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Deployment

Render

The project includes a render.yaml for one-click deployment to Render.

Services

Agent (Python):

  • Runtime: Python 3.12.6
  • Build: pip install uv && uv sync
  • Start: uv run uvicorn main:app --host 0.0.0.0 --port $PORT
  • Health check: GET /health
  • Root directory: apps/agent

Frontend (Node):

  • Runtime: Node 22
  • Build: corepack enable && pnpm install --no-frozen-lockfile && pnpm --filter @repo/app build
  • Start: pnpm --filter @repo/app start
  • Health check: GET /api/health
  • Root directory: (repo root)

Environment Variables

Variable Service Required Notes
OPENAI_API_KEY Agent Yes Your OpenAI API key
LLM_MODEL Agent No Defaults to gpt-5.4-2026-03-05
LANGSMITH_API_KEY Agent No For LangSmith tracing
LANGGRAPH_DEPLOYMENT_URL Frontend Auto Injected from agent service via fromService
SKIP_INSTALL_DEPS Frontend No Set to true to skip redundant installs

Auto-Scaling

Both services are configured with:

  • Min instances: 1
  • Max instances: 3
  • Memory target: 80%
  • CPU target: 70%

Deploy

  1. Fork the repository
  2. Create a new Blueprint on Render
  3. Connect your forked repo
  4. Add OPENAI_API_KEY as a secret
  5. Deploy

Render reads render.yaml and creates both services. The frontend automatically gets the agent URL via service discovery.

General Deployment

For other platforms, you need to deploy two services:

1. Agent (Python)

cd apps/agent
pip install uv
uv sync
uv run uvicorn main:app --host 0.0.0.0 --port 8123

Requirements:

  • Python 3.12+
  • OPENAI_API_KEY environment variable
  • Port exposed for the frontend to reach

2. Frontend (Node)

# From repo root
corepack enable
pnpm install
pnpm --filter @repo/app build
LANGGRAPH_DEPLOYMENT_URL=http://your-agent-host:8123 pnpm --filter @repo/app start

Requirements:

  • Node 22+
  • LANGGRAPH_DEPLOYMENT_URL pointing to the agent service
  • Port 3000 exposed

Health Checks

Service Endpoint Expected
Agent GET /health {"status": "ok"}
Frontend GET /api/health 200 OK

Docker

A Dockerfile for the frontend is available at docker/Dockerfile.app. The agent can be containerized with a standard Python Dockerfile using uv.

Next Steps