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No local Python or Node.js required — everything is built inside the container. 
git clone https://github.com/fim-ai/fim-agent.git
cd fim-agent

# Configure — only LLM_API_KEY is required
cp example.env .env
# Edit .env: set LLM_API_KEY (and optionally LLM_BASE_URL, LLM_MODEL)

# Build and run (first time, or after pulling new code)
docker compose up --build -d
Open http://localhost:3000 — on first launch you’ll be guided through creating an admin account. That’s it. After the initial build, subsequent starts only need: 
docker compose up -d          # start (skip rebuild if image unchanged)
docker compose down           # stop
docker compose logs -f        # view logs
Data is persisted in Docker named volumes (fim-data, fim-uploads) and survives container restarts. Note: Docker mode does not support hot reload. Code changes require rebuilding the image (docker compose up --build -d). For active development with live reload, use Option B below.

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Option B: Local Development

Prerequisites: Python 3.11+, uv, Node.js 18+, pnpm. 
git clone https://github.com/fim-ai/fim-agent.git
cd fim-agent

cp example.env .env
# Edit .env: set LLM_API_KEY

# Install
uv sync --all-extras
cd frontend && pnpm install && cd ..

# Launch (with hot reload)
./start.sh
CommandWhat startsURL
./start.shNext.js + FastAPIhttp://localhost:3000 (UI) + :8000 (API)
./start.sh devSame, with hot reload (Python --reload + Next.js HMR)Same
./start.sh apiFastAPI only (headless, for integration or testing)http://localhost:8000/api

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Configuration

FIM Agent works with any OpenAI-compatible LLM provider — OpenAI, DeepSeek, Anthropic, Qwen, Ollama, vLLM, and more.
ProviderLLM_API_KEYLLM_BASE_URLLLM_MODEL
OpenAIsk-...(default)gpt-4o
DeepSeeksk-...https://api.deepseek.com/v1deepseek-chat
Anthropicsk-ant-...https://api.anthropic.com/v1claude-sonnet-4-6
Ollama (local)ollamahttp://localhost:11434/v1qwen2.5:14b
Jina AI unlocks web search/fetch, embedding, and the full RAG pipeline (free tier available). Minimal .env: 
LLM_API_KEY=sk-your-key
# LLM_BASE_URL=https://api.openai.com/v1   # default — change for other providers
# LLM_MODEL=gpt-4o                         # default — change for other models

JINA_API_KEY=jina_...                       # unlocks web tools + RAG
For a complete list of all configuration options, see the Environment Variables reference.

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Production Deployment

Both options work in production:
MethodCommandBest for
Dockerdocker compose up -dHands-off deployment, easy updates
Script./start.shBare-metal servers, custom process managers
For either method, put an Nginx reverse proxy in front for HTTPS and custom domain: 
User → Nginx (443/HTTPS) → localhost:3000
The API runs internally on port 8000 — Next.js proxies /api/* requests automatically. Only port 3000 needs to be exposed. If you use the code execution sandbox (CODE_EXEC_BACKEND=docker), mount the Docker socket: 
# docker-compose.yml
volumes:
  - /var/run/docker.sock:/var/run/docker.sock