diff --git a/.dockerignore b/.dockerignore index 19aaf83..8439270 100644 --- a/.dockerignore +++ b/.dockerignore @@ -1 +1,2 @@ -api/.env \ No newline at end of file +api/.env +evals/ diff --git a/.github/workflows/docker-image.yml b/.github/workflows/docker-image.yml index 20d0de3..418b67f 100644 --- a/.github/workflows/docker-image.yml +++ b/.github/workflows/docker-image.yml @@ -4,7 +4,7 @@ on: release: types: [published] -# Ensure only one workflow run per branch at a time; cancel any in-progress runs on new push +# Ensure only one workflow run per branch at a time; cancel any in-progress runs on new push concurrency: group: ${{ github.workflow }}-${{ github.ref }} cancel-in-progress: true @@ -13,11 +13,11 @@ jobs: build: runs-on: ubuntu-latest env: - COMMIT_SHA: ${{ github.sha }} # Used to tag images with short commit SHA + COMMIT_SHA: ${{ github.sha }} strategy: matrix: - service: + service: - "dograh-api|api/Dockerfile|." - "dograh-ui|ui/Dockerfile|." @@ -25,14 +25,12 @@ jobs: - name: Checkout repository uses: actions/checkout@v4 with: - submodules: true # Only for version check, not used in build + submodules: true - # Pipecat version check removed - now using local submodule - - - name: Set up QEMU # Enables cross-platform builds (e.g., arm64) + - name: Set up QEMU uses: docker/setup-qemu-action@v3 - - name: Set up Docker Buildx # Enables multi-arch and advanced Docker builds + - name: Set up Docker Buildx uses: docker/setup-buildx-action@v3 - name: Log in to DockerHub @@ -51,48 +49,50 @@ jobs: - name: Set build variables id: build-vars run: | - # Parse matrix entry and set variables early (before build) SERVICE="${{ matrix.service }}" IMAGE_NAME=$(echo "$SERVICE" | cut -d '|' -f1) SHORT_SHA=${COMMIT_SHA::8} - - # Export for use in subsequent steps + + # Get version from release tag (removes 'dograh-' and 'v' prefixes if present) + VERSION="${{ github.event.release.tag_name }}" + VERSION="${VERSION#dograh-}" + VERSION="${VERSION#v}" + echo "image_name=${IMAGE_NAME}" >> $GITHUB_OUTPUT echo "short_sha=${SHORT_SHA}" >> $GITHUB_OUTPUT - echo "service=${SERVICE}" >> $GITHUB_OUTPUT - + echo "version=${VERSION}" >> $GITHUB_OUTPUT + - name: Build and Push ${{ matrix.service }} id: docker-build run: | - # Parse matrix entry into individual variables SERVICE="${{ matrix.service }}" IMAGE_NAME=$(echo "$SERVICE" | cut -d '|' -f1) DOCKERFILE=$(echo "$SERVICE" | cut -d '|' -f2) CONTEXT=$(echo "$SERVICE" | cut -d '|' -f3) SHORT_SHA=${COMMIT_SHA::8} + VERSION="${{ steps.build-vars.outputs.version }}" echo "Building and pushing image: $IMAGE_NAME" echo "Dockerfile: $DOCKERFILE" echo "Context: $CONTEXT" - echo "Commit SHA: $SHORT_SHA" - - # Export tags for Slack notification + echo "Version: $VERSION" + echo "image_name=${IMAGE_NAME}" >> $GITHUB_OUTPUT echo "dockerhub_tag=${{ secrets.DOCKERHUB_USERNAME }}/${IMAGE_NAME}:${SHORT_SHA}" >> $GITHUB_OUTPUT echo "ghcr_tag=ghcr.io/${{ secrets.GHCR_USERNAME }}/${IMAGE_NAME}:${SHORT_SHA}" >> $GITHUB_OUTPUT echo "short_sha=${SHORT_SHA}" >> $GITHUB_OUTPUT - # Build and push multi-arch Docker image to DockerHub and GHCR docker buildx build \ -f "$DOCKERFILE" \ --platform linux/amd64,linux/arm64 \ + --tag ${{ secrets.DOCKERHUB_USERNAME }}/$IMAGE_NAME:$VERSION \ --tag ${{ secrets.DOCKERHUB_USERNAME }}/$IMAGE_NAME:$SHORT_SHA \ --tag ${{ secrets.DOCKERHUB_USERNAME }}/$IMAGE_NAME:latest \ + --tag ghcr.io/${{ secrets.GHCR_USERNAME }}/$IMAGE_NAME:$VERSION \ --tag ghcr.io/${{ secrets.GHCR_USERNAME }}/$IMAGE_NAME:$SHORT_SHA \ --tag ghcr.io/${{ secrets.GHCR_USERNAME }}/$IMAGE_NAME:latest \ --push "$CONTEXT" - - # Success notification + - name: Send Slack notification - Success if: success() uses: slackapi/slack-github-action@v1.26.0 @@ -101,10 +101,9 @@ jobs: with: payload: | { - "text": "✅ Docker Build Successful - ${{ steps.build-vars.outputs.image_name }} (${{ steps.build-vars.outputs.short_sha }}) on ${{ github.ref_name }} by ${{ github.actor }}" + "text": "✅ Docker Build Successful - ${{ steps.build-vars.outputs.image_name }} (${{ steps.build-vars.outputs.version }}) on ${{ github.ref_name }} by ${{ github.actor }}" } - - # Failure notification + - name: Send Slack notification - Failure if: failure() uses: slackapi/slack-github-action@v1.26.0 @@ -113,5 +112,5 @@ jobs: with: payload: | { - "text": "❌ Docker Build Failed - ${{ steps.build-vars.outputs.image_name }} (${{ steps.build-vars.outputs.short_sha }}) on ${{ github.ref_name }} by ${{ github.actor }} - <${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}|View Logs>" + "text": "❌ Docker Build Failed - ${{ steps.build-vars.outputs.image_name }} (${{ steps.build-vars.outputs.version }}) on ${{ github.ref_name }} by ${{ github.actor }} - <${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}|View Logs>" } diff --git a/.gitignore b/.gitignore index c8acf44..7f268eb 100644 --- a/.gitignore +++ b/.gitignore @@ -1,6 +1,7 @@ __pycache__ .DS_Store .env +.env.prod .env.test # logs and run directory on production diff --git a/api/alembic/versions/181475b2a1a1_add_public_access_token.py b/api/alembic/versions/181475b2a1a1_add_public_access_token.py new file mode 100644 index 0000000..a796285 --- /dev/null +++ b/api/alembic/versions/181475b2a1a1_add_public_access_token.py @@ -0,0 +1,72 @@ +"""add public_access_token + +Revision ID: 181475b2a1a1 +Revises: dc33eef8dabe +Create Date: 2026-01-23 17:37:54.449308 + +""" + +from typing import Sequence, Union + +import sqlalchemy as sa +from alembic import op + +# revision identifiers, used by Alembic. +revision: str = "181475b2a1a1" +down_revision: Union[str, None] = "dc33eef8dabe" +branch_labels: Union[str, Sequence[str], None] = None +depends_on: Union[str, Sequence[str], None] = None + + +def upgrade() -> None: + # ### commands auto generated by Alembic - please adjust! ### + op.drop_index(op.f("ix_api_keys_key_hash"), table_name="api_keys") + op.create_index("ix_api_keys_key_hash", "api_keys", ["key_hash"], unique=False) + op.create_index( + "ix_kb_chunks_embedding_ivfflat", + "knowledge_base_chunks", + ["embedding"], + unique=False, + postgresql_using="ivfflat", + postgresql_with={"lists": 100}, + postgresql_ops={"embedding": "vector_cosine_ops"}, + ) + op.create_index( + "ix_kb_chunks_embedding_model", + "knowledge_base_chunks", + ["embedding_model"], + unique=False, + ) + op.add_column( + "workflow_runs", + sa.Column("public_access_token", sa.String(length=36), nullable=True), + ) + op.create_index( + "idx_workflow_runs_public_access_token", + "workflow_runs", + ["public_access_token"], + unique=True, + postgresql_where=sa.text("public_access_token IS NOT NULL"), + ) + # ### end Alembic commands ### + + +def downgrade() -> None: + # ### commands auto generated by Alembic - please adjust! ### + op.drop_index( + "idx_workflow_runs_public_access_token", + table_name="workflow_runs", + postgresql_where=sa.text("public_access_token IS NOT NULL"), + ) + op.drop_column("workflow_runs", "public_access_token") + op.drop_index("ix_kb_chunks_embedding_model", table_name="knowledge_base_chunks") + op.drop_index( + "ix_kb_chunks_embedding_ivfflat", + table_name="knowledge_base_chunks", + postgresql_using="ivfflat", + postgresql_with={"lists": 100}, + postgresql_ops={"embedding": "vector_cosine_ops"}, + ) + op.drop_index("ix_api_keys_key_hash", table_name="api_keys") + op.create_index(op.f("ix_api_keys_key_hash"), "api_keys", ["key_hash"], unique=True) + # ### end Alembic commands ### diff --git a/api/constants.py b/api/constants.py index 366a256..b92596a 100644 --- a/api/constants.py +++ b/api/constants.py @@ -14,7 +14,6 @@ FILLER_SOUND_PROBABILITY = 0.0 VOICEMAIL_RECORDING_DURATION = 5.0 # Configuration constants -ENABLE_SMART_TURN = os.getenv("ENABLE_SMART_TURN", "false").lower() == "true" ENABLE_TRACING = os.getenv("ENABLE_TRACING", "false").lower() == "true" ENABLE_RNNOISE = os.getenv("ENABLE_RNNOISE", "false").lower() == "true" @@ -52,6 +51,23 @@ ENABLE_ARI_STASIS = os.getenv("ENABLE_ARI_STASIS", "false").lower() == "true" SERIALIZE_LOG_OUTPUT = os.getenv("SERIALIZE_LOG_OUTPUT", "false").lower() == "true" ENABLE_TELEMETRY = os.getenv("ENABLE_TELEMETRY", "false").lower() == "true" + +def _get_version() -> str: + """Read version from pyproject.toml.""" + try: + import tomllib + + pyproject_path = APP_ROOT_DIR / "pyproject.toml" + with open(pyproject_path, "rb") as f: + pyproject = tomllib.load(f) + return pyproject.get("project", {}).get("version", "dev") + except Exception: + return "dev" + + +# Application version (read from pyproject.toml) +APP_VERSION = _get_version() + # Country code mapping: ISO country code -> international dialing prefix COUNTRY_CODES = { "US": "1", # United States diff --git a/api/db/models.py b/api/db/models.py index 55d0305..4f44636 100644 --- a/api/db/models.py +++ b/api/db/models.py @@ -360,6 +360,17 @@ class WorkflowRunModel(Base): campaign = relationship("CampaignModel") queued_run_id = Column(Integer, ForeignKey("queued_runs.id"), nullable=True) queued_run = relationship("QueuedRunModel", foreign_keys=[queued_run_id]) + public_access_token = Column(String(36), nullable=True) + + # Indexes + __table_args__ = ( + Index( + "idx_workflow_runs_public_access_token", + "public_access_token", + unique=True, + postgresql_where=text("public_access_token IS NOT NULL"), + ), + ) # LoopTalk Testing Models diff --git a/api/db/workflow_client.py b/api/db/workflow_client.py index 7ce4078..53eb00c 100644 --- a/api/db/workflow_client.py +++ b/api/db/workflow_client.py @@ -4,7 +4,7 @@ from typing import Optional from sqlalchemy import func from sqlalchemy.future import select -from sqlalchemy.orm import selectinload +from sqlalchemy.orm import load_only, selectinload from api.db.base_client import BaseDBClient from api.db.models import WorkflowDefinitionModel, WorkflowModel, WorkflowRunModel @@ -111,6 +111,70 @@ class WorkflowClient(BaseDBClient): result = await session.execute(query) return result.scalars().all() + async def get_all_workflows_for_listing( + self, organization_id: int = None, status: str = None + ) -> list[WorkflowModel]: + """Get workflows with only the columns needed for listing. + + This is an optimized version that excludes large JSON columns like + workflow_definition, template_context_variables, etc. + + Args: + organization_id: Filter by organization ID + status: Filter by status (active/archived) + + Returns: + List of WorkflowModel with only id, name, status, created_at loaded + """ + async with self.async_session() as session: + query = select(WorkflowModel).options( + load_only( + WorkflowModel.id, + WorkflowModel.name, + WorkflowModel.status, + WorkflowModel.created_at, + ) + ) + + if organization_id: + query = query.where(WorkflowModel.organization_id == organization_id) + + if status: + query = query.where(WorkflowModel.status == status) + + result = await session.execute(query) + return result.scalars().all() + + async def get_workflow_counts(self, organization_id: int = None) -> dict[str, int]: + """Get workflow counts by status. + + Args: + organization_id: Filter by organization ID + + Returns: + Dict with 'total', 'active', 'archived' counts + """ + async with self.async_session() as session: + query = select( + WorkflowModel.status, + func.count(WorkflowModel.id).label("count"), + ) + + if organization_id: + query = query.where(WorkflowModel.organization_id == organization_id) + + query = query.group_by(WorkflowModel.status) + + result = await session.execute(query) + rows = result.all() + + counts = {"total": 0, "active": 0, "archived": 0} + for status, count in rows: + counts[status] = count + counts["total"] += count + + return counts + async def get_workflow( self, workflow_id: int, user_id: int = None, organization_id: int = None ) -> WorkflowModel | None: @@ -310,3 +374,33 @@ class WorkflowClient(BaseDBClient): ) ) return result.scalar() or 0 + + async def get_workflow_run_counts(self, workflow_ids: list[int]) -> dict[int, int]: + """Get run counts for multiple workflows in a single query. + + Args: + workflow_ids: List of workflow IDs to get counts for + + Returns: + Dict mapping workflow_id to run count + """ + if not workflow_ids: + return {} + + async with self.async_session() as session: + result = await session.execute( + select( + WorkflowRunModel.workflow_id, + func.count(WorkflowRunModel.id).label("run_count"), + ) + .where(WorkflowRunModel.workflow_id.in_(workflow_ids)) + .group_by(WorkflowRunModel.workflow_id) + ) + rows = result.all() + + # Build dict with counts, defaulting to 0 for workflows with no runs + counts = {workflow_id: 0 for workflow_id in workflow_ids} + for workflow_id, run_count in rows: + counts[workflow_id] = run_count + + return counts diff --git a/api/db/workflow_run_client.py b/api/db/workflow_run_client.py index 27cffac..604a431 100644 --- a/api/db/workflow_run_client.py +++ b/api/db/workflow_run_client.py @@ -1,3 +1,4 @@ +import uuid from datetime import datetime, timezone from typing import Any, Dict, List, Optional, Tuple @@ -414,3 +415,56 @@ class WorkflowRunClient(BaseDBClient): organization_id = workflow_run.workflow.user.selected_organization_id return workflow_run, organization_id + + async def ensure_public_access_token(self, workflow_run_id: int) -> Optional[str]: + """Generate a public access token if not exists, return existing if present (idempotent). + + Args: + workflow_run_id: The ID of the workflow run + + Returns: + The public access token string, or None if workflow run not found + """ + async with self.async_session() as session: + result = await session.execute( + select(WorkflowRunModel).where(WorkflowRunModel.id == workflow_run_id) + ) + run = result.scalars().first() + if not run: + return None + + # Return existing token if present + if run.public_access_token: + return run.public_access_token + + # Generate and persist new token + token = str(uuid.uuid4()) + run.public_access_token = token + + try: + await session.commit() + except Exception as e: + await session.rollback() + raise e + await session.refresh(run) + + return run.public_access_token + + async def get_workflow_run_by_public_token( + self, token: str + ) -> Optional[WorkflowRunModel]: + """Lookup workflow run by public access token. + + Args: + token: The public access token + + Returns: + The WorkflowRunModel if found, None otherwise + """ + async with self.async_session() as session: + result = await session.execute( + select(WorkflowRunModel).where( + WorkflowRunModel.public_access_token == token + ) + ) + return result.scalars().first() diff --git a/api/pyproject.toml b/api/pyproject.toml new file mode 100644 index 0000000..7825d5a --- /dev/null +++ b/api/pyproject.toml @@ -0,0 +1,5 @@ +[project] +name = "dograh-api" +version = "1.10.0" +description = "Backend API for Dograh voice AI platform" +requires-python = ">=3.12" diff --git a/api/routes/main.py b/api/routes/main.py index 2141172..8086114 100644 --- a/api/routes/main.py +++ b/api/routes/main.py @@ -1,5 +1,6 @@ from fastapi import APIRouter from loguru import logger +from pydantic import BaseModel from api.routes.campaign import router as campaign_router from api.routes.credentials import router as credentials_router @@ -9,6 +10,7 @@ from api.routes.looptalk import router as looptalk_router from api.routes.organization import router as organization_router from api.routes.organization_usage import router as organization_usage_router from api.routes.public_agent import router as public_agent_router +from api.routes.public_download import router as public_download_router from api.routes.public_embed import router as public_embed_router from api.routes.reports import router as reports_router from api.routes.s3_signed_url import router as s3_router @@ -43,11 +45,24 @@ router.include_router(reports_router) router.include_router(webrtc_signaling_router) router.include_router(public_embed_router) router.include_router(public_agent_router) +router.include_router(public_download_router) router.include_router(workflow_embed_router) router.include_router(knowledge_base_router) -@router.get("/health") -async def health(): +class HealthResponse(BaseModel): + status: str + version: str + backend_api_endpoint: str + + +@router.get("/health", response_model=HealthResponse) +async def health() -> HealthResponse: + from api.constants import APP_VERSION, BACKEND_API_ENDPOINT + logger.debug("Health endpoint called") - return {"message": "OK"} + return HealthResponse( + status="ok", + version=APP_VERSION, + backend_api_endpoint=BACKEND_API_ENDPOINT, + ) diff --git a/api/routes/public_download.py b/api/routes/public_download.py new file mode 100644 index 0000000..38793d9 --- /dev/null +++ b/api/routes/public_download.py @@ -0,0 +1,95 @@ +"""Public download endpoints for workflow recordings and transcripts. + +These endpoints provide secure, token-based public access to workflow artifacts +without requiring authentication. Tokens are generated on-demand when webhooks +are executed and included in the webhook payload. +""" + +from typing import Literal + +from fastapi import APIRouter, HTTPException, Query +from fastapi.responses import RedirectResponse +from loguru import logger + +from api.db import db_client +from api.services.storage import get_storage_for_backend + +router = APIRouter(prefix="/public/download") + + +@router.get("/workflow/{token}/{artifact_type}") +async def download_workflow_artifact( + token: str, + artifact_type: Literal["recording", "transcript"], + inline: bool = Query( + default=False, description="Display inline in browser instead of download" + ), +): + """Download a workflow recording or transcript via public access token. + + This endpoint: + 1. Validates the public access token + 2. Looks up the corresponding workflow run + 3. Generates a signed URL for the requested artifact + 4. Redirects to the signed URL + + Args: + token: The public access token (UUID format) + artifact_type: Type of artifact - "recording" or "transcript" + inline: If true, sets Content-Disposition to inline for browser preview + + Returns: + RedirectResponse to the signed URL (302 redirect) + + Raises: + HTTPException 404: If token is invalid or artifact not found + """ + # 1. Lookup workflow run by token + workflow_run = await db_client.get_workflow_run_by_public_token(token) + if not workflow_run: + logger.warning(f"Invalid public access token: {token[:8]}...") + raise HTTPException(status_code=404, detail="Invalid or expired token") + + # 2. Get file path based on artifact type + if artifact_type == "recording": + file_path = workflow_run.recording_url + else: # transcript + file_path = workflow_run.transcript_url + + if not file_path: + logger.warning( + f"Artifact not found: type={artifact_type}, workflow_run_id={workflow_run.id}" + ) + raise HTTPException( + status_code=404, + detail=f"No {artifact_type} available for this workflow run", + ) + + # 3. Get storage backend for this workflow run + try: + storage = get_storage_for_backend(workflow_run.storage_backend) + except ValueError as e: + logger.error(f"Invalid storage backend: {workflow_run.storage_backend}") + raise HTTPException(status_code=500, detail="Storage configuration error") + + # 4. Generate signed URL (1 hour expiration) + try: + signed_url = await storage.aget_signed_url( + file_path=file_path, + expiration=3600, # 1 hour + force_inline=inline, + ) + except Exception as e: + logger.error(f"Failed to generate signed URL: {e}") + raise HTTPException(status_code=500, detail="Failed to generate download URL") + + if not signed_url: + logger.error(f"Storage returned None for signed URL: {file_path}") + raise HTTPException(status_code=500, detail="Failed to generate download URL") + + logger.info( + f"Generated signed URL for {artifact_type}: workflow_run_id={workflow_run.id}, token={token[:8]}..." + ) + + # 5. Redirect to signed URL + return RedirectResponse(url=signed_url, status_code=302) diff --git a/api/routes/workflow.py b/api/routes/workflow.py index f8e47eb..126314e 100644 --- a/api/routes/workflow.py +++ b/api/routes/workflow.py @@ -97,6 +97,24 @@ class WorkflowResponse(BaseModel): workflow_configurations: dict | None = None +class WorkflowListResponse(BaseModel): + """Lightweight response for workflow listings (excludes large fields).""" + + id: int + name: str + status: str + created_at: datetime + total_runs: int + + +class WorkflowCountResponse(BaseModel): + """Response for workflow count endpoint.""" + + total: int + active: int + archived: int + + class WorkflowTemplateResponse(BaseModel): id: int template_name: str @@ -359,6 +377,26 @@ class WorkflowSummaryResponse(BaseModel): name: str +@router.get("/count") +async def get_workflow_count( + user: UserModel = Depends(get_user), +) -> WorkflowCountResponse: + """Get workflow counts for the authenticated user's organization. + + This is a lightweight endpoint for checking if the user has workflows, + useful for redirect logic without fetching full workflow data. + """ + counts = await db_client.get_workflow_counts( + organization_id=user.selected_organization_id + ) + + return WorkflowCountResponse( + total=counts["total"], + active=counts["active"], + archived=counts["archived"], + ) + + @router.get("/fetch") async def get_workflows( user: UserModel = Depends(get_user), @@ -366,45 +404,43 @@ async def get_workflows( None, description="Filter by status - can be single value (active/archived) or comma-separated (active,archived)", ), -) -> List[WorkflowResponse]: - """Get all workflows for the authenticated user's organization""" +) -> List[WorkflowListResponse]: + """Get all workflows for the authenticated user's organization. + + Returns a lightweight response with only essential fields for listing. + Use GET /workflow/fetch/{workflow_id} to get full workflow details. + """ # Handle comma-separated status values if status and "," in status: # Split comma-separated values and fetch workflows for each status status_list = [s.strip() for s in status.split(",")] all_workflows = [] for status_value in status_list: - workflows = await db_client.get_all_workflows( + workflows = await db_client.get_all_workflows_for_listing( organization_id=user.selected_organization_id, status=status_value ) all_workflows.extend(workflows) workflows = all_workflows else: # Single status or no status filter - workflows = await db_client.get_all_workflows( + workflows = await db_client.get_all_workflows_for_listing( organization_id=user.selected_organization_id, status=status ) - # Get run counts for each workflow - workflow_responses = [] - for workflow in workflows: - run_count = await db_client.get_workflow_run_count(workflow.id) - workflow_responses.append( - { - "id": workflow.id, - "name": workflow.name, - "status": workflow.status, - "created_at": workflow.created_at, - "workflow_definition": workflow.workflow_definition_with_fallback, - "current_definition_id": workflow.current_definition_id, - "template_context_variables": workflow.template_context_variables, - "call_disposition_codes": workflow.call_disposition_codes, - "workflow_configurations": workflow.workflow_configurations, - "total_runs": run_count, - } - ) + # Get run counts for all workflows in a single query + workflow_ids = [workflow.id for workflow in workflows] + run_counts = await db_client.get_workflow_run_counts(workflow_ids) - return workflow_responses + return [ + WorkflowListResponse( + id=workflow.id, + name=workflow.name, + status=workflow.status, + created_at=workflow.created_at, + total_runs=run_counts.get(workflow.id, 0), + ) + for workflow in workflows + ] @router.get("/fetch/{workflow_id}") diff --git a/api/services/campaign/call_dispatcher.py b/api/services/campaign/call_dispatcher.py index d32bb32..353a42d 100644 --- a/api/services/campaign/call_dispatcher.py +++ b/api/services/campaign/call_dispatcher.py @@ -170,13 +170,6 @@ class CampaignCallDispatcher: ) raise ValueError(f"Workflow {campaign.workflow_id} not found") - # Merge context variables (queued_run context already includes retry info if applicable) - initial_context = { - **workflow.template_context_variables, - **queued_run.context_variables, - "campaign_id": campaign.id, - } - # Extract phone number phone_number = queued_run.context_variables.get("phone_number") if not phone_number: @@ -186,13 +179,25 @@ class CampaignCallDispatcher: ) raise ValueError(f"No phone number in queued run {queued_run.id}") - # Create workflow run with queued_run_id tracking - workflow_run_name = f"WR-CAMPAIGN-{campaign.id}-{queued_run.id}" - # Get provider first to determine the mode provider = await self.get_telephony_provider(campaign.organization_id) workflow_run_mode = provider.PROVIDER_NAME + + logger.info(f"Provider name: {provider.PROVIDER_NAME}") + logger.info(f"Queued run context: {queued_run.context_variables}") + # Merge context variables (queued_run context already includes retry info if applicable) + initial_context = { + **workflow.template_context_variables, + **queued_run.context_variables, + "campaign_id": campaign.id, + "provider": provider.PROVIDER_NAME, + } + + logger.info(f"Final initial_context: {initial_context}") + + # Create workflow run with queued_run_id tracking + workflow_run_name = f"WR-CAMPAIGN-{campaign.id}-{queued_run.id}" try: workflow_run = await db_client.create_workflow_run( name=workflow_run_name, @@ -243,6 +248,8 @@ class CampaignCallDispatcher: to_number=phone_number, webhook_url=webhook_url, workflow_run_id=workflow_run.id, + workflow_id=campaign.workflow_id, + user_id=campaign.created_by, ) # Store provider type and metadata in gathered_context diff --git a/api/services/configuration/registry.py b/api/services/configuration/registry.py index 8ea8409..f1d0b69 100644 --- a/api/services/configuration/registry.py +++ b/api/services/configuration/registry.py @@ -300,7 +300,7 @@ TTSConfig = Annotated[ ###################################################### STT ######################################################################## -DEEPGRAM_STT_MODELS = ["nova-2", "nova-3-general"] +DEEPGRAM_STT_MODELS = ["nova-2", "nova-3-general", "flux-general-en"] DEEPGRAM_LANGUAGES = [ "multi", "en", diff --git a/api/services/looptalk/core/pipeline_builder.py b/api/services/looptalk/core/pipeline_builder.py index 0de82fd..8e1ceb5 100644 --- a/api/services/looptalk/core/pipeline_builder.py +++ b/api/services/looptalk/core/pipeline_builder.py @@ -103,7 +103,6 @@ class LoopTalkPipelineBuilder: # Set the context and audio_buffer after creation engine.set_context(context) - engine.set_audio_buffer(audio_buffer) context_aggregator = LLMContextAggregatorPair(context) diff --git a/api/services/looptalk/internal_serializer.py b/api/services/looptalk/internal_serializer.py index 0f59b50..75d89ea 100644 --- a/api/services/looptalk/internal_serializer.py +++ b/api/services/looptalk/internal_serializer.py @@ -12,9 +12,8 @@ from pipecat.frames.frames import ( Frame, InputAudioRawFrame, OutputAudioRawFrame, - StartFrame, ) -from pipecat.serializers.base_serializer import FrameSerializer, FrameSerializerType +from pipecat.serializers.base_serializer import FrameSerializer class InternalFrameSerializer(FrameSerializer): @@ -24,15 +23,6 @@ class InternalFrameSerializer(FrameSerializer): preventing control frames from creating infinite loops. """ - @property - def type(self) -> FrameSerializerType: - """Internal transport uses binary frames.""" - return FrameSerializerType.BINARY - - async def setup(self, frame: StartFrame): - """No setup required for internal transport.""" - pass - async def serialize(self, frame: Frame) -> bytes | None: """Only serialize audio frames for transmission between agents.""" # Only pass audio frames between agents diff --git a/api/services/pipecat/event_handlers.py b/api/services/pipecat/event_handlers.py index f96c36f..1e68109 100644 --- a/api/services/pipecat/event_handlers.py +++ b/api/services/pipecat/event_handlers.py @@ -22,16 +22,21 @@ from pipecat.pipeline.task import PipelineTask from pipecat.processors.audio.audio_buffer_processor import AudioBufferProcessor -def register_transport_event_handlers( +def register_event_handlers( task: PipelineTask, transport, - workflow_run_id, + workflow_run_id: int, engine: PipecatEngine, audio_buffer: AudioBufferProcessor, + in_memory_logs_buffer: InMemoryLogsBuffer, + pipeline_metrics_aggregator: PipelineMetricsAggregator, audio_config=AudioConfig, ): - """Register event handlers for transport events""" + """Register all event handlers for transport and task events. + Returns: + Tuple of (in_memory_audio_buffer, in_memory_transcript_buffer) for use by other handlers. + """ # Initialize in-memory buffers with proper audio configuration sample_rate = audio_config.pipeline_sample_rate if audio_config else 16000 num_channels = 1 # Pipeline audio is always mono @@ -48,13 +53,35 @@ def register_transport_event_handlers( ) in_memory_transcript_buffer = InMemoryTranscriptBuffer(workflow_run_id) + # Track both events to ensure LLM is only triggered after both occur + ready_state = { + "pipeline_started": False, + "client_connected": False, + "llm_triggered": False, + } + + async def maybe_trigger_llm(): + """Trigger LLM only after both pipeline_started and client_connected events.""" + if ( + ready_state["pipeline_started"] + and ready_state["client_connected"] + and not ready_state["llm_triggered"] + ): + ready_state["llm_triggered"] = True + logger.debug( + "Both pipeline_started and client_connected received - triggering initial LLM generation" + ) + await engine.llm.queue_frame(LLMContextFrame(engine.context)) + @transport.event_handler("on_client_connected") - async def on_client_connected(transport, participant): - logger.debug("In on_client_connected callback handler - initializing workflow") + async def on_client_connected(_transport, _participant): + logger.debug("In on_client_connected callback handler") await audio_buffer.start_recording() + ready_state["client_connected"] = True + await maybe_trigger_llm() @transport.event_handler("on_client_disconnected") - async def on_client_disconnected(transport, participant): + async def on_client_disconnected(_transport, _participant): call_disposed = engine.is_call_disposed() logger.debug( @@ -69,33 +96,16 @@ def register_transport_event_handlers( if not call_disposed: await task.cancel() - # Return the buffers so they can be passed to other handlers - return in_memory_audio_buffer, in_memory_transcript_buffer - - -def register_task_event_handler( - workflow_run_id: int, - engine: PipecatEngine, - task: PipelineTask, - transport, - audio_buffer: AudioBufferProcessor, - in_memory_audio_buffer: InMemoryAudioBuffer, - in_memory_transcript_buffer: InMemoryTranscriptBuffer, - in_memory_logs_buffer: InMemoryLogsBuffer, - pipeline_metrics_aggregator: PipelineMetricsAggregator, -): @task.event_handler("on_pipeline_started") - async def on_pipeline_started(task: PipelineTask, frame: Frame): - logger.debug( - "In on_pipeline_started callback handler - triggering initial LLM generation" - ) - # Trigger initial LLM generation after pipeline has started - await engine.llm.queue_frame(LLMContextFrame(engine.context)) + async def on_pipeline_started(_task: PipelineTask, _frame: Frame): + logger.debug("In on_pipeline_started callback handler") + ready_state["pipeline_started"] = True + await maybe_trigger_llm() @task.event_handler("on_pipeline_finished") async def on_pipeline_finished( task: PipelineTask, - frame: Frame, + _frame: Frame, ): logger.debug(f"In on_pipeline_finished callback handler") @@ -207,14 +217,13 @@ def register_task_event_handler( if workflow_run and workflow_run.campaign_id: await campaign_call_dispatcher.release_call_slot(workflow_run_id) - # Write buffers to temp files and enqueue S3 upload + # Write buffers to temp files and enqueue combined processing task + audio_temp_path = None + transcript_temp_path = None + try: - # Only upload if buffers have content if not in_memory_audio_buffer.is_empty: audio_temp_path = await in_memory_audio_buffer.write_to_temp_file() - await enqueue_job( - FunctionNames.UPLOAD_AUDIO_TO_S3, workflow_run_id, audio_temp_path - ) else: logger.debug("Audio buffer is empty, skipping upload") @@ -222,11 +231,6 @@ def register_task_event_handler( transcript_temp_path = ( await in_memory_transcript_buffer.write_to_temp_file() ) - await enqueue_job( - FunctionNames.UPLOAD_TRANSCRIPT_TO_S3, - workflow_run_id, - transcript_temp_path, - ) else: logger.debug("Transcript buffer is empty, skipping upload") @@ -234,10 +238,18 @@ def register_task_event_handler( logger.error(f"Error preparing buffers for S3 upload: {e}", exc_info=True) await enqueue_job(FunctionNames.CALCULATE_WORKFLOW_RUN_COST, workflow_run_id) + + # Combined task: uploads artifacts then runs integrations sequentially await enqueue_job( - FunctionNames.RUN_INTEGRATIONS_POST_WORKFLOW_RUN, workflow_run_id + FunctionNames.PROCESS_WORKFLOW_COMPLETION, + workflow_run_id, + audio_temp_path, + transcript_temp_path, ) + # Return the buffers so they can be passed to other handlers + return in_memory_audio_buffer, in_memory_transcript_buffer + def register_audio_data_handler( audio_buffer: AudioBufferProcessor, @@ -260,18 +272,26 @@ def register_audio_data_handler( # Could implement overflow to disk here if needed -def register_transcript_handler( - transcript, workflow_run_id, in_memory_buffer: InMemoryTranscriptBuffer +def register_transcript_handlers( + user_aggregator, + assistant_aggregator, + workflow_run_id, + in_memory_buffer: InMemoryTranscriptBuffer, ): - """Register event handler for transcript updates""" + """Register event handlers for transcript updates on context aggregators. - @transcript.event_handler("on_transcript_update") - async def on_transcript_update(processor, frame): - transcript_text = "" - for msg in frame.messages: - timestamp = f"[{msg.timestamp}] " if msg.timestamp else "" - line = f"{timestamp}{msg.role}: {msg.content}\n" - transcript_text += line + Uses the on_user_turn_stopped and on_assistant_turn_stopped events to capture + transcripts as turns complete, following the event-based pattern. + """ - # Use in-memory buffer - await in_memory_buffer.append(transcript_text) + @user_aggregator.event_handler("on_user_turn_stopped") + async def on_user_turn_stopped(aggregator, strategy, message): + timestamp = f"[{message.timestamp}] " if message.timestamp else "" + line = f"{timestamp}user: {message.content}\n" + await in_memory_buffer.append(line) + + @assistant_aggregator.event_handler("on_assistant_turn_stopped") + async def on_assistant_turn_stopped(aggregator, message): + timestamp = f"[{message.timestamp}] " if message.timestamp else "" + line = f"{timestamp}assistant: {message.content}\n" + await in_memory_buffer.append(line) diff --git a/api/services/pipecat/pipeline_builder.py b/api/services/pipecat/pipeline_builder.py index 853f32d..0f6de5d 100644 --- a/api/services/pipecat/pipeline_builder.py +++ b/api/services/pipecat/pipeline_builder.py @@ -1,5 +1,4 @@ import os -from typing import TYPE_CHECKING from loguru import logger @@ -11,14 +10,10 @@ from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.audio.audio_buffer_processor import AudioBufferProcessor -from pipecat.processors.transcript_processor import TranscriptProcessor from pipecat.utils.context import turn_var -if TYPE_CHECKING: - from api.services.workflow.pipecat_engine import PipecatEngine - -def create_pipeline_components(audio_config: AudioConfig, engine: "PipecatEngine"): +def create_pipeline_components(audio_config: AudioConfig): """Create and return the main pipeline components with proper audio configuration""" logger.info(f"Creating pipeline components with audio config: {audio_config}") @@ -28,28 +23,21 @@ def create_pipeline_components(audio_config: AudioConfig, engine: "PipecatEngine buffer_size=audio_config.buffer_size_bytes, ) - transcript = TranscriptProcessor( - assistant_correct_aggregation_callback=engine.create_aggregation_correction_callback() - ) - context = LLMContext() - return audio_buffer, transcript, context + return audio_buffer, context def build_pipeline( transport, stt, - transcript, audio_buffer, llm, tts, user_context_aggregator, assistant_context_aggregator, pipeline_engine_callback_processor, - stt_mute_filter, pipeline_metrics_aggregator, - user_idle_disconnect, voicemail_detector=None, ): """Build the main pipeline with all components. @@ -63,7 +51,7 @@ def build_pipeline( # Build processors list with optional voicemail detection processors = [ transport.input(), # Transport user input - stt, # STT (audio_passthrough=True by default, passes InputAudioRawFrame) + stt, ] # Insert voicemail detector after STT if enabled @@ -76,16 +64,12 @@ def build_pipeline( # Continue with the rest of the pipeline processors.extend( [ - stt_mute_filter, # STTMuteFilters don't let VAD related events pass through if muted - user_idle_disconnect, - transcript.user(), user_context_aggregator, llm, # LLM pipeline_engine_callback_processor, tts, # TTS transport.output(), # Transport bot output audio_buffer, # AudioBufferProcessor - records both input and output audio - transcript.assistant(), assistant_context_aggregator, # Assistant spoken responses pipeline_metrics_aggregator, ] @@ -98,7 +82,6 @@ def create_pipeline_task(pipeline, workflow_run_id, audio_config: AudioConfig = """Create a pipeline task with appropriate parameters""" # Set up pipeline params with audio configuration if provided pipeline_params = PipelineParams( - allow_interruptions=True, enable_metrics=True, enable_usage_metrics=True, send_initial_empty_metrics=False, @@ -119,6 +102,7 @@ def create_pipeline_task(pipeline, workflow_run_id, audio_config: AudioConfig = pipeline, params=pipeline_params, enable_tracing=ENABLE_TRACING, + enable_rtvi=False, conversation_id=f"{workflow_run_id}", ) diff --git a/api/services/pipecat/run_pipeline.py b/api/services/pipecat/run_pipeline.py index 11ae7cc..91b1e18 100644 --- a/api/services/pipecat/run_pipeline.py +++ b/api/services/pipecat/run_pipeline.py @@ -7,12 +7,12 @@ from loguru import logger from api.db import db_client from api.db.models import WorkflowModel from api.enums import WorkflowRunMode +from api.services.configuration.registry import ServiceProviders from api.services.pipecat.audio_config import AudioConfig, create_audio_config from api.services.pipecat.event_handlers import ( register_audio_data_handler, - register_task_event_handler, - register_transcript_handler, - register_transport_event_handlers, + register_event_handlers, + register_transcript_handlers, ) from api.services.pipecat.in_memory_buffers import InMemoryLogsBuffer from api.services.pipecat.pipeline_builder import ( @@ -46,20 +46,25 @@ from api.services.workflow.pipecat_engine import PipecatEngine from api.services.workflow.workflow import WorkflowGraph from pipecat.extensions.voicemail.voicemail_detector import VoicemailDetector from pipecat.pipeline.base_task import PipelineTaskParams -from pipecat.processors.aggregators.llm_response import ( +from pipecat.processors.aggregators.llm_response_universal import ( LLMAssistantAggregatorParams, + LLMContextAggregatorPair, LLMUserAggregatorParams, ) -from pipecat.processors.aggregators.llm_response_universal import ( - LLMContextAggregatorPair, -) -from pipecat.processors.filters.stt_mute_filter import ( - STTMuteConfig, - STTMuteFilter, - STTMuteStrategy, -) -from pipecat.processors.user_idle_processor import UserIdleProcessor from pipecat.transports.smallwebrtc.connection import SmallWebRTCConnection +from pipecat.turns.user_mute import MuteUntilFirstBotCompleteUserMuteStrategy +from pipecat.turns.user_start import ( + ExternalUserTurnStartStrategy, + TranscriptionUserTurnStartStrategy, +) +from pipecat.turns.user_start.vad_user_turn_start_strategy import ( + VADUserTurnStartStrategy, +) +from pipecat.turns.user_stop import ( + ExternalUserTurnStopStrategy, + TranscriptionUserTurnStopStrategy, +) +from pipecat.turns.user_turn_strategies import UserTurnStrategies from pipecat.utils.context import set_current_run_id from pipecat.utils.enums import EndTaskReason from pipecat.utils.tracing.context_registry import ContextProviderRegistry @@ -517,12 +522,11 @@ async def _run_pipeline( embeddings_model=embeddings_model, ) - # Create pipeline components with audio configuration and engine - audio_buffer, transcript, context = create_pipeline_components(audio_config, engine) + # Create pipeline components with audio configuration + audio_buffer, context = create_pipeline_components(audio_config) # Set the context and audio_buffer after creation engine.set_context(context) - engine.set_audio_buffer(audio_buffer) # Set Stasis connection for immediate transfers (if available) if stasis_connection: @@ -532,7 +536,31 @@ async def _run_pipeline( expect_stripped_words=True, correct_aggregation_callback=engine.create_aggregation_correction_callback(), ) - user_params = LLMUserAggregatorParams(enable_emulated_vad_interruptions=True) + + # Configure turn strategies based on STT provider and model + # Deepgram Flux uses external turn detection (VAD + External start/stop) + # Other models use transcription-based turn detection with smart turn analyzer + is_deepgram_flux = ( + user_config.stt.provider == ServiceProviders.DEEPGRAM.value + and user_config.stt.model == "flux-general-en" + ) + + if is_deepgram_flux: + user_turn_strategies = UserTurnStrategies( + start=[VADUserTurnStartStrategy(), ExternalUserTurnStartStrategy()], + stop=[ExternalUserTurnStopStrategy()], + ) + else: + user_turn_strategies = UserTurnStrategies( + start=[VADUserTurnStartStrategy(), TranscriptionUserTurnStartStrategy()], + stop=[TranscriptionUserTurnStopStrategy()], + ) + + user_params = LLMUserAggregatorParams( + user_turn_strategies=user_turn_strategies, + user_mute_strategies=[MuteUntilFirstBotCompleteUserMuteStrategy()], + user_idle_timeout=max_user_idle_timeout, + ) context_aggregator = LLMContextAggregatorPair( context, assistant_params=assistant_params, user_params=user_params ) @@ -547,25 +575,20 @@ async def _run_pipeline( pipeline_metrics_aggregator = PipelineMetricsAggregator() - # Create STT mute filter using the selected strategies and the engine's callback - stt_mute_filter = STTMuteFilter( - config=STTMuteConfig( - strategies={ - STTMuteStrategy.MUTE_UNTIL_FIRST_BOT_COMPLETE, - STTMuteStrategy.CUSTOM, - }, - should_mute_callback=engine.create_should_mute_callback(), - ) - ) - - # Use engine's user idle callback with configured timeout - user_idle_disconnect = UserIdleProcessor( - callback=engine.create_user_idle_callback(), timeout=max_user_idle_timeout - ) - user_context_aggregator = context_aggregator.user() assistant_context_aggregator = context_aggregator.assistant() + # Register user idle event handlers + user_idle_handler = engine.create_user_idle_handler() + + @user_context_aggregator.event_handler("on_user_turn_idle") + async def on_user_turn_idle(aggregator): + await user_idle_handler.handle_idle(aggregator) + + @user_context_aggregator.event_handler("on_user_turn_started") + async def on_user_turn_started(aggregator, strategy): + user_idle_handler.reset() + # Create voicemail detector if enabled in the workflow's start node voicemail_detector = None start_node = workflow_graph.nodes.get(workflow_graph.start_node_id) @@ -592,16 +615,13 @@ async def _run_pipeline( pipeline = build_pipeline( transport, stt, - transcript, audio_buffer, llm, tts, user_context_aggregator, assistant_context_aggregator, pipeline_engine_callback_processor, - stt_mute_filter, pipeline_metrics_aggregator, - user_idle_disconnect, voicemail_detector=voicemail_detector, ) @@ -614,18 +634,6 @@ async def _run_pipeline( # Initialize the engine to set the initial context await engine.initialize() - # Register event handlers - in_memory_audio_buffer, in_memory_transcript_buffer = ( - register_transport_event_handlers( - task, - transport, - workflow_run_id, - engine=engine, - audio_buffer=audio_buffer, - audio_config=audio_config, - ) - ) - # Add real-time feedback observer if WebSocket sender is available # Note: ws_sender was already fetched earlier for node_transition_callback if ws_sender: @@ -635,21 +643,24 @@ async def _run_pipeline( ) task.add_observer(feedback_observer) - register_task_event_handler( - workflow_run_id, - engine, + # Register event handlers + in_memory_audio_buffer, in_memory_transcript_buffer = register_event_handlers( task, transport, - audio_buffer, - in_memory_audio_buffer, - in_memory_transcript_buffer, - in_memory_logs_buffer, - pipeline_metrics_aggregator, + workflow_run_id, + engine=engine, + audio_buffer=audio_buffer, + in_memory_logs_buffer=in_memory_logs_buffer, + pipeline_metrics_aggregator=pipeline_metrics_aggregator, + audio_config=audio_config, ) register_audio_data_handler(audio_buffer, workflow_run_id, in_memory_audio_buffer) - register_transcript_handler( - transcript, workflow_run_id, in_memory_transcript_buffer + register_transcript_handlers( + user_context_aggregator, + assistant_context_aggregator, + workflow_run_id, + in_memory_transcript_buffer, ) try: diff --git a/api/services/pipecat/service_factory.py b/api/services/pipecat/service_factory.py index ab11f18..4fd1445 100644 --- a/api/services/pipecat/service_factory.py +++ b/api/services/pipecat/service_factory.py @@ -7,6 +7,7 @@ from api.constants import MPS_API_URL from api.services.configuration.registry import ServiceProviders from pipecat.services.azure.llm import AzureLLMService from pipecat.services.cartesia.stt import CartesiaSTTService +from pipecat.services.deepgram.flux.stt import DeepgramFluxSTTService from pipecat.services.deepgram.stt import DeepgramSTTService, LiveOptions from pipecat.services.deepgram.tts import DeepgramTTSService from pipecat.services.dograh.llm import DograhLLMService @@ -34,6 +35,20 @@ def create_stt_service(user_config): f"Creating STT service: provider={user_config.stt.provider}, model={user_config.stt.model}" ) if user_config.stt.provider == ServiceProviders.DEEPGRAM.value: + # Check if using Flux model (English-only, no language selection) + if user_config.stt.model == "flux-general-en": + logger.debug("Using DeepGram Flux Model") + return DeepgramFluxSTTService( + api_key=user_config.stt.api_key, + model=user_config.stt.model, + params=DeepgramFluxSTTService.InputParams( + eot_timeout_ms=3000, + eot_threshold=0.7, + ), + should_interrupt=False, # Let UserAggregator take care of sending InterruptionFrame + ) + + # Other models than flux # Use language from user config, defaulting to "multi" for multilingual support language = getattr(user_config.stt, "language", None) or "multi" live_options = LiveOptions( @@ -44,7 +59,9 @@ def create_stt_service(user_config): ) logger.debug(f"Using DeepGram Model - {user_config.stt.model}") return DeepgramSTTService( - live_options=live_options, api_key=user_config.stt.api_key + live_options=live_options, + api_key=user_config.stt.api_key, + should_interrupt=False, # Let UserAggregator take care of sending InterruptionFrame ) elif user_config.stt.provider == ServiceProviders.OPENAI.value: return OpenAISTTService( diff --git a/api/services/pipecat/transport_setup.py b/api/services/pipecat/transport_setup.py index 4798841..237829b 100644 --- a/api/services/pipecat/transport_setup.py +++ b/api/services/pipecat/transport_setup.py @@ -2,10 +2,9 @@ import os from fastapi import WebSocket -from api.constants import APP_ROOT_DIR, ENABLE_RNNOISE, ENABLE_SMART_TURN +from api.constants import APP_ROOT_DIR from api.db import db_client from api.enums import OrganizationConfigurationKey -from api.services.looptalk.internal_transport import InternalTransport from api.services.pipecat.audio_config import AudioConfig from api.services.telephony.stasis_rtp_connection import StasisRTPConnection from api.services.telephony.stasis_rtp_serializer import StasisRTPFrameSerializer @@ -13,11 +12,8 @@ from api.services.telephony.stasis_rtp_transport import ( StasisRTPTransport, StasisRTPTransportParams, ) -from pipecat.audio.filters.rnnoise_filter import RNNoiseFilter from pipecat.audio.mixers.silence_mixer import SilenceAudioMixer from pipecat.audio.mixers.soundfile_mixer import SoundfileMixer -from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams -from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3 from pipecat.audio.vad.silero import SileroVADAnalyzer, VADParams from pipecat.serializers.twilio import TwilioFrameSerializer from pipecat.serializers.vobiz import VobizFrameSerializer @@ -35,19 +31,6 @@ librnnoise_path = os.path.normpath( ) -def create_turn_analyzer(workflow_run_id: int, audio_config: AudioConfig): - """Create a turn analyzer backed by the local Smart Turn HTTP service. - - Args: - workflow_run_id: ID of the workflow run for turn analyzer context - audio_config: Audio configuration containing pipeline sample rate - """ - if ENABLE_SMART_TURN: - return LocalSmartTurnAnalyzerV3(params=SmartTurnParams()) - - return None - - async def create_twilio_transport( websocket_client: WebSocket, stream_sid: str, @@ -78,8 +61,6 @@ async def create_twilio_transport( f"Incomplete Twilio configuration for organization {organization_id}" ) - turn_analyzer = create_turn_analyzer(workflow_run_id, audio_config) - serializer = TwilioFrameSerializer( stream_sid=stream_sid, call_sid=call_sid, @@ -119,11 +100,7 @@ async def create_twilio_transport( if ambient_noise_config and ambient_noise_config.get("enabled", False) else SilenceAudioMixer() ), - turn_analyzer=turn_analyzer, serializer=serializer, - audio_in_filter=RNNoiseFilter(library_path=librnnoise_path) - if ENABLE_RNNOISE - else None, ), ) @@ -158,8 +135,6 @@ async def create_cloudonix_transport( f"Required: bearer_token, domain_id" ) - turn_analyzer = create_turn_analyzer(workflow_run_id, audio_config) - from pipecat.serializers.cloudonix import CloudonixFrameSerializer serializer = CloudonixFrameSerializer( @@ -202,11 +177,7 @@ async def create_cloudonix_transport( if ambient_noise_config and ambient_noise_config.get("enabled", False) else SilenceAudioMixer() ), - turn_analyzer=turn_analyzer, serializer=serializer, - audio_in_filter=RNNoiseFilter(library_path=librnnoise_path) - if ENABLE_RNNOISE - else None, ), ) @@ -238,8 +209,6 @@ async def create_vonage_transport( f"Incomplete Vonage configuration for organization {organization_id}" ) - turn_analyzer = create_turn_analyzer(workflow_run_id, audio_config) - serializer = VonageFrameSerializer( call_uuid=call_uuid, application_id=application_id, @@ -283,11 +252,7 @@ async def create_vonage_transport( if ambient_noise_config and ambient_noise_config.get("enabled", False) else SilenceAudioMixer() ), - turn_analyzer=turn_analyzer, serializer=serializer, - audio_in_filter=RNNoiseFilter(library_path=librnnoise_path) - if ENABLE_RNNOISE - else None, ), ) @@ -337,8 +302,6 @@ async def create_vobiz_transport( f"from_numbers={len(config.get('from_numbers', []))} numbers" ) - turn_analyzer = create_turn_analyzer(workflow_run_id, audio_config) - # Use VobizFrameSerializer for Vobiz WebSocket protocol serializer = VobizFrameSerializer( stream_id=stream_id, @@ -389,11 +352,7 @@ async def create_vobiz_transport( if ambient_noise_config and ambient_noise_config.get("enabled", False) else SilenceAudioMixer() ), - turn_analyzer=turn_analyzer, serializer=serializer, - audio_in_filter=RNNoiseFilter(library_path=librnnoise_path) - if ENABLE_RNNOISE - else None, ), ) @@ -411,7 +370,6 @@ def create_webrtc_transport( ambient_noise_config: dict | None = None, ): """Create a transport for WebRTC connections""" - turn_analyzer = create_turn_analyzer(workflow_run_id, audio_config) return SmallWebRTCTransport( webrtc_connection=webrtc_connection, @@ -445,10 +403,6 @@ def create_webrtc_transport( if ambient_noise_config and ambient_noise_config.get("enabled", False) else SilenceAudioMixer() ), - turn_analyzer=turn_analyzer, - audio_in_filter=RNNoiseFilter(library_path=librnnoise_path) - if ENABLE_RNNOISE - else None, ), ) @@ -461,7 +415,6 @@ def create_stasis_transport( ambient_noise_config: dict | None = None, ): """Create a transport for ARI connections""" - turn_analyzer = create_turn_analyzer(workflow_run_id, audio_config) serializer = StasisRTPFrameSerializer( StasisRTPFrameSerializer.InputParams( @@ -502,11 +455,7 @@ def create_stasis_transport( if ambient_noise_config and ambient_noise_config.get("enabled", False) else SilenceAudioMixer() ), - turn_analyzer=turn_analyzer, serializer=serializer, - audio_in_filter=RNNoiseFilter(library_path=librnnoise_path) - if ENABLE_RNNOISE - else None, ), ) @@ -528,46 +477,44 @@ def create_internal_transport( Returns: InternalTransport instance configured with turn analyzer """ - turn_analyzer = create_turn_analyzer(workflow_run_id, audio_config) + pass + # Commented out because looptalk coming in the regular import flow + # was causing issue. May be move this to looptalk/orchestrator.py # Create and return the internal transport with latency - return InternalTransport( - params=TransportParams( - audio_out_enabled=True, - audio_out_sample_rate=audio_config.transport_out_sample_rate, - audio_out_channels=1, - audio_in_enabled=True, - audio_in_sample_rate=audio_config.transport_in_sample_rate, - audio_in_channels=1, - vad_analyzer=( - SileroVADAnalyzer( - params=VADParams( - confidence=vad_config.get("confidence", 0.7), - start_secs=vad_config.get("start_seconds", 0.4), - stop_secs=vad_config.get("stop_seconds", 0.8), - min_volume=vad_config.get("minimum_volume", 0.6), - ) - ) - if vad_config - else SileroVADAnalyzer() - ), - audio_out_mixer=( - SoundfileMixer( - sound_files={ - "office": APP_ROOT_DIR - / "assets" - / f"office-ambience-{audio_config.transport_out_sample_rate}-mono.wav" - }, - default_sound="office", - volume=ambient_noise_config.get("volume", 0.3), - ) - if ambient_noise_config and ambient_noise_config.get("enabled", False) - else SilenceAudioMixer() - ), - turn_analyzer=turn_analyzer, - audio_in_filter=RNNoiseFilter(library_path=librnnoise_path) - if ENABLE_RNNOISE - else None, - ), - latency_seconds=latency_seconds, - ) + # return InternalTransport( + # params=TransportParams( + # audio_out_enabled=True, + # audio_out_sample_rate=audio_config.transport_out_sample_rate, + # audio_out_channels=1, + # audio_in_enabled=True, + # audio_in_sample_rate=audio_config.transport_in_sample_rate, + # audio_in_channels=1, + # vad_analyzer=( + # SileroVADAnalyzer( + # params=VADParams( + # confidence=vad_config.get("confidence", 0.7), + # start_secs=vad_config.get("start_seconds", 0.4), + # stop_secs=vad_config.get("stop_seconds", 0.8), + # min_volume=vad_config.get("minimum_volume", 0.6), + # ) + # ) + # if vad_config + # else SileroVADAnalyzer() + # ), + # audio_out_mixer=( + # SoundfileMixer( + # sound_files={ + # "office": APP_ROOT_DIR + # / "assets" + # / f"office-ambience-{audio_config.transport_out_sample_rate}-mono.wav" + # }, + # default_sound="office", + # volume=ambient_noise_config.get("volume", 0.3), + # ) + # if ambient_noise_config and ambient_noise_config.get("enabled", False) + # else SilenceAudioMixer() + # ), + # ), + # latency_seconds=latency_seconds, + # ) diff --git a/api/services/telephony/stasis_rtp_serializer.py b/api/services/telephony/stasis_rtp_serializer.py index 751d68b..c4caf02 100644 --- a/api/services/telephony/stasis_rtp_serializer.py +++ b/api/services/telephony/stasis_rtp_serializer.py @@ -15,6 +15,8 @@ The serializer: from typing import Optional from loguru import logger +from pydantic import BaseModel + from pipecat.audio.utils import create_default_resampler, pcm_to_ulaw, ulaw_to_pcm from pipecat.frames.frames import ( AudioRawFrame, @@ -22,8 +24,7 @@ from pipecat.frames.frames import ( InputAudioRawFrame, StartFrame, ) -from pipecat.serializers.base_serializer import FrameSerializer, FrameSerializerType -from pydantic import BaseModel +from pipecat.serializers.base_serializer import FrameSerializer class StasisRTPFrameSerializer(FrameSerializer): @@ -59,11 +60,6 @@ class StasisRTPFrameSerializer(FrameSerializer): # Resampler shared between encode / decode paths self._resampler = create_default_resampler() - @property - def type(self) -> FrameSerializerType: - """Stasis uses raw bytes → BINARY.""" - return FrameSerializerType.BINARY - async def setup(self, frame: StartFrame): """Remember pipeline configuration.""" self._sample_rate = self._params.sample_rate or frame.audio_in_sample_rate diff --git a/api/services/workflow/pipecat_engine.py b/api/services/workflow/pipecat_engine.py index 5cbbd5f..d3b3cc1 100644 --- a/api/services/workflow/pipecat_engine.py +++ b/api/services/workflow/pipecat_engine.py @@ -19,7 +19,6 @@ from pipecat.utils.enums import EndTaskReason if TYPE_CHECKING: from api.services.telephony.stasis_rtp_connection import StasisRTPConnection - from pipecat.processors.audio.audio_buffer_processor import AudioBuffer from pipecat.services.anthropic.llm import AnthropicLLMService from pipecat.services.google.llm import GoogleLLMService from pipecat.services.openai.llm import OpenAILLMService @@ -64,7 +63,6 @@ class PipecatEngine: transport: Optional[BaseTransport] = None, workflow: WorkflowGraph, call_context_vars: dict, - audio_buffer: Optional["AudioBuffer"] = None, workflow_run_id: Optional[int] = None, node_transition_callback: Optional[ Callable[[str, Optional[str]], Awaitable[None]] @@ -78,7 +76,6 @@ class PipecatEngine: self.transport = transport self.workflow = workflow self._call_context_vars = call_context_vars - self._audio_buffer = audio_buffer self._workflow_run_id = workflow_run_id self._node_transition_callback = node_transition_callback self._initialized = False @@ -204,6 +201,7 @@ class PipecatEngine: logger.info(f"Arguments: {function_call_params.arguments}") await self.set_node(transition_to_node) try: + async def on_context_updated() -> None: """ pipecat framework will run this function after the function call result has been updated in the context. @@ -215,6 +213,12 @@ class PipecatEngine: self._current_node ) + # Queue EndFrame if we just transitioned to EndNode + if self._current_node.is_end: + await self.send_end_task_frame( + EndTaskReason.USER_QUALIFIED.value + ) + result = {"status": "done"} properties = FunctionCallResultProperties( @@ -478,8 +482,6 @@ class PipecatEngine: if node.extraction_enabled and node.extraction_variables: await self._perform_variable_extraction_if_needed(node) - await self.send_end_task_frame(EndTaskReason.USER_QUALIFIED.value) - async def _handle_agent_node(self, node: Node) -> None: """Handle agent node execution.""" if node.is_static: @@ -680,12 +682,12 @@ class PipecatEngine: """ return engine_callbacks.create_should_mute_callback(self) - def create_user_idle_callback(self): + def create_user_idle_handler(self): """ - This callback is called when the user is idle for a certain duration. - We use this to either play the static text or end the call + Returns a UserIdleHandler that manages user-idle timeouts with state. + The handler tracks retry count and handles escalating prompts. """ - return engine_callbacks.create_user_idle_callback(self) + return engine_callbacks.create_user_idle_handler(self) def create_max_duration_callback(self): """ @@ -721,14 +723,6 @@ class PipecatEngine: """ self.task = task - def set_audio_buffer(self, audio_buffer: "AudioBuffer") -> None: - """Set the audio buffer. - - This allows setting the audio buffer after the engine has been created, - which is useful when the audio buffer needs to be created after the engine. - """ - self._audio_buffer = audio_buffer - def set_stasis_connection( self, connection: Optional["StasisRTPConnection"] ) -> None: diff --git a/api/services/workflow/pipecat_engine_callbacks.py b/api/services/workflow/pipecat_engine_callbacks.py index 6449026..a6ac51c 100644 --- a/api/services/workflow/pipecat_engine_callbacks.py +++ b/api/services/workflow/pipecat_engine_callbacks.py @@ -23,7 +23,6 @@ from pipecat.utils.enums import EndTaskReason if TYPE_CHECKING: from api.services.workflow.pipecat_engine import PipecatEngine - from pipecat.processors.user_idle_processor import UserIdleProcessor # --------------------------------------------------------------------------- @@ -57,33 +56,43 @@ def create_should_mute_callback( # --------------------------------------------------------------------------- -def create_user_idle_callback(engine: "PipecatEngine"): - """Return a callback that handles user-idle timeouts.""" +class UserIdleHandler: + """Helper class to manage user idle retry logic with state.""" - async def handle_user_idle( - user_idle: "UserIdleProcessor", retry_count: int - ) -> bool: - logger.debug(f"Handling user_idle, attempt: {retry_count}") + def __init__(self, engine: "PipecatEngine"): + self._engine = engine + self._retry_count = 0 - if retry_count == 1: + def reset(self): + """Reset the retry count when user becomes active.""" + self._retry_count = 0 + + async def handle_idle(self, aggregator): + """Handle user idle event with escalating prompts.""" + self._retry_count += 1 + logger.debug(f"Handling user_idle, attempt: {self._retry_count}") + + if self._retry_count == 1: message = { "role": "system", "content": "The user has been quiet. Politely and briefly ask if they're still there in the language that the user has been speaking so far.", } - await user_idle.push_frame(LLMMessagesAppendFrame([message], run_llm=True)) - return True + await aggregator.push_frame(LLMMessagesAppendFrame([message], run_llm=True)) + return message = { "role": "system", "content": "The user has been quiet. We will be disconnecting the call now. Wish them a good day in the language that the user has been speaking so far.", } - await user_idle.push_frame(LLMMessagesAppendFrame([message], run_llm=True)) - await engine.send_end_task_frame( + await aggregator.push_frame(LLMMessagesAppendFrame([message], run_llm=True)) + await self._engine.send_end_task_frame( EndTaskReason.USER_IDLE_MAX_DURATION_EXCEEDED.value ) - return False - return handle_user_idle + +def create_user_idle_handler(engine: "PipecatEngine") -> UserIdleHandler: + """Return a UserIdleHandler that manages user-idle timeouts with state.""" + return UserIdleHandler(engine) # --------------------------------------------------------------------------- diff --git a/api/tasks/arq.py b/api/tasks/arq.py index 8e8f58c..102e94e 100644 --- a/api/tasks/arq.py +++ b/api/tasks/arq.py @@ -49,8 +49,7 @@ from api.tasks.campaign_tasks import ( from api.tasks.knowledge_base_processing import process_knowledge_base_document from api.tasks.run_integrations import run_integrations_post_workflow_run from api.tasks.s3_upload import ( - upload_audio_to_s3, - upload_transcript_to_s3, + process_workflow_completion, upload_voicemail_audio_to_s3, ) @@ -59,9 +58,8 @@ class WorkerSettings: functions = [ calculate_workflow_run_cost, run_integrations_post_workflow_run, - upload_audio_to_s3, - upload_transcript_to_s3, upload_voicemail_audio_to_s3, + process_workflow_completion, sync_campaign_source, process_campaign_batch, monitor_campaign_progress, diff --git a/api/tasks/function_names.py b/api/tasks/function_names.py index c3e7486..e3aeb54 100644 --- a/api/tasks/function_names.py +++ b/api/tasks/function_names.py @@ -1,8 +1,7 @@ class FunctionNames: CALCULATE_WORKFLOW_RUN_COST = "calculate_workflow_run_cost" RUN_INTEGRATIONS_POST_WORKFLOW_RUN = "run_integrations_post_workflow_run" - UPLOAD_AUDIO_TO_S3 = "upload_audio_to_s3" - UPLOAD_TRANSCRIPT_TO_S3 = "upload_transcript_to_s3" + PROCESS_WORKFLOW_COMPLETION = "process_workflow_completion" UPLOAD_VOICEMAIL_AUDIO_TO_S3 = "upload_voicemail_audio_to_s3" SYNC_CAMPAIGN_SOURCE = "sync_campaign_source" PROCESS_CAMPAIGN_BATCH = "process_campaign_batch" diff --git a/api/tasks/run_integrations.py b/api/tasks/run_integrations.py index 44e981e..8a3d77c 100644 --- a/api/tasks/run_integrations.py +++ b/api/tasks/run_integrations.py @@ -1,10 +1,11 @@ """Execute webhook integrations after workflow run completion.""" -from typing import Any, Dict +from typing import Any, Dict, Optional import httpx from loguru import logger +from api.constants import BACKEND_API_ENDPOINT from api.db import db_client from api.db.models import WorkflowRunModel from api.utils.credential_auth import build_auth_header @@ -54,10 +55,13 @@ async def run_integrations_post_workflow_run(_ctx, workflow_run_id: int): logger.info(f"Found {len(webhook_nodes)} webhook nodes to execute") - # Step 4: Build render context - render_context = _build_render_context(workflow_run) + # Step 4: Generate public access token (on-demand, only when webhooks exist) + public_token = await db_client.ensure_public_access_token(workflow_run_id) - # Step 5: Execute each webhook node + # Step 5: Build render context + render_context = _build_render_context(workflow_run, public_token) + + # Step 6: Execute each webhook node for node in webhook_nodes: webhook_data = node.get("data", {}) try: @@ -77,9 +81,19 @@ async def run_integrations_post_workflow_run(_ctx, workflow_run_id: int): raise -def _build_render_context(workflow_run: WorkflowRunModel) -> Dict[str, Any]: - """Build the context dict for template rendering.""" - return { +def _build_render_context( + workflow_run: WorkflowRunModel, public_token: Optional[str] = None +) -> Dict[str, Any]: + """Build the context dict for template rendering. + + Args: + workflow_run: The workflow run model + public_token: Optional public access token for download URLs + + Returns: + Dict containing all fields available for template rendering + """ + context = { # Top-level fields "workflow_run_id": workflow_run.id, "workflow_run_name": workflow_run.name, @@ -89,10 +103,25 @@ def _build_render_context(workflow_run: WorkflowRunModel) -> Dict[str, Any]: "initial_context": workflow_run.initial_context or {}, "gathered_context": workflow_run.gathered_context or {}, "cost_info": workflow_run.usage_info or {}, - "recording_url": getattr(workflow_run, "recording_url", None), - "transcript_url": getattr(workflow_run, "transcript_url", None), } + # Add public download URLs if token is available + if public_token: + base_url = ( + f"{BACKEND_API_ENDPOINT}/api/v1/public/download/workflow/{public_token}" + ) + context["recording_url"] = ( + f"{base_url}/recording" if workflow_run.recording_url else None + ) + context["transcript_url"] = ( + f"{base_url}/transcript" if workflow_run.transcript_url else None + ) + else: + context["recording_url"] = workflow_run.recording_url + context["transcript_url"] = workflow_run.transcript_url + + return context + async def _execute_webhook_node( webhook_data: Dict[str, Any], diff --git a/api/tasks/s3_upload.py b/api/tasks/s3_upload.py index 9faf432..d1c55a6 100644 --- a/api/tasks/s3_upload.py +++ b/api/tasks/s3_upload.py @@ -1,129 +1,27 @@ import os +from typing import Optional from loguru import logger -from pipecat.utils.context import set_current_run_id from api.db import db_client from api.services.storage import get_current_storage_backend, storage_fs - - -async def upload_audio_to_s3(ctx, workflow_run_id: int, temp_file_path: str): - """Upload audio file from temp path to S3.""" - run_id = str(workflow_run_id) - set_current_run_id(run_id) - - logger.info(f"Starting audio upload to S3 from {temp_file_path}") - - try: - # Verify temp file exists - if not os.path.exists(temp_file_path): - logger.error(f"Temp audio file not found: {temp_file_path}") - raise FileNotFoundError(f"Temp audio file not found: {temp_file_path}") - - file_size = os.path.getsize(temp_file_path) - logger.debug(f"Audio file size: {file_size} bytes") - - recording_url = f"recordings/{workflow_run_id}.wav" - storage_backend = get_current_storage_backend() - - logger.info( - f"UPLOAD: Using {storage_backend.name} (value: {storage_backend.value}) for audio upload - workflow_run_id: {workflow_run_id}" - ) - - await storage_fs.aupload_file(temp_file_path, recording_url) - - # Update DB with recording URL and storage backend - await db_client.update_workflow_run( - run_id=workflow_run_id, - recording_url=recording_url, - storage_backend=storage_backend.value, - ) - - logger.info( - f"Successfully uploaded audio to {storage_backend.name}: {recording_url} (stored backend: {storage_backend.name})" - ) - - except Exception as e: - logger.error(f"Error uploading audio to S3 for workflow {workflow_run_id}: {e}") - raise - finally: - # Clean up temp file - if os.path.exists(temp_file_path): - try: - os.remove(temp_file_path) - logger.debug(f"Cleaned up temp audio file: {temp_file_path}") - except Exception as e: - logger.warning( - f"Failed to clean up temp audio file {temp_file_path}: {e}" - ) - - -async def upload_transcript_to_s3(ctx, workflow_run_id: int, temp_file_path: str): - """Upload transcript file from temp path to S3.""" - run_id = str(workflow_run_id) - set_current_run_id(run_id) - - logger.info(f"Starting transcript upload to S3 from {temp_file_path}") - - try: - # Verify temp file exists - if not os.path.exists(temp_file_path): - logger.error(f"Temp transcript file not found: {temp_file_path}") - raise FileNotFoundError(f"Temp transcript file not found: {temp_file_path}") - - file_size = os.path.getsize(temp_file_path) - logger.debug(f"Transcript file size: {file_size} bytes") - - transcript_url = f"transcripts/{workflow_run_id}.txt" - storage_backend = get_current_storage_backend() - - logger.info( - f"UPLOAD: Using {storage_backend.name} (value: {storage_backend.value}) for transcript upload - workflow_run_id: {workflow_run_id}" - ) - - await storage_fs.aupload_file(temp_file_path, transcript_url) - - # Update DB with transcript URL and storage backend - await db_client.update_workflow_run( - run_id=workflow_run_id, - transcript_url=transcript_url, - storage_backend=storage_backend.value, - ) - - logger.info( - f"Successfully uploaded transcript to {storage_backend.name}: {transcript_url} (stored backend: {storage_backend.name})" - ) - - except Exception as e: - logger.error( - f"Error uploading transcript to S3 for workflow {workflow_run_id}: {e}" - ) - raise - finally: - # Clean up temp file - if os.path.exists(temp_file_path): - try: - os.remove(temp_file_path) - logger.debug(f"Cleaned up temp transcript file: {temp_file_path}") - except Exception as e: - logger.warning( - f"Failed to clean up temp transcript file {temp_file_path}: {e}" - ) +from api.tasks.run_integrations import run_integrations_post_workflow_run +from pipecat.utils.context import set_current_run_id async def upload_voicemail_audio_to_s3( - ctx, + _ctx, workflow_run_id: int, temp_file_path: str, s3_key: str, ): """Upload voicemail detection audio from temp file to S3. - This function is similar to upload_audio_to_s3 but handles voicemail-specific - paths and doesn't update the workflow run's recording_url field. + Handles voicemail-specific paths and doesn't update the workflow run's + recording_url field. Args: - ctx: ARQ context + _ctx: ARQ context (unused) workflow_run_id: The workflow run ID temp_file_path: Path to the temporary WAV file s3_key: The S3 key where the file should be uploaded @@ -161,7 +59,7 @@ async def upload_voicemail_audio_to_s3( ) raise finally: - # Clean up temp file (same pattern as upload_audio_to_s3) + # Clean up temp file if os.path.exists(temp_file_path): try: os.remove(temp_file_path) @@ -170,3 +68,104 @@ async def upload_voicemail_audio_to_s3( logger.warning( f"Failed to clean up temp voicemail audio file {temp_file_path}: {e}" ) + + +async def process_workflow_completion( + _ctx, + workflow_run_id: int, + audio_temp_path: Optional[str] = None, + transcript_temp_path: Optional[str] = None, +): + """Process workflow completion: upload artifacts and run integrations. + + This task combines audio upload, transcript upload, and webhook integrations + into a single sequential task to ensure integrations run after uploads complete. + + Args: + _ctx: ARQ context (unused) + workflow_run_id: The workflow run ID + audio_temp_path: Optional path to temp audio file + transcript_temp_path: Optional path to temp transcript file + """ + run_id = str(workflow_run_id) + set_current_run_id(run_id) + + logger.info(f"Processing workflow completion for run {workflow_run_id}") + + storage_backend = get_current_storage_backend() + + # Step 1: Upload audio if provided + if audio_temp_path: + try: + if os.path.exists(audio_temp_path): + file_size = os.path.getsize(audio_temp_path) + logger.debug(f"Audio file size: {file_size} bytes") + + recording_url = f"recordings/{workflow_run_id}.wav" + logger.info( + f"Uploading audio to {storage_backend.name} - workflow_run_id: {workflow_run_id}" + ) + + await storage_fs.aupload_file(audio_temp_path, recording_url) + await db_client.update_workflow_run( + run_id=workflow_run_id, + recording_url=recording_url, + storage_backend=storage_backend.value, + ) + logger.info(f"Successfully uploaded audio: {recording_url}") + else: + logger.warning(f"Audio temp file not found: {audio_temp_path}") + except Exception as e: + logger.error(f"Error uploading audio for workflow {workflow_run_id}: {e}") + finally: + if audio_temp_path and os.path.exists(audio_temp_path): + try: + os.remove(audio_temp_path) + logger.debug(f"Cleaned up temp audio file: {audio_temp_path}") + except Exception as e: + logger.warning(f"Failed to clean up temp audio file: {e}") + + # Step 2: Upload transcript if provided + if transcript_temp_path: + try: + if os.path.exists(transcript_temp_path): + file_size = os.path.getsize(transcript_temp_path) + logger.debug(f"Transcript file size: {file_size} bytes") + + transcript_url = f"transcripts/{workflow_run_id}.txt" + logger.info( + f"Uploading transcript to {storage_backend.name} - workflow_run_id: {workflow_run_id}" + ) + + await storage_fs.aupload_file(transcript_temp_path, transcript_url) + await db_client.update_workflow_run( + run_id=workflow_run_id, + transcript_url=transcript_url, + storage_backend=storage_backend.value, + ) + logger.info(f"Successfully uploaded transcript: {transcript_url}") + else: + logger.warning( + f"Transcript temp file not found: {transcript_temp_path}" + ) + except Exception as e: + logger.error( + f"Error uploading transcript for workflow {workflow_run_id}: {e}" + ) + finally: + if transcript_temp_path and os.path.exists(transcript_temp_path): + try: + os.remove(transcript_temp_path) + logger.debug( + f"Cleaned up temp transcript file: {transcript_temp_path}" + ) + except Exception as e: + logger.warning(f"Failed to clean up temp transcript file: {e}") + + # Step 3: Run webhook integrations (after uploads are complete) + try: + await run_integrations_post_workflow_run(_ctx, workflow_run_id) + except Exception as e: + logger.error(f"Error running integrations for workflow {workflow_run_id}: {e}") + + logger.info(f"Completed workflow completion processing for run {workflow_run_id}") diff --git a/api/tests/conftest.py b/api/tests/conftest.py index 9f97778..a7fe452 100644 --- a/api/tests/conftest.py +++ b/api/tests/conftest.py @@ -1,5 +1,5 @@ -from dataclasses import dataclass -from typing import Any, Dict +from dataclasses import dataclass, field +from typing import Any, Dict, Optional from unittest.mock import Mock import pytest @@ -28,6 +28,87 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor START_CALL_SYSTEM_PROMPT = "start_call_system_prompt" END_CALL_SYSTEM_PROMPT = "end_call_system_prompt" +# Default workflow definition for mocking database WorkflowModel +DEFAULT_WORKFLOW_DEFINITION = { + "nodes": [ + { + "id": "1", + "type": "startCall", + "position": {"x": 0, "y": 0}, + "data": { + "name": "Start", + "prompt": START_CALL_SYSTEM_PROMPT, + "is_start": True, + "allow_interrupt": False, + "add_global_prompt": False, + }, + }, + { + "id": "2", + "type": "endCall", + "position": {"x": 0, "y": 200}, + "data": { + "name": "End", + "prompt": END_CALL_SYSTEM_PROMPT, + "is_end": True, + "allow_interrupt": False, + "add_global_prompt": False, + }, + }, + ], + "edges": [ + { + "id": "1-2", + "source": "1", + "target": "2", + "data": {"label": "End", "condition": "End the call"}, + } + ], +} + + +@dataclass +class MockWorkflowModel: + """Mock database WorkflowModel for testing. + + This mimics the structure of the database WorkflowModel, not the parsed WorkflowGraph. + Use this when mocking db_client.get_workflow() responses. + """ + + workflow_id: int = 1 + organization_id: int = 1 + workflow_configurations: Dict[str, Any] = field(default_factory=dict) + workflow_definition_with_fallback: Dict[str, Any] = field(default_factory=dict) + + def __post_init__(self): + if not self.workflow_definition_with_fallback: + self.workflow_definition_with_fallback = DEFAULT_WORKFLOW_DEFINITION.copy() + + +@dataclass +class MockWorkflowRun: + """Mock database WorkflowRun for testing. + + Use this when mocking db_client.get_workflow_run() responses. + """ + + is_completed: bool = False + initial_context: Dict[str, Any] = field(default_factory=dict) + gathered_context: Dict[str, Any] = field(default_factory=dict) + + +@dataclass +class MockUserConfig: + """Mock user configuration for testing. + + Use this when mocking db_client.get_user_configurations() responses. + """ + + stt: Optional[Any] = None + tts: Optional[Any] = None + llm: Optional[Any] = None + embeddings: Optional[Any] = None + class MockTransportProcessor(FrameProcessor): """ @@ -41,7 +122,7 @@ class MockTransportProcessor(FrameProcessor): Args: emit_bot_speaking: If True, also emits BotSpeakingFrame on TTSAudioRawFrame - which is needed for UserIdleProcessor to start conversation tracking. Default True. + which is needed for user idle tracking to start conversation tracking. Default True. """ def __init__( @@ -63,7 +144,7 @@ class MockTransportProcessor(FrameProcessor): BotStartedSpeakingFrame(), direction=FrameDirection.UPSTREAM ) elif isinstance(frame, TTSAudioRawFrame): - # Emit BotSpeakingFrame - this is what triggers the UserIdleProcessor + # Emit BotSpeakingFrame - this is what triggers user idle tracking # to start conversation tracking if self._emit_bot_speaking: await self.push_frame(BotSpeakingFrame()) @@ -101,6 +182,24 @@ def mock_engine(): return engine +@pytest.fixture +def mock_workflow_model(): + """Create a mock WorkflowModel for testing database responses.""" + return MockWorkflowModel() + + +@pytest.fixture +def mock_workflow_run(): + """Create a mock WorkflowRun for testing database responses.""" + return MockWorkflowRun() + + +@pytest.fixture +def mock_user_config(): + """Create a mock user configuration for testing.""" + return MockUserConfig() + + @pytest.fixture def sample_tools(): """Create sample mock tools for testing.""" diff --git a/api/tests/test_pipecat_engine_context_update.py b/api/tests/test_pipecat_engine_context_update.py index e37db03..1a67665 100644 --- a/api/tests/test_pipecat_engine_context_update.py +++ b/api/tests/test_pipecat_engine_context_update.py @@ -42,7 +42,6 @@ from pipecat.processors.aggregators.llm_response_universal import ( ) from pipecat.tests import MockLLMService, MockTTSService - # Define prompts for test nodes START_NODE_PROMPT = "Start Node System Prompt" AGENT_NODE_PROMPT = "Agent Node System Prompt" @@ -143,14 +142,20 @@ class ContextCapturingMockLLM(MockLLMService): msg_copy = dict(msg) # Copy content to avoid reference issues if "content" in msg_copy: - msg_copy["content"] = str(msg_copy["content"]) if msg_copy["content"] else None + msg_copy["content"] = ( + str(msg_copy["content"]) if msg_copy["content"] else None + ) messages_snapshot.append(msg_copy) - self.captured_contexts.append({ - "step": self._current_step, - "messages": messages_snapshot, - "system_prompt": messages_snapshot[0]["content"] if messages_snapshot else None, - }) + self.captured_contexts.append( + { + "step": self._current_step, + "messages": messages_snapshot, + "system_prompt": messages_snapshot[0]["content"] + if messages_snapshot + else None, + } + ) # Call parent implementation to stream the mock chunks return await super()._stream_chat_completions_universal_context(context) @@ -306,14 +311,26 @@ class TestContextUpdateBeforeNextCompletion: transition completes. The test verifies the context is still correctly updated. """ # Step 0 (Start node): call collect_info to transition to agent - step_0_chunks = MockLLMService.create_multiple_function_call_chunks([ - {"name": "collect_info", "arguments": {}, "tool_call_id": "call_transition_1"}, - ]) + step_0_chunks = MockLLMService.create_multiple_function_call_chunks( + [ + { + "name": "collect_info", + "arguments": {}, + "tool_call_id": "call_transition_1", + }, + ] + ) # Step 1 (Agent node): call end_call to transition to end - step_1_chunks = MockLLMService.create_multiple_function_call_chunks([ - {"name": "end_call", "arguments": {}, "tool_call_id": "call_transition_2"}, - ]) + step_1_chunks = MockLLMService.create_multiple_function_call_chunks( + [ + { + "name": "end_call", + "arguments": {}, + "tool_call_id": "call_transition_2", + }, + ] + ) # Step 2 (End node): text response (end node has no outgoing edges) step_2_chunks = MockLLMService.create_text_chunks("Goodbye!") @@ -327,7 +344,7 @@ class TestContextUpdateBeforeNextCompletion: ) # Should have been called 3 times: start node, agent node, end node - assert llm.get_current_step() == 2, ( + assert llm.get_current_step() == 3, ( f"Expected 3 LLM generations (start, agent, end), got {llm.get_current_step()}" ) @@ -376,14 +393,26 @@ class TestContextUpdateBeforeNextCompletion: is handled correctly. """ # Step 0 (Start node): call collect_info to transition to agent - step_0_chunks = MockLLMService.create_multiple_function_call_chunks([ - {"name": "collect_info", "arguments": {}, "tool_call_id": "call_transition_1"}, - ]) + step_0_chunks = MockLLMService.create_multiple_function_call_chunks( + [ + { + "name": "collect_info", + "arguments": {}, + "tool_call_id": "call_transition_1", + }, + ] + ) # Step 1 (Agent node): call end_call to transition to end - step_1_chunks = MockLLMService.create_multiple_function_call_chunks([ - {"name": "end_call", "arguments": {}, "tool_call_id": "call_transition_2"}, - ]) + step_1_chunks = MockLLMService.create_multiple_function_call_chunks( + [ + { + "name": "end_call", + "arguments": {}, + "tool_call_id": "call_transition_2", + }, + ] + ) # Step 2 (End node): text response step_2_chunks = MockLLMService.create_text_chunks("Goodbye!") @@ -397,7 +426,7 @@ class TestContextUpdateBeforeNextCompletion: ) # Verify all three nodes were executed - assert llm.get_current_step() == 2, ( + assert llm.get_current_step() == 3, ( f"Expected 3 steps, got {llm.get_current_step()}" ) @@ -408,8 +437,7 @@ class TestContextUpdateBeforeNextCompletion: assert AGENT_NODE_PROMPT in llm.get_system_prompt_at_step(1) # Step 2: End node - should have end prompt - # FIXME - EndFrame is getting processed before LLMContextFrame - # assert END_NODE_PROMPT in llm.get_system_prompt_at_step(2) + assert END_NODE_PROMPT in llm.get_system_prompt_at_step(2) # Verify each subsequent step has the previous tool results step_1_ctx = llm.get_context_at_step(1) @@ -423,14 +451,14 @@ class TestContextUpdateBeforeNextCompletion: assert step_1_has_tool, "Agent node should see collect_info tool result" # Step 2 should have tool results from both transitions - # FIXME - EndFrame is getting processed before LLMContextFrame - # step_2_tool_messages = [ - # msg for msg in step_2_ctx["messages"] - # if msg.get("role") == "tool" or msg.get("tool_call_id") - # ] - # assert len(step_2_tool_messages) >= 2, ( - # f"End node should see at least 2 tool results, got {len(step_2_tool_messages)}" - # ) + step_2_tool_messages = [ + msg + for msg in step_2_ctx["messages"] + if msg.get("role") == "tool" or msg.get("tool_call_id") + ] + assert len(step_2_tool_messages) >= 2, ( + f"End node should see at least 2 tool results, got {len(step_2_tool_messages)}" + ) @pytest.mark.asyncio async def test_context_messages_preserve_conversation_history( @@ -444,14 +472,26 @@ class TestContextUpdateBeforeNextCompletion: - Tool call messages and results """ # Step 0 (Start node): call collect_info to transition to agent - step_0_chunks = MockLLMService.create_multiple_function_call_chunks([ - {"name": "collect_info", "arguments": {}, "tool_call_id": "call_transition_1"}, - ]) + step_0_chunks = MockLLMService.create_multiple_function_call_chunks( + [ + { + "name": "collect_info", + "arguments": {}, + "tool_call_id": "call_transition_1", + }, + ] + ) # Step 1 (Agent node): call end_call to transition to end - step_1_chunks = MockLLMService.create_multiple_function_call_chunks([ - {"name": "end_call", "arguments": {}, "tool_call_id": "call_transition_2"}, - ]) + step_1_chunks = MockLLMService.create_multiple_function_call_chunks( + [ + { + "name": "end_call", + "arguments": {}, + "tool_call_id": "call_transition_2", + }, + ] + ) # Step 2 (End node): text response step_2_chunks = MockLLMService.create_text_chunks("Goodbye!") @@ -472,18 +512,15 @@ class TestContextUpdateBeforeNextCompletion: assert len(ctx_1["messages"]) > len(ctx_0["messages"]), ( "Context at step 1 should have more messages than step 0" ) - - # FIXME - # assert len(ctx_2["messages"]) > len(ctx_1["messages"]), ( - # "Context at step 2 should have more messages than step 1" - # ) + + assert len(ctx_2["messages"]) > len(ctx_1["messages"]), ( + "Context at step 2 should have more messages than step 1" + ) # Verify assistant messages are accumulated - # FIXME - # assistant_messages_at_step_2 = [ - # msg for msg in ctx_2["messages"] - # if msg.get("role") == "assistant" - # ] - # assert len(assistant_messages_at_step_2) >= 2, ( - # "Should have at least 2 assistant messages by step 2" - # ) + assistant_messages_at_step_2 = [ + msg for msg in ctx_2["messages"] if msg.get("role") == "assistant" + ] + assert len(assistant_messages_at_step_2) >= 2, ( + "Should have at least 2 assistant messages by step 2" + ) diff --git a/api/tests/test_pipeline_cancellation.py b/api/tests/test_pipeline_cancellation.py new file mode 100644 index 0000000..45f04c5 --- /dev/null +++ b/api/tests/test_pipeline_cancellation.py @@ -0,0 +1,100 @@ +import asyncio + +import pytest +from loguru import logger + +from pipecat.frames.frames import ( + EndTaskFrame, + Frame, + InterruptionTaskFrame, + LLMRunFrame, +) +from pipecat.pipeline.base_task import PipelineTaskParams +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.task import PipelineTask +from pipecat.processors.frame_processor import FrameDirection, FrameProcessor + + +class MockTransport(FrameProcessor): + def __init__(self, **kwargs): + super().__init__(**kwargs) + + async def process_frame(self, frame: Frame, direction: FrameDirection): + await super().process_frame(frame, direction) + await self.push_frame(frame, direction) + + +class BusyWaitProcessor(FrameProcessor): + def __init__(self, wait_time=5.0, **kwargs): + super().__init__(**kwargs) + self._wait_time = wait_time + + async def process_frame(self, frame: Frame, direction: FrameDirection): + await super().process_frame(frame, direction) + if isinstance(frame, LLMRunFrame): + # Simulate a delay, which can happen sometimes due to slow LLM Inferencing or + # other reasons + try: + logger.debug(f"{self} sleeping with frame: {frame}") + await asyncio.sleep(5) + logger.debug(f"{self} woke up with frame: {frame}") + except asyncio.CancelledError: + logger.debug(f"{self} was cancelled") + raise + await self.push_frame(frame, direction) + + +@pytest.mark.asyncio +async def test_interruption_with_blocked_end_frame(): + busy_wait_processor = BusyWaitProcessor(wait_time=5) + transport = MockTransport() + pipeline = Pipeline([transport, busy_wait_processor]) + + task = PipelineTask(pipeline) + + async def run_pipeline(): + loop = asyncio.get_running_loop() + params = PipelineTaskParams(loop=loop) + await task.run(params=params) + + async def queue_frame(): + await task.queue_frames([LLMRunFrame()]) + + # Send EndTaskFrame to simulate EndFrame + await asyncio.sleep(0.1) + await transport.queue_frame(EndTaskFrame(), direction=FrameDirection.UPSTREAM) + + # Simulate an Interruption, which can happen if the user + # has started to speak + await asyncio.sleep(0.1) + await transport.queue_frame( + InterruptionTaskFrame(), direction=FrameDirection.UPSTREAM + ) + + # Create tasks explicitly for better control + pipeline_task = asyncio.create_task(run_pipeline()) + queue_task = asyncio.create_task(queue_frame()) + + # Wait with timeout + done, pending = await asyncio.wait( + [pipeline_task, queue_task], + timeout=1.0, + return_when=asyncio.ALL_COMPLETED, + ) + + # If there are pending tasks, we timed out + if pending: + # Cancel all pending tasks + for t in pending: + t.cancel() + + # Give limited time for cleanup, then move on regardless + try: + await asyncio.wait_for( + asyncio.gather(*pending, return_exceptions=True), + timeout=1.0, + ) + except asyncio.TimeoutError: + pass # Cleanup took too long, continue anyway + + pytest.fail("Test timed out after 1 second") diff --git a/api/tests/test_user_idle_handler.py b/api/tests/test_user_idle_handler.py index 4d73abf..ac5252c 100644 --- a/api/tests/test_user_idle_handler.py +++ b/api/tests/test_user_idle_handler.py @@ -1,10 +1,10 @@ """ Simulates a user idle condition and tests the behaviour -of the user idle processor. +of the user idle handler. This module tests the behavior when the user becomes idle during a conversation, -ensuring the UserIdleProcessor properly triggers the callback and the engine -handles it correctly. +ensuring the user_idle_timeout in LLMUserAggregatorParams properly triggers +the on_user_turn_idle event and the engine handles it correctly. """ import asyncio @@ -23,8 +23,8 @@ from pipecat.processors.aggregators.llm_context import LLMContext from pipecat.processors.aggregators.llm_response import LLMAssistantAggregatorParams from pipecat.processors.aggregators.llm_response_universal import ( LLMContextAggregatorPair, + LLMUserAggregatorParams, ) -from pipecat.processors.user_idle_processor import UserIdleProcessor from pipecat.tests import MockLLMService, MockTTSService @@ -32,8 +32,8 @@ async def run_pipeline_with_user_idle( workflow: WorkflowGraph, user_idle_timeout: float = 0.2, mock_steps: list | None = None, -) -> tuple[MockLLMService, LLMContext, UserIdleProcessor]: - """Run a pipeline with UserIdleProcessor and simulate user idle condition. +) -> tuple[MockLLMService, LLMContext]: + """Run a pipeline with user_idle_timeout and simulate user idle condition. Args: workflow: The workflow graph to use. @@ -42,7 +42,7 @@ async def run_pipeline_with_user_idle( defaults to a simple greeting followed by text responses. Returns: - Tuple of (MockLLMService, LLMContext, UserIdleProcessor) for assertions. + Tuple of (MockLLMService, LLMContext) for assertions. """ # Create mock responses - bot will speak first, then respond to idle prompts # Step 1: Initial greeting @@ -64,10 +64,11 @@ async def run_pipeline_with_user_idle( # Create LLM context context = LLMContext() - # Create context aggregator with both user and assistant aggregators + # Create context aggregator with user_idle_timeout in user_params assistant_params = LLMAssistantAggregatorParams(expect_stripped_words=True) + user_params = LLMUserAggregatorParams(user_idle_timeout=user_idle_timeout) context_aggregator = LLMContextAggregatorPair( - context, assistant_params=assistant_params + context, assistant_params=assistant_params, user_params=user_params ) user_context_aggregator = context_aggregator.user() assistant_context_aggregator = context_aggregator.assistant() @@ -81,18 +82,20 @@ async def run_pipeline_with_user_idle( workflow_run_id=1, ) - # Create UserIdleProcessor with engine's callback and a short timeout - user_idle_processor = UserIdleProcessor( - callback=engine.create_user_idle_callback(), - timeout=user_idle_timeout, - ) + # Register user idle event handlers + user_idle_handler = engine.create_user_idle_handler() - # Build the pipeline: - # llm -> mock_transport -> user_idle_processor -> assistant_context_aggregator - # The user_context_aggregator would normally be at the start for user input + @user_context_aggregator.event_handler("on_user_turn_idle") + async def on_user_turn_idle(aggregator): + await user_idle_handler.handle_idle(aggregator) + + @user_context_aggregator.event_handler("on_user_turn_started") + async def on_user_turn_started(aggregator, strategy): + user_idle_handler.reset() + + # Build the pipeline pipeline = Pipeline( [ - user_idle_processor, user_context_aggregator, llm, tts, @@ -154,11 +157,11 @@ async def run_pipeline_with_user_idle( return_exceptions=True, ) - return llm, context, user_idle_processor + return llm, context class TestUserIdleHandler: - """Test user idle handling through PipecatEngine and UserIdleProcessor.""" + """Test user idle handling through PipecatEngine and UserIdleHandler.""" @pytest.mark.asyncio async def test_user_idle_triggers_callback(self, simple_workflow: WorkflowGraph): @@ -167,13 +170,13 @@ class TestUserIdleHandler: This test verifies that when: 1. The bot starts speaking (triggers conversation tracking) 2. No user input is received for the timeout period - 3. The UserIdleProcessor triggers the idle callback + 3. The on_user_turn_idle event triggers the idle handler - The engine's user idle callback should: + The engine's user idle handler should: - First retry: Send a message asking if user is still there - Second retry: Send goodbye message and end the call """ - llm, context, user_idle_processor = await run_pipeline_with_user_idle( + llm, context = await run_pipeline_with_user_idle( workflow=simple_workflow, user_idle_timeout=0.2, # Short timeout for faster test ) @@ -220,7 +223,7 @@ class TestUserIdleHandler: MockLLMService.create_text_chunks("Response 3"), ] - llm, context, user_idle_processor = await run_pipeline_with_user_idle( + llm, context = await run_pipeline_with_user_idle( workflow=three_node_workflow, user_idle_timeout=0.2, mock_steps=mock_steps, diff --git a/docker-compose.yaml b/docker-compose.yaml index 26f2144..7dc661f 100644 --- a/docker-compose.yaml +++ b/docker-compose.yaml @@ -1,6 +1,6 @@ services: postgres: - image: postgres:17 + image: pgvector/pgvector:pg17 environment: POSTGRES_USER: postgres POSTGRES_PASSWORD: postgres @@ -83,6 +83,10 @@ services: ENVIRONMENT: "local" LOG_LEVEL: "INFO" + # Replace this environment variable if you are using a custom + # domain to host the stack + BACKEND_API_ENDPOINT: "http://localhost:8000" + # Database configuration (using containerized postgres) DATABASE_URL: "postgresql+asyncpg://postgres:postgres@postgres:5432/postgres" diff --git a/docs/deployment/custom-domain.mdx b/docs/deployment/custom-domain.mdx index 073b080..e2bedbb 100644 --- a/docs/deployment/custom-domain.mdx +++ b/docs/deployment/custom-domain.mdx @@ -162,6 +162,10 @@ server { } ``` +### Add environment variable + +Replace `BACKEND_API_ENDPOINT` environment variable the `docker-compose.yaml` with your custom domain with the scheme. + ### Start Dograh Services Start Dograh with the updated configuration: diff --git a/evals/stt/README.md b/evals/stt/README.md new file mode 100644 index 0000000..6e2802b --- /dev/null +++ b/evals/stt/README.md @@ -0,0 +1,135 @@ +# STT Evaluation Benchmark + +Benchmark for comparing Speech-to-Text providers using **WebSocket streaming** with focus on: +- **Speaker diarization** - identifying who said what +- **Keyterm boosting** - improving recognition of specific terms (Deepgram) + +## Providers + +| Provider | Diarization | Keyterm Boost | Streaming | +|----------|-------------|---------------|-----------| +| Deepgram | Yes | Yes | WebSocket (v1/v2) | +| Speechmatics | Yes | Additional vocab | WebSocket RT | + +## Setup + +```bash +# Install dependencies +pip install websockets + +# Set API keys +export DEEPGRAM_API_KEY="your-key" +export SPEECHMATICS_API_KEY="your-key" +``` + +**Note:** Requires `ffmpeg` installed for audio conversion to PCM16. + +## Usage + +Run from the project root directory: + +```bash +# Test both providers with diarization +python -m evals.stt.benchmark audio/multi_speaker.m4a --diarize + +# Test only Deepgram +python -m evals.stt.benchmark audio/multi_speaker.m4a --diarize --providers deepgram + +# Test with keyterm boosting (Deepgram) +python -m evals.stt.benchmark audio/multi_speaker.m4a --diarize --keyterms "Dograh" "Pipecat" + +# Use different sample rate (default: 8000 Hz) +python -m evals.stt.benchmark audio/multi_speaker.m4a --diarize --sample-rate 16000 + +# Show word-level timings +python -m evals.stt.benchmark audio/multi_speaker.m4a --diarize --show-words + +# Save results to JSON +python -m evals.stt.benchmark audio/multi_speaker.m4a --diarize --save +``` + +## CLI Options + +| Option | Description | +|--------|-------------| +| `audio_file` | Path to audio file (relative to evals/stt/ or absolute) | +| `--providers` | Providers to test: `deepgram`, `speechmatics` (default: both) | +| `--diarize` | Enable speaker diarization | +| `--keyterms` | Keywords to boost (Deepgram) / additional vocab (Speechmatics) | +| `--language` | Language code (default: en) | +| `--sample-rate` | Audio sample rate for streaming (default: 8000) | +| `--show-words` | Show individual word timings | +| `--save` | Save results to JSON in `results/` | + +## Directory Structure + +``` +evals/stt/ +├── audio/ # Audio test files +│ └── multi_speaker.m4a +├── results/ # Saved benchmark results (JSON) +├── providers/ # STT provider implementations +│ ├── base.py # Base classes +│ ├── deepgram_provider.py # WebSocket streaming +│ └── speechmatics_provider.py # WebSocket streaming +├── audio_streamer.py # PCM16 audio file streamer +├── benchmark.py # Main runner script +└── README.md +``` + +## How It Works + +1. **Audio Conversion**: The `AudioStreamer` converts any audio file to raw PCM16 using ffmpeg +2. **WebSocket Connection**: Providers connect to their respective WebSocket APIs +3. **Streaming**: Audio is sent in chunks (configurable sample rate, default 8kHz) +4. **Result Collection**: Transcripts and speaker info are collected from WebSocket responses +5. **Comparison**: Results are parsed into a common format for comparison + +## Output Example + +``` +Audio file: /path/to/audio/multi_speaker.m4a +Providers: ['deepgram', 'speechmatics'] +Diarization: True +Sample rate: 8000 Hz + +============================================================ +Provider: DEEPGRAM +============================================================ + +Duration: 45.32s +Speakers detected: 2 - ['0', '1'] + +Transcript: +Hello, welcome to the demo... + +--- Speaker Segments --- +[0.0s] Speaker 0: Hello, welcome to the demo. +[2.5s] Speaker 1: Thanks for having me. +... + +============================================================ +COMPARISON SUMMARY +============================================================ + +Provider Duration Speakers Words +--------------------------------------------- +deepgram 45.32 2 312 +speechmatics 45.32 2 308 +``` + +## Adding New Providers + +1. Create a new file in `providers/` (e.g., `whisper_provider.py`) +2. Implement the `STTProvider` abstract class with WebSocket streaming +3. Use `AudioStreamer` for PCM16 conversion +4. Add to `providers/__init__.py` +5. Add to `benchmark.py` provider choices + +## API Documentation + +- Deepgram Streaming: https://developers.deepgram.com/docs/live-streaming-audio +- Deepgram Diarization: https://developers.deepgram.com/docs/diarization +- Deepgram Keyterms: https://developers.deepgram.com/docs/keyterm +- Speechmatics RT API: https://docs.speechmatics.com/rt-api-ref +- Speechmatics Diarization: https://docs.speechmatics.com/features/diarization diff --git a/evals/stt/__init__.py b/evals/stt/__init__.py new file mode 100644 index 0000000..8c12ae8 --- /dev/null +++ b/evals/stt/__init__.py @@ -0,0 +1 @@ +# STT Evaluation Benchmark diff --git a/evals/stt/audio/multi_speaker.m4a b/evals/stt/audio/multi_speaker.m4a new file mode 100644 index 0000000..d1ab1f5 Binary files /dev/null and b/evals/stt/audio/multi_speaker.m4a differ diff --git a/evals/stt/audio/nope.m4a b/evals/stt/audio/nope.m4a new file mode 100644 index 0000000..f9c86c2 Binary files /dev/null and b/evals/stt/audio/nope.m4a differ diff --git a/evals/stt/audio/not_so_sure.m4a b/evals/stt/audio/not_so_sure.m4a new file mode 100644 index 0000000..acaae9a Binary files /dev/null and b/evals/stt/audio/not_so_sure.m4a differ diff --git a/evals/stt/audio/vad.m4a b/evals/stt/audio/vad.m4a new file mode 100644 index 0000000..e0488c7 Binary files /dev/null and b/evals/stt/audio/vad.m4a differ diff --git a/evals/stt/audio/yes.m4a b/evals/stt/audio/yes.m4a new file mode 100644 index 0000000..3c6e5a9 Binary files /dev/null and b/evals/stt/audio/yes.m4a differ diff --git a/evals/stt/audio_streamer.py b/evals/stt/audio_streamer.py new file mode 100644 index 0000000..d9c98fc --- /dev/null +++ b/evals/stt/audio_streamer.py @@ -0,0 +1,140 @@ +"""Audio file streamer - converts audio files to PCM16 streams.""" + +import asyncio +import subprocess +from dataclasses import dataclass +from pathlib import Path +from typing import AsyncIterator + + +@dataclass +class AudioConfig: + """Audio streaming configuration.""" + + sample_rate: int = 8000 + channels: int = 1 + sample_width: int = 2 # 16-bit = 2 bytes + chunk_duration_ms: int = 80 # Send chunks every 80ms + + @property + def chunk_size(self) -> int: + """Bytes per chunk based on duration.""" + samples_per_chunk = int(self.sample_rate * self.chunk_duration_ms / 1000) + return samples_per_chunk * self.channels * self.sample_width + + +class AudioStreamer: + """Streams audio files as PCM16 chunks. + + Converts any audio format to raw PCM16 using ffmpeg and streams + in real-time chunks to simulate live audio. + """ + + def __init__(self, config: AudioConfig | None = None): + self.config = config or AudioConfig() + + def convert_to_pcm16(self, audio_path: Path) -> bytes: + """Convert audio file to raw PCM16 bytes using ffmpeg. + + Args: + audio_path: Path to input audio file + + Returns: + Raw PCM16 audio bytes + """ + cmd = [ + "ffmpeg", + "-i", + str(audio_path), + "-f", + "s16le", # signed 16-bit little-endian + "-acodec", + "pcm_s16le", + "-ar", + str(self.config.sample_rate), + "-ac", + str(self.config.channels), + "-", # output to stdout + ] + + result = subprocess.run( + cmd, + capture_output=True, + check=True, + ) + return result.stdout + + async def stream_file( + self, + audio_path: Path, + realtime: bool = True, + trailing_silence_seconds: float = 0.0, + ) -> AsyncIterator[bytes]: + """Stream audio file as PCM16 chunks. + + Args: + audio_path: Path to audio file + realtime: If True, add delays to simulate real-time streaming + trailing_silence_seconds: Seconds of silence to append after audio ends. + Useful for capturing pending end-of-turn events from STT providers. + + Yields: + PCM16 audio chunks + """ + # Convert entire file to PCM16 + pcm_data = self.convert_to_pcm16(audio_path) + + chunk_size = self.config.chunk_size + delay = self.config.chunk_duration_ms / 1000.0 if realtime else 0 + + # Stream audio chunks + for i in range(0, len(pcm_data), chunk_size): + chunk = pcm_data[i : i + chunk_size] + if chunk: + yield chunk + if realtime and delay > 0: + await asyncio.sleep(delay) + + # Stream trailing silence if requested + if trailing_silence_seconds > 0: + silence_chunk = bytes(chunk_size) # Zero-filled bytes = silence + num_silence_chunks = int(trailing_silence_seconds / (self.config.chunk_duration_ms / 1000.0)) + + for _ in range(num_silence_chunks): + yield silence_chunk + if realtime and delay > 0: + await asyncio.sleep(delay) + + async def stream_file_fast(self, audio_path: Path) -> AsyncIterator[bytes]: + """Stream audio file as fast as possible (no real-time delay). + + Args: + audio_path: Path to audio file + + Yields: + PCM16 audio chunks + """ + async for chunk in self.stream_file(audio_path, realtime=False): + yield chunk + + def get_duration(self, audio_path: Path) -> float: + """Get audio file duration in seconds. + + Args: + audio_path: Path to audio file + + Returns: + Duration in seconds + """ + cmd = [ + "ffprobe", + "-v", + "error", + "-show_entries", + "format=duration", + "-of", + "default=noprint_wrappers=1:nokey=1", + str(audio_path), + ] + result = subprocess.run(cmd, capture_output=True, text=True, check=True) + return float(result.stdout.strip()) diff --git a/evals/stt/benchmark.py b/evals/stt/benchmark.py new file mode 100644 index 0000000..7740cee --- /dev/null +++ b/evals/stt/benchmark.py @@ -0,0 +1,247 @@ +#!/usr/bin/env python3 +"""STT Benchmark Runner. + +Compare speech-to-text transcription across providers with focus on: +- Speaker diarization accuracy +- Keyword/keyterm recognition +- Transcription quality + +Usage: + python -m evals.stt.benchmark audio/multi_speaker.m4a --diarize + python -m evals.stt.benchmark audio/multi_speaker.m4a --diarize --providers deepgram + python -m evals.stt.benchmark audio/multi_speaker.m4a --diarize --keyterms "Dograh" "Pipecat" +""" + +import argparse +import asyncio +import json +import sys +from datetime import datetime +from pathlib import Path +from typing import Any + +from evals.stt.providers import ( + DeepgramProvider, + DeepgramFluxProvider, + SpeechmaticsProvider, + LocalSmartTurnProvider, + STTProvider, + TranscriptionResult, +) + + +def get_provider(name: str) -> STTProvider: + """Get provider instance by name.""" + providers = { + "deepgram": DeepgramProvider, + "deepgram-flux": DeepgramFluxProvider, + "speechmatics": SpeechmaticsProvider, + "local-smart-turn": LocalSmartTurnProvider, + } + if name not in providers: + raise ValueError(f"Unknown provider: {name}. Available: {list(providers.keys())}") + return providers[name]() + + +async def run_transcription( + provider: STTProvider, + audio_path: Path, + diarize: bool = False, + keyterms: list[str] | None = None, + **kwargs: Any, +) -> TranscriptionResult: + """Run transcription with a provider.""" + print(f"\n{'='*60}") + print(f"Provider: {provider.name.upper()}") + print(f"{'='*60}") + + try: + result = await provider.transcribe( + audio_path, + diarize=diarize, + keyterms=keyterms, + **kwargs, + ) + return result + except Exception as e: + print(f"Error with {provider.name}: {e}") + raise + + +def print_result(result: TranscriptionResult, show_words: bool = False) -> None: + """Print transcription result.""" + print(f"\nDuration: {result.duration:.2f}s") + print(f"Speakers detected: {len(result.speakers)} - {result.speakers}") + print(f"\nTranscript:\n{result.transcript}") + + if result.speakers: + print(f"\n--- Speaker Segments ---") + for segment in result.get_speaker_segments(): + speaker = segment["speaker"] or "?" + text = segment["text"] + start = segment["start"] + print(f"[{start:.1f}s] Speaker {speaker}: {text}") + + if show_words: + print(f"\n--- Words ---") + for word in result.words[:50]: # First 50 words + speaker_info = f" (S{word.speaker})" if word.speaker else "" + print(f" {word.start:.2f}s: {word.word}{speaker_info} [{word.confidence:.2f}]") + if len(result.words) > 50: + print(f" ... and {len(result.words) - 50} more words") + + +def save_results( + results: list[TranscriptionResult], + output_dir: Path, + audio_name: str, +) -> Path: + """Save results to JSON file.""" + output_dir.mkdir(parents=True, exist_ok=True) + timestamp = datetime.now().strftime("%Y%m%d_%H%M%S") + output_file = output_dir / f"{audio_name}_{timestamp}.json" + + output_data = { + "timestamp": timestamp, + "audio_file": audio_name, + "results": [r.to_dict() for r in results], + } + + with open(output_file, "w") as f: + json.dump(output_data, f, indent=2) + + print(f"\nResults saved to: {output_file}") + return output_file + + +def compare_results(results: list[TranscriptionResult]) -> None: + """Compare results across providers.""" + if len(results) < 2: + return + + print(f"\n{'='*60}") + print("COMPARISON SUMMARY") + print(f"{'='*60}") + + print(f"\n{'Provider':<15} {'Duration':<10} {'Speakers':<10} {'Words':<10}") + print("-" * 45) + for r in results: + print(f"{r.provider:<15} {r.duration:<10.2f} {len(r.speakers):<10} {len(r.words):<10}") + + # Compare speaker counts + speaker_counts = {r.provider: len(r.speakers) for r in results} + if len(set(speaker_counts.values())) > 1: + print(f"\nNote: Providers detected different speaker counts: {speaker_counts}") + + +async def main() -> int: + parser = argparse.ArgumentParser( + description="STT Benchmark - Compare transcription providers", + formatter_class=argparse.RawDescriptionHelpFormatter, + epilog=""" +Examples: + python -m evals.stt.benchmark audio/multi_speaker.m4a --diarize + python -m evals.stt.benchmark audio/multi_speaker.m4a --diarize --providers deepgram + python -m evals.stt.benchmark audio/multi_speaker.m4a --keyterms "Dograh" "API" + """, + ) + parser.add_argument( + "audio_file", + type=str, + help="Path to audio file (relative to evals/stt/ or absolute)", + ) + parser.add_argument( + "--providers", + nargs="+", + default=["deepgram", "speechmatics"], + choices=["deepgram", "deepgram-flux", "speechmatics", "local-smart-turn"], + help="Providers to test (default: all)", + ) + parser.add_argument( + "--diarize", + action="store_true", + help="Enable speaker diarization", + ) + parser.add_argument( + "--keyterms", + nargs="+", + help="Keywords to boost (Deepgram only)", + ) + parser.add_argument( + "--language", + default="en", + help="Language code (default: en)", + ) + parser.add_argument( + "--sample-rate", + type=int, + default=8000, + help="Audio sample rate for streaming (default: 8000)", + ) + parser.add_argument( + "--show-words", + action="store_true", + help="Show individual word timings", + ) + parser.add_argument( + "--save", + action="store_true", + help="Save results to JSON file", + ) + parser.add_argument( + "--output-dir", + type=str, + default="results", + help="Output directory for results (default: results)", + ) + + args = parser.parse_args() + + # Resolve audio path + script_dir = Path(__file__).parent + audio_path = Path(args.audio_file) + if not audio_path.is_absolute(): + audio_path = script_dir / audio_path + + if not audio_path.exists(): + print(f"Error: Audio file not found: {audio_path}") + return 1 + + print(f"Audio file: {audio_path}") + print(f"Providers: {args.providers}") + print(f"Diarization: {args.diarize}") + print(f"Sample rate: {args.sample_rate} Hz") + if args.keyterms: + print(f"Keyterms: {args.keyterms}") + + results: list[TranscriptionResult] = [] + + for provider_name in args.providers: + try: + provider = get_provider(provider_name) + result = await run_transcription( + provider, + audio_path, + diarize=args.diarize, + keyterms=args.keyterms, + language=args.language, + sample_rate=args.sample_rate, + ) + print_result(result, show_words=args.show_words) + results.append(result) + except Exception as e: + print(f"\nFailed to run {provider_name}: {e}") + continue + + if len(results) > 1: + compare_results(results) + + if args.save and results: + output_dir = script_dir / args.output_dir + save_results(results, output_dir, audio_path.stem) + + return 0 + + +if __name__ == "__main__": + sys.exit(asyncio.run(main())) diff --git a/evals/stt/event_capture.py b/evals/stt/event_capture.py new file mode 100644 index 0000000..7370dfb --- /dev/null +++ b/evals/stt/event_capture.py @@ -0,0 +1,251 @@ +#!/usr/bin/env python3 +"""STT Event Capture Runner. + +Streams audio to STT providers and captures raw WebSocket events with timestamps +for visualization in the web UI. + +Usage: + python -m evals.stt.event_capture audio/multi_speaker.m4a --provider deepgram + python -m evals.stt.event_capture audio/multi_speaker.m4a --provider speechmatics +""" + +import argparse +import asyncio +import json +import sys +from dataclasses import asdict, dataclass, field +from datetime import datetime +from pathlib import Path +from typing import Any, Callable + +from evals.stt.audio_streamer import AudioStreamer +from evals.stt.providers import ( + DeepgramFluxProvider, + DeepgramProvider, + SpeechmaticsProvider, + STTProvider, +) + + +@dataclass +class CapturedEvent: + """A captured WebSocket event with timestamp.""" + + timestamp: float # Time since stream start (seconds) + event_type: str # e.g., "Results", "TurnInfo", "AddTranscript" + data: dict[str, Any] # Raw event payload + + def to_dict(self) -> dict[str, Any]: + return { + "timestamp": self.timestamp, + "event_type": self.event_type, + "data": self.data, + } + + +@dataclass +class EventCaptureResult: + """Result from event capture session.""" + + audio_file: str + audio_path: str # Relative path to audio from results dir + provider: str + duration: float + created_at: str + events: list[CapturedEvent] = field(default_factory=list) + transcript: str = "" # Final transcript for reference + + def to_dict(self) -> dict[str, Any]: + return { + "audio_file": self.audio_file, + "audio_path": self.audio_path, + "provider": self.provider, + "duration": self.duration, + "created_at": self.created_at, + "events": [e.to_dict() for e in self.events], + "transcript": self.transcript, + } + + +EventCallback = Callable[[str, dict[str, Any]], None] + + +def get_provider(name: str) -> STTProvider: + """Get provider instance by name.""" + providers = { + "deepgram": DeepgramProvider, + "deepgram-flux": DeepgramFluxProvider, + "speechmatics": SpeechmaticsProvider, + } + if name not in providers: + raise ValueError(f"Unknown provider: {name}. Available: {list(providers.keys())}") + return providers[name]() + + +async def capture_events( + provider: STTProvider, + audio_path: Path, + sample_rate: int = 8000, + **kwargs: Any, +) -> EventCaptureResult: + """Capture WebSocket events from a provider. + + Args: + provider: The STT provider to use + audio_path: Path to the audio file + sample_rate: Audio sample rate + **kwargs: Additional provider parameters + + Returns: + EventCaptureResult with all captured events + """ + # Get audio duration + streamer = AudioStreamer() + duration = streamer.get_duration(audio_path) + + # Event list and start time + events: list[CapturedEvent] = [] + start_time: float | None = None + + def on_event(event_type: str, data: dict[str, Any]) -> None: + """Callback for capturing events.""" + nonlocal start_time + if start_time is None: + start_time = asyncio.get_event_loop().time() + + timestamp = asyncio.get_event_loop().time() - start_time + events.append(CapturedEvent(timestamp=timestamp, event_type=event_type, data=data)) + + # Run transcription with event callback + result = await provider.transcribe( + audio_path, + sample_rate=sample_rate, + on_event=on_event, + **kwargs, + ) + + return EventCaptureResult( + audio_file=audio_path.name, + audio_path=f"../audio/{audio_path.name}", + provider=provider.name, + duration=duration, + created_at=datetime.now().isoformat(), + events=events, + transcript=result.transcript, + ) + + +def save_result(result: EventCaptureResult, output_dir: Path) -> Path: + """Save capture result to JSON file. + + Args: + result: The capture result to save + output_dir: Directory to save results + + Returns: + Path to the saved file + """ + output_dir.mkdir(parents=True, exist_ok=True) + + # Format: {audio_name}-{provider}.json + audio_name = Path(result.audio_file).stem + output_file = output_dir / f"{audio_name}-{result.provider}.json" + + with open(output_file, "w") as f: + json.dump(result.to_dict(), f, indent=2) + + return output_file + + +async def main() -> int: + parser = argparse.ArgumentParser( + description="STT Event Capture - Capture WebSocket events for visualization", + formatter_class=argparse.RawDescriptionHelpFormatter, + epilog=""" +Examples: + python -m evals.stt.event_capture audio/multi_speaker.m4a --provider deepgram + python -m evals.stt.event_capture audio/multi_speaker.m4a --provider speechmatics --diarize + """, + ) + parser.add_argument( + "audio_file", + type=str, + help="Path to audio file (relative to evals/stt/ or absolute)", + ) + parser.add_argument( + "--provider", + required=True, + choices=["deepgram", "deepgram-flux", "speechmatics"], + help="STT provider to use", + ) + parser.add_argument( + "--sample-rate", + type=int, + default=8000, + help="Audio sample rate for streaming (default: 8000)", + ) + parser.add_argument( + "--diarize", + action="store_true", + help="Enable speaker diarization", + ) + parser.add_argument( + "--output-dir", + type=str, + default="results", + help="Output directory for results (default: results)", + ) + + args = parser.parse_args() + + # Resolve audio path + script_dir = Path(__file__).parent + audio_path = Path(args.audio_file) + if not audio_path.is_absolute(): + audio_path = script_dir / audio_path + + if not audio_path.exists(): + print(f"Error: Audio file not found: {audio_path}") + return 1 + + print(f"Audio file: {audio_path}") + print(f"Provider: {args.provider}") + print(f"Sample rate: {args.sample_rate} Hz") + print(f"Diarization: {args.diarize}") + + try: + provider = get_provider(args.provider) + print(f"\nCapturing events from {provider.name}...") + + result = await capture_events( + provider, + audio_path, + sample_rate=args.sample_rate, + diarize=args.diarize, + ) + + output_dir = script_dir / args.output_dir + output_file = save_result(result, output_dir) + + print(f"\nCapture complete!") + print(f" Duration: {result.duration:.2f}s") + print(f" Events: {len(result.events)}") + print(f" Saved to: {output_file}") + + # Show first few events + print(f"\nFirst 5 events:") + for event in result.events[:5]: + print(f" [{event.timestamp:.2f}s] {event.event_type}") + + return 0 + + except Exception as e: + print(f"\nError: {e}") + import traceback + + traceback.print_exc() + return 1 + + +if __name__ == "__main__": + sys.exit(asyncio.run(main())) diff --git a/evals/stt/providers/__init__.py b/evals/stt/providers/__init__.py new file mode 100644 index 0000000..5df045c --- /dev/null +++ b/evals/stt/providers/__init__.py @@ -0,0 +1,16 @@ +from .base import EventCallback, STTProvider, TranscriptionResult, Word +from .deepgram_provider import DeepgramProvider +from .deepgram_flux_provider import DeepgramFluxProvider +from .speechmatics_provider import SpeechmaticsProvider +from .local_smart_turn_provider import LocalSmartTurnProvider + +__all__ = [ + "EventCallback", + "STTProvider", + "TranscriptionResult", + "Word", + "DeepgramProvider", + "DeepgramFluxProvider", + "SpeechmaticsProvider", + "LocalSmartTurnProvider", +] diff --git a/evals/stt/providers/base.py b/evals/stt/providers/base.py new file mode 100644 index 0000000..de41265 --- /dev/null +++ b/evals/stt/providers/base.py @@ -0,0 +1,128 @@ +"""Base classes for STT providers.""" + +from abc import ABC, abstractmethod +from dataclasses import dataclass, field +from pathlib import Path +from typing import Any, Callable + +# Event callback type: (event_type, data) -> None +EventCallback = Callable[[str, dict[str, Any]], None] + + +@dataclass +class Word: + """Represents a transcribed word with metadata.""" + + word: str + start: float + end: float + confidence: float + speaker: str | None = None + speaker_confidence: float | None = None + + def to_dict(self) -> dict[str, Any]: + return { + "word": self.word, + "start": self.start, + "end": self.end, + "confidence": self.confidence, + "speaker": self.speaker, + "speaker_confidence": self.speaker_confidence, + } + + +@dataclass +class TranscriptionResult: + """Result from STT transcription.""" + + provider: str + transcript: str + words: list[Word] + speakers: list[str] + duration: float + raw_response: dict[str, Any] = field(default_factory=dict) + params: dict[str, Any] = field(default_factory=dict) + + def to_dict(self) -> dict[str, Any]: + return { + "provider": self.provider, + "transcript": self.transcript, + "words": [w.to_dict() for w in self.words], + "speakers": self.speakers, + "duration": self.duration, + "params": self.params, + } + + def get_speaker_segments(self) -> list[dict[str, Any]]: + """Get transcript segmented by speaker.""" + if not self.words: + return [] + + segments = [] + current_speaker = None + current_text = [] + segment_start = 0.0 + + for word in self.words: + if word.speaker != current_speaker: + if current_text: + segments.append( + { + "speaker": current_speaker, + "text": " ".join(current_text), + "start": segment_start, + "end": self.words[len(segments) - 1].end + if segments + else word.start, + } + ) + current_speaker = word.speaker + current_text = [word.word] + segment_start = word.start + else: + current_text.append(word.word) + + if current_text: + segments.append( + { + "speaker": current_speaker, + "text": " ".join(current_text), + "start": segment_start, + "end": self.words[-1].end if self.words else 0.0, + } + ) + + return segments + + +class STTProvider(ABC): + """Abstract base class for STT providers.""" + + @property + @abstractmethod + def name(self) -> str: + """Provider name.""" + pass + + @abstractmethod + async def transcribe( + self, + audio_path: Path, + diarize: bool = False, + keyterms: list[str] | None = None, + on_event: EventCallback | None = None, + **kwargs: Any, + ) -> TranscriptionResult: + """Transcribe audio file. + + Args: + audio_path: Path to the audio file + diarize: Enable speaker diarization + keyterms: List of keywords to boost (if supported) + on_event: Optional callback for raw WebSocket events (event_type, data) + **kwargs: Provider-specific parameters + + Returns: + TranscriptionResult with transcript and metadata + """ + pass diff --git a/evals/stt/providers/deepgram_flux_provider.py b/evals/stt/providers/deepgram_flux_provider.py new file mode 100644 index 0000000..860dbd2 --- /dev/null +++ b/evals/stt/providers/deepgram_flux_provider.py @@ -0,0 +1,235 @@ +"""Deepgram Flux STT provider with WebSocket streaming. + +Flux is Deepgram's conversational AI model with built-in turn detection. +It has a different API than Nova models - no language/punctuate/diarize params. +""" + +import asyncio +import json +import os +from pathlib import Path +from typing import Any +from urllib.parse import urlencode + +from loguru import logger + +from ..audio_streamer import AudioConfig, AudioStreamer +from .base import EventCallback, STTProvider, TranscriptionResult, Word + +try: + from websockets.asyncio.client import connect as websocket_connect +except ImportError: + raise ImportError("websockets required: pip install websockets") + + +class DeepgramFluxProvider(STTProvider): + """Deepgram Flux Speech-to-Text provider with WebSocket streaming. + + Flux is optimized for conversational AI with built-in turn detection. + + Key differences from Nova: + - Uses v2 API endpoint + - Only supports English (flux-general-en) + - No punctuate, diarize, or language params + - Has turn detection events (StartOfTurn, EndOfTurn, EagerEndOfTurn) + - Supports keyterm boosting + + API Docs: https://developers.deepgram.com/docs/ + """ + + WS_URL = "wss://api.deepgram.com/v2/listen" + + def __init__(self, api_key: str | None = None): + self.api_key = api_key or os.getenv("DEEPGRAM_API_KEY") + if not self.api_key: + raise ValueError( + "Deepgram API key required. Set DEEPGRAM_API_KEY env var or pass api_key." + ) + + @property + def name(self) -> str: + return "deepgram-flux" + + async def transcribe( + self, + audio_path: Path, + diarize: bool = False, # Ignored - Flux doesn't support diarization + keyterms: list[str] | None = None, + on_event: EventCallback | None = None, + model: str = "flux-general-en", + sample_rate: int = 16000, + eot_threshold: float | None = 0.70, + eot_timeout_ms: int | None = 3000, + eager_eot_threshold: float | None = None, + trailing_silence_seconds: float = 3.0, + **kwargs: Any, + ) -> TranscriptionResult: + """Transcribe audio using Deepgram Flux WebSocket streaming. + + Args: + audio_path: Path to audio file + diarize: IGNORED - Flux does not support diarization + keyterms: List of keywords to boost recognition + on_event: Optional callback for raw WebSocket events + model: Flux model (default: flux-general-en) + sample_rate: Audio sample rate (default: 16000 for Flux) + eot_threshold: End-of-turn confidence threshold (0-1, default 0.7) + eot_timeout_ms: Timeout in ms to force end of turn (default 5000) + eager_eot_threshold: Threshold for eager end-of-turn events + trailing_silence_seconds: Seconds of silence after audio to capture pending events + **kwargs: Additional Flux parameters + + Returns: + TranscriptionResult with transcript (no speaker info - Flux doesn't support diarization) + """ + if diarize: + logger.warning("Flux does not support diarization - ignoring diarize=True") + + # Build query params - Flux only supports specific params + params: dict[str, Any] = { + "model": model, + "encoding": "linear16", + "sample_rate": sample_rate, + } + + # Flux-specific turn detection params + if eot_threshold is not None: + params["eot_threshold"] = eot_threshold + if eot_timeout_ms is not None: + params["eot_timeout_ms"] = eot_timeout_ms + if eager_eot_threshold is not None: + params["eager_eot_threshold"] = eager_eot_threshold + + # Build URL with params + url_parts = [f"{k}={v}" for k, v in params.items()] + + # Add keyterms (repeated params) + if keyterms: + for term in keyterms: + url_parts.append(urlencode({"keyterm": term})) + + ws_url = f"{self.WS_URL}?{'&'.join(url_parts)}" + logger.debug(f"Flux WebSocket URL: {ws_url}") + + # Setup audio streamer + audio_config = AudioConfig(sample_rate=sample_rate) + streamer = AudioStreamer(audio_config) + + # Collect results + all_transcripts: list[dict[str, Any]] = [] + final_transcript = "" + duration = 0.0 + connected = asyncio.Event() + + async with websocket_connect( + ws_url, + additional_headers={"Authorization": f"Token {self.api_key}"}, + ) as ws: + + async def send_audio(): + """Send audio chunks to Deepgram Flux.""" + await connected.wait() + + chunk_no = 0 + async for chunk in streamer.stream_file( + audio_path, trailing_silence_seconds=trailing_silence_seconds + ): + logger.trace(f"[deepgram-flux] Sent audio chunk {chunk_no}") + await ws.send(chunk) + chunk_no += 1 + + async def receive_messages(): + """Receive and collect Flux messages.""" + nonlocal all_transcripts, final_transcript, duration + + async for message in ws: + if isinstance(message, str): + data = json.loads(message) + msg_type = data.get("type") + logger.debug(f"[deepgram-flux] Received {msg_type}: {data}") + + # Emit event via callback if provided + if on_event and msg_type: + on_event(msg_type, data) + + if msg_type == "Connected": + logger.info("[deepgram-flux] Connected") + connected.set() + + elif msg_type == "TurnInfo": + event = data.get("event") + transcript = data.get("transcript", "") + words = data.get("words", []) + + if event == "EndOfTurn": + if transcript: + final_transcript += transcript + " " + if words: + all_transcripts.append({ + "transcript": transcript, + "words": words, + }) + # Get duration from last word + if words: + last_word = words[-1] + duration = max(duration, last_word.get("end", 0)) + + elif event == "TurnResumed": + logger.debug("TurnResumed") + + elif msg_type == "Error": + raise Exception(f"Deepgram Flux error: {data}") + + # Run send and receive concurrently + send_task = asyncio.create_task(send_audio()) + receive_task = asyncio.create_task(receive_messages()) + + await send_task + + logger.debug("[deepgram-flux] Send task done") + try: + await asyncio.wait_for(receive_task, timeout=10.0) + except asyncio.TimeoutError: + pass + + return self._parse_results( + all_transcripts, final_transcript.strip(), duration, params, keyterms + ) + + def _parse_results( + self, + transcripts: list[dict[str, Any]], + final_transcript: str, + duration: float, + params: dict[str, Any], + keyterms: list[str] | None, + ) -> TranscriptionResult: + """Parse collected Flux results into TranscriptionResult.""" + words = [] + + for turn in transcripts: + for w in turn.get("words", []): + words.append( + Word( + word=w.get("word", ""), + start=w.get("start", 0.0), + end=w.get("end", 0.0), + confidence=w.get("confidence", 0.0), + speaker=None, # Flux doesn't support diarization + speaker_confidence=None, + ) + ) + + stored_params = dict(params) + if keyterms: + stored_params["keyterms"] = keyterms + + return TranscriptionResult( + provider=self.name, + transcript=final_transcript, + words=words, + speakers=[], # Flux doesn't support diarization + duration=duration, + raw_response={"transcripts": transcripts}, + params=stored_params, + ) diff --git a/evals/stt/providers/deepgram_provider.py b/evals/stt/providers/deepgram_provider.py new file mode 100644 index 0000000..14311a4 --- /dev/null +++ b/evals/stt/providers/deepgram_provider.py @@ -0,0 +1,236 @@ +"""Deepgram STT provider with WebSocket streaming.""" + +import asyncio +import json +import os +from pathlib import Path +from typing import Any +from urllib.parse import urlencode + +from ..audio_streamer import AudioConfig, AudioStreamer +from .base import EventCallback, STTProvider, TranscriptionResult, Word +from loguru import logger + +try: + from websockets.asyncio.client import connect as websocket_connect +except ImportError: + raise ImportError("websockets required: pip install websockets") + + +class DeepgramProvider(STTProvider): + """Deepgram Nova Speech-to-Text provider with WebSocket streaming. + + API Docs: https://developers.deepgram.com/docs/ + + Supports: + - Speaker diarization via `diarize=true` + - Keyterm boosting via `keyterm` parameter + - Real-time streaming via WebSocket + - Multiple languages + - Punctuation + + For Flux models, use DeepgramFluxProvider instead. + """ + + WS_URL = "wss://api.deepgram.com/v1/listen" + + def __init__(self, api_key: str | None = None): + self.api_key = api_key or os.getenv("DEEPGRAM_API_KEY") + if not self.api_key: + raise ValueError( + "Deepgram API key required. Set DEEPGRAM_API_KEY env var or pass api_key." + ) + + @property + def name(self) -> str: + return "deepgram" + + async def transcribe( + self, + audio_path: Path, + diarize: bool = False, + keyterms: list[str] | None = None, + on_event: EventCallback | None = None, + model: str = "nova-3-general", + language: str = "en", + sample_rate: int = 8000, + punctuate: bool = True, + trailing_silence_seconds: float = 3.0, + **kwargs: Any, + ) -> TranscriptionResult: + """Transcribe audio using Deepgram Nova WebSocket streaming. + + Args: + audio_path: Path to audio file + diarize: Enable speaker diarization + keyterms: List of keywords to boost recognition + on_event: Optional callback for raw WebSocket events + model: Deepgram Nova model (nova-3, nova-2, etc.) + language: Language code + sample_rate: Audio sample rate for streaming + punctuate: Add punctuation + trailing_silence_seconds: Seconds of silence after audio to capture pending events + **kwargs: Additional Deepgram parameters + + Returns: + TranscriptionResult with transcript and speaker info + """ + # Build query params + params: dict[str, Any] = { + "model": model, + "language": language, + "punctuate": str(punctuate).lower(), + "encoding": "linear16", + "sample_rate": sample_rate, + "channels": 1, + "interim_results": "true", + "smart_format": "true", + "profanity_filter": "true", + "vad_events": "true", + "utterance_end_ms": "1000" + } + + if diarize: + params["diarize"] = "true" + + # Build URL with params + url_parts = [f"{k}={v}" for k, v in params.items()] + + # Add keyterms (repeated params) + if keyterms: + for term in keyterms: + url_parts.append(urlencode({"keyterm": term})) + + # Add extra kwargs + for k, v in kwargs.items(): + url_parts.append(f"{k}={v}") + + ws_url = f"{self.WS_URL}?{'&'.join(url_parts)}" + logger.debug(f"Deepgram WebSocket URL: {ws_url}") + + # Setup audio streamer + audio_config = AudioConfig(sample_rate=sample_rate) + streamer = AudioStreamer(audio_config) + + # Collect results + all_words: list[dict[str, Any]] = [] + final_transcript = "" + duration = 0.0 + + try: + async with websocket_connect( + ws_url, + additional_headers={"Authorization": f"Token {self.api_key}"}, + ) as ws: + # Create tasks for sending and receiving + send_complete = asyncio.Event() + + async def send_audio(): + """Send audio chunks to Deepgram.""" + chunk_no = 0 + async for chunk in streamer.stream_file( + audio_path, trailing_silence_seconds=trailing_silence_seconds + ): + logger.trace(f"[deepgram] Sent audio chunk {chunk_no}") + await ws.send(chunk) + chunk_no += 1 + # Send close message + logger.debug(f"[deepgram] Sending CloseStream after {chunk_no} chunks") + await ws.send(json.dumps({"type": "CloseStream"})) + send_complete.set() + + async def receive_transcripts(): + """Receive and collect transcription results.""" + nonlocal all_words, final_transcript, duration + + async for message in ws: + if isinstance(message, str): + data = json.loads(message) + msg_type = data.get("type") + logger.debug(f"[deepgram] Received {msg_type}: {data}") + + # Emit event via callback if provided + if on_event and msg_type: + on_event(msg_type, data) + + if msg_type == "Results": + # Nova-style response + channel = data.get("channel", {}) + alternatives = channel.get("alternatives", []) + if alternatives: + alt = alternatives[0] + words = alt.get("words", []) + all_words.extend(words) + + # Check if final + if data.get("is_final"): + final_transcript += alt.get("transcript", "") + " " + duration = max( + duration, data.get("duration", 0) + data.get("start", 0) + ) + + elif msg_type == "Metadata": + # Get duration from metadata + duration = data.get("duration", duration) + + elif msg_type == "Error": + raise Exception(f"Deepgram error: {data}") + + # Run send and receive concurrently + send_task = asyncio.create_task(send_audio()) + receive_task = asyncio.create_task(receive_transcripts()) + + # Wait for send to complete, then wait a bit for final results + await send_task + try: + await asyncio.wait_for(receive_task, timeout=5.0) + except asyncio.TimeoutError: + pass # Normal - websocket closes after final results + except Exception as e: + logger.exception(e) + + return self._parse_results( + all_words, final_transcript.strip(), duration, params, keyterms + ) + + def _parse_results( + self, + raw_words: list[dict[str, Any]], + transcript: str, + duration: float, + params: dict[str, Any], + keyterms: list[str] | None, + ) -> TranscriptionResult: + """Parse collected results into TranscriptionResult.""" + words = [] + speakers_set: set[str] = set() + + for w in raw_words: + speaker = str(w.get("speaker", "")) if "speaker" in w else None + if speaker: + speakers_set.add(speaker) + + words.append( + Word( + word=w.get("word", ""), + start=w.get("start", 0.0), + end=w.get("end", 0.0), + confidence=w.get("confidence", 0.0), + speaker=speaker, + speaker_confidence=w.get("speaker_confidence"), + ) + ) + + stored_params = dict(params) + if keyterms: + stored_params["keyterms"] = keyterms + + return TranscriptionResult( + provider=self.name, + transcript=transcript, + words=words, + speakers=sorted(speakers_set), + duration=duration, + raw_response={"words": raw_words}, + params=stored_params, + ) diff --git a/evals/stt/providers/local_smart_turn_provider.py b/evals/stt/providers/local_smart_turn_provider.py new file mode 100644 index 0000000..2133ef1 --- /dev/null +++ b/evals/stt/providers/local_smart_turn_provider.py @@ -0,0 +1,287 @@ +"""Local Smart Turn provider for benchmarking end-of-turn detection. + +Uses the pipecat smart-turn-v3 ONNX model for local ML-based turn detection. +This is NOT an STT provider - it only detects when a speaker has finished talking. +""" + +import os +import time +from dataclasses import dataclass +from pathlib import Path +from typing import Any + +import numpy as np +from loguru import logger + +from ..audio_streamer import AudioConfig, AudioStreamer +from .base import EventCallback, STTProvider, TranscriptionResult, Word + +try: + import onnxruntime as ort + from transformers import WhisperFeatureExtractor +except ImportError: + raise ImportError( + "onnxruntime and transformers required: pip install onnxruntime transformers" + ) + + +@dataclass +class TurnEvent: + """Represents a detected turn event.""" + timestamp: float # Time in audio when turn was detected + probability: float # Model confidence + prediction: int # 1=complete, 0=incomplete + inference_time_ms: float + + +class LocalSmartTurnProvider(STTProvider): + """Local Smart Turn provider for end-of-turn detection benchmarking. + + Uses the smart-turn-v3 ONNX model to detect when speakers finish talking. + This is useful for comparing turn detection accuracy against cloud services + like Deepgram Flux's built-in turn detection. + + NOTE: This provider does NOT produce transcripts - only turn detection events. + """ + + # Smart turn model requires 16kHz audio + REQUIRED_SAMPLE_RATE = 16000 + # Model analyzes 8 seconds of audio + WINDOW_SECONDS = 8 + + def __init__( + self, + model_path: str | None = None, + cpu_count: int = 1, + ): + """Initialize the local smart turn provider. + + Args: + model_path: Path to ONNX model file. If None, uses bundled model. + cpu_count: Number of CPUs for inference (default: 1) + """ + self.model_path = model_path + self.cpu_count = cpu_count + self._session = None + self._feature_extractor = None + + def _load_model(self): + """Lazy load the ONNX model.""" + if self._session is not None: + return + + model_path = self.model_path + + if not model_path: + # Try to load bundled model from pipecat + model_name = "smart-turn-v3.1-cpu.onnx" + package_path = "pipecat.audio.turn.smart_turn.data" + + try: + import importlib_resources as impresources + model_path = str(impresources.files(package_path).joinpath(model_name)) + except Exception: + from importlib import resources as impresources + try: + with impresources.path(package_path, model_name) as f: + model_path = str(f) + except Exception: + model_path = str(impresources.files(package_path).joinpath(model_name)) + + logger.info(f"[local-smart-turn] Loading model from {model_path}") + + # Configure ONNX runtime + so = ort.SessionOptions() + so.execution_mode = ort.ExecutionMode.ORT_SEQUENTIAL + so.inter_op_num_threads = 1 + so.intra_op_num_threads = self.cpu_count + so.graph_optimization_level = ort.GraphOptimizationLevel.ORT_ENABLE_ALL + + self._feature_extractor = WhisperFeatureExtractor(chunk_length=8) + self._session = ort.InferenceSession(model_path, sess_options=so) + + logger.info("[local-smart-turn] Model loaded") + + @property + def name(self) -> str: + return "local-smart-turn" + + def _predict_endpoint(self, audio_array: np.ndarray) -> dict[str, Any]: + """Predict end-of-turn using the ONNX model. + + Args: + audio_array: Audio samples as float32 numpy array (16kHz) + + Returns: + Dict with prediction (0/1) and probability + """ + # Truncate to last 8 seconds or pad to 8 seconds + max_samples = self.WINDOW_SECONDS * self.REQUIRED_SAMPLE_RATE + if len(audio_array) > max_samples: + audio_array = audio_array[-max_samples:] + elif len(audio_array) < max_samples: + padding = max_samples - len(audio_array) + audio_array = np.pad(audio_array, (padding, 0), mode="constant", constant_values=0) + + # Process using Whisper's feature extractor + inputs = self._feature_extractor( + audio_array, + sampling_rate=self.REQUIRED_SAMPLE_RATE, + return_tensors="np", + padding="max_length", + max_length=self.WINDOW_SECONDS * self.REQUIRED_SAMPLE_RATE, + truncation=True, + do_normalize=True, + ) + + # Extract features for ONNX + input_features = inputs.input_features.squeeze(0).astype(np.float32) + input_features = np.expand_dims(input_features, axis=0) + + # Run inference + start_time = time.perf_counter() + outputs = self._session.run(None, {"input_features": input_features}) + inference_time = (time.perf_counter() - start_time) * 1000 + + # Extract probability (model returns sigmoid probabilities) + probability = outputs[0][0].item() + prediction = 1 if probability > 0.5 else 0 + + return { + "prediction": prediction, + "probability": probability, + "inference_time_ms": inference_time, + } + + async def transcribe( + self, + audio_path: Path, + diarize: bool = False, # Ignored - not applicable + keyterms: list[str] | None = None, # Ignored - not applicable + on_event: EventCallback | None = None, # Ignored - not applicable + sample_rate: int = 16000, # Must be 16kHz for smart turn + analysis_interval_ms: int = 500, # How often to check for turn completion + **kwargs: Any, + ) -> TranscriptionResult: + """Analyze audio for turn detection events. + + NOTE: This does NOT produce transcripts. It detects when speakers + finish talking using ML-based turn detection. + + Args: + audio_path: Path to audio file + diarize: Ignored (not applicable for turn detection) + keyterms: Ignored (not applicable for turn detection) + on_event: Ignored (not applicable for turn detection) + sample_rate: Must be 16000 Hz for smart turn model + analysis_interval_ms: How often to run turn detection (ms) + **kwargs: Additional parameters (ignored) + + Returns: + TranscriptionResult with turn detection events in raw_response + """ + if sample_rate != self.REQUIRED_SAMPLE_RATE: + logger.warning( + f"[local-smart-turn] Sample rate must be {self.REQUIRED_SAMPLE_RATE}Hz, " + f"overriding {sample_rate}Hz" + ) + sample_rate = self.REQUIRED_SAMPLE_RATE + + # Load model if not already loaded + self._load_model() + + # Setup audio streamer at 16kHz + audio_config = AudioConfig(sample_rate=sample_rate) + streamer = AudioStreamer(audio_config) + + # Get audio duration + duration = streamer.get_duration(audio_path) + logger.info(f"[local-smart-turn] Processing {audio_path} ({duration:.2f}s)") + + # Collect all audio first (smart turn needs to analyze segments) + pcm_data = streamer.convert_to_pcm16(audio_path) + + # Convert to float32 for model + audio_int16 = np.frombuffer(pcm_data, dtype=np.int16) + audio_float32 = audio_int16.astype(np.float32) / 32768.0 + + # Analyze at intervals + turn_events: list[TurnEvent] = [] + samples_per_interval = int(sample_rate * analysis_interval_ms / 1000) + window_samples = self.WINDOW_SECONDS * sample_rate + + chunk_no = 0 + for end_sample in range(samples_per_interval, len(audio_float32), samples_per_interval): + # Get window of audio ending at current position + start_sample = max(0, end_sample - window_samples) + audio_window = audio_float32[start_sample:end_sample] + + current_time = end_sample / sample_rate + logger.debug(f"[local-smart-turn] Analyzing chunk {chunk_no} at {current_time:.2f}s") + + result = self._predict_endpoint(audio_window) + + turn_events.append(TurnEvent( + timestamp=current_time, + probability=result["probability"], + prediction=result["prediction"], + inference_time_ms=result["inference_time_ms"], + )) + + if result["prediction"] == 1: + logger.info( + f"[local-smart-turn] Turn complete at {current_time:.2f}s " + f"(prob={result['probability']:.3f})" + f"(inf time ms={result["inference_time_ms"]})" + ) + + chunk_no += 1 + + # Create result + # Convert turn events to word-like format for compatibility + words = [] + for event in turn_events: + if event.prediction == 1: + words.append(Word( + word=f"[END_OF_TURN prob={event.probability:.2f}]", + start=event.timestamp - 0.1, + end=event.timestamp, + confidence=event.probability, + speaker=None, + speaker_confidence=None, + )) + + # Count completed turns + completed_turns = sum(1 for e in turn_events if e.prediction == 1) + + params = { + "sample_rate": sample_rate, + "analysis_interval_ms": analysis_interval_ms, + "window_seconds": self.WINDOW_SECONDS, + } + + return TranscriptionResult( + provider=self.name, + transcript=f"[Turn detection only - {completed_turns} turns detected]", + words=words, + speakers=[], # Not applicable + duration=duration, + raw_response={ + "turn_events": [ + { + "timestamp": e.timestamp, + "probability": e.probability, + "prediction": e.prediction, + "inference_time_ms": e.inference_time_ms, + } + for e in turn_events + ], + "completed_turns": completed_turns, + "total_analyses": len(turn_events), + "avg_inference_time_ms": ( + sum(e.inference_time_ms for e in turn_events) / len(turn_events) + if turn_events else 0 + ), + }, + params=params, + ) diff --git a/evals/stt/providers/speechmatics_provider.py b/evals/stt/providers/speechmatics_provider.py new file mode 100644 index 0000000..1efd51e --- /dev/null +++ b/evals/stt/providers/speechmatics_provider.py @@ -0,0 +1,258 @@ +"""Speechmatics STT provider with WebSocket streaming.""" + +import asyncio +import json +import os +from pathlib import Path +from typing import Any + +from loguru import logger + +from ..audio_streamer import AudioConfig, AudioStreamer +from .base import EventCallback, STTProvider, TranscriptionResult, Word + +try: + from websockets.asyncio.client import connect as websocket_connect +except ImportError: + raise ImportError("websockets required: pip install websockets") + + +class SpeechmaticsProvider(STTProvider): + """Speechmatics Speech-to-Text provider with WebSocket streaming. + + API Docs: https://docs.speechmatics.com/ + + Supports: + - Speaker diarization via `diarization: "speaker"` config + - Speaker sensitivity tuning + - Real-time streaming via WebSocket + """ + + def __init__(self, api_key: str | None = None, region: str = "eu2"): + self.api_key = api_key or os.getenv("SPEECHMATICS_API_KEY") + if not self.api_key: + raise ValueError( + "Speechmatics API key required. Set SPEECHMATICS_API_KEY env var or pass api_key." + ) + # Set region-specific endpoint + self.ws_url = f"wss://{region}.rt.speechmatics.com/v2" + + @property + def name(self) -> str: + return "speechmatics" + + async def transcribe( + self, + audio_path: Path, + diarize: bool = False, + keyterms: list[str] | None = None, + on_event: EventCallback | None = None, + language: str = "en", + operating_point: str = "enhanced", + sample_rate: int = 8000, + speaker_sensitivity: float | None = None, + max_speakers: int | None = None, + trailing_silence_seconds: float = 3.0, + **kwargs: Any, + ) -> TranscriptionResult: + """Transcribe audio using Speechmatics WebSocket streaming. + + Args: + audio_path: Path to audio file + diarize: Enable speaker diarization + keyterms: Additional vocabulary (limited support) + on_event: Optional callback for raw WebSocket events + language: Language code + operating_point: "standard" or "enhanced" + sample_rate: Audio sample rate for streaming + speaker_sensitivity: 0.0-1.0, higher = more speakers detected + max_speakers: Maximum number of speakers to detect + trailing_silence_seconds: Seconds of silence after audio to capture pending events + **kwargs: Additional config parameters + + Returns: + TranscriptionResult with transcript and speaker info + """ + # Build transcription config for StartRecognition message + transcription_config: dict[str, Any] = { + "language": language, + "operating_point": operating_point, + "enable_partials": False, + } + + if diarize: + transcription_config["diarization"] = "speaker" + if speaker_sensitivity is not None: + transcription_config["speaker_diarization_config"] = { + "speaker_sensitivity": speaker_sensitivity + } + if max_speakers is not None: + if "speaker_diarization_config" not in transcription_config: + transcription_config["speaker_diarization_config"] = {} + transcription_config["speaker_diarization_config"]["max_speakers"] = max_speakers + + # Add additional vocabulary if provided + if keyterms: + transcription_config["additional_vocab"] = [{"content": term} for term in keyterms] + + # Audio format config + audio_format = { + "type": "raw", + "encoding": "pcm_s16le", + "sample_rate": sample_rate, + } + + # Store params for result + params = { + "diarize": diarize, + "language": language, + "operating_point": operating_point, + "sample_rate": sample_rate, + "speaker_sensitivity": speaker_sensitivity, + "max_speakers": max_speakers, + } + + # Setup audio streamer + audio_config = AudioConfig(sample_rate=sample_rate) + streamer = AudioStreamer(audio_config) + + # Collect results + all_results: list[dict[str, Any]] = [] + recognition_started = asyncio.Event() + transcription_complete = asyncio.Event() + + async with websocket_connect( + self.ws_url, + additional_headers={"Authorization": f"Bearer {self.api_key}"}, + ) as ws: + # Send StartRecognition message + start_msg = { + "message": "StartRecognition", + "transcription_config": transcription_config, + "audio_format": audio_format, + } + await ws.send(json.dumps(start_msg)) + + async def send_audio(): + """Send audio chunks after recognition starts.""" + await recognition_started.wait() + + chunk_no = 0 + async for chunk in streamer.stream_file( + audio_path, trailing_silence_seconds=trailing_silence_seconds + ): + logger.debug(f"[speechmatics] Sent audio chunk {chunk_no}") + await ws.send(chunk) + chunk_no += 1 + + # Signal end of audio with last sequence number + logger.debug(f"[speechmatics] Sending EndOfStream after {chunk_no} chunks") + await ws.send(json.dumps({"message": "EndOfStream", "last_seq_no": chunk_no})) + + async def receive_messages(): + """Receive and process messages.""" + nonlocal all_results + + async for message in ws: + if isinstance(message, str): + data = json.loads(message) + msg_type = data.get("message") + logger.debug(f"[speechmatics] Received {msg_type}: {data}") + + # Emit event via callback if provided + if on_event and msg_type: + on_event(msg_type, data) + + if msg_type == "RecognitionStarted": + logger.info("[speechmatics] Connected") + recognition_started.set() + + elif msg_type == "AddTranscript": + # Final transcript segment + results = data.get("results", []) + all_results.extend(results) + + elif msg_type == "EndOfTranscript": + transcription_complete.set() + return + + elif msg_type == "Error": + raise Exception(f"Speechmatics error: {data}") + + elif msg_type == "Warning": + logger.warning(f"[speechmatics] Warning: {data.get('reason')}") + + # Run send and receive concurrently + send_task = asyncio.create_task(send_audio()) + receive_task = asyncio.create_task(receive_messages()) + + # Wait for completion + await send_task + try: + await asyncio.wait_for(transcription_complete.wait(), timeout=30.0) + except asyncio.TimeoutError: + pass + + receive_task.cancel() + try: + await receive_task + except asyncio.CancelledError: + pass + + return self._parse_results(all_results, params) + + def _parse_results( + self, + results: list[dict[str, Any]], + params: dict[str, Any], + ) -> TranscriptionResult: + """Parse Speechmatics results.""" + words = [] + speakers_set: set[str] = set() + transcript_parts = [] + duration = 0.0 + + for item in results: + item_type = item.get("type") + alternatives = item.get("alternatives", []) + + if not alternatives: + continue + + alt = alternatives[0] + content = alt.get("content", "") + speaker = alt.get("speaker") + + if speaker: + speakers_set.add(speaker) + + end_time = item.get("end_time", 0.0) + duration = max(duration, end_time) + + if item_type == "word": + words.append( + Word( + word=content, + start=item.get("start_time", 0.0), + end=end_time, + confidence=alt.get("confidence", 0.0), + speaker=speaker, + speaker_confidence=None, + ) + ) + transcript_parts.append(content) + elif item_type == "punctuation": + if transcript_parts: + transcript_parts[-1] += content + + transcript = " ".join(transcript_parts) + + return TranscriptionResult( + provider=self.name, + 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newline at end of file diff --git a/evals/visualizer/.gitignore b/evals/visualizer/.gitignore new file mode 100644 index 0000000..5ef6a52 --- /dev/null +++ b/evals/visualizer/.gitignore @@ -0,0 +1,41 @@ +# See https://help.github.com/articles/ignoring-files/ for more about ignoring files. + +# dependencies +/node_modules +/.pnp +.pnp.* +.yarn/* +!.yarn/patches +!.yarn/plugins +!.yarn/releases +!.yarn/versions + +# testing +/coverage + +# next.js +/.next/ +/out/ + +# production +/build + +# misc +.DS_Store +*.pem + +# debug +npm-debug.log* +yarn-debug.log* +yarn-error.log* +.pnpm-debug.log* + +# env files (can opt-in for committing if needed) +.env* + +# vercel +.vercel + +# typescript +*.tsbuildinfo +next-env.d.ts diff --git a/evals/visualizer/README.md b/evals/visualizer/README.md new file mode 100644 index 0000000..e215bc4 --- /dev/null +++ b/evals/visualizer/README.md @@ -0,0 +1,36 @@ +This is a [Next.js](https://nextjs.org) project bootstrapped with [`create-next-app`](https://nextjs.org/docs/app/api-reference/cli/create-next-app). + +## Getting Started + +First, run the development server: + +```bash +npm run dev +# or +yarn dev +# or +pnpm dev +# or +bun dev +``` + +Open [http://localhost:3000](http://localhost:3000) with your browser to see the result. + +You can start editing the page by modifying `app/page.tsx`. The page auto-updates as you edit the file. + +This project uses [`next/font`](https://nextjs.org/docs/app/building-your-application/optimizing/fonts) to automatically optimize and load [Geist](https://vercel.com/font), a new font family for Vercel. + +## Learn More + +To learn more about Next.js, take a look at the following resources: + +- [Next.js Documentation](https://nextjs.org/docs) - learn about Next.js features and API. +- [Learn Next.js](https://nextjs.org/learn) - an interactive Next.js tutorial. + +You can check out [the Next.js GitHub repository](https://github.com/vercel/next.js) - your feedback and contributions are welcome! + +## Deploy on Vercel + +The easiest way to deploy your Next.js app is to use the [Vercel Platform](https://vercel.com/new?utm_medium=default-template&filter=next.js&utm_source=create-next-app&utm_campaign=create-next-app-readme) from the creators of Next.js. + +Check out our [Next.js deployment documentation](https://nextjs.org/docs/app/building-your-application/deploying) for more details. diff --git a/evals/visualizer/eslint.config.mjs b/evals/visualizer/eslint.config.mjs new file mode 100644 index 0000000..05e726d --- /dev/null +++ b/evals/visualizer/eslint.config.mjs @@ -0,0 +1,18 @@ +import { defineConfig, globalIgnores } from "eslint/config"; +import nextVitals from "eslint-config-next/core-web-vitals"; +import nextTs from "eslint-config-next/typescript"; + +const eslintConfig = defineConfig([ + ...nextVitals, + ...nextTs, + // Override default ignores of eslint-config-next. + globalIgnores([ + // Default ignores of eslint-config-next: + ".next/**", + "out/**", + "build/**", + "next-env.d.ts", + ]), +]); + +export default eslintConfig; diff --git a/evals/visualizer/next.config.ts b/evals/visualizer/next.config.ts new file mode 100644 index 0000000..e9ffa30 --- /dev/null +++ b/evals/visualizer/next.config.ts @@ -0,0 +1,7 @@ +import type { NextConfig } from "next"; + +const nextConfig: NextConfig = { + /* config options here */ +}; + +export default nextConfig; diff --git a/evals/visualizer/package.json b/evals/visualizer/package.json new file mode 100644 index 0000000..5d44c50 --- /dev/null +++ b/evals/visualizer/package.json @@ -0,0 +1,26 @@ +{ + "name": "visualizer", + "version": "0.1.0", + "private": true, + "scripts": { + "dev": "next dev", + "build": "next build", + "start": "next start", + "lint": "eslint" + }, + "dependencies": { + "next": "16.1.4", + "react": "19.2.3", + "react-dom": "19.2.3" + }, + "devDependencies": { + "@tailwindcss/postcss": "^4", + "@types/node": "^20", + "@types/react": "^19", + "@types/react-dom": "^19", + "eslint": "^9", + "eslint-config-next": "16.1.4", + "tailwindcss": "^4", + "typescript": "^5" + } +} diff --git a/evals/visualizer/pnpm-lock.yaml b/evals/visualizer/pnpm-lock.yaml new file mode 100644 index 0000000..11a9e03 --- /dev/null +++ b/evals/visualizer/pnpm-lock.yaml @@ -0,0 +1,4008 @@ +lockfileVersion: 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side-channel-map: 1.0.1 + side-channel-weakmap: 1.0.2 + + source-map-js@1.2.1: {} + + stable-hash@0.0.5: {} + + stop-iteration-iterator@1.1.0: + dependencies: + es-errors: 1.3.0 + internal-slot: 1.1.0 + + string.prototype.includes@2.0.1: + dependencies: + call-bind: 1.0.8 + define-properties: 1.2.1 + es-abstract: 1.24.1 + + string.prototype.matchall@4.0.12: + dependencies: + call-bind: 1.0.8 + call-bound: 1.0.4 + define-properties: 1.2.1 + es-abstract: 1.24.1 + es-errors: 1.3.0 + es-object-atoms: 1.1.1 + get-intrinsic: 1.3.0 + gopd: 1.2.0 + has-symbols: 1.1.0 + internal-slot: 1.1.0 + regexp.prototype.flags: 1.5.4 + set-function-name: 2.0.2 + side-channel: 1.1.0 + + string.prototype.repeat@1.0.0: + dependencies: + define-properties: 1.2.1 + es-abstract: 1.24.1 + + string.prototype.trim@1.2.10: + dependencies: + call-bind: 1.0.8 + call-bound: 1.0.4 + define-data-property: 1.1.4 + define-properties: 1.2.1 + es-abstract: 1.24.1 + es-object-atoms: 1.1.1 + has-property-descriptors: 1.0.2 + + string.prototype.trimend@1.0.9: + dependencies: + call-bind: 1.0.8 + call-bound: 1.0.4 + define-properties: 1.2.1 + es-object-atoms: 1.1.1 + + string.prototype.trimstart@1.0.8: + dependencies: + call-bind: 1.0.8 + define-properties: 1.2.1 + es-object-atoms: 1.1.1 + + strip-bom@3.0.0: {} + + strip-json-comments@3.1.1: {} + + styled-jsx@5.1.6(@babel/core@7.28.6)(react@19.2.3): + dependencies: + client-only: 0.0.1 + react: 19.2.3 + optionalDependencies: + '@babel/core': 7.28.6 + + supports-color@7.2.0: + dependencies: + has-flag: 4.0.0 + + supports-preserve-symlinks-flag@1.0.0: {} + + tailwindcss@4.1.18: {} + + tapable@2.3.0: {} + + tinyglobby@0.2.15: + dependencies: + fdir: 6.5.0(picomatch@4.0.3) + picomatch: 4.0.3 + + to-regex-range@5.0.1: + dependencies: + is-number: 7.0.0 + + ts-api-utils@2.4.0(typescript@5.9.3): + dependencies: + typescript: 5.9.3 + + tsconfig-paths@3.15.0: + dependencies: + '@types/json5': 0.0.29 + json5: 1.0.2 + minimist: 1.2.8 + strip-bom: 3.0.0 + + tslib@2.8.1: 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call-bound: 1.0.4 + function.prototype.name: 1.1.8 + has-tostringtag: 1.0.2 + is-async-function: 2.1.1 + is-date-object: 1.1.0 + is-finalizationregistry: 1.1.1 + is-generator-function: 1.1.2 + is-regex: 1.2.1 + is-weakref: 1.1.1 + isarray: 2.0.5 + which-boxed-primitive: 1.1.1 + which-collection: 1.0.2 + which-typed-array: 1.1.20 + + which-collection@1.0.2: + dependencies: + is-map: 2.0.3 + is-set: 2.0.3 + is-weakmap: 2.0.2 + is-weakset: 2.0.4 + + which-typed-array@1.1.20: + dependencies: + available-typed-arrays: 1.0.7 + call-bind: 1.0.8 + call-bound: 1.0.4 + for-each: 0.3.5 + get-proto: 1.0.1 + gopd: 1.2.0 + has-tostringtag: 1.0.2 + + which@2.0.2: + dependencies: + isexe: 2.0.0 + + word-wrap@1.2.5: {} + + yallist@3.1.1: {} + + yocto-queue@0.1.0: {} + + zod-validation-error@4.0.2(zod@4.3.5): + dependencies: + zod: 4.3.5 + + zod@4.3.5: {} diff --git a/evals/visualizer/pnpm-workspace.yaml b/evals/visualizer/pnpm-workspace.yaml new file mode 100644 index 0000000..4851e0c --- /dev/null +++ b/evals/visualizer/pnpm-workspace.yaml @@ -0,0 +1,5 @@ +packages: + - . +ignoredBuiltDependencies: + - sharp + - unrs-resolver diff --git a/evals/visualizer/postcss.config.mjs b/evals/visualizer/postcss.config.mjs new file mode 100644 index 0000000..61e3684 --- /dev/null +++ b/evals/visualizer/postcss.config.mjs @@ -0,0 +1,7 @@ +const config = { + plugins: { + "@tailwindcss/postcss": {}, + }, +}; + +export default config; diff --git a/evals/visualizer/public/file.svg b/evals/visualizer/public/file.svg new file mode 100644 index 0000000..004145c --- /dev/null +++ b/evals/visualizer/public/file.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/evals/visualizer/public/globe.svg b/evals/visualizer/public/globe.svg new file mode 100644 index 0000000..567f17b --- /dev/null +++ b/evals/visualizer/public/globe.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/evals/visualizer/public/next.svg b/evals/visualizer/public/next.svg new file mode 100644 index 0000000..5174b28 --- /dev/null +++ b/evals/visualizer/public/next.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/evals/visualizer/public/vercel.svg b/evals/visualizer/public/vercel.svg new file mode 100644 index 0000000..7705396 --- /dev/null +++ b/evals/visualizer/public/vercel.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/evals/visualizer/public/window.svg b/evals/visualizer/public/window.svg new file mode 100644 index 0000000..b2b2a44 --- /dev/null +++ b/evals/visualizer/public/window.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/evals/visualizer/src/app/api/audio/[filename]/route.ts b/evals/visualizer/src/app/api/audio/[filename]/route.ts new file mode 100644 index 0000000..e7dba65 --- /dev/null +++ b/evals/visualizer/src/app/api/audio/[filename]/route.ts @@ -0,0 +1,42 @@ +import { NextRequest, NextResponse } from "next/server"; +import fs from "fs"; +import path from "path"; + +const AUDIO_DIR = path.join(process.cwd(), "..", "stt", "audio"); + +const MIME_TYPES: Record = { + ".mp3": "audio/mpeg", + ".wav": "audio/wav", + ".m4a": "audio/mp4", + ".ogg": "audio/ogg", + ".webm": "audio/webm", +}; + +export async function GET( + request: NextRequest, + { params }: { params: Promise<{ filename: string }> } +) { + try { + const { filename } = await params; + const filePath = path.join(AUDIO_DIR, filename); + + if (!fs.existsSync(filePath)) { + return NextResponse.json({ error: "Audio file not found" }, { status: 404 }); + } + + const ext = path.extname(filename).toLowerCase(); + const contentType = MIME_TYPES[ext] || "application/octet-stream"; + + const fileBuffer = fs.readFileSync(filePath); + + return new NextResponse(fileBuffer, { + headers: { + "Content-Type": contentType, + "Content-Length": fileBuffer.length.toString(), + }, + }); + } catch (error) { + console.error("Error serving audio:", error); + return NextResponse.json({ error: "Failed to serve audio" }, { status: 500 }); + } +} diff --git a/evals/visualizer/src/app/api/results/[id]/route.ts b/evals/visualizer/src/app/api/results/[id]/route.ts new file mode 100644 index 0000000..08711f4 --- /dev/null +++ b/evals/visualizer/src/app/api/results/[id]/route.ts @@ -0,0 +1,27 @@ +import { NextRequest, NextResponse } from "next/server"; +import fs from "fs"; +import path from "path"; + +const RESULTS_DIR = path.join(process.cwd(), "..", "stt", "results"); + +export async function GET( + request: NextRequest, + { params }: { params: Promise<{ id: string }> } +) { + try { + const { id } = await params; + const filePath = path.join(RESULTS_DIR, `${id}.json`); + + if (!fs.existsSync(filePath)) { + return NextResponse.json({ error: "Result not found" }, { status: 404 }); + } + + const content = fs.readFileSync(filePath, "utf-8"); + const data = JSON.parse(content); + + return NextResponse.json(data); + } catch (error) { + console.error("Error reading result:", error); + return NextResponse.json({ error: "Failed to read result" }, { status: 500 }); + } +} diff --git a/evals/visualizer/src/app/api/results/route.ts b/evals/visualizer/src/app/api/results/route.ts new file mode 100644 index 0000000..08b2095 --- /dev/null +++ b/evals/visualizer/src/app/api/results/route.ts @@ -0,0 +1,47 @@ +import { NextResponse } from "next/server"; +import fs from "fs"; +import path from "path"; +import { ResultSummary, EventCaptureResult } from "@/types"; + +const RESULTS_DIR = path.join(process.cwd(), "..", "stt", "results"); + +export async function GET() { + try { + if (!fs.existsSync(RESULTS_DIR)) { + return NextResponse.json([]); + } + + const files = fs.readdirSync(RESULTS_DIR).filter((f) => f.endsWith(".json")); + const results: ResultSummary[] = []; + + for (const file of files) { + try { + const filePath = path.join(RESULTS_DIR, file); + const content = fs.readFileSync(filePath, "utf-8"); + const data: EventCaptureResult = JSON.parse(content); + + results.push({ + id: file.replace(".json", ""), + audio_file: data.audio_file, + provider: data.provider, + duration: data.duration, + created_at: data.created_at, + event_count: data.events.length, + }); + } catch { + console.error(`Failed to parse ${file}`); + } + } + + // Sort by created_at descending + results.sort( + (a, b) => + new Date(b.created_at).getTime() - new Date(a.created_at).getTime() + ); + + return NextResponse.json(results); + } catch (error) { + console.error("Error reading results:", error); + return NextResponse.json({ error: "Failed to read results" }, { status: 500 }); + } +} diff --git a/evals/visualizer/src/app/favicon.ico b/evals/visualizer/src/app/favicon.ico new file mode 100644 index 0000000..718d6fe Binary files /dev/null and b/evals/visualizer/src/app/favicon.ico differ diff --git a/evals/visualizer/src/app/globals.css b/evals/visualizer/src/app/globals.css new file mode 100644 index 0000000..a2dc41e --- /dev/null +++ b/evals/visualizer/src/app/globals.css @@ -0,0 +1,26 @@ +@import "tailwindcss"; + +:root { + --background: #ffffff; + --foreground: #171717; +} + +@theme inline { + --color-background: var(--background); + --color-foreground: var(--foreground); + --font-sans: var(--font-geist-sans); + --font-mono: var(--font-geist-mono); +} + +@media (prefers-color-scheme: dark) { + :root { + --background: #0a0a0a; + --foreground: #ededed; + } +} + +body { + background: var(--background); + color: var(--foreground); + font-family: Arial, Helvetica, sans-serif; +} diff --git a/evals/visualizer/src/app/layout.tsx b/evals/visualizer/src/app/layout.tsx new file mode 100644 index 0000000..fc37a19 --- /dev/null +++ b/evals/visualizer/src/app/layout.tsx @@ -0,0 +1,34 @@ +import type { Metadata } from "next"; +import { Geist, Geist_Mono } from "next/font/google"; +import "./globals.css"; + +const geistSans = Geist({ + variable: "--font-geist-sans", + subsets: ["latin"], +}); + +const geistMono = Geist_Mono({ + variable: "--font-geist-mono", + subsets: ["latin"], +}); + +export const metadata: Metadata = { + title: "STT Event Visualizer", + description: "Visualize WebSocket events from STT providers", +}; + +export default function RootLayout({ + children, +}: Readonly<{ + children: React.ReactNode; +}>) { + return ( + + + {children} + + + ); +} diff --git a/evals/visualizer/src/app/page.tsx b/evals/visualizer/src/app/page.tsx new file mode 100644 index 0000000..422c61d --- /dev/null +++ b/evals/visualizer/src/app/page.tsx @@ -0,0 +1,129 @@ +"use client"; + +import { useEffect, useState } from "react"; +import Link from "next/link"; +import { ResultSummary } from "@/types"; + +function formatDuration(seconds: number): string { + const mins = Math.floor(seconds / 60); + const secs = Math.floor(seconds % 60); + return `${mins}:${secs.toString().padStart(2, "0")}`; +} + +function formatDate(isoString: string): string { + const date = new Date(isoString); + return date.toLocaleDateString("en-US", { + year: "numeric", + month: "short", + day: "numeric", + hour: "2-digit", + minute: "2-digit", + }); +} + +const PROVIDER_COLORS: Record = { + deepgram: "bg-blue-500/20 text-blue-300", + "deepgram-flux": "bg-green-500/20 text-green-300", + speechmatics: "bg-purple-500/20 text-purple-300", +}; + +export default function Home() { + const [results, setResults] = useState([]); + const [loading, setLoading] = useState(true); + const [error, setError] = useState(null); + + useEffect(() => { + async function fetchResults() { + try { + const response = await fetch("/api/results"); + if (!response.ok) { + throw new Error("Failed to fetch results"); + } + const data = await response.json(); + setResults(data); + } catch (err) { + setError(err instanceof Error ? err.message : "Unknown error"); + } finally { + setLoading(false); + } + } + + fetchResults(); + }, []); + + return ( +
+
+
+

STT Event Visualizer

+

+ Visualize captured WebSocket events from STT providers +

+
+ + {loading && ( +
+
+
+ )} + + {error && ( +
+ {error} +
+ )} + + {!loading && !error && results.length === 0 && ( +
+

No results found

+

+ Run the event capture script to generate results: +

+ + python -m evals.stt.event_capture audio/multi_speaker.m4a --provider deepgram + +
+ )} + + {!loading && !error && results.length > 0 && ( +
+ {results.map((result) => ( + +
+
+
+ {result.audio_file} + + {result.provider} + +
+
+ {formatDate(result.created_at)} +
+
+
+
+ {formatDuration(result.duration)} +
+
+ {result.event_count} events +
+
+
+ + ))} +
+ )} +
+
+ ); +} diff --git a/evals/visualizer/src/app/view/[id]/page.tsx b/evals/visualizer/src/app/view/[id]/page.tsx new file mode 100644 index 0000000..a217312 --- /dev/null +++ b/evals/visualizer/src/app/view/[id]/page.tsx @@ -0,0 +1,158 @@ +"use client"; + +import { useEffect, useState, useCallback } from "react"; +import { useParams } from "next/navigation"; +import Link from "next/link"; +import { EventCaptureResult } from "@/types"; +import AudioPlayer from "@/components/AudioPlayer"; +import EventTimeline from "@/components/EventTimeline"; +import EventList from "@/components/EventList"; + +const PROVIDER_COLORS: Record = { + deepgram: "bg-blue-500/20 text-blue-300", + "deepgram-flux": "bg-green-500/20 text-green-300", + speechmatics: "bg-purple-500/20 text-purple-300", +}; + +export default function ViewPage() { + const params = useParams(); + const id = params.id as string; + + const [result, setResult] = useState(null); + const [loading, setLoading] = useState(true); + const [error, setError] = useState(null); + const [currentTime, setCurrentTime] = useState(0); + const [isPlaying, setIsPlaying] = useState(false); + + useEffect(() => { + async function fetchResult() { + try { + const response = await fetch(`/api/results/${id}`); + if (!response.ok) { + if (response.status === 404) { + throw new Error("Result not found"); + } + throw new Error("Failed to fetch result"); + } + const data = await response.json(); + setResult(data); + } catch (err) { + setError(err instanceof Error ? err.message : "Unknown error"); + } finally { + setLoading(false); + } + } + + if (id) { + fetchResult(); + } + }, [id]); + + const handleTimeUpdate = useCallback((time: number) => { + setCurrentTime(time); + }, []); + + const handlePlayingChange = useCallback((playing: boolean) => { + setIsPlaying(playing); + }, []); + + const handleSeek = useCallback((time: number) => { + setCurrentTime(time); + }, []); + + if (loading) { + return ( +
+
+
+ ); + } + + if (error) { + return ( +
+
+ + ← Back to results + +
{error}
+
+
+ ); + } + + if (!result) { + return null; + } + + const audioUrl = `/api/audio/${result.audio_file}`; + + return ( +
+
+ {/* Header */} +
+ + ← Back to results + +
+

{result.audio_file}

+ + {result.provider} + +
+ {result.transcript && ( +

+ {result.transcript} +

+ )} +
+ + {/* Main content */} +
+ {/* Left column: Audio player and timeline */} +
+ + + + + {/* Transcript section */} + {result.transcript && ( +
+
+ Final Transcript +
+

{result.transcript}

+
+ )} +
+ + {/* Right column: Event list */} +
+ +
+
+
+
+ ); +} diff --git a/evals/visualizer/src/components/AudioPlayer.tsx b/evals/visualizer/src/components/AudioPlayer.tsx new file mode 100644 index 0000000..e5795e5 --- /dev/null +++ b/evals/visualizer/src/components/AudioPlayer.tsx @@ -0,0 +1,145 @@ +"use client"; + +import { useRef, useEffect, useState, useCallback } from "react"; + +interface AudioPlayerProps { + audioUrl: string; + duration: number; + currentTime: number; + onTimeUpdate: (time: number) => void; + onPlayingChange: (playing: boolean) => void; +} + +function formatTime(seconds: number): string { + const mins = Math.floor(seconds / 60); + const secs = Math.floor(seconds % 60); + return `${mins}:${secs.toString().padStart(2, "0")}`; +} + +export default function AudioPlayer({ + audioUrl, + duration, + currentTime, + onTimeUpdate, + onPlayingChange, +}: AudioPlayerProps) { + const audioRef = useRef(null); + const [isPlaying, setIsPlaying] = useState(false); + const [internalTime, setInternalTime] = useState(0); + + useEffect(() => { + const audio = audioRef.current; + if (!audio) return; + + const handleTimeUpdate = () => { + setInternalTime(audio.currentTime); + onTimeUpdate(audio.currentTime); + }; + + const handlePlay = () => { + setIsPlaying(true); + onPlayingChange(true); + }; + + const handlePause = () => { + setIsPlaying(false); + onPlayingChange(false); + }; + + const handleEnded = () => { + setIsPlaying(false); + onPlayingChange(false); + }; + + audio.addEventListener("timeupdate", handleTimeUpdate); + audio.addEventListener("play", handlePlay); + audio.addEventListener("pause", handlePause); + audio.addEventListener("ended", handleEnded); + + return () => { + audio.removeEventListener("timeupdate", handleTimeUpdate); + audio.removeEventListener("play", handlePlay); + audio.removeEventListener("pause", handlePause); + audio.removeEventListener("ended", handleEnded); + }; + }, [onTimeUpdate, onPlayingChange]); + + // Seek to currentTime when it changes externally + useEffect(() => { + const audio = audioRef.current; + if (!audio) return; + + // Only seek if the difference is significant (user clicked timeline) + if (Math.abs(audio.currentTime - currentTime) > 0.5) { + audio.currentTime = currentTime; + } + }, [currentTime]); + + const togglePlay = useCallback(() => { + const audio = audioRef.current; + if (!audio) return; + + if (isPlaying) { + audio.pause(); + } else { + audio.play(); + } + }, [isPlaying]); + + const handleSeek = useCallback((e: React.ChangeEvent) => { + const audio = audioRef.current; + if (!audio) return; + + const newTime = parseFloat(e.target.value); + audio.currentTime = newTime; + setInternalTime(newTime); + onTimeUpdate(newTime); + }, [onTimeUpdate]); + + return ( +
+
+ ); +} diff --git a/evals/visualizer/src/components/EventList.tsx b/evals/visualizer/src/components/EventList.tsx new file mode 100644 index 0000000..02a3f9e --- /dev/null +++ b/evals/visualizer/src/components/EventList.tsx @@ -0,0 +1,141 @@ +"use client"; + +import { useEffect, useRef, useMemo, useState } from "react"; +import { CapturedEvent } from "@/types"; +import { DeepgramEventItem, FluxEventItem, SpeechmaticsEventItem } from "./events"; + +interface EventListProps { + events: CapturedEvent[]; + currentTime: number; + onSeek: (time: number) => void; + provider: string; +} + +function formatTime(seconds: number): string { + const mins = Math.floor(seconds / 60); + const secs = Math.floor(seconds % 60); + const ms = Math.floor((seconds % 1) * 100); + return `${mins}:${secs.toString().padStart(2, "0")}.${ms.toString().padStart(2, "0")}`; +} + +function getEventItemComponent(provider: string) { + if (provider === "deepgram-flux") { + return FluxEventItem; + } + if (provider === "speechmatics") { + return SpeechmaticsEventItem; + } + // Default to Deepgram Nova + return DeepgramEventItem; +} + +export default function EventList({ + events, + currentTime, + onSeek, + provider, +}: EventListProps) { + const containerRef = useRef(null); + const [expandedEvents, setExpandedEvents] = useState>(new Set()); + const [autoScroll, setAutoScroll] = useState(true); + + const EventItemComponent = getEventItemComponent(provider); + + // Find the current event index based on time + const currentEventIndex = useMemo(() => { + for (let i = events.length - 1; i >= 0; i--) { + if (events[i].timestamp <= currentTime) { + return i; + } + } + return -1; + }, [events, currentTime]); + + // Auto-scroll to current event + useEffect(() => { + if (!autoScroll || currentEventIndex < 0) return; + + const container = containerRef.current; + if (!container) return; + + const eventElement = container.querySelector(`[data-index="${currentEventIndex}"]`); + if (eventElement) { + eventElement.scrollIntoView({ behavior: "smooth", block: "center" }); + } + }, [currentEventIndex, autoScroll]); + + const toggleExpand = (index: number) => { + setExpandedEvents((prev) => { + const next = new Set(prev); + if (next.has(index)) { + next.delete(index); + } else { + next.add(index); + } + return next; + }); + }; + + return ( +
+
+
+ Events ({events.length}) +
+ +
+ +
+ {events.map((event, index) => { + const isCurrent = index === currentEventIndex; + const isExpanded = expandedEvents.has(index); + + return ( +
onSeek(event.timestamp)} + > +
+ {/* Current indicator */} +
+ {isCurrent ? ( +
+ ) : ( +
+ )} +
+ + {/* Timestamp */} + + {formatTime(event.timestamp)} + + + {/* Provider-specific event item */} + toggleExpand(index)} + /> +
+
+ ); + })} +
+
+ ); +} diff --git a/evals/visualizer/src/components/EventTimeline.tsx b/evals/visualizer/src/components/EventTimeline.tsx new file mode 100644 index 0000000..2efa8f2 --- /dev/null +++ b/evals/visualizer/src/components/EventTimeline.tsx @@ -0,0 +1,119 @@ +"use client"; + +import { useMemo } from "react"; +import { CapturedEvent } from "@/types"; + +interface EventTimelineProps { + events: CapturedEvent[]; + duration: number; + currentTime: number; + onSeek: (time: number) => void; +} + +const EVENT_COLORS: Record = { + Results: "bg-blue-500", + TurnInfo: "bg-green-500", + AddTranscript: "bg-purple-500", + Connected: "bg-yellow-500", + RecognitionStarted: "bg-yellow-500", + EndOfTranscript: "bg-red-500", + Metadata: "bg-gray-500", + Error: "bg-red-600", + default: "bg-zinc-400", +}; + +function formatTime(seconds: number): string { + const mins = Math.floor(seconds / 60); + const secs = Math.floor(seconds % 60); + return `${mins}:${secs.toString().padStart(2, "0")}`; +} + +export default function EventTimeline({ + events, + duration, + currentTime, + onSeek, +}: EventTimelineProps) { + const timeMarkers = useMemo(() => { + const markers: number[] = []; + const interval = Math.ceil(duration / 6); + for (let i = 0; i <= duration; i += interval) { + markers.push(i); + } + if (markers[markers.length - 1] !== Math.floor(duration)) { + markers.push(Math.floor(duration)); + } + return markers; + }, [duration]); + + const handleClick = (e: React.MouseEvent) => { + const rect = e.currentTarget.getBoundingClientRect(); + const x = e.clientX - rect.left; + const percent = x / rect.width; + const time = percent * duration; + onSeek(Math.max(0, Math.min(time, duration))); + }; + + const progressPercent = (currentTime / duration) * 100; + + return ( +
+
Event Timeline
+ +
+ {/* Progress indicator */} +
+ + {/* Current time indicator */} +
+ + {/* Event markers */} +
+ {events.map((event, index) => { + const leftPercent = Math.min((event.timestamp / duration) * 100, 100); + const colorClass = + EVENT_COLORS[event.event_type] || EVENT_COLORS.default; + + return ( +
+ ); + })} +
+
+ + {/* Time markers */} +
+ {timeMarkers.map((time, index) => ( + {formatTime(time)} + ))} +
+ + {/* Legend */} +
+ {Object.entries(EVENT_COLORS) + .filter(([key]) => key !== "default") + .slice(0, 6) + .map(([eventType, colorClass]) => ( +
+
+ {eventType} +
+ ))} +
+
+ ); +} diff --git a/evals/visualizer/src/components/events/DeepgramEventItem.tsx b/evals/visualizer/src/components/events/DeepgramEventItem.tsx new file mode 100644 index 0000000..7419658 --- /dev/null +++ b/evals/visualizer/src/components/events/DeepgramEventItem.tsx @@ -0,0 +1,98 @@ +"use client"; + +import { CapturedEvent } from "@/types"; + +interface DeepgramEventItemProps { + event: CapturedEvent; + isExpanded: boolean; + onToggleExpand: () => void; +} + +const EVENT_COLORS: Record = { + Results: "text-blue-400 bg-blue-500/10", + SpeechStarted: "text-yellow-400 bg-yellow-500/10", + Metadata: "text-gray-400 bg-gray-500/10", + UtteranceEnd: "text-red-500 bg-red-600/10", + default: "text-zinc-400 bg-zinc-500/10", +}; + +function getTranscript(event: CapturedEvent): string { + const data = event.data; + const channel = data.channel as Record | undefined; + if (channel) { + const alternatives = channel.alternatives as Array<{ transcript?: string }> | undefined; + if (alternatives?.[0]?.transcript) { + return alternatives[0].transcript; + } + } + return ""; +} + +export default function DeepgramEventItem({ + event, + isExpanded, + onToggleExpand, +}: DeepgramEventItemProps) { + const colorClass = EVENT_COLORS[event.event_type] || EVENT_COLORS.default; + const data = event.data; + + const transcript = getTranscript(event); + const isFinal = data.is_final as boolean | undefined; + const speechFinal = data.speech_final as boolean | undefined; + + // For non-Results events + const isConnection = event.event_type === "Connected"; + const isMetadata = event.event_type === "Metadata"; + + return ( +
+
+ + {event.event_type} + + + {/* Final/Partial indicator for Results */} + {isFinal !== undefined && ( + + {isFinal ? "Final" : "Partial"} + + )} + + {/* Speech Final indicator */} + {speechFinal && ( + + Speech Final + + )} +
+ + {/* Transcript or status message */} +
+ {transcript} +
+ + {/* Expand/collapse button */} + + + {/* Expanded JSON view */} + {isExpanded && ( + 
+          {JSON.stringify(event.data, null, 2)}
+
+ )} +
+ ); +} diff --git a/evals/visualizer/src/components/events/FluxEventItem.tsx b/evals/visualizer/src/components/events/FluxEventItem.tsx new file mode 100644 index 0000000..6e85e5f --- /dev/null +++ b/evals/visualizer/src/components/events/FluxEventItem.tsx @@ -0,0 +1,115 @@ +"use client"; + +import { CapturedEvent } from "@/types"; + +interface FluxEventItemProps { + event: CapturedEvent; + isExpanded: boolean; + onToggleExpand: () => void; +} + +const EVENT_COLORS: Record = { + TurnInfo: "text-green-400 bg-green-500/10", + Connected: "text-yellow-400 bg-yellow-500/10", + Error: "text-red-500 bg-red-600/10", + default: "text-zinc-400 bg-zinc-500/10", +}; + +const FLUX_EVENT_COLORS: Record = { + Update: "text-amber-300 bg-amber-500/20", + EndOfTurn: "text-emerald-300 bg-emerald-500/20", + EagerEndOfTurn: "text-cyan-300 bg-cyan-500/20", + StartOfTurn: "text-blue-300 bg-blue-500/20", + TurnResumed: "text-purple-300 bg-purple-500/20", + default: "text-zinc-300 bg-zinc-500/20", +}; + +export default function FluxEventItem({ + event, + isExpanded, + onToggleExpand, +}: FluxEventItemProps) { + const colorClass = EVENT_COLORS[event.event_type] || EVENT_COLORS.default; + const data = event.data; + + // Flux TurnInfo fields + const fluxEvent = data.event as string | undefined; + const transcript = data.transcript as string | undefined; + const endOfTurnConfidence = data.end_of_turn_confidence as number | undefined; + const turnIndex = data.turn_index as number | undefined; + + const isFinal = fluxEvent === "EndOfTurn"; + const fluxEventColor = fluxEvent + ? FLUX_EVENT_COLORS[fluxEvent] || FLUX_EVENT_COLORS.default + : ""; + + // For non-TurnInfo events + const isConnection = event.event_type === "Connected"; + + return ( +
+
+ + {event.event_type} + + + {/* Flux sub-event type */} + {fluxEvent && ( + + {fluxEvent} + + )} + + {/* Final/Partial indicator */} + {fluxEvent && ( + + {isFinal ? "Final" : "Partial"} + + )} + + {/* Turn index */} + {turnIndex !== undefined && ( + + Turn {turnIndex} + + )} + + {/* EOT confidence */} + {endOfTurnConfidence !== undefined && ( + + EOT: {(endOfTurnConfidence * 100).toFixed(1)}% + + )} +
+ + {/* Transcript or status message */} +
+ {transcript || (isConnection ? "[Connected]" : `[${fluxEvent || event.event_type}]`)} +
+ + {/* Expand/collapse button */} + + + {/* Expanded JSON view */} + {isExpanded && ( + 
+          {JSON.stringify(event.data, null, 2)}
+
+ )} +
+ ); +} diff --git a/evals/visualizer/src/components/events/SpeechmaticsEventItem.tsx b/evals/visualizer/src/components/events/SpeechmaticsEventItem.tsx new file mode 100644 index 0000000..e6411d3 --- /dev/null +++ b/evals/visualizer/src/components/events/SpeechmaticsEventItem.tsx @@ -0,0 +1,101 @@ +"use client"; + +import { CapturedEvent } from "@/types"; + +interface SpeechmaticsEventItemProps { + event: CapturedEvent; + isExpanded: boolean; + onToggleExpand: () => void; +} + +const EVENT_COLORS: Record = { + AddTranscript: "text-purple-400 bg-purple-500/10", + RecognitionStarted: "text-yellow-400 bg-yellow-500/10", + EndOfTranscript: "text-red-400 bg-red-500/10", + Warning: "text-orange-400 bg-orange-500/10", + Error: "text-red-500 bg-red-600/10", + default: "text-zinc-400 bg-zinc-500/10", +}; + +function getTranscript(event: CapturedEvent): string { + const data = event.data; + const results = data.results as Array<{ + type?: string; + alternatives?: Array<{ content?: string }>; + }> | undefined; + + if (results) { + const words = results + .filter((r) => r.type === "word" && r.alternatives?.[0]?.content) + .map((r) => r.alternatives![0].content) + .join(" "); + return words; + } + return ""; +} + +export default function SpeechmaticsEventItem({ + event, + isExpanded, + onToggleExpand, +}: SpeechmaticsEventItemProps) { + const colorClass = EVENT_COLORS[event.event_type] || EVENT_COLORS.default; + const data = event.data; + + const transcript = getTranscript(event); + + // Status events + const isRecognitionStarted = event.event_type === "RecognitionStarted"; + const isEndOfTranscript = event.event_type === "EndOfTranscript"; + const isWarning = event.event_type === "Warning"; + + // Warning reason + const warningReason = isWarning ? (data.reason as string | undefined) : undefined; + + return ( +
+
+ + {event.event_type} + + + {/* AddTranscript is always final in Speechmatics */} + {event.event_type === "AddTranscript" && ( + + Final + + )} +
+ + {/* Transcript or status message */} +
+ {transcript || + (isRecognitionStarted + ? "[Recognition Started]" + : isEndOfTranscript + ? "[End of Transcript]" + : isWarning + ? `[Warning: ${warningReason || "unknown"}]` + : `[${event.event_type}]`)} +
+ + {/* Expand/collapse button */} + + + {/* Expanded JSON view */} + {isExpanded && ( + 
+          {JSON.stringify(event.data, null, 2)}
+
+ )} +
+ ); +} diff --git a/evals/visualizer/src/components/events/index.ts b/evals/visualizer/src/components/events/index.ts new file mode 100644 index 0000000..e436198 --- /dev/null +++ b/evals/visualizer/src/components/events/index.ts @@ -0,0 +1,3 @@ +export { default as DeepgramEventItem } from "./DeepgramEventItem"; +export { default as FluxEventItem } from "./FluxEventItem"; +export { default as SpeechmaticsEventItem } from "./SpeechmaticsEventItem"; diff --git a/evals/visualizer/src/types/index.ts b/evals/visualizer/src/types/index.ts new file mode 100644 index 0000000..787e89d --- /dev/null +++ b/evals/visualizer/src/types/index.ts @@ -0,0 +1,24 @@ +export interface CapturedEvent { + timestamp: number; + event_type: string; + data: Record; +} + +export interface EventCaptureResult { + audio_file: string; + audio_path: string; + provider: string; + duration: number; + created_at: string; + events: CapturedEvent[]; + transcript: string; +} + +export interface ResultSummary { + id: string; + audio_file: string; + provider: string; + duration: number; + created_at: string; + event_count: number; +} diff --git a/evals/visualizer/tsconfig.json b/evals/visualizer/tsconfig.json new file mode 100644 index 0000000..cf9c65d --- /dev/null +++ b/evals/visualizer/tsconfig.json @@ -0,0 +1,34 @@ +{ + "compilerOptions": { + "target": "ES2017", + "lib": ["dom", "dom.iterable", "esnext"], + "allowJs": true, + "skipLibCheck": true, + "strict": true, + "noEmit": true, + "esModuleInterop": true, + "module": "esnext", + "moduleResolution": "bundler", + "resolveJsonModule": true, + "isolatedModules": true, + "jsx": "react-jsx", + "incremental": true, + "plugins": [ + { + "name": "next" + } + ], + "paths": { + "@/*": ["./src/*"] + } + }, + "include": [ + "next-env.d.ts", + "**/*.ts", + "**/*.tsx", + ".next/types/**/*.ts", + ".next/dev/types/**/*.ts", + "**/*.mts" + ], + "exclude": ["node_modules"] +} diff --git a/pipecat b/pipecat index a1d3062..f11fad8 160000 --- a/pipecat +++ b/pipecat @@ -1 +1 @@ -Subproject commit a1d3062446240b6b27ebc787d28578e4561e7441 +Subproject commit f11fad8f3e90e06b1625b9dc49c13e26f3c9e716 diff --git a/release-please-config.json b/release-please-config.json index 1e07b35..83acde6 100644 --- a/release-please-config.json +++ b/release-please-config.json @@ -16,6 +16,11 @@ "type": "json", "path": "ui/package.json", "jsonpath": "$.version" + }, + { + "type": "toml", + "path": "api/pyproject.toml", + "key": "project.version" } ] } diff --git a/ui/src/app/after-sign-in/page.tsx b/ui/src/app/after-sign-in/page.tsx index 21f0ea8..39796e9 100644 --- a/ui/src/app/after-sign-in/page.tsx +++ b/ui/src/app/after-sign-in/page.tsx @@ -1,6 +1,6 @@ import { redirect } from "next/navigation"; -import { getWorkflowsApiV1WorkflowFetchGet } from "@/client/sdk.gen"; +import { getWorkflowCountApiV1WorkflowCountGet } from "@/client/sdk.gen"; import { getServerAccessToken,getServerAuthProvider, getServerUser } from "@/lib/auth/server"; import logger from '@/lib/logger'; import { getRedirectUrl } from "@/lib/utils"; @@ -34,21 +34,18 @@ export default async function AfterSignInPage() { try { const accessToken = await getServerAccessToken(); if (accessToken) { - const workflowsResponse = await getWorkflowsApiV1WorkflowFetchGet({ + const countResponse = await getWorkflowCountApiV1WorkflowCountGet({ headers: { Authorization: `Bearer ${accessToken}`, }, }); - const workflows = workflowsResponse.data ? (Array.isArray(workflowsResponse.data) ? workflowsResponse.data : [workflowsResponse.data]) : []; - const activeWorkflows = workflows.filter(w => w.status === 'active'); - logger.debug('[AfterSignInPage] Found workflows:', { - total: workflows.length, - active: activeWorkflows.length + total: countResponse.data?.total, + active: countResponse.data?.active }); - if (activeWorkflows.length > 0) { + if (countResponse.data && countResponse.data.active > 0) { logger.debug('[AfterSignInPage] Redirecting to /workflow - user has workflows'); redirect('/workflow'); } else { diff --git a/ui/src/app/api/config/version/route.ts b/ui/src/app/api/config/version/route.ts new file mode 100644 index 0000000..241085f --- /dev/null +++ b/ui/src/app/api/config/version/route.ts @@ -0,0 +1,33 @@ +import { NextResponse } from "next/server"; + +import { healthApiV1HealthGet } from "@/client/sdk.gen"; +import type { HealthResponse } from "@/client/types.gen"; + +// Import version from package.json at build time +import packageJson from "../../../../../package.json"; + +export async function GET() { + const uiVersion = packageJson.version || "dev"; + + // Fetch backend version and config from health endpoint + let apiVersion = "unknown"; + let backendApiEndpoint: string | null = null; + + try { + const response = await healthApiV1HealthGet(); + if (response.data) { + const data = response.data as HealthResponse; + apiVersion = data.version; + backendApiEndpoint = data.backend_api_endpoint; + } + } catch { + // Backend might not be reachable during build or in some deployments + apiVersion = "unavailable"; + } + + return NextResponse.json({ + ui: uiVersion, + api: apiVersion, + backendApiEndpoint, + }); +} diff --git a/ui/src/app/layout.tsx b/ui/src/app/layout.tsx index b0a4ced..060fdd3 100644 --- a/ui/src/app/layout.tsx +++ b/ui/src/app/layout.tsx @@ -9,6 +9,7 @@ import AppLayout from "@/components/layout/AppLayout"; import PostHogIdentify from "@/components/PostHogIdentify"; import SpinLoader from "@/components/SpinLoader"; import { Toaster } from "@/components/ui/sonner"; +import { AppConfigProvider } from "@/context/AppConfigContext"; import { OnboardingProvider } from "@/context/OnboardingContext"; import { UserConfigProvider } from "@/context/UserConfigContext"; import { AuthProvider } from "@/lib/auth"; @@ -59,18 +60,20 @@ export default function RootLayout({ - }> - - - - - {children} - - - - - - + + }> + + + + + {children} + + + + + + + diff --git a/ui/src/app/page.tsx b/ui/src/app/page.tsx index ae6e151..60a175f 100644 --- a/ui/src/app/page.tsx +++ b/ui/src/app/page.tsx @@ -1,7 +1,7 @@ import { isNextRouterError } from "next/dist/client/components/is-next-router-error"; import { redirect } from "next/navigation"; -import { getWorkflowsApiV1WorkflowFetchGet } from "@/client/sdk.gen"; +import { getWorkflowCountApiV1WorkflowCountGet } from "@/client/sdk.gen"; import SignInClient from "@/components/SignInClient"; import { getServerAccessToken,getServerAuthProvider,getServerUser } from "@/lib/auth/server"; import logger from '@/lib/logger'; @@ -21,21 +21,18 @@ export default async function Home() { try { const accessToken = await getServerAccessToken(); if (accessToken) { - const workflowsResponse = await getWorkflowsApiV1WorkflowFetchGet({ + const countResponse = await getWorkflowCountApiV1WorkflowCountGet({ headers: { Authorization: `Bearer ${accessToken}`, }, }); - const workflows = workflowsResponse.data ? (Array.isArray(workflowsResponse.data) ? workflowsResponse.data : [workflowsResponse.data]) : []; - const activeWorkflows = workflows.filter(w => w.status === 'active'); - logger.debug('[HomePage] Found workflows for local provider:', { - total: workflows.length, - active: activeWorkflows.length + total: countResponse.data?.total, + active: countResponse.data?.active }); - if (activeWorkflows.length > 0) { + if (countResponse.data && countResponse.data.active > 0) { logger.debug('[HomePage] Redirecting to /workflow - user has workflows'); redirect('/workflow'); } else { diff --git a/ui/src/app/usage/page.tsx b/ui/src/app/usage/page.tsx index 688b47b..d38b7ce 100644 --- a/ui/src/app/usage/page.tsx +++ b/ui/src/app/usage/page.tsx @@ -326,14 +326,64 @@ export default function UsagePage() { isDisabled={savingTimezone || userConfigLoading} placeholder={userConfigLoading ? "Loading..." : "Select timezone"} styles={{ - control: (base) => ({ + control: (base, state) => ({ ...base, minHeight: '36px', fontSize: '14px', + backgroundColor: 'var(--background)', + borderColor: state.isFocused ? 'var(--ring)' : 'var(--border)', + boxShadow: state.isFocused ? '0 0 0 2px color-mix(in srgb, var(--ring) 20%, transparent)' : 'none', + '&:hover': { + borderColor: 'var(--border)', + }, }), menu: (base) => ({ ...base, zIndex: 9999, + backgroundColor: 'var(--popover)', + border: '1px solid var(--border)', + boxShadow: '0 4px 6px -1px rgb(0 0 0 / 0.1), 0 2px 4px -2px rgb(0 0 0 / 0.1)', + }), + menuList: (base) => ({ + ...base, + backgroundColor: 'var(--popover)', + padding: 0, + }), + option: (base, state) => ({ + ...base, + backgroundColor: state.isSelected + ? 'var(--accent)' + : state.isFocused + ? 'var(--accent)' + : 'var(--popover)', + color: 'var(--foreground)', + cursor: 'pointer', + '&:active': { + backgroundColor: 'var(--accent)', + }, + }), + singleValue: (base) => ({ + ...base, + color: 'var(--foreground)', + }), + input: (base) => ({ + ...base, + color: 'var(--foreground)', + }), + placeholder: (base) => ({ + ...base, + color: 'var(--muted-foreground)', + }), + indicatorSeparator: (base) => ({ + ...base, + backgroundColor: 'var(--border)', + }), + dropdownIndicator: (base) => ({ + ...base, + color: 'var(--muted-foreground)', + '&:hover': { + color: 'var(--foreground)', + }, }), }} /> diff --git a/ui/src/client/sdk.gen.ts b/ui/src/client/sdk.gen.ts index c925c76..57a9786 100644 --- a/ui/src/client/sdk.gen.ts +++ b/ui/src/client/sdk.gen.ts @@ -3,7 +3,7 @@ import type { Client,Options as ClientOptions, TDataShape } from '@hey-api/client-fetch'; import { client as _heyApiClient } from './client.gen'; -import type { ArchiveApiKeyApiV1UserApiKeysApiKeyIdDeleteData, ArchiveApiKeyApiV1UserApiKeysApiKeyIdDeleteError, ArchiveApiKeyApiV1UserApiKeysApiKeyIdDeleteResponse, ArchiveServiceKeyApiV1UserServiceKeysServiceKeyIdDeleteData, ArchiveServiceKeyApiV1UserServiceKeysServiceKeyIdDeleteError, CreateApiKeyApiV1UserApiKeysPostData, CreateApiKeyApiV1UserApiKeysPostError, CreateApiKeyApiV1UserApiKeysPostResponse, CreateCampaignApiV1CampaignCreatePostData, CreateCampaignApiV1CampaignCreatePostError, CreateCampaignApiV1CampaignCreatePostResponse, CreateCredentialApiV1CredentialsPostData, CreateCredentialApiV1CredentialsPostError, CreateCredentialApiV1CredentialsPostResponse, CreateLoadTestApiV1LooptalkLoadTestsPostData, CreateLoadTestApiV1LooptalkLoadTestsPostError, CreateLoadTestApiV1LooptalkLoadTestsPostResponse, CreateOrUpdateEmbedTokenApiV1WorkflowWorkflowIdEmbedTokenPostData, CreateOrUpdateEmbedTokenApiV1WorkflowWorkflowIdEmbedTokenPostError, CreateOrUpdateEmbedTokenApiV1WorkflowWorkflowIdEmbedTokenPostResponse, CreateServiceKeyApiV1UserServiceKeysPostData, CreateServiceKeyApiV1UserServiceKeysPostError, CreateServiceKeyApiV1UserServiceKeysPostResponse, CreateSessionApiV1IntegrationSessionPostData, CreateSessionApiV1IntegrationSessionPostError, CreateSessionApiV1IntegrationSessionPostResponse, CreateTestSessionApiV1LooptalkTestSessionsPostData, CreateTestSessionApiV1LooptalkTestSessionsPostError, CreateTestSessionApiV1LooptalkTestSessionsPostResponse, CreateToolApiV1ToolsPostData, CreateToolApiV1ToolsPostError, CreateToolApiV1ToolsPostResponse, CreateWorkflowApiV1WorkflowCreateDefinitionPostData, CreateWorkflowApiV1WorkflowCreateDefinitionPostError, CreateWorkflowApiV1WorkflowCreateDefinitionPostResponse, CreateWorkflowFromTemplateApiV1WorkflowCreateTemplatePostData, CreateWorkflowFromTemplateApiV1WorkflowCreateTemplatePostError, CreateWorkflowFromTemplateApiV1WorkflowCreateTemplatePostResponse, CreateWorkflowRunApiV1WorkflowWorkflowIdRunsPostData, CreateWorkflowRunApiV1WorkflowWorkflowIdRunsPostError, CreateWorkflowRunApiV1WorkflowWorkflowIdRunsPostResponse, DeactivateEmbedTokenApiV1WorkflowWorkflowIdEmbedTokenDeleteData, DeactivateEmbedTokenApiV1WorkflowWorkflowIdEmbedTokenDeleteError, DeactivateEmbedTokenApiV1WorkflowWorkflowIdEmbedTokenDeleteResponse, DeleteCredentialApiV1CredentialsCredentialUuidDeleteData, DeleteCredentialApiV1CredentialsCredentialUuidDeleteError, DeleteCredentialApiV1CredentialsCredentialUuidDeleteResponse, DeleteDocumentApiV1KnowledgeBaseDocumentsDocumentUuidDeleteData, DeleteDocumentApiV1KnowledgeBaseDocumentsDocumentUuidDeleteError, DeleteToolApiV1ToolsToolUuidDeleteData, DeleteToolApiV1ToolsToolUuidDeleteError, DeleteToolApiV1ToolsToolUuidDeleteResponse, DuplicateWorkflowTemplateApiV1WorkflowTemplatesDuplicatePostData, DuplicateWorkflowTemplateApiV1WorkflowTemplatesDuplicatePostError, DuplicateWorkflowTemplateApiV1WorkflowTemplatesDuplicatePostResponse, GetActiveTestsApiV1LooptalkActiveTestsGetData, GetActiveTestsApiV1LooptalkActiveTestsGetError, GetApiKeysApiV1UserApiKeysGetData, GetApiKeysApiV1UserApiKeysGetError, GetApiKeysApiV1UserApiKeysGetResponse, GetAuthUserApiV1UserAuthUserGetData, GetAuthUserApiV1UserAuthUserGetError, GetAuthUserApiV1UserAuthUserGetResponse, GetCampaignApiV1CampaignCampaignIdGetData, GetCampaignApiV1CampaignCampaignIdGetError, GetCampaignApiV1CampaignCampaignIdGetResponse, GetCampaignProgressApiV1CampaignCampaignIdProgressGetData, GetCampaignProgressApiV1CampaignCampaignIdProgressGetError, GetCampaignProgressApiV1CampaignCampaignIdProgressGetResponse, GetCampaignRunsApiV1CampaignCampaignIdRunsGetData, GetCampaignRunsApiV1CampaignCampaignIdRunsGetError, GetCampaignRunsApiV1CampaignCampaignIdRunsGetResponse, GetCampaignsApiV1CampaignGetData, GetCampaignsApiV1CampaignGetError, GetCampaignsApiV1CampaignGetResponse, GetCampaignSourceDownloadUrlApiV1CampaignCampaignIdSourceDownloadUrlGetData, GetCampaignSourceDownloadUrlApiV1CampaignCampaignIdSourceDownloadUrlGetError, GetCampaignSourceDownloadUrlApiV1CampaignCampaignIdSourceDownloadUrlGetResponse, GetCredentialApiV1CredentialsCredentialUuidGetData, GetCredentialApiV1CredentialsCredentialUuidGetError, GetCredentialApiV1CredentialsCredentialUuidGetResponse, GetCurrentPeriodUsageApiV1OrganizationsUsageCurrentPeriodGetData, GetCurrentPeriodUsageApiV1OrganizationsUsageCurrentPeriodGetError, GetCurrentPeriodUsageApiV1OrganizationsUsageCurrentPeriodGetResponse, GetDailyReportApiV1OrganizationsReportsDailyGetData, GetDailyReportApiV1OrganizationsReportsDailyGetError, GetDailyReportApiV1OrganizationsReportsDailyGetResponse, GetDailyRunsDetailApiV1OrganizationsReportsDailyRunsGetData, GetDailyRunsDetailApiV1OrganizationsReportsDailyRunsGetError, GetDailyRunsDetailApiV1OrganizationsReportsDailyRunsGetResponse, GetDailyUsageBreakdownApiV1OrganizationsUsageDailyBreakdownGetData, GetDailyUsageBreakdownApiV1OrganizationsUsageDailyBreakdownGetError, GetDailyUsageBreakdownApiV1OrganizationsUsageDailyBreakdownGetResponse, GetDefaultConfigurationsApiV1UserConfigurationsDefaultsGetData, GetDefaultConfigurationsApiV1UserConfigurationsDefaultsGetResponse, GetDocumentApiV1KnowledgeBaseDocumentsDocumentUuidGetData, GetDocumentApiV1KnowledgeBaseDocumentsDocumentUuidGetError, GetDocumentApiV1KnowledgeBaseDocumentsDocumentUuidGetResponse, GetEmbedConfigApiV1PublicEmbedConfigTokenGetData, GetEmbedConfigApiV1PublicEmbedConfigTokenGetError, GetEmbedConfigApiV1PublicEmbedConfigTokenGetResponse, GetEmbedTokenApiV1WorkflowWorkflowIdEmbedTokenGetData, GetEmbedTokenApiV1WorkflowWorkflowIdEmbedTokenGetError, GetEmbedTokenApiV1WorkflowWorkflowIdEmbedTokenGetResponse, GetFileMetadataApiV1S3FileMetadataGetData, GetFileMetadataApiV1S3FileMetadataGetError, GetFileMetadataApiV1S3FileMetadataGetResponse, GetIntegrationAccessTokenApiV1IntegrationIntegrationIdAccessTokenGetData, GetIntegrationAccessTokenApiV1IntegrationIntegrationIdAccessTokenGetError, GetIntegrationAccessTokenApiV1IntegrationIntegrationIdAccessTokenGetResponse, GetIntegrationsApiV1IntegrationGetData, GetIntegrationsApiV1IntegrationGetError, GetIntegrationsApiV1IntegrationGetResponse, GetLoadTestStatsApiV1LooptalkLoadTestsLoadTestGroupIdStatsGetData, GetLoadTestStatsApiV1LooptalkLoadTestsLoadTestGroupIdStatsGetError, GetLoadTestStatsApiV1LooptalkLoadTestsLoadTestGroupIdStatsGetResponse, GetPresignedUploadUrlApiV1S3PresignedUploadUrlPostData, GetPresignedUploadUrlApiV1S3PresignedUploadUrlPostError, GetPresignedUploadUrlApiV1S3PresignedUploadUrlPostResponse, GetServiceKeysApiV1UserServiceKeysGetData, GetServiceKeysApiV1UserServiceKeysGetError, GetServiceKeysApiV1UserServiceKeysGetResponse, GetSignedUrlApiV1S3SignedUrlGetData, GetSignedUrlApiV1S3SignedUrlGetError, GetSignedUrlApiV1S3SignedUrlGetResponse, GetTelephonyConfigurationApiV1OrganizationsTelephonyConfigGetData, GetTelephonyConfigurationApiV1OrganizationsTelephonyConfigGetError, GetTelephonyConfigurationApiV1OrganizationsTelephonyConfigGetResponse, GetTestSessionApiV1LooptalkTestSessionsTestSessionIdGetData, GetTestSessionApiV1LooptalkTestSessionsTestSessionIdGetError, GetTestSessionApiV1LooptalkTestSessionsTestSessionIdGetResponse, GetTestSessionConversationApiV1LooptalkTestSessionsTestSessionIdConversationGetData, GetTestSessionConversationApiV1LooptalkTestSessionsTestSessionIdConversationGetError, GetToolApiV1ToolsToolUuidGetData, GetToolApiV1ToolsToolUuidGetError, GetToolApiV1ToolsToolUuidGetResponse, GetUploadUrlApiV1KnowledgeBaseUploadUrlPostData, GetUploadUrlApiV1KnowledgeBaseUploadUrlPostError, GetUploadUrlApiV1KnowledgeBaseUploadUrlPostResponse, GetUsageHistoryApiV1OrganizationsUsageRunsGetData, GetUsageHistoryApiV1OrganizationsUsageRunsGetError, GetUsageHistoryApiV1OrganizationsUsageRunsGetResponse, GetUserConfigurationsApiV1UserConfigurationsUserGetData, GetUserConfigurationsApiV1UserConfigurationsUserGetError, GetUserConfigurationsApiV1UserConfigurationsUserGetResponse, GetVoicesApiV1UserConfigurationsVoicesProviderGetData, GetVoicesApiV1UserConfigurationsVoicesProviderGetError, GetVoicesApiV1UserConfigurationsVoicesProviderGetResponse, GetWorkflowApiV1WorkflowFetchWorkflowIdGetData, GetWorkflowApiV1WorkflowFetchWorkflowIdGetError, GetWorkflowApiV1WorkflowFetchWorkflowIdGetResponse, GetWorkflowOptionsApiV1OrganizationsReportsWorkflowsGetData, GetWorkflowOptionsApiV1OrganizationsReportsWorkflowsGetError, GetWorkflowOptionsApiV1OrganizationsReportsWorkflowsGetResponse, GetWorkflowRunApiV1WorkflowWorkflowIdRunsRunIdGetData, GetWorkflowRunApiV1WorkflowWorkflowIdRunsRunIdGetError, GetWorkflowRunApiV1WorkflowWorkflowIdRunsRunIdGetResponse, GetWorkflowRunsApiV1SuperuserWorkflowRunsGetData, GetWorkflowRunsApiV1SuperuserWorkflowRunsGetError, GetWorkflowRunsApiV1SuperuserWorkflowRunsGetResponse, GetWorkflowRunsApiV1WorkflowWorkflowIdRunsGetData, GetWorkflowRunsApiV1WorkflowWorkflowIdRunsGetError, GetWorkflowRunsApiV1WorkflowWorkflowIdRunsGetResponse, GetWorkflowsApiV1WorkflowFetchGetData, GetWorkflowsApiV1WorkflowFetchGetError, GetWorkflowsApiV1WorkflowFetchGetResponse, GetWorkflowsSummaryApiV1WorkflowSummaryGetData, GetWorkflowsSummaryApiV1WorkflowSummaryGetError, GetWorkflowsSummaryApiV1WorkflowSummaryGetResponse, GetWorkflowTemplatesApiV1WorkflowTemplatesGetData, GetWorkflowTemplatesApiV1WorkflowTemplatesGetResponse, HandleCloudonixStatusCallbackApiV1TelephonyCloudonixStatusCallbackWorkflowRunIdPostData, HandleCloudonixStatusCallbackApiV1TelephonyCloudonixStatusCallbackWorkflowRunIdPostError, HandleInboundFallbackApiV1TelephonyInboundFallbackPostData, HandleInboundTelephonyApiV1TelephonyInboundWorkflowIdPostData, HandleInboundTelephonyApiV1TelephonyInboundWorkflowIdPostError, HandleTwilioStatusCallbackApiV1TelephonyTwilioStatusCallbackWorkflowRunIdPostData, HandleTwilioStatusCallbackApiV1TelephonyTwilioStatusCallbackWorkflowRunIdPostError, HandleVobizHangupCallbackApiV1TelephonyVobizHangupCallbackWorkflowRunIdPostData, HandleVobizHangupCallbackApiV1TelephonyVobizHangupCallbackWorkflowRunIdPostError, HandleVobizHangupCallbackByWorkflowApiV1TelephonyVobizHangupCallbackWorkflowWorkflowIdPostData, HandleVobizHangupCallbackByWorkflowApiV1TelephonyVobizHangupCallbackWorkflowWorkflowIdPostError, HandleVobizRingCallbackApiV1TelephonyVobizRingCallbackWorkflowRunIdPostData, HandleVobizRingCallbackApiV1TelephonyVobizRingCallbackWorkflowRunIdPostError, HandleVonageEventsApiV1TelephonyVonageEventsWorkflowRunIdPostData, HandleVonageEventsApiV1TelephonyVonageEventsWorkflowRunIdPostError, HealthApiV1HealthGetData,ImpersonateApiV1SuperuserImpersonatePostData, ImpersonateApiV1SuperuserImpersonatePostError, ImpersonateApiV1SuperuserImpersonatePostResponse, InitializeEmbedSessionApiV1PublicEmbedInitPostData, InitializeEmbedSessionApiV1PublicEmbedInitPostError, InitializeEmbedSessionApiV1PublicEmbedInitPostResponse, InitiateCallApiV1PublicAgentUuidPostData, InitiateCallApiV1PublicAgentUuidPostError, InitiateCallApiV1PublicAgentUuidPostResponse, InitiateCallApiV1TelephonyInitiateCallPostData, InitiateCallApiV1TelephonyInitiateCallPostError, ListCredentialsApiV1CredentialsGetData, ListCredentialsApiV1CredentialsGetError, ListCredentialsApiV1CredentialsGetResponse, ListDocumentsApiV1KnowledgeBaseDocumentsGetData, ListDocumentsApiV1KnowledgeBaseDocumentsGetError, ListDocumentsApiV1KnowledgeBaseDocumentsGetResponse, ListTestSessionsApiV1LooptalkTestSessionsGetData, ListTestSessionsApiV1LooptalkTestSessionsGetError, ListTestSessionsApiV1LooptalkTestSessionsGetResponse, ListToolsApiV1ToolsGetData, ListToolsApiV1ToolsGetError, ListToolsApiV1ToolsGetResponse, OptionsConfigApiV1PublicEmbedConfigTokenOptionsData, OptionsConfigApiV1PublicEmbedConfigTokenOptionsError, OptionsInitApiV1PublicEmbedInitOptionsData, PauseCampaignApiV1CampaignCampaignIdPausePostData, PauseCampaignApiV1CampaignCampaignIdPausePostError, PauseCampaignApiV1CampaignCampaignIdPausePostResponse, ProcessDocumentApiV1KnowledgeBaseProcessDocumentPostData, ProcessDocumentApiV1KnowledgeBaseProcessDocumentPostError, ProcessDocumentApiV1KnowledgeBaseProcessDocumentPostResponse, ReactivateApiKeyApiV1UserApiKeysApiKeyIdReactivatePutData, ReactivateApiKeyApiV1UserApiKeysApiKeyIdReactivatePutError, ReactivateApiKeyApiV1UserApiKeysApiKeyIdReactivatePutResponse, ReactivateServiceKeyApiV1UserServiceKeysServiceKeyIdReactivatePutData, ReactivateServiceKeyApiV1UserServiceKeysServiceKeyIdReactivatePutError, ResumeCampaignApiV1CampaignCampaignIdResumePostData, ResumeCampaignApiV1CampaignCampaignIdResumePostError, ResumeCampaignApiV1CampaignCampaignIdResumePostResponse, SaveTelephonyConfigurationApiV1OrganizationsTelephonyConfigPostData, SaveTelephonyConfigurationApiV1OrganizationsTelephonyConfigPostError, SearchChunksApiV1KnowledgeBaseSearchPostData, SearchChunksApiV1KnowledgeBaseSearchPostError, SearchChunksApiV1KnowledgeBaseSearchPostResponse, SetAdminCommentApiV1SuperuserWorkflowRunsRunIdCommentPostData, SetAdminCommentApiV1SuperuserWorkflowRunsRunIdCommentPostError, SetAdminCommentApiV1SuperuserWorkflowRunsRunIdCommentPostResponse, StartCampaignApiV1CampaignCampaignIdStartPostData, StartCampaignApiV1CampaignCampaignIdStartPostError, StartCampaignApiV1CampaignCampaignIdStartPostResponse, StartTestSessionApiV1LooptalkTestSessionsTestSessionIdStartPostData, StartTestSessionApiV1LooptalkTestSessionsTestSessionIdStartPostError, StopTestSessionApiV1LooptalkTestSessionsTestSessionIdStopPostData, StopTestSessionApiV1LooptalkTestSessionsTestSessionIdStopPostError, UnarchiveToolApiV1ToolsToolUuidUnarchivePostData, UnarchiveToolApiV1ToolsToolUuidUnarchivePostError, UnarchiveToolApiV1ToolsToolUuidUnarchivePostResponse, UpdateCredentialApiV1CredentialsCredentialUuidPutData, UpdateCredentialApiV1CredentialsCredentialUuidPutError, UpdateCredentialApiV1CredentialsCredentialUuidPutResponse, UpdateIntegrationApiV1IntegrationIntegrationIdPutData, UpdateIntegrationApiV1IntegrationIntegrationIdPutError, UpdateIntegrationApiV1IntegrationIntegrationIdPutResponse, UpdateToolApiV1ToolsToolUuidPutData, UpdateToolApiV1ToolsToolUuidPutError, UpdateToolApiV1ToolsToolUuidPutResponse, UpdateUserConfigurationsApiV1UserConfigurationsUserPutData, UpdateUserConfigurationsApiV1UserConfigurationsUserPutError, UpdateUserConfigurationsApiV1UserConfigurationsUserPutResponse, UpdateWorkflowApiV1WorkflowWorkflowIdPutData, UpdateWorkflowApiV1WorkflowWorkflowIdPutError, UpdateWorkflowApiV1WorkflowWorkflowIdPutResponse, UpdateWorkflowStatusApiV1WorkflowWorkflowIdStatusPutData, UpdateWorkflowStatusApiV1WorkflowWorkflowIdStatusPutError, UpdateWorkflowStatusApiV1WorkflowWorkflowIdStatusPutResponse, ValidateUserConfigurationsApiV1UserConfigurationsUserValidateGetData, ValidateUserConfigurationsApiV1UserConfigurationsUserValidateGetError, ValidateUserConfigurationsApiV1UserConfigurationsUserValidateGetResponse, ValidateWorkflowApiV1WorkflowWorkflowIdValidatePostData, ValidateWorkflowApiV1WorkflowWorkflowIdValidatePostError, ValidateWorkflowApiV1WorkflowWorkflowIdValidatePostResponse } from './types.gen'; +import type { ArchiveApiKeyApiV1UserApiKeysApiKeyIdDeleteData, ArchiveApiKeyApiV1UserApiKeysApiKeyIdDeleteError, ArchiveApiKeyApiV1UserApiKeysApiKeyIdDeleteResponse, ArchiveServiceKeyApiV1UserServiceKeysServiceKeyIdDeleteData, ArchiveServiceKeyApiV1UserServiceKeysServiceKeyIdDeleteError, CreateApiKeyApiV1UserApiKeysPostData, CreateApiKeyApiV1UserApiKeysPostError, CreateApiKeyApiV1UserApiKeysPostResponse, CreateCampaignApiV1CampaignCreatePostData, CreateCampaignApiV1CampaignCreatePostError, CreateCampaignApiV1CampaignCreatePostResponse, CreateCredentialApiV1CredentialsPostData, CreateCredentialApiV1CredentialsPostError, CreateCredentialApiV1CredentialsPostResponse, CreateLoadTestApiV1LooptalkLoadTestsPostData, CreateLoadTestApiV1LooptalkLoadTestsPostError, CreateLoadTestApiV1LooptalkLoadTestsPostResponse, CreateOrUpdateEmbedTokenApiV1WorkflowWorkflowIdEmbedTokenPostData, CreateOrUpdateEmbedTokenApiV1WorkflowWorkflowIdEmbedTokenPostError, CreateOrUpdateEmbedTokenApiV1WorkflowWorkflowIdEmbedTokenPostResponse, CreateServiceKeyApiV1UserServiceKeysPostData, CreateServiceKeyApiV1UserServiceKeysPostError, CreateServiceKeyApiV1UserServiceKeysPostResponse, CreateSessionApiV1IntegrationSessionPostData, CreateSessionApiV1IntegrationSessionPostError, CreateSessionApiV1IntegrationSessionPostResponse, CreateTestSessionApiV1LooptalkTestSessionsPostData, CreateTestSessionApiV1LooptalkTestSessionsPostError, CreateTestSessionApiV1LooptalkTestSessionsPostResponse, CreateToolApiV1ToolsPostData, CreateToolApiV1ToolsPostError, CreateToolApiV1ToolsPostResponse, CreateWorkflowApiV1WorkflowCreateDefinitionPostData, CreateWorkflowApiV1WorkflowCreateDefinitionPostError, CreateWorkflowApiV1WorkflowCreateDefinitionPostResponse, CreateWorkflowFromTemplateApiV1WorkflowCreateTemplatePostData, CreateWorkflowFromTemplateApiV1WorkflowCreateTemplatePostError, CreateWorkflowFromTemplateApiV1WorkflowCreateTemplatePostResponse, CreateWorkflowRunApiV1WorkflowWorkflowIdRunsPostData, CreateWorkflowRunApiV1WorkflowWorkflowIdRunsPostError, CreateWorkflowRunApiV1WorkflowWorkflowIdRunsPostResponse, DeactivateEmbedTokenApiV1WorkflowWorkflowIdEmbedTokenDeleteData, DeactivateEmbedTokenApiV1WorkflowWorkflowIdEmbedTokenDeleteError, DeactivateEmbedTokenApiV1WorkflowWorkflowIdEmbedTokenDeleteResponse, DeleteCredentialApiV1CredentialsCredentialUuidDeleteData, DeleteCredentialApiV1CredentialsCredentialUuidDeleteError, DeleteCredentialApiV1CredentialsCredentialUuidDeleteResponse, DeleteDocumentApiV1KnowledgeBaseDocumentsDocumentUuidDeleteData, DeleteDocumentApiV1KnowledgeBaseDocumentsDocumentUuidDeleteError, DeleteToolApiV1ToolsToolUuidDeleteData, DeleteToolApiV1ToolsToolUuidDeleteError, DeleteToolApiV1ToolsToolUuidDeleteResponse, DownloadWorkflowArtifactApiV1PublicDownloadWorkflowTokenArtifactTypeGetData, DownloadWorkflowArtifactApiV1PublicDownloadWorkflowTokenArtifactTypeGetError, DuplicateWorkflowTemplateApiV1WorkflowTemplatesDuplicatePostData, DuplicateWorkflowTemplateApiV1WorkflowTemplatesDuplicatePostError, DuplicateWorkflowTemplateApiV1WorkflowTemplatesDuplicatePostResponse, GetActiveTestsApiV1LooptalkActiveTestsGetData, GetActiveTestsApiV1LooptalkActiveTestsGetError, GetApiKeysApiV1UserApiKeysGetData, GetApiKeysApiV1UserApiKeysGetError, GetApiKeysApiV1UserApiKeysGetResponse, GetAuthUserApiV1UserAuthUserGetData, GetAuthUserApiV1UserAuthUserGetError, GetAuthUserApiV1UserAuthUserGetResponse, GetCampaignApiV1CampaignCampaignIdGetData, GetCampaignApiV1CampaignCampaignIdGetError, GetCampaignApiV1CampaignCampaignIdGetResponse, GetCampaignProgressApiV1CampaignCampaignIdProgressGetData, GetCampaignProgressApiV1CampaignCampaignIdProgressGetError, GetCampaignProgressApiV1CampaignCampaignIdProgressGetResponse, GetCampaignRunsApiV1CampaignCampaignIdRunsGetData, GetCampaignRunsApiV1CampaignCampaignIdRunsGetError, GetCampaignRunsApiV1CampaignCampaignIdRunsGetResponse, GetCampaignsApiV1CampaignGetData, GetCampaignsApiV1CampaignGetError, GetCampaignsApiV1CampaignGetResponse, GetCampaignSourceDownloadUrlApiV1CampaignCampaignIdSourceDownloadUrlGetData, GetCampaignSourceDownloadUrlApiV1CampaignCampaignIdSourceDownloadUrlGetError, GetCampaignSourceDownloadUrlApiV1CampaignCampaignIdSourceDownloadUrlGetResponse, GetCredentialApiV1CredentialsCredentialUuidGetData, GetCredentialApiV1CredentialsCredentialUuidGetError, GetCredentialApiV1CredentialsCredentialUuidGetResponse, GetCurrentPeriodUsageApiV1OrganizationsUsageCurrentPeriodGetData, GetCurrentPeriodUsageApiV1OrganizationsUsageCurrentPeriodGetError, GetCurrentPeriodUsageApiV1OrganizationsUsageCurrentPeriodGetResponse, GetDailyReportApiV1OrganizationsReportsDailyGetData, GetDailyReportApiV1OrganizationsReportsDailyGetError, GetDailyReportApiV1OrganizationsReportsDailyGetResponse, GetDailyRunsDetailApiV1OrganizationsReportsDailyRunsGetData, GetDailyRunsDetailApiV1OrganizationsReportsDailyRunsGetError, GetDailyRunsDetailApiV1OrganizationsReportsDailyRunsGetResponse, GetDailyUsageBreakdownApiV1OrganizationsUsageDailyBreakdownGetData, GetDailyUsageBreakdownApiV1OrganizationsUsageDailyBreakdownGetError, GetDailyUsageBreakdownApiV1OrganizationsUsageDailyBreakdownGetResponse, GetDefaultConfigurationsApiV1UserConfigurationsDefaultsGetData, GetDefaultConfigurationsApiV1UserConfigurationsDefaultsGetResponse, GetDocumentApiV1KnowledgeBaseDocumentsDocumentUuidGetData, GetDocumentApiV1KnowledgeBaseDocumentsDocumentUuidGetError, GetDocumentApiV1KnowledgeBaseDocumentsDocumentUuidGetResponse, GetEmbedConfigApiV1PublicEmbedConfigTokenGetData, GetEmbedConfigApiV1PublicEmbedConfigTokenGetError, GetEmbedConfigApiV1PublicEmbedConfigTokenGetResponse, GetEmbedTokenApiV1WorkflowWorkflowIdEmbedTokenGetData, GetEmbedTokenApiV1WorkflowWorkflowIdEmbedTokenGetError, GetEmbedTokenApiV1WorkflowWorkflowIdEmbedTokenGetResponse, GetFileMetadataApiV1S3FileMetadataGetData, GetFileMetadataApiV1S3FileMetadataGetError, GetFileMetadataApiV1S3FileMetadataGetResponse, GetIntegrationAccessTokenApiV1IntegrationIntegrationIdAccessTokenGetData, GetIntegrationAccessTokenApiV1IntegrationIntegrationIdAccessTokenGetError, GetIntegrationAccessTokenApiV1IntegrationIntegrationIdAccessTokenGetResponse, GetIntegrationsApiV1IntegrationGetData, GetIntegrationsApiV1IntegrationGetError, GetIntegrationsApiV1IntegrationGetResponse, GetLoadTestStatsApiV1LooptalkLoadTestsLoadTestGroupIdStatsGetData, GetLoadTestStatsApiV1LooptalkLoadTestsLoadTestGroupIdStatsGetError, GetLoadTestStatsApiV1LooptalkLoadTestsLoadTestGroupIdStatsGetResponse, GetPresignedUploadUrlApiV1S3PresignedUploadUrlPostData, GetPresignedUploadUrlApiV1S3PresignedUploadUrlPostError, GetPresignedUploadUrlApiV1S3PresignedUploadUrlPostResponse, GetServiceKeysApiV1UserServiceKeysGetData, GetServiceKeysApiV1UserServiceKeysGetError, GetServiceKeysApiV1UserServiceKeysGetResponse, GetSignedUrlApiV1S3SignedUrlGetData, GetSignedUrlApiV1S3SignedUrlGetError, GetSignedUrlApiV1S3SignedUrlGetResponse, GetTelephonyConfigurationApiV1OrganizationsTelephonyConfigGetData, GetTelephonyConfigurationApiV1OrganizationsTelephonyConfigGetError, GetTelephonyConfigurationApiV1OrganizationsTelephonyConfigGetResponse, GetTestSessionApiV1LooptalkTestSessionsTestSessionIdGetData, GetTestSessionApiV1LooptalkTestSessionsTestSessionIdGetError, GetTestSessionApiV1LooptalkTestSessionsTestSessionIdGetResponse, GetTestSessionConversationApiV1LooptalkTestSessionsTestSessionIdConversationGetData, GetTestSessionConversationApiV1LooptalkTestSessionsTestSessionIdConversationGetError, GetToolApiV1ToolsToolUuidGetData, GetToolApiV1ToolsToolUuidGetError, GetToolApiV1ToolsToolUuidGetResponse, GetUploadUrlApiV1KnowledgeBaseUploadUrlPostData, GetUploadUrlApiV1KnowledgeBaseUploadUrlPostError, GetUploadUrlApiV1KnowledgeBaseUploadUrlPostResponse, GetUsageHistoryApiV1OrganizationsUsageRunsGetData, GetUsageHistoryApiV1OrganizationsUsageRunsGetError, GetUsageHistoryApiV1OrganizationsUsageRunsGetResponse, GetUserConfigurationsApiV1UserConfigurationsUserGetData, GetUserConfigurationsApiV1UserConfigurationsUserGetError, GetUserConfigurationsApiV1UserConfigurationsUserGetResponse, GetVoicesApiV1UserConfigurationsVoicesProviderGetData, GetVoicesApiV1UserConfigurationsVoicesProviderGetError, GetVoicesApiV1UserConfigurationsVoicesProviderGetResponse, GetWorkflowApiV1WorkflowFetchWorkflowIdGetData, GetWorkflowApiV1WorkflowFetchWorkflowIdGetError, GetWorkflowApiV1WorkflowFetchWorkflowIdGetResponse, GetWorkflowCountApiV1WorkflowCountGetData, GetWorkflowCountApiV1WorkflowCountGetError, GetWorkflowCountApiV1WorkflowCountGetResponse, GetWorkflowOptionsApiV1OrganizationsReportsWorkflowsGetData, GetWorkflowOptionsApiV1OrganizationsReportsWorkflowsGetError, GetWorkflowOptionsApiV1OrganizationsReportsWorkflowsGetResponse, GetWorkflowRunApiV1WorkflowWorkflowIdRunsRunIdGetData, GetWorkflowRunApiV1WorkflowWorkflowIdRunsRunIdGetError, GetWorkflowRunApiV1WorkflowWorkflowIdRunsRunIdGetResponse, GetWorkflowRunsApiV1SuperuserWorkflowRunsGetData, GetWorkflowRunsApiV1SuperuserWorkflowRunsGetError, GetWorkflowRunsApiV1SuperuserWorkflowRunsGetResponse, GetWorkflowRunsApiV1WorkflowWorkflowIdRunsGetData, GetWorkflowRunsApiV1WorkflowWorkflowIdRunsGetError, GetWorkflowRunsApiV1WorkflowWorkflowIdRunsGetResponse, GetWorkflowsApiV1WorkflowFetchGetData, GetWorkflowsApiV1WorkflowFetchGetError, GetWorkflowsApiV1WorkflowFetchGetResponse, GetWorkflowsSummaryApiV1WorkflowSummaryGetData, GetWorkflowsSummaryApiV1WorkflowSummaryGetError, GetWorkflowsSummaryApiV1WorkflowSummaryGetResponse, GetWorkflowTemplatesApiV1WorkflowTemplatesGetData, GetWorkflowTemplatesApiV1WorkflowTemplatesGetResponse, HandleCloudonixStatusCallbackApiV1TelephonyCloudonixStatusCallbackWorkflowRunIdPostData, HandleCloudonixStatusCallbackApiV1TelephonyCloudonixStatusCallbackWorkflowRunIdPostError, HandleInboundFallbackApiV1TelephonyInboundFallbackPostData, HandleInboundTelephonyApiV1TelephonyInboundWorkflowIdPostData, HandleInboundTelephonyApiV1TelephonyInboundWorkflowIdPostError, HandleTwilioStatusCallbackApiV1TelephonyTwilioStatusCallbackWorkflowRunIdPostData, HandleTwilioStatusCallbackApiV1TelephonyTwilioStatusCallbackWorkflowRunIdPostError, HandleVobizHangupCallbackApiV1TelephonyVobizHangupCallbackWorkflowRunIdPostData, HandleVobizHangupCallbackApiV1TelephonyVobizHangupCallbackWorkflowRunIdPostError, HandleVobizHangupCallbackByWorkflowApiV1TelephonyVobizHangupCallbackWorkflowWorkflowIdPostData, HandleVobizHangupCallbackByWorkflowApiV1TelephonyVobizHangupCallbackWorkflowWorkflowIdPostError, HandleVobizRingCallbackApiV1TelephonyVobizRingCallbackWorkflowRunIdPostData, HandleVobizRingCallbackApiV1TelephonyVobizRingCallbackWorkflowRunIdPostError, HandleVonageEventsApiV1TelephonyVonageEventsWorkflowRunIdPostData, HandleVonageEventsApiV1TelephonyVonageEventsWorkflowRunIdPostError, HealthApiV1HealthGetData, HealthApiV1HealthGetResponse,ImpersonateApiV1SuperuserImpersonatePostData, ImpersonateApiV1SuperuserImpersonatePostError, ImpersonateApiV1SuperuserImpersonatePostResponse, InitializeEmbedSessionApiV1PublicEmbedInitPostData, InitializeEmbedSessionApiV1PublicEmbedInitPostError, InitializeEmbedSessionApiV1PublicEmbedInitPostResponse, InitiateCallApiV1PublicAgentUuidPostData, InitiateCallApiV1PublicAgentUuidPostError, InitiateCallApiV1PublicAgentUuidPostResponse, InitiateCallApiV1TelephonyInitiateCallPostData, InitiateCallApiV1TelephonyInitiateCallPostError, ListCredentialsApiV1CredentialsGetData, ListCredentialsApiV1CredentialsGetError, ListCredentialsApiV1CredentialsGetResponse, ListDocumentsApiV1KnowledgeBaseDocumentsGetData, ListDocumentsApiV1KnowledgeBaseDocumentsGetError, ListDocumentsApiV1KnowledgeBaseDocumentsGetResponse, ListTestSessionsApiV1LooptalkTestSessionsGetData, ListTestSessionsApiV1LooptalkTestSessionsGetError, ListTestSessionsApiV1LooptalkTestSessionsGetResponse, ListToolsApiV1ToolsGetData, ListToolsApiV1ToolsGetError, ListToolsApiV1ToolsGetResponse, OptionsConfigApiV1PublicEmbedConfigTokenOptionsData, OptionsConfigApiV1PublicEmbedConfigTokenOptionsError, OptionsInitApiV1PublicEmbedInitOptionsData, PauseCampaignApiV1CampaignCampaignIdPausePostData, PauseCampaignApiV1CampaignCampaignIdPausePostError, PauseCampaignApiV1CampaignCampaignIdPausePostResponse, ProcessDocumentApiV1KnowledgeBaseProcessDocumentPostData, ProcessDocumentApiV1KnowledgeBaseProcessDocumentPostError, ProcessDocumentApiV1KnowledgeBaseProcessDocumentPostResponse, ReactivateApiKeyApiV1UserApiKeysApiKeyIdReactivatePutData, ReactivateApiKeyApiV1UserApiKeysApiKeyIdReactivatePutError, ReactivateApiKeyApiV1UserApiKeysApiKeyIdReactivatePutResponse, ReactivateServiceKeyApiV1UserServiceKeysServiceKeyIdReactivatePutData, ReactivateServiceKeyApiV1UserServiceKeysServiceKeyIdReactivatePutError, ResumeCampaignApiV1CampaignCampaignIdResumePostData, ResumeCampaignApiV1CampaignCampaignIdResumePostError, ResumeCampaignApiV1CampaignCampaignIdResumePostResponse, SaveTelephonyConfigurationApiV1OrganizationsTelephonyConfigPostData, SaveTelephonyConfigurationApiV1OrganizationsTelephonyConfigPostError, SearchChunksApiV1KnowledgeBaseSearchPostData, SearchChunksApiV1KnowledgeBaseSearchPostError, SearchChunksApiV1KnowledgeBaseSearchPostResponse, SetAdminCommentApiV1SuperuserWorkflowRunsRunIdCommentPostData, SetAdminCommentApiV1SuperuserWorkflowRunsRunIdCommentPostError, SetAdminCommentApiV1SuperuserWorkflowRunsRunIdCommentPostResponse, StartCampaignApiV1CampaignCampaignIdStartPostData, StartCampaignApiV1CampaignCampaignIdStartPostError, StartCampaignApiV1CampaignCampaignIdStartPostResponse, StartTestSessionApiV1LooptalkTestSessionsTestSessionIdStartPostData, StartTestSessionApiV1LooptalkTestSessionsTestSessionIdStartPostError, StopTestSessionApiV1LooptalkTestSessionsTestSessionIdStopPostData, StopTestSessionApiV1LooptalkTestSessionsTestSessionIdStopPostError, UnarchiveToolApiV1ToolsToolUuidUnarchivePostData, UnarchiveToolApiV1ToolsToolUuidUnarchivePostError, UnarchiveToolApiV1ToolsToolUuidUnarchivePostResponse, UpdateCredentialApiV1CredentialsCredentialUuidPutData, UpdateCredentialApiV1CredentialsCredentialUuidPutError, UpdateCredentialApiV1CredentialsCredentialUuidPutResponse, UpdateIntegrationApiV1IntegrationIntegrationIdPutData, UpdateIntegrationApiV1IntegrationIntegrationIdPutError, UpdateIntegrationApiV1IntegrationIntegrationIdPutResponse, UpdateToolApiV1ToolsToolUuidPutData, UpdateToolApiV1ToolsToolUuidPutError, UpdateToolApiV1ToolsToolUuidPutResponse, UpdateUserConfigurationsApiV1UserConfigurationsUserPutData, UpdateUserConfigurationsApiV1UserConfigurationsUserPutError, UpdateUserConfigurationsApiV1UserConfigurationsUserPutResponse, UpdateWorkflowApiV1WorkflowWorkflowIdPutData, UpdateWorkflowApiV1WorkflowWorkflowIdPutError, UpdateWorkflowApiV1WorkflowWorkflowIdPutResponse, UpdateWorkflowStatusApiV1WorkflowWorkflowIdStatusPutData, UpdateWorkflowStatusApiV1WorkflowWorkflowIdStatusPutError, UpdateWorkflowStatusApiV1WorkflowWorkflowIdStatusPutResponse, ValidateUserConfigurationsApiV1UserConfigurationsUserValidateGetData, ValidateUserConfigurationsApiV1UserConfigurationsUserValidateGetError, ValidateUserConfigurationsApiV1UserConfigurationsUserValidateGetResponse, ValidateWorkflowApiV1WorkflowWorkflowIdValidatePostData, ValidateWorkflowApiV1WorkflowWorkflowIdValidatePostError, ValidateWorkflowApiV1WorkflowWorkflowIdValidatePostResponse } from './types.gen'; export type Options = ClientOptions & { /** @@ -251,9 +251,26 @@ export const createWorkflowFromTemplateApiV1WorkflowCreateTemplatePost = (options?: Options) => { + return (options?.client ?? _heyApiClient).get({ + url: '/api/v1/workflow/count', + ...options + }); +}; + /** * Get Workflows - * Get all workflows for the authenticated user's organization + * Get all workflows for the authenticated user's organization. + * + * Returns a lightweight response with only essential fields for listing. + * Use GET /workflow/fetch/{workflow_id} to get full workflow details. */ export const getWorkflowsApiV1WorkflowFetchGet = (options?: Options) => { return (options?.client ?? _heyApiClient).get({ @@ -1300,6 +1317,34 @@ export const initiateCallApiV1PublicAgentUuidPost = (options: Options) => { + return (options.client ?? _heyApiClient).get({ + url: '/api/v1/public/download/workflow/{token}/{artifact_type}', + ...options + }); +}; + /** * Deactivate Embed Token * Deactivate the embed token for a workflow. @@ -1461,7 +1506,7 @@ export const searchChunksApiV1KnowledgeBaseSearchPost = (options?: Options) => { - return (options?.client ?? _heyApiClient).get({ + return (options?.client ?? _heyApiClient).get({ url: '/api/v1/health', ...options }); diff --git a/ui/src/client/types.gen.ts b/ui/src/client/types.gen.ts index 9e1a028..cd1eeb9 100644 --- a/ui/src/client/types.gen.ts +++ b/ui/src/client/types.gen.ts @@ -524,6 +524,12 @@ export type HttpValidationError = { detail?: Array; }; +export type HealthResponse = { + status: string; + version: string; + backend_api_endpoint: string; +}; + /** * Configuration for HTTP API tools. */ @@ -1042,6 +1048,15 @@ export type VonageConfigurationResponse = { */ export type WebhookCredentialType = 'none' | 'api_key' | 'bearer_token' | 'basic_auth' | 'custom_header'; +/** + * Response for workflow count endpoint. + */ +export type WorkflowCountResponse = { + total: number; + active: number; + archived: number; +}; + export type WorkflowError = { kind: ItemKind; id: string | null; @@ -1049,6 +1064,17 @@ export type WorkflowError = { message: string; }; +/** + * Lightweight response for workflow listings (excludes large fields). + */ +export type WorkflowListResponse = { + id: number; + name: string; + status: string; + created_at: string; + total_runs: number; +}; + export type WorkflowOption = { id: number; name: string; @@ -1391,6 +1417,7 @@ export type HandleInboundTelephonyApiV1TelephonyInboundWorkflowIdPostData = { 'x-twilio-signature'?: string | null; 'x-vobiz-signature'?: string | null; 'x-vobiz-timestamp'?: string | null; + 'x-cx-apikey'?: string | null; }; path: { workflow_id: number; @@ -1655,6 +1682,39 @@ export type CreateWorkflowFromTemplateApiV1WorkflowCreateTemplatePostResponses = export type CreateWorkflowFromTemplateApiV1WorkflowCreateTemplatePostResponse = CreateWorkflowFromTemplateApiV1WorkflowCreateTemplatePostResponses[keyof CreateWorkflowFromTemplateApiV1WorkflowCreateTemplatePostResponses]; +export type GetWorkflowCountApiV1WorkflowCountGetData = { + body?: never; + headers?: { + authorization?: string | null; + 'X-API-Key'?: string | null; + }; + path?: never; + query?: never; + url: '/api/v1/workflow/count'; +}; + +export type GetWorkflowCountApiV1WorkflowCountGetErrors = { + /** + * Not found + */ + 404: unknown; + /** + * Validation Error + */ + 422: HttpValidationError; +}; + +export type GetWorkflowCountApiV1WorkflowCountGetError = GetWorkflowCountApiV1WorkflowCountGetErrors[keyof GetWorkflowCountApiV1WorkflowCountGetErrors]; + +export type GetWorkflowCountApiV1WorkflowCountGetResponses = { + /** + * Successful Response + */ + 200: WorkflowCountResponse; +}; + +export type GetWorkflowCountApiV1WorkflowCountGetResponse = GetWorkflowCountApiV1WorkflowCountGetResponses[keyof GetWorkflowCountApiV1WorkflowCountGetResponses]; + export type GetWorkflowsApiV1WorkflowFetchGetData = { body?: never; headers?: { @@ -1688,7 +1748,7 @@ export type GetWorkflowsApiV1WorkflowFetchGetResponses = { /** * Successful Response */ - 200: Array; + 200: Array; }; export type GetWorkflowsApiV1WorkflowFetchGetResponse = GetWorkflowsApiV1WorkflowFetchGetResponses[keyof GetWorkflowsApiV1WorkflowFetchGetResponses]; @@ -4168,6 +4228,41 @@ export type InitiateCallApiV1PublicAgentUuidPostResponses = { export type InitiateCallApiV1PublicAgentUuidPostResponse = InitiateCallApiV1PublicAgentUuidPostResponses[keyof InitiateCallApiV1PublicAgentUuidPostResponses]; +export type DownloadWorkflowArtifactApiV1PublicDownloadWorkflowTokenArtifactTypeGetData = { + body?: never; + path: { + token: string; + artifact_type: 'recording' | 'transcript'; + }; + query?: { + /** + * Display inline in browser instead of download + */ + inline?: boolean; + }; + url: '/api/v1/public/download/workflow/{token}/{artifact_type}'; +}; + +export type DownloadWorkflowArtifactApiV1PublicDownloadWorkflowTokenArtifactTypeGetErrors = { + /** + * Not found + */ + 404: unknown; + /** + * Validation Error + */ + 422: HttpValidationError; +}; + +export type DownloadWorkflowArtifactApiV1PublicDownloadWorkflowTokenArtifactTypeGetError = DownloadWorkflowArtifactApiV1PublicDownloadWorkflowTokenArtifactTypeGetErrors[keyof DownloadWorkflowArtifactApiV1PublicDownloadWorkflowTokenArtifactTypeGetErrors]; + +export type DownloadWorkflowArtifactApiV1PublicDownloadWorkflowTokenArtifactTypeGetResponses = { + /** + * Successful Response + */ + 200: unknown; +}; + export type DeactivateEmbedTokenApiV1WorkflowWorkflowIdEmbedTokenDeleteData = { body?: never; headers?: { @@ -4500,9 +4595,11 @@ export type HealthApiV1HealthGetResponses = { /** * Successful Response */ - 200: unknown; + 200: HealthResponse; }; +export type HealthApiV1HealthGetResponse = HealthApiV1HealthGetResponses[keyof HealthApiV1HealthGetResponses]; + export type ClientOptions = { baseUrl: 'http://127.0.0.1:8000' | (string & {}); }; diff --git a/ui/src/components/MediaPreviewDialog.tsx b/ui/src/components/MediaPreviewDialog.tsx index a463d48..fd406f2 100644 --- a/ui/src/components/MediaPreviewDialog.tsx +++ b/ui/src/components/MediaPreviewDialog.tsx @@ -22,6 +22,7 @@ export function MediaPreviewDialog({ accessToken }: MediaPreviewDialogProps) { const [isOpen, setIsOpen] = useState(false); const [mediaType, setMediaType] = useState<'audio' | 'transcript' | null>(null); const [mediaSignedUrl, setMediaSignedUrl] = useState(null); + const [transcriptContent, setTranscriptContent] = useState(null); const [selectedRunId, setSelectedRunId] = useState(null); const [mediaDownloadKey, setMediaDownloadKey] = useState(null); const [mediaLoading, setMediaLoading] = useState(false); @@ -47,6 +48,7 @@ export function MediaPreviewDialog({ accessToken }: MediaPreviewDialogProps) { async (fileKey: string | null, runId: number) => { if (!fileKey || !accessToken) return; setMediaLoading(true); + setTranscriptContent(null); const signed = await getSignedUrl(fileKey, accessToken, true); if (signed) { setMediaType('transcript'); @@ -54,6 +56,14 @@ export function MediaPreviewDialog({ accessToken }: MediaPreviewDialogProps) { setMediaDownloadKey(fileKey); setSelectedRunId(runId); setIsOpen(true); + // Fetch transcript content with proper UTF-8 encoding + try { + const response = await fetch(signed); + const text = await response.text(); + setTranscriptContent(text); + } catch (error) { + console.error('Error fetching transcript:', error); + } } setMediaLoading(false); }, @@ -84,12 +94,10 @@ export function MediaPreviewDialog({ accessToken }: MediaPreviewDialogProps) {