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fix: Added API_BASE param for LiteLLM.

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DESKTOP-RTLN3BA\$punk 2025-05-08 19:31:47 -07:00
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113
surfsense_web/content/docs/docker-installation.mdx
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@ -1,8 +1,9 @@
---
title: Docker Installation
description: Setting up SurfSense using Docker
description: Setting up SurfSense using Docker
full: true
---
## Known Limitations
⚠️ **Important Note:** Currently, the following features have limited functionality when running in Docker:
@ -12,8 +13,7 @@ full: true
We're actively working to resolve these limitations in future releases.
# Docker Installation
# Docker Installation
This guide explains how to run SurfSense using Docker Compose, which is the preferred and recommended method for deployment.
@ -32,23 +32,26 @@ Before you begin, ensure you have:
## Installation Steps
1. **Configure Environment Variables**
Set up the necessary environment variables:
**Linux/macOS:**
```bash
# Copy example environment files
cp surfsense_backend/.env.example surfsense_backend/.env
cp surfsense_web/.env.example surfsense_web/.env
```
**Windows (Command Prompt):**
```cmd
copy surfsense_backend\.env.example surfsense_backend\.env
copy surfsense_web\.env.example surfsense_web\.env
```
**Windows (PowerShell):**
```powershell
Copy-Item -Path surfsense_backend\.env.example -Destination surfsense_backend\.env
Copy-Item -Path surfsense_web\.env.example -Destination surfsense_web\.env
@ -58,47 +61,65 @@ Before you begin, ensure you have:
**Backend Environment Variables:**
| ENV VARIABLE | DESCRIPTION |
|--------------|-------------|
| DATABASE_URL | PostgreSQL connection string (e.g., `postgresql+asyncpg://postgres:postgres@localhost:5432/surfsense`) |
| SECRET_KEY | JWT Secret key for authentication (should be a secure random string) |
| GOOGLE_OAUTH_CLIENT_ID | Google OAuth client ID obtained from Google Cloud Console |
| GOOGLE_OAUTH_CLIENT_SECRET | Google OAuth client secret obtained from Google Cloud Console |
| NEXT_FRONTEND_URL | URL where your frontend application is hosted (e.g., `http://localhost:3000`) |
| EMBEDDING_MODEL | Name of the embedding model (e.g., `openai://text-embedding-ada-002`, `anthropic://claude-v1`, `mixedbread-ai/mxbai-embed-large-v1`) |
| RERANKERS_MODEL_NAME | Name of the reranker model (e.g., `ms-marco-MiniLM-L-12-v2`) |
| RERANKERS_MODEL_TYPE | Type of reranker model (e.g., `flashrank`) |
| FAST_LLM | LiteLLM routed smaller, faster LLM (e.g., `openai/gpt-4o-mini`, `ollama/deepseek-r1:8b`) |
| STRATEGIC_LLM | LiteLLM routed advanced LLM for complex tasks (e.g., `openai/gpt-4o`, `ollama/gemma3:12b`) |
| LONG_CONTEXT_LLM | LiteLLM routed LLM for longer context windows (e.g., `gemini/gemini-2.0-flash`, `ollama/deepseek-r1:8b`) |
| UNSTRUCTURED_API_KEY | API key for Unstructured.io service for document parsing |
| FIRECRAWL_API_KEY | API key for Firecrawl service for web crawling |
| TTS_SERVICE | Text-to-Speech API provider for Podcasts (e.g., `openai/tts-1`, `azure/neural`, `vertex_ai/`). See [supported providers](https://docs.litellm.ai/docs/text_to_speech#supported-providers) |
| ENV VARIABLE | DESCRIPTION |
| -------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| DATABASE_URL | PostgreSQL connection string (e.g., `postgresql+asyncpg://postgres:postgres@localhost:5432/surfsense`) |
| SECRET_KEY | JWT Secret key for authentication (should be a secure random string) |
| GOOGLE_OAUTH_CLIENT_ID | Google OAuth client ID obtained from Google Cloud Console |
| GOOGLE_OAUTH_CLIENT_SECRET | Google OAuth client secret obtained from Google Cloud Console |
| NEXT_FRONTEND_URL | URL where your frontend application is hosted (e.g., `http://localhost:3000`) |
| EMBEDDING_MODEL | Name of the embedding model (e.g., `openai://text-embedding-ada-002`, `anthropic://claude-v1`, `mixedbread-ai/mxbai-embed-large-v1`) |
| RERANKERS_MODEL_NAME | Name of the reranker model (e.g., `ms-marco-MiniLM-L-12-v2`) |
| RERANKERS_MODEL_TYPE | Type of reranker model (e.g., `flashrank`) |
| FAST_LLM | LiteLLM routed smaller, faster LLM (e.g., `openai/gpt-4o-mini`, `ollama/deepseek-r1:8b`) |
| STRATEGIC_LLM | LiteLLM routed advanced LLM for complex tasks (e.g., `openai/gpt-4o`, `ollama/gemma3:12b`) |
| LONG_CONTEXT_LLM | LiteLLM routed LLM for longer context windows (e.g., `gemini/gemini-2.0-flash`, `ollama/deepseek-r1:8b`) |
| UNSTRUCTURED_API_KEY | API key for Unstructured.io service for document parsing |
| FIRECRAWL_API_KEY | API key for Firecrawl service for web crawling |
| TTS_SERVICE | Text-to-Speech API provider for Podcasts (e.g., `openai/tts-1`, `azure/neural`, `vertex_ai/`). See [supported providers](https://docs.litellm.ai/docs/text_to_speech#supported-providers) |
Include API keys for the LLM providers you're using. For example:
- `OPENAI_API_KEY`: If using OpenAI models
- `GEMINI_API_KEY`: If using Google Gemini models
For other LLM providers, refer to the [LiteLLM documentation](https://docs.litellm.ai/docs/providers).
Include API keys for the LLM providers you're using. For example:
**Frontend Environment Variables:**
- `OPENAI_API_KEY`: If using OpenAI models
- `GEMINI_API_KEY`: If using Google Gemini models
| ENV VARIABLE | DESCRIPTION |
|--------------|-------------|
| NEXT_PUBLIC_FASTAPI_BACKEND_URL | URL of the backend service (e.g., `http://localhost:8000`) |
**Optional LangSmith Observability:**
| ENV VARIABLE | DESCRIPTION |
|--------------|-------------|
| LANGSMITH_TRACING | Enable LangSmith tracing (e.g., `true`) |
| LANGSMITH_ENDPOINT | LangSmith API endpoint (e.g., `https://api.smith.langchain.com`) |
| LANGSMITH_API_KEY | Your LangSmith API key |
| LANGSMITH_PROJECT | LangSmith project name (e.g., `surfsense`) |
**Optional LiteLLM API Base URLs:**
| ENV VARIABLE | DESCRIPTION |
|--------------|-------------|
| FAST_LLM_API_BASE | Custom API base URL for the fast LLM |
| STRATEGIC_LLM_API_BASE | Custom API base URL for the strategic LLM |
| LONG_CONTEXT_LLM_API_BASE | Custom API base URL for the long context LLM |
For other LLM providers, refer to the [LiteLLM documentation](https://docs.litellm.ai/docs/providers).
**Frontend Environment Variables:**
| ENV VARIABLE | DESCRIPTION |
| ------------------------------- | ---------------------------------------------------------- |
| NEXT_PUBLIC_FASTAPI_BACKEND_URL | URL of the backend service (e.g., `http://localhost:8000`) |
2. **Build and Start Containers**
Start the Docker containers:
**Linux/macOS/Windows:**
```bash
docker-compose up --build
```
To run in detached mode (in the background):
**Linux/macOS/Windows:**
```bash
docker-compose up -d
```
@ -106,8 +127,9 @@ Before you begin, ensure you have:
**Note for Windows users:** If you're using older Docker Desktop versions, you might need to use `docker compose` (with a space) instead of `docker-compose`.
3. **Access the Applications**
Once the containers are running, you can access:
- Frontend: [http://localhost:3000](http://localhost:3000)
- Backend API: [http://localhost:8000](http://localhost:8000)
- API Documentation: [http://localhost:8000/docs](http://localhost:8000/docs)
@ -117,19 +139,21 @@ Before you begin, ensure you have:
### Container Management
- **Stop containers:**
**Linux/macOS/Windows:**
```bash
docker-compose down
```
- **View logs:**
**Linux/macOS/Windows:**
```bash
# All services
docker-compose logs -f
# Specific service
docker-compose logs -f backend
docker-compose logs -f frontend
@ -137,19 +161,21 @@ Before you begin, ensure you have:
```
- **Restart a specific service:**
**Linux/macOS/Windows:**
```bash
docker-compose restart backend
```
- **Execute commands in a running container:**
**Linux/macOS/Windows:**
```bash
# Backend
docker-compose exec backend python -m pytest
# Frontend
docker-compose exec frontend pnpm lint
```
@ -163,7 +189,6 @@ Before you begin, ensure you have:
- For frontend dependency issues, check the `Dockerfile` in the frontend directory.
- **Windows-specific:** If you encounter line ending issues (CRLF vs LF), configure Git to handle line endings properly with `git config --global core.autocrlf true` before cloning the repository.
## Next Steps
Once your installation is complete, you can start using SurfSense! Navigate to the frontend URL and log in using your Google account.
Once your installation is complete, you can start using SurfSense! Navigate to the frontend URL and log in using your Google account.