSL_KEYFILE | Path to SSL key file | | -| UVICORN_SSL_CERTFILE | Path to SSL certificate file | | -| UVICORN_SSL_KEYFILE_PASSWORD | Password for SSL key file | | -| UVICORN_SSL_VERSION | SSL version | | -| UVICORN_SSL_CERT_REQS | SSL certificate requirements | | -| UVICORN_SSL_CA_CERTS | Path to CA certificates file | | -| UVICORN_SSL_CIPHERS | SSL ciphers | | -| UVICORN_HEADERS | Comma-separated list of headers | | -| UVICORN_USE_COLORS | Enable/disable colored logs | true | -| UVICORN_UDS | Unix domain socket path | | -| UVICORN_FD | File descriptor to bind to | | -| UVICORN_ROOT_PATH | Root path for the application | | - -For more details, see the [Uvicorn documentation](https://www.uvicorn.org/#command-line-options). - -### Frontend Environment Variables - -**Important:** Frontend environment variables are now configured in the **Docker-Specific Environment Variables** section above since the Next.js application runs as a production build in Docker. The following `NEXT_PUBLIC_*` variables should be set in your root `.env` file: - -- `NEXT_PUBLIC_FASTAPI_BACKEND_URL` - URL of the backend service -- `NEXT_PUBLIC_FASTAPI_BACKEND_AUTH_TYPE` - Authentication method (`LOCAL` or `GOOGLE`) -- `NEXT_PUBLIC_ETL_SERVICE` - Document parsing service (should match backend `ETL_SERVICE`) -- `NEXT_PUBLIC_ELECTRIC_URL` - URL for Electric-SQL service (default: `http://localhost:5133`) -- `NEXT_PUBLIC_ELECTRIC_AUTH_MODE` - Electric-SQL authentication mode (default: `insecure`) - -These variables are embedded into the application during the Docker build process and affect the frontend's behavior and available features. - -2. **Build and Start Containers** - - Start the Docker containers: - - **Linux/macOS/Windows:** - - ```bash - docker compose up --build - ``` - - To run in detached mode (in the background): - - **Linux/macOS/Windows:** - - ```bash - docker compose up -d - ``` - - **Note for Windows users:** If you're using older Docker Desktop versions, you might need to use `docker compose` (with a space) instead of `docker compose`. - -3. **Access the Applications** - - Once the containers are running, you can access: - - - Frontend: [http://localhost:3000](http://localhost:3000) - - Backend API: [http://localhost:8000](http://localhost:8000) - - API Documentation: [http://localhost:8000/docs](http://localhost:8000/docs) - - Electric-SQL: [http://localhost:5133](http://localhost:5133) - - pgAdmin: [http://localhost:5050](http://localhost:5050) - -## Docker Services Overview - -The Docker setup includes several services that work together: - -- **Backend**: FastAPI application server -- **Frontend**: Next.js web application -- **PostgreSQL (db)**: Database with pgvector extension -- **Redis**: Message broker for Celery -- **Electric-SQL**: Real-time sync service for database operations -- **Celery Worker**: Handles background tasks (document processing, indexing, etc.) -- **Celery Beat**: Scheduler for periodic tasks (enables scheduled connector indexing) - - The schedule interval can be configured using the `SCHEDULE_CHECKER_INTERVAL` environment variable in your backend `.env` file - - Default: checks every minute for connectors that need indexing -- **pgAdmin**: Database management interface - -All services start automatically with `docker compose up`. The Celery Beat service ensures that periodic indexing functionality works out of the box. - -## Using pgAdmin - -pgAdmin is included in the Docker setup to help manage your PostgreSQL database. To connect: - -1. Open pgAdmin at [http://localhost:5050](http://localhost:5050) -2. Login with the credentials from your `.env` file (default: admin@surfsense.com / surfsense) -3. Right-click "Servers" > "Create" > "Server" -4. In the "General" tab, name your connection (e.g., "SurfSense DB") -5. In the "Connection" tab: - - Host: `db` - - Port: `5432` - - Maintenance database: `surfsense` - - Username: `postgres` (or your custom POSTGRES_USER) - - Password: `postgres` (or your custom POSTGRES_PASSWORD) -6. Click "Save" to connect - -## Updating (Full Docker Compose) - -To update the full Docker Compose production setup to the latest version: - -```bash -# Pull latest changes -git pull - -# Rebuild and restart containers -docker compose up --build -d -``` - -Database migrations are applied automatically on startup. - -## Useful Docker Commands - -### Container Management - -- **Stop containers:** - - **Linux/macOS/Windows:** - - ```bash - docker compose down - ``` - -- **View logs:** - - **Linux/macOS/Windows:** - - ```bash - # All services - docker compose logs -f - - # Specific service - docker compose logs -f backend - docker compose logs -f frontend - docker compose logs -f db - ``` - -- **Restart a specific service:** - - **Linux/macOS/Windows:** - - ```bash - docker compose restart backend - ``` - -- **Execute commands in a running container:** - - **Linux/macOS/Windows:** - - ```bash - # Backend - docker compose exec backend python -m pytest - - # Frontend - docker compose exec frontend pnpm lint - ``` - ## Troubleshooting -- **Linux/macOS:** If you encounter permission errors, you may need to run the docker commands with `sudo`. -- **Windows:** If you see access denied errors, make sure you're running Command Prompt or PowerShell as Administrator. -- If ports are already in use, modify the port mappings in the `docker-compose.yml` file. -- For backend dependency issues, check the `Dockerfile` in the backend directory. -- For frontend dependency issues, check the `Dockerfile` in the frontend directory. -- **Windows-specific:** If you encounter line ending issues (CRLF vs LF), configure Git to handle line endings properly with `git config --global core.autocrlf true` before cloning the repository. - -## Next Steps - -Once your installation is complete, you can start using SurfSense! Navigate to the frontend URL and log in using your Google account. +- **Ports already in use** — Change the relevant `*_PORT` variable in `.env` and restart. +- **Permission errors on Linux** — You may need to prefix `docker` commands with `sudo`. +- **Electric SQL not connecting** — Check `docker compose logs electric`. If it shows `domain does not exist: db`, ensure `ELECTRIC_DATABASE_URL` is not set to a stale value in `.env`. +- **Real-time updates not working in browser** — Open DevTools → Console and look for `[Electric]` errors. Check that `NEXT_PUBLIC_ELECTRIC_URL` matches the running Electric SQL address. +- **Line ending issues on Windows** — Run `git config --global core.autocrlf true` before cloning. diff --git a/surfsense_web/content/docs/how-to/electric-sql.mdx b/surfsense_web/content/docs/how-to/electric-sql.mdx index 288745850..fb2cf941a 100644 --- a/surfsense_web/content/docs/how-to/electric-sql.mdx +++ b/surfsense_web/content/docs/how-to/electric-sql.mdx @@ -3,8 +3,6 @@ title: Electric SQL description: Setting up Electric SQL for real-time data synchronization in SurfSense --- -# Electric SQL - [Electric SQL](https://electric-sql.com/) enables real-time data synchronization in SurfSense, providing instant updates for inbox items, document indexing status, and connector sync progress without manual refresh. The frontend uses [PGlite](https://pglite.dev/) (a lightweight PostgreSQL in the browser) to maintain a local database that syncs with the backend via Electric SQL. ## What Does Electric SQL Do? @@ -25,74 +23,29 @@ This means: ## Docker Setup -### All-in-One Quickstart - -The simplest way to run SurfSense with Electric SQL is using the all-in-one Docker image. This bundles everything into a single container: - -- PostgreSQL + pgvector (vector database) -- Redis (task queue) -- Electric SQL (real-time sync) -- Backend API -- Frontend +The `docker-compose.yml` includes the Electric SQL service. It is pre-configured to connect to the Docker-managed `db` container out of the box. ```bash -docker run -d \ - -p 3000:3000 \ - -p 8000:8000 \ - -p 5133:5133 \ - -v surfsense-data:/data \ - --name surfsense \ - ghcr.io/modsetter/surfsense:latest +docker compose up -d ``` -**With custom Electric SQL credentials:** - -```bash -docker run -d \ - -p 3000:3000 \ - -p 8000:8000 \ - -p 5133:5133 \ - -v surfsense-data:/data \ - -e ELECTRIC_DB_USER=your_electric_user \ - -e ELECTRIC_DB_PASSWORD=your_electric_password \ - --name surfsense \ - ghcr.io/modsetter/surfsense:latest -``` - -Access SurfSense at `http://localhost:3000`. Electric SQL is automatically configured and running on port 5133. - -### Docker Compose - -For more control over individual services, use Docker Compose. - -**Quickstart (all-in-one image):** - -```bash -docker compose -f docker-compose.quickstart.yml up -d -``` - -**Standard setup (separate services):** - -The `docker-compose.yml` includes the Electric SQL service configuration: +The Electric SQL service configuration in `docker-compose.yml`: ```yaml electric: - image: electricsql/electric:latest + image: electricsql/electric:1.4.6 ports: - "${ELECTRIC_PORT:-5133}:3000" environment: - - DATABASE_URL=${ELECTRIC_DATABASE_URL:-postgresql://${ELECTRIC_DB_USER:-electric}:${ELECTRIC_DB_PASSWORD:-electric_password}@${POSTGRES_HOST:-db}:${POSTGRES_PORT:-5432}/${POSTGRES_DB:-surfsense}?sslmode=disable} - - ELECTRIC_INSECURE=true - - ELECTRIC_WRITE_TO_PG_MODE=direct - restart: unless-stopped - healthcheck: - test: ["CMD", "curl", "-f", "http://localhost:3000/v1/health"] - interval: 10s - timeout: 5s - retries: 5 + DATABASE_URL: ${ELECTRIC_DATABASE_URL:-postgresql://${ELECTRIC_DB_USER:-electric}:${ELECTRIC_DB_PASSWORD:-electric_password}@${DB_HOST:-db}:${DB_PORT:-5432}/${DB_NAME:-surfsense}?sslmode=${DB_SSLMODE:-disable}} + ELECTRIC_INSECURE: "true" + ELECTRIC_WRITE_TO_PG_MODE: direct + depends_on: + db: + condition: service_healthy ``` -No additional configuration is required - Electric SQL is pre-configured to work with the Docker PostgreSQL instance. +No additional configuration is required — Electric SQL is pre-configured to work with the Docker PostgreSQL instance. ## Manual Setup @@ -102,19 +55,16 @@ Follow the steps below based on your PostgreSQL setup. Ensure your environment files are configured. If you haven't set up SurfSense yet, follow the [Manual Installation Guide](/docs/manual-installation) first. -For Electric SQL, verify these variables are set: - -**Root `.env`:** +For Electric SQL, verify these variables are set in `docker/.env`: ```bash ELECTRIC_PORT=5133 -POSTGRES_HOST=host.docker.internal # Use 'db' for Docker PostgreSQL instance ELECTRIC_DB_USER=electric ELECTRIC_DB_PASSWORD=electric_password NEXT_PUBLIC_ELECTRIC_URL=http://localhost:5133 ``` -**Frontend `.env` (`surfsense_web/.env`):** +**Frontend (`surfsense_web/.env`):** ```bash NEXT_PUBLIC_ELECTRIC_URL=http://localhost:5133 @@ -125,32 +75,17 @@ NEXT_PUBLIC_ELECTRIC_AUTH_MODE=insecure ### Option A: Using Docker PostgreSQL -If you're using the Docker-managed PostgreSQL instance, follow these steps: - -**1. Update environment variable:** - -In your root `.env` file, set: +If you're using the Docker-managed PostgreSQL instance, no extra configuration is needed. Just start the services: ```bash -POSTGRES_HOST=db +docker compose up -d db electric ``` -**2. Start PostgreSQL and Electric SQL:** - -```bash -docker-compose up -d db electric -``` - -**3. Run database migration:** +Then run the database migration and start the backend: ```bash cd surfsense_backend uv run alembic upgrade head -``` - -**4. Start the backend:** - -```bash uv run main.py ``` @@ -160,17 +95,17 @@ Electric SQL is now configured and connected to your Docker PostgreSQL database. ### Option B: Using Local PostgreSQL -If you're using a local PostgreSQL installation, follow these steps: +If you're using a local PostgreSQL installation (e.g. Postgres.app on macOS), follow these steps: **1. Enable logical replication in PostgreSQL:** -Open your `postgresql.conf` file using vim (or your preferred editor): +Open your `postgresql.conf` file: ```bash # Common locations: -# macOS (Homebrew): /opt/homebrew/var/postgresql@15/postgresql.conf -# Linux: /etc/postgresql/15/main/postgresql.conf -# Windows: C:\Program Files\PostgreSQL\15\data\postgresql.conf +# macOS (Postgres.app): ~/Library/Application Support/Postgres/var-17/postgresql.conf +# macOS (Homebrew): /opt/homebrew/var/postgresql@17/postgresql.conf +# Linux: /etc/postgresql/17/main/postgresql.conf sudo vim /path/to/postgresql.conf ``` @@ -178,38 +113,51 @@ sudo vim /path/to/postgresql.conf Add the following settings: ```ini -# Enable logical replication (required for Electric SQL) +# Required for Electric SQL wal_level = logical max_replication_slots = 10 max_wal_senders = 10 ``` -After saving the changes (`:wq` in vim), restart your PostgreSQL server for the configuration to take effect. +After saving, restart PostgreSQL for the settings to take effect. -**2. Update environment variable:** +**2. Create the Electric replication user:** -In your root `.env` file, set: +Connect to your local database as a superuser and run: -```bash -POSTGRES_HOST=host.docker.internal +```sql +CREATE USER electric WITH REPLICATION PASSWORD 'electric_password'; +GRANT CONNECT ON DATABASE surfsense TO electric; +GRANT CREATE ON DATABASE surfsense TO electric; +GRANT USAGE ON SCHEMA public TO electric; +GRANT SELECT ON ALL TABLES IN SCHEMA public TO electric; +GRANT SELECT ON ALL SEQUENCES IN SCHEMA public TO electric; +ALTER DEFAULT PRIVILEGES IN SCHEMA public GRANT SELECT ON TABLES TO electric; +ALTER DEFAULT PRIVILEGES IN SCHEMA public GRANT SELECT ON SEQUENCES TO electric; +CREATE PUBLICATION electric_publication_default; ``` -**3. Start Electric SQL:** +**3. Set `ELECTRIC_DATABASE_URL` in `docker/.env`:** + +Uncomment and update this line to point Electric at your local Postgres via `host.docker.internal` (the hostname Docker containers use to reach the host machine): ```bash -docker-compose up -d electric +ELECTRIC_DATABASE_URL=postgresql://electric:electric_password@host.docker.internal:5432/surfsense?sslmode=disable ``` -**4. Run database migration:** +**4. Start Electric SQL only (skip the Docker `db` container):** + +```bash +docker compose up -d --no-deps electric +``` + +The `--no-deps` flag starts only the `electric` service without starting the Docker-managed `db` container. + +**5. Run database migration and start the backend:** ```bash cd surfsense_backend uv run alembic upgrade head -``` - -**5. Start the backend:** - -```bash uv run main.py ``` @@ -219,12 +167,13 @@ Electric SQL is now configured and connected to your local PostgreSQL database. | Variable | Location | Description | Default | |----------|----------|-------------|---------| -| `ELECTRIC_PORT` | Root `.env` | Port to expose Electric SQL | `5133` | -| `POSTGRES_HOST` | Root `.env` | PostgreSQL host (`db` for Docker, `host.docker.internal` for local) | `host.docker.internal` | -| `ELECTRIC_DB_USER` | Root `.env` | Database user for Electric | `electric` | -| `ELECTRIC_DB_PASSWORD` | Root `.env` | Database password for Electric | `electric_password` | +| `ELECTRIC_PORT` | `docker/.env` | Port to expose Electric SQL | `5133` | +| `ELECTRIC_DB_USER` | `docker/.env` | Database user for Electric replication | `electric` | +| `ELECTRIC_DB_PASSWORD` | `docker/.env` | Database password for Electric replication | `electric_password` | +| `ELECTRIC_DATABASE_URL` | `docker/.env` | Full connection URL override for Electric. Set to use `host.docker.internal` when pointing at a local Postgres instance | *(built from above defaults)* | | `NEXT_PUBLIC_ELECTRIC_URL` | Frontend `.env` | Electric SQL server URL (PGlite connects to this) | `http://localhost:5133` | | `NEXT_PUBLIC_ELECTRIC_AUTH_MODE` | Frontend `.env` | Authentication mode (`insecure` for dev, `secure` for production) | `insecure` | + ## Verify Setup To verify Electric SQL is running correctly: @@ -262,7 +211,7 @@ You should receive: ### Data Not Syncing -- Check Electric SQL logs: `docker logs electric` +- Check Electric SQL logs: `docker compose logs electric` - Verify PostgreSQL replication is working - Ensure the Electric user has proper table permissions diff --git a/surfsense_web/content/docs/how-to/meta.json b/surfsense_web/content/docs/how-to/meta.json index 9051b0585..c8ecb05d9 100644 --- a/surfsense_web/content/docs/how-to/meta.json +++ b/surfsense_web/content/docs/how-to/meta.json @@ -1,5 +1,6 @@ { "title": "How to", - "pages": ["electric-sql", "realtime-collaboration"], + "pages": ["electric-sql", "realtime-collaboration", "migrate-from-allinone"], + "icon": "BookOpen", "defaultOpen": false } diff --git a/surfsense_web/content/docs/how-to/migrate-from-allinone.mdx b/surfsense_web/content/docs/how-to/migrate-from-allinone.mdx new file mode 100644 index 000000000..3de0b043d --- /dev/null +++ b/surfsense_web/content/docs/how-to/migrate-from-allinone.mdx @@ -0,0 +1,195 @@ +--- +title: Migrate from the All-in-One Container +description: How to migrate your data from the legacy surfsense all-in-one Docker image to the current multi-container setup +--- + +The original SurfSense all-in-one image (`ghcr.io/modsetter/surfsense:latest`, run via `docker-compose.quickstart.yml`) stored all data — PostgreSQL, Redis, and configuration — in a single Docker volume named `surfsense-data`. The current setup uses separate named volumes and has upgraded PostgreSQL from **version 14 to 17**. + +Because PostgreSQL data files are not compatible between major versions, a **logical dump and restore** is required. This is a one-time migration. + + +This guide only applies to users who ran the legacy `docker-compose.quickstart.yml` (the all-in-one `surfsense` container). If you were already using `docker/docker-compose.yml`, you do not need to migrate. + + +--- + +## Option A — One command (recommended) + +`install.sh` detects the legacy `surfsense-data` volume and handles the full migration automatically — no separate migration script needed. Just run the same install command you would use for a fresh install: + +```bash +curl -fsSL https://raw.githubusercontent.com/MODSetter/SurfSense/main/docker/scripts/install.sh | bash +``` + +**What it does automatically:** + +1. Downloads all SurfSense files (including `migrate-database.sh`) into `./surfsense/` +2. Detects the `surfsense-data` volume and enters migration mode +3. Stops the old all-in-one container if it is still running +4. Starts a temporary PostgreSQL 14 container and dumps your database +5. Recovers your `SECRET_KEY` from the old volume +6. Starts PostgreSQL 17, restores the dump, runs a smoke test +7. Starts all services + +Your original `surfsense-data` volume is **never deleted** — you remove it manually after verifying. + +### After it completes + +1. Open [http://localhost:3000](http://localhost:3000) and confirm your data is intact. +2. Once satisfied, remove the old volume (irreversible): + ```bash + docker volume rm surfsense-data + ``` +3. Delete the dump file once you no longer need it as a backup: + ```bash + rm ./surfsense_migration_backup.sql + ``` + +### If the migration fails mid-way + +The dump file is saved to `./surfsense_migration_backup.sql` as a checkpoint. Simply re-run `install.sh` — it will detect the existing dump and skip straight to the restore step without re-extracting. + +--- + +## Option B — Manual migration script (custom credentials) + +If you launched the old all-in-one container with custom database credentials (`POSTGRES_USER`, `POSTGRES_PASSWORD`, `POSTGRES_DB` environment variables), the automatic path will use wrong credentials. Run `migrate-database.sh` manually first: + +```bash +# 1. Extract data with your custom credentials +bash ./surfsense/scripts/migrate-database.sh --db-user myuser --db-password mypass --db-name mydb + +# 2. Install and restore (detects the dump automatically) +curl -fsSL https://raw.githubusercontent.com/MODSetter/SurfSense/main/docker/scripts/install.sh | bash +``` + +Or download and run if you haven't run `install.sh` yet: + +```bash +curl -fsSL https://raw.githubusercontent.com/MODSetter/SurfSense/main/docker/scripts/migrate-database.sh -o migrate-database.sh +bash migrate-database.sh --db-user myuser --db-password mypass --db-name mydb +``` + +### Migration script options + +| Flag | Description | Default | +|------|-------------|---------| +| `--db-user USER` | Old PostgreSQL username | `surfsense` | +| `--db-password PASS` | Old PostgreSQL password | `surfsense` | +| `--db-name NAME` | Old PostgreSQL database | `surfsense` | +| `--yes` / `-y` | Skip confirmation prompts (used automatically by `install.sh`) | — | + +--- + +## Option C — Manual steps + +For users who prefer full control or whose platform doesn't support bash scripts (e.g. Windows without WSL2). + +### Step 1 — Stop the old all-in-one container + +Before mounting the `surfsense-data` volume into a new container, stop the existing one to prevent two PostgreSQL processes from writing to the same data directory: + +```bash +docker stop surfsense 2>/dev/null || true +``` + +### Step 2 — Start a temporary PostgreSQL 14 container + +```bash +docker run -d --name surfsense-pg14-temp \ + -v surfsense-data:/data \ + -e PGDATA=/data/postgres \ + -e POSTGRES_USER=surfsense \ + -e POSTGRES_PASSWORD=surfsense \ + -e POSTGRES_DB=surfsense \ + pgvector/pgvector:pg14 +``` + +Wait ~10 seconds, then confirm it is healthy: + +```bash +docker exec surfsense-pg14-temp pg_isready -U surfsense +``` + +### Step 3 — Dump the database + +```bash +docker exec -e PGPASSWORD=surfsense surfsense-pg14-temp \ + pg_dump -U surfsense surfsense > surfsense_backup.sql +``` + +### Step 4 — Recover your SECRET\_KEY + +```bash +docker run --rm -v surfsense-data:/data alpine cat /data/.secret_key +``` + +### Step 5 — Set up the new stack + +```bash +mkdir -p surfsense/scripts +curl -fsSL https://raw.githubusercontent.com/MODSetter/SurfSense/main/docker/docker-compose.yml -o surfsense/docker-compose.yml +curl -fsSL https://raw.githubusercontent.com/MODSetter/SurfSense/main/docker/.env.example -o surfsense/.env.example +curl -fsSL https://raw.githubusercontent.com/MODSetter/SurfSense/main/docker/postgresql.conf -o surfsense/postgresql.conf +curl -fsSL https://raw.githubusercontent.com/MODSetter/SurfSense/main/docker/scripts/init-electric-user.sh -o surfsense/scripts/init-electric-user.sh +chmod +x surfsense/scripts/init-electric-user.sh +cp surfsense/.env.example surfsense/.env +``` + +Set `SECRET_KEY` in `surfsense/.env` to the value from Step 4. + +### Step 6 — Start PostgreSQL 17 and restore + +```bash +cd surfsense +docker compose up -d db +docker compose exec db pg_isready -U surfsense # wait until ready +docker compose exec -T db psql -U surfsense -d surfsense < ../surfsense_backup.sql +``` + +### Step 7 — Start all services + +```bash +docker compose up -d +``` + +### Step 8 — Clean up + +```bash +docker stop surfsense-pg14-temp && docker rm surfsense-pg14-temp +docker volume rm surfsense-data # only after verifying migration succeeded +``` + +--- + +## Troubleshooting + +### `install.sh` runs normally with a blank database (no migration happened) + +The legacy volume was not detected. Confirm it exists: + +```bash +docker volume ls | grep surfsense-data +``` + +If it doesn't appear, the old container may have used a different volume name. Check with: + +```bash +docker volume ls | grep -i surfsense +``` + +### Extraction fails with permission errors + +The script detects the UID of the data files and runs the temporary PG14 container as that user. If you see permission errors in `./surfsense-migration.log`, run `migrate-database.sh` manually and check the log for details. + +### Cannot find `/data/.secret_key` + +The all-in-one entrypoint always writes the key to `/data/.secret_key` unless you explicitly set `SECRET_KEY=` as an environment variable. If the key is missing, the migration script auto-generates a new one (with a warning). You can update it manually in `./surfsense/.env` afterwards. Note that a new key invalidates all existing browser sessions — users will need to log in again. + +### Restore errors after re-running `install.sh` + +If `surfsense-postgres` volume already exists from a previous partial run, remove it before retrying: + +```bash +docker volume rm surfsense-postgres +``` diff --git a/surfsense_web/content/docs/index.mdx b/surfsense_web/content/docs/index.mdx index bb07c5f68..6c0450297 100644 --- a/surfsense_web/content/docs/index.mdx +++ b/surfsense_web/content/docs/index.mdx @@ -1,6 +1,7 @@ --- title: Prerequisites description: Required setup's before setting up SurfSense +icon: ClipboardCheck --- diff --git a/surfsense_web/content/docs/installation.mdx b/surfsense_web/content/docs/installation.mdx index f5e948b64..6aa2eeb90 100644 --- a/surfsense_web/content/docs/installation.mdx +++ b/surfsense_web/content/docs/installation.mdx @@ -1,6 +1,7 @@ --- title: Installation description: Current ways to use SurfSense +icon: Download --- # Installing SurfSense diff --git a/surfsense_web/content/docs/manual-installation.mdx b/surfsense_web/content/docs/manual-installation.mdx index 1d30a12ef..7a974150c 100644 --- a/surfsense_web/content/docs/manual-installation.mdx +++ b/surfsense_web/content/docs/manual-installation.mdx @@ -1,6 +1,7 @@ --- title: Manual Installation description: Setting up SurfSense manually for customized deployments (Preferred) +icon: Wrench --- # Manual Installation (Preferred) diff --git a/surfsense_web/content/docs/meta.json b/surfsense_web/content/docs/meta.json index 3f938f541..f73b59e18 100644 --- a/surfsense_web/content/docs/meta.json +++ b/surfsense_web/content/docs/meta.json @@ -9,6 +9,8 @@ "docker-installation", "manual-installation", "connectors", - "how-to" + "how-to", + "---Development---", + "testing" ] } diff --git a/surfsense_web/content/docs/testing.mdx b/surfsense_web/content/docs/testing.mdx new file mode 100644 index 000000000..9c4682b90 --- /dev/null +++ b/surfsense_web/content/docs/testing.mdx @@ -0,0 +1,105 @@ +--- +title: Testing +description: Running and writing tests for SurfSense +icon: FlaskConical +--- + +SurfSense uses [pytest](https://docs.pytest.org/) with two test layers: **unit** tests (no database) and **integration** tests (require PostgreSQL + pgvector). Tests are self-bootstrapping — they configure the test database, register a user, and clean up automatically. + +## Prerequisites + +- **PostgreSQL + pgvector** running locally (database `surfsense_test` will be used) +- **`REGISTRATION_ENABLED=TRUE`** in your `.env` (this is the default) +- A working LLM model with a valid API key in `global_llm_config.yaml` (for integration tests) + +No Redis or Celery is required — integration tests use an inline task dispatcher. + +## Running Tests + +**Run all tests:** + +```bash +uv run pytest +``` + +**Run by marker:** + +```bash +uv run pytest -m unit # fast, no DB needed +uv run pytest -m integration # requires PostgreSQL + pgvector +``` + +**Available markers:** + +| Marker | Description | +|---|---| +| `unit` | Pure logic tests, no DB or external services | +| `integration` | Tests that require a real PostgreSQL database | + +**Useful flags:** + +| Flag | Description | +|---|---| +| `-s` | Show live output (useful for debugging polling loops) | +| `--tb=long` | Full tracebacks instead of short summaries | +| `-k "test_name"` | Run a single test by name | +| `-o addopts=""` | Override default flags from `pyproject.toml` | + +## Configuration + +Default pytest options are in `surfsense_backend/pyproject.toml`: + +```toml +[tool.pytest.ini_options] +addopts = "-v --tb=short -x --strict-markers -ra --durations=5" +``` + +- `-v` — verbose test names +- `--tb=short` — concise tracebacks on failure +- `-x` — stop on first failure +- `--strict-markers` — reject unregistered markers +- `-ra` — show summary of all non-passing tests +- `--durations=5` — show the 5 slowest tests + +## Environment Variables + +| Variable | Default | Description | +|---|---|---| +| `TEST_DATABASE_URL` | `postgresql+asyncpg://postgres:postgres@localhost:5432/surfsense_test` | Database URL for tests | + +The test suite forces `DATABASE_URL` to point at the test database, so your production database is never touched. + +### Unit Tests + +Pure logic tests that run without a database. Cover model validation, chunking, hashing, and summarization. + +### Integration Tests + +Require PostgreSQL + pgvector. Split into two suites: + +- **`document_upload/`** — Tests the HTTP API through public endpoints: upload, multi-file, duplicate detection, auth, error handling, page limits, and file size limits. Uses an in-process FastAPI client with `ASGITransport`. +- **`indexing_pipeline/`** — Tests pipeline internals directly: `prepare_for_indexing`, `index()`, and `index_uploaded_file()` covering chunking, embedding, summarization, fallbacks, and error handling. + +External boundaries (LLM, embedding, chunking, Redis) are mocked in both suites. + +## How It Works + +1. **Database setup** — `TEST_DATABASE_URL` defaults to `surfsense_test`. Tables and extensions (`vector`, `pg_trgm`) are created once per session and dropped after. +2. **Transaction isolation** — Each test runs inside a savepoint that rolls back, so tests don't affect each other. +3. **User creation** — Integration tests register a test user via `POST /auth/register` on first run, then log in for subsequent requests. +4. **Search space discovery** — Tests call `GET /api/v1/searchspaces` and use the first available space. +5. **Cleanup** — A session fixture purges stale documents before tests run. Per-test cleanup deletes documents via API, falling back to direct DB access for stuck records. + +## Writing New Tests + +1. Create a test file in the appropriate directory (`unit/` or `integration/`). +2. Add the marker at the top of the file: + +```python +import pytest + +pytestmark = pytest.mark.integration # or pytest.mark.unit +``` + +3. Use fixtures from `conftest.py` — `client`, `headers`, `search_space_id`, and `cleanup_doc_ids` are available to integration tests. Unit tests get `make_connector_document` and sample ID fixtures. +4. Register any new markers in `pyproject.toml` under `markers`. diff --git a/surfsense_web/contracts/types/chat-comments.types.ts b/surfsense_web/contracts/types/chat-comments.types.ts index 46e064a4e..cdeca0a44 100644 --- a/surfsense_web/contracts/types/chat-comments.types.ts +++ b/surfsense_web/contracts/types/chat-comments.types.ts @@ -82,6 +82,22 @@ export const getCommentsResponse = z.object({ total_count: z.number(), }); +/** + * Batch-fetch comments for multiple messages + */ +export const getBatchCommentsRequest = z.object({ + message_ids: z.array(z.number()).min(1).max(200), +}); + +export const commentListResponse = z.object({ + comments: z.array(comment), + total_count: z.number(), +}); + +export const getBatchCommentsResponse = z.object({ + comments_by_message: z.record(z.string(), commentListResponse), +}); + /** * Create comment */ @@ -145,6 +161,8 @@ export type MentionComment = z.infer; export type Mention = z.infer; export type GetCommentsRequest = z.infer; export type GetCommentsResponse = z.infer; +export type GetBatchCommentsRequest = z.infer; +export type GetBatchCommentsResponse = z.infer; export type CreateCommentRequest = z.infer; export type CreateCommentResponse = z.infer; export type CreateReplyRequest = z.infer; diff --git a/surfsense_web/contracts/types/connector.types.ts b/surfsense_web/contracts/types/connector.types.ts index a7f8fce99..2204d4e5e 100644 --- a/surfsense_web/contracts/types/connector.types.ts +++ b/surfsense_web/contracts/types/connector.types.ts @@ -41,6 +41,7 @@ export const searchSourceConnector = z.object({ is_active: z.boolean().default(true), last_indexed_at: z.string().nullable(), config: z.record(z.string(), z.any()), + enable_summary: z.boolean().default(false), periodic_indexing_enabled: z.boolean(), indexing_frequency_minutes: z.number().nullable(), next_scheduled_at: z.string().nullable(), @@ -94,6 +95,7 @@ export const createConnectorRequest = z.object({ is_active: true, last_indexed_at: true, config: true, + enable_summary: true, periodic_indexing_enabled: true, indexing_frequency_minutes: true, next_scheduled_at: true, @@ -118,6 +120,7 @@ export const updateConnectorRequest = z.object({ is_active: true, last_indexed_at: true, config: true, + enable_summary: true, periodic_indexing_enabled: true, indexing_frequency_minutes: true, next_scheduled_at: true, diff --git a/surfsense_web/contracts/types/document.types.ts b/surfsense_web/contracts/types/document.types.ts index 6ec577f51..8f4e4c2fd 100644 --- a/surfsense_web/contracts/types/document.types.ts +++ b/surfsense_web/contracts/types/document.types.ts @@ -135,6 +135,7 @@ export const createDocumentResponse = z.object({ export const uploadDocumentRequest = z.object({ files: z.array(z.instanceof(File)), search_space_id: z.number(), + should_summarize: z.boolean().default(false), }); export const uploadDocumentResponse = z.object({ diff --git a/surfsense_web/docker-entrypoint.js b/surfsense_web/docker-entrypoint.js new file mode 100644 index 000000000..7fe697e46 --- /dev/null +++ b/surfsense_web/docker-entrypoint.js @@ -0,0 +1,100 @@ +/** + * Runtime environment variable substitution for Next.js Docker images. + * + * Next.js inlines NEXT_PUBLIC_* values at build time. The Docker image is built + * with unique placeholder strings (e.g. __NEXT_PUBLIC_FASTAPI_BACKEND_URL__). + * This script replaces those placeholders with real values from the container's + * environment variables before the server starts. + * + * Runs once at container startup via docker-entrypoint.sh. + */ + +const fs = require("fs"); +const path = require("path"); + +const replacements = [ + [ + "__NEXT_PUBLIC_FASTAPI_BACKEND_URL__", + process.env.NEXT_PUBLIC_FASTAPI_BACKEND_URL || "http://localhost:8000", + ], + [ + "__NEXT_PUBLIC_ELECTRIC_URL__", + process.env.NEXT_PUBLIC_ELECTRIC_URL || "http://localhost:5133", + ], + [ + "__NEXT_PUBLIC_FASTAPI_BACKEND_AUTH_TYPE__", + process.env.NEXT_PUBLIC_FASTAPI_BACKEND_AUTH_TYPE || "LOCAL", + ], + [ + "__NEXT_PUBLIC_ETL_SERVICE__", + process.env.NEXT_PUBLIC_ETL_SERVICE || "DOCLING", + ], + [ + "__NEXT_PUBLIC_DEPLOYMENT_MODE__", + process.env.NEXT_PUBLIC_DEPLOYMENT_MODE || "self-hosted", + ], + [ + "__NEXT_PUBLIC_ELECTRIC_AUTH_MODE__", + process.env.NEXT_PUBLIC_ELECTRIC_AUTH_MODE || "insecure", + ], +]; + +let filesProcessed = 0; +let filesModified = 0; + +function walk(dir) { + let entries; + try { + entries = fs.readdirSync(dir, { withFileTypes: true }); + } catch { + return; + } + for (const entry of entries) { + const full = path.join(dir, entry.name); + if (entry.isDirectory()) { + walk(full); + } else if (entry.name.endsWith(".js")) { + filesProcessed++; + let content = fs.readFileSync(full, "utf8"); + let changed = false; + for (const [placeholder, value] of replacements) { + if (content.includes(placeholder)) { + content = content.replaceAll(placeholder, value); + changed = true; + } + } + if (changed) { + fs.writeFileSync(full, content); + filesModified++; + } + } + } +} + +console.log("[entrypoint] Replacing environment variable placeholders..."); +for (const [placeholder, value] of replacements) { + console.log(` ${placeholder} -> ${value}`); +} + +walk(path.join(__dirname, ".next")); + +const serverJs = path.join(__dirname, "server.js"); +if (fs.existsSync(serverJs)) { + let content = fs.readFileSync(serverJs, "utf8"); + let changed = false; + filesProcessed++; + for (const [placeholder, value] of replacements) { + if (content.includes(placeholder)) { + content = content.replaceAll(placeholder, value); + changed = true; + } + } + if (changed) { + fs.writeFileSync(serverJs, content); + filesModified++; + } +} + +console.log( + `[entrypoint] Done. Scanned ${filesProcessed} files, modified ${filesModified}.` +); diff --git a/surfsense_web/docker-entrypoint.sh b/surfsense_web/docker-entrypoint.sh new file mode 100644 index 000000000..7f4dfbf25 --- /dev/null +++ b/surfsense_web/docker-entrypoint.sh @@ -0,0 +1,6 @@ +#!/bin/sh +set -e + +node /app/docker-entrypoint.js + +exec node server.js diff --git a/surfsense_web/hooks/use-comments.ts b/surfsense_web/hooks/use-comments.ts index 4f027d67c..2f7128149 100644 --- a/surfsense_web/hooks/use-comments.ts +++ b/surfsense_web/hooks/use-comments.ts @@ -1,4 +1,6 @@ -import { useQuery } from "@tanstack/react-query"; +import { useQuery, useQueryClient } from "@tanstack/react-query"; +import { useEffect, useRef } from "react"; +import type { GetCommentsResponse } from "@/contracts/types/chat-comments.types"; import { chatCommentsApiService } from "@/lib/apis/chat-comments-api.service"; import { cacheKeys } from "@/lib/query-client/cache-keys"; @@ -7,12 +9,109 @@ interface UseCommentsOptions { enabled?: boolean; } +// --------------------------------------------------------------------------- +// Module-level coordination: when a batch request is in-flight, individual +// useComments queryFns piggy-back on it instead of making their own requests. +// +// _batchReady is a promise that resolves once the batch useEffect has had a +// chance to set _batchInflight. Individual queryFns await this gate before +// deciding whether to piggy-back or fetch on their own, eliminating the +// previous race where setTimeout(0) was not enough. +// --------------------------------------------------------------------------- +let _batchInflight: Promise | null = null; +let _batchTargetIds = new Set(); +let _batchReady: Promise | null = null; +let _resolveBatchReady: (() => void) | null = null; + +function resetBatchGate(resolveImmediately = false) { + _batchReady = new Promise((r) => { + _resolveBatchReady = r; + if (resolveImmediately) r(); + }); +} + +// Open the initial gate immediately (no batch pending yet) +resetBatchGate(true); + export function useComments({ messageId, enabled = true }: UseCommentsOptions) { - return useQuery({ + const queryClient = useQueryClient(); + + return useQuery({ queryKey: cacheKeys.comments.byMessage(messageId), queryFn: async () => { + // Wait for the batch gate so the useEffect in useBatchCommentsPreload + // has a chance to set _batchInflight before we decide. + if (_batchReady) { + await _batchReady; + } + + if (_batchInflight && _batchTargetIds.has(messageId)) { + await _batchInflight; + const cached = queryClient.getQueryData(cacheKeys.comments.byMessage(messageId)); + if (cached) return cached; + } + return chatCommentsApiService.getComments({ message_id: messageId }); }, enabled: enabled && !!messageId, + staleTime: 30_000, }); } + +/** + * Batch-fetch comments for all given message IDs in a single request, then + * seed the per-message React Query cache so individual useComments hooks + * resolve from cache instead of firing their own requests. + */ +export function useBatchCommentsPreload(messageIds: number[]) { + const queryClient = useQueryClient(); + const prevKeyRef = useRef(""); + + useEffect(() => { + if (!messageIds.length) return; + + const key = messageIds + .slice() + .sort((a, b) => a - b) + .join(","); + if (key === prevKeyRef.current) return; + prevKeyRef.current = key; + + // Open a new gate so individual queryFns wait for us + resetBatchGate(); + + _batchTargetIds = new Set(messageIds); + let cancelled = false; + + const promise = chatCommentsApiService + .getBatchComments({ message_ids: messageIds }) + .then((data) => { + if (cancelled) return; + for (const [msgIdStr, commentList] of Object.entries(data.comments_by_message)) { + queryClient.setQueryData(cacheKeys.comments.byMessage(Number(msgIdStr)), commentList); + } + }) + .catch(() => { + // Batch failed; individual queryFns will fall through to their own fetch + }) + .finally(() => { + if (_batchInflight === promise) { + _batchInflight = null; + _batchTargetIds = new Set(); + } + }); + + _batchInflight = promise; + + // Release the gate — individual queryFns can now check _batchInflight + _resolveBatchReady?.(); + + return () => { + cancelled = true; + if (_batchInflight === promise) { + _batchInflight = null; + _batchTargetIds = new Set(); + } + }; + }, [messageIds, queryClient]); +} diff --git a/surfsense_web/hooks/use-documents.ts b/surfsense_web/hooks/use-documents.ts index 55d48c4f1..36a359696 100644 --- a/surfsense_web/hooks/use-documents.ts +++ b/surfsense_web/hooks/use-documents.ts @@ -1,5 +1,6 @@ "use client"; +import { useQuery } from "@tanstack/react-query"; import { useCallback, useEffect, useMemo, useRef, useState } from "react"; import type { DocumentTypeEnum } from "@/contracts/types/document.types"; import { documentsApiService } from "@/lib/apis/documents-api.service"; @@ -183,56 +184,47 @@ export function useDocuments( [] ); - // EFFECT 1: Load ALL documents from API (PRIMARY source of truth) - // No type filter — always fetches everything so typeCounts stay complete + // STEP 1: Load ALL documents from API (PRIMARY source of truth). + // Uses React Query for automatic deduplication, caching, and staleTime so + // multiple components mounting useDocuments(sameId) share a single request. + const { + data: apiResponse, + isLoading: apiLoading, + error: apiError, + } = useQuery({ + queryKey: ["documents", "all", searchSpaceId], + queryFn: () => + documentsApiService.getDocuments({ + queryParams: { + search_space_id: searchSpaceId!, + page: 0, + page_size: -1, + }, + }), + enabled: !!searchSpaceId, + staleTime: 30_000, + }); + + // Seed local state from API response (runs once per fresh fetch) useEffect(() => { - if (!searchSpaceId) { - setLoading(false); - return; + if (!apiResponse) return; + populateUserCache(apiResponse.items); + const docs = apiResponse.items.map(apiToDisplayDoc); + setAllDocuments(docs); + apiLoadedRef.current = true; + setError(null); + }, [apiResponse, populateUserCache, apiToDisplayDoc]); + + // Propagate loading / error from React Query + useEffect(() => { + setLoading(apiLoading); + }, [apiLoading]); + + useEffect(() => { + if (apiError) { + setError(apiError instanceof Error ? apiError : new Error("Failed to load documents")); } - - // Capture validated value for async closure - const spaceId = searchSpaceId; - - let mounted = true; - apiLoadedRef.current = false; - - async function loadFromApi() { - try { - setLoading(true); - console.log("[useDocuments] Loading from API (source of truth):", spaceId); - - const response = await documentsApiService.getDocuments({ - queryParams: { - search_space_id: spaceId, - page: 0, - page_size: -1, // Fetch all documents (unfiltered) - }, - }); - - if (!mounted) return; - - populateUserCache(response.items); - const docs = response.items.map(apiToDisplayDoc); - setAllDocuments(docs); - apiLoadedRef.current = true; - setError(null); - console.log("[useDocuments] API loaded", docs.length, "documents"); - } catch (err) { - if (!mounted) return; - console.error("[useDocuments] API load failed:", err); - setError(err instanceof Error ? err : new Error("Failed to load documents")); - } finally { - if (mounted) setLoading(false); - } - } - - loadFromApi(); - - return () => { - mounted = false; - }; - }, [searchSpaceId, populateUserCache, apiToDisplayDoc]); + }, [apiError]); // EFFECT 2: Start Electric sync + live query for real-time updates // No type filter — syncs and queries ALL documents; filtering is client-side diff --git a/surfsense_web/lib/apis/chat-comments-api.service.ts b/surfsense_web/lib/apis/chat-comments-api.service.ts index 952de7a25..f1ec7a5d9 100644 --- a/surfsense_web/lib/apis/chat-comments-api.service.ts +++ b/surfsense_web/lib/apis/chat-comments-api.service.ts @@ -8,8 +8,11 @@ import { type DeleteCommentRequest, deleteCommentRequest, deleteCommentResponse, + type GetBatchCommentsRequest, type GetCommentsRequest, type GetMentionsRequest, + getBatchCommentsRequest, + getBatchCommentsResponse, getCommentsRequest, getCommentsResponse, getMentionsRequest, @@ -22,6 +25,22 @@ import { ValidationError } from "@/lib/error"; import { baseApiService } from "./base-api.service"; class ChatCommentsApiService { + /** + * Batch-fetch comments for multiple messages in one request + */ + getBatchComments = async (request: GetBatchCommentsRequest) => { + const parsed = getBatchCommentsRequest.safeParse(request); + + if (!parsed.success) { + const errorMessage = parsed.error.issues.map((issue) => issue.message).join(", "); + throw new ValidationError(`Invalid request: ${errorMessage}`); + } + + return baseApiService.post("/api/v1/messages/comments/batch", getBatchCommentsResponse, { + body: { message_ids: parsed.data.message_ids }, + }); + }; + /** * Get comments for a message */ diff --git a/surfsense_web/lib/apis/documents-api.service.ts b/surfsense_web/lib/apis/documents-api.service.ts index c9d649c68..9b0d847f4 100644 --- a/surfsense_web/lib/apis/documents-api.service.ts +++ b/surfsense_web/lib/apis/documents-api.service.ts @@ -109,7 +109,9 @@ class DocumentsApiService { }; /** - * Upload document files + * Upload document files in batches to avoid proxy/LB timeouts. + * Files are split into chunks of UPLOAD_BATCH_SIZE and sent as separate + * requests. Results are aggregated into a single response. */ uploadDocument = async (request: UploadDocumentRequest) => { const parsedRequest = uploadDocumentRequest.safeParse(request); @@ -121,16 +123,54 @@ class DocumentsApiService { throw new ValidationError(`Invalid request: ${errorMessage}`); } - // Create FormData for file upload - const formData = new FormData(); - parsedRequest.data.files.forEach((file) => { - formData.append("files", file); - }); - formData.append("search_space_id", String(parsedRequest.data.search_space_id)); + const { files, search_space_id, should_summarize } = parsedRequest.data; + const UPLOAD_BATCH_SIZE = 5; - return baseApiService.postFormData(`/api/v1/documents/fileupload`, uploadDocumentResponse, { - body: formData, - }); + const batches: File[][] = []; + for (let i = 0; i < files.length; i += UPLOAD_BATCH_SIZE) { + batches.push(files.slice(i, i + UPLOAD_BATCH_SIZE)); + } + + const allDocumentIds: number[] = []; + const allDuplicateIds: number[] = []; + let totalFiles = 0; + let pendingFiles = 0; + let skippedDuplicates = 0; + + for (const batch of batches) { + const formData = new FormData(); + batch.forEach((file) => formData.append("files", file)); + formData.append("search_space_id", String(search_space_id)); + formData.append("should_summarize", String(should_summarize)); + + const controller = new AbortController(); + const timeoutId = setTimeout(() => controller.abort(), 120_000); + + try { + const result = await baseApiService.postFormData( + `/api/v1/documents/fileupload`, + uploadDocumentResponse, + { body: formData, signal: controller.signal } + ); + + allDocumentIds.push(...(result.document_ids ?? [])); + allDuplicateIds.push(...(result.duplicate_document_ids ?? [])); + totalFiles += result.total_files ?? batch.length; + pendingFiles += result.pending_files ?? 0; + skippedDuplicates += result.skipped_duplicates ?? 0; + } finally { + clearTimeout(timeoutId); + } + } + + return { + message: "Files uploaded for processing" as const, + document_ids: allDocumentIds, + duplicate_document_ids: allDuplicateIds, + total_files: totalFiles, + pending_files: pendingFiles, + skipped_duplicates: skippedDuplicates, + }; }; /** diff --git a/surfsense_web/lib/electric/client.ts b/surfsense_web/lib/electric/client.ts index c8bbd60fa..6dda662d7 100644 --- a/surfsense_web/lib/electric/client.ts +++ b/surfsense_web/lib/electric/client.ts @@ -70,7 +70,8 @@ const pendingSyncs = new Map>(); // v5: fixed duplicate key errors, stable cutoff dates, onMustRefetch handler, // real-time documents table with title/created_by_id/status columns, // consolidated single documents sync, pending state for document queue visibility -const SYNC_VERSION = 5; +// v6: added enable_summary column to search_source_connectors +const SYNC_VERSION = 6; // Database name prefix for identifying SurfSense databases const DB_PREFIX = "surfsense-"; @@ -214,20 +215,21 @@ export async function initElectric(userId: string): Promise { // Create the search_source_connectors table schema in PGlite // This matches the backend schema await db.exec(` - CREATE TABLE IF NOT EXISTS search_source_connectors ( - id INTEGER PRIMARY KEY, - search_space_id INTEGER NOT NULL, - user_id TEXT NOT NULL, - connector_type TEXT NOT NULL, - name TEXT NOT NULL, - is_indexable BOOLEAN NOT NULL DEFAULT FALSE, - last_indexed_at TIMESTAMPTZ, - config JSONB DEFAULT '{}', - periodic_indexing_enabled BOOLEAN NOT NULL DEFAULT FALSE, - indexing_frequency_minutes INTEGER, - next_scheduled_at TIMESTAMPTZ, - created_at TIMESTAMPTZ NOT NULL DEFAULT NOW() - ); + CREATE TABLE IF NOT EXISTS search_source_connectors ( + id INTEGER PRIMARY KEY, + search_space_id INTEGER NOT NULL, + user_id TEXT NOT NULL, + connector_type TEXT NOT NULL, + name TEXT NOT NULL, + is_indexable BOOLEAN NOT NULL DEFAULT FALSE, + last_indexed_at TIMESTAMPTZ, + config JSONB DEFAULT '{}', + periodic_indexing_enabled BOOLEAN NOT NULL DEFAULT FALSE, + indexing_frequency_minutes INTEGER, + next_scheduled_at TIMESTAMPTZ, + enable_summary BOOLEAN NOT NULL DEFAULT FALSE, + created_at TIMESTAMPTZ NOT NULL DEFAULT NOW() + ); CREATE INDEX IF NOT EXISTS idx_connectors_search_space_id ON search_source_connectors(search_space_id); CREATE INDEX IF NOT EXISTS idx_connectors_type ON search_source_connectors(connector_type); diff --git a/surfsense_web/lib/query-client/client.ts b/surfsense_web/lib/query-client/client.ts index 6c7b9ded3..0dcc2ef03 100644 --- a/surfsense_web/lib/query-client/client.ts +++ b/surfsense_web/lib/query-client/client.ts @@ -1,3 +1,10 @@ import { QueryClient } from "@tanstack/react-query"; -export const queryClient = new QueryClient(); +export const queryClient = new QueryClient({ + defaultOptions: { + queries: { + staleTime: 30_000, + refetchOnWindowFocus: false, + }, + }, +}); diff --git a/surfsense_web/lib/source.ts b/surfsense_web/lib/source.ts index 9d879b517..162cca57a 100644 --- a/surfsense_web/lib/source.ts +++ b/surfsense_web/lib/source.ts @@ -1,7 +1,12 @@ import { loader } from "fumadocs-core/source"; +import { icons } from "lucide-react"; +import { createElement } from "react"; import { docs } from "@/.source/server"; export const source = loader({ baseUrl: "/docs", source: docs.toFumadocsSource(), + icon(icon) { + if (icon && icon in icons) return createElement(icons[icon as keyof typeof icons]); + }, });