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Deployment

Render (Frontend Only)

The project includes a render.yaml that deploys the frontend to Render. The agent is deployed separately — see LangGraph Platform below.

Frontend Service (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

Environment Variables

Variable Required Notes
LANGGRAPH_DEPLOYMENT_URL Yes URL of your LangGraph agent (e.g., https://<id>.default.us.langgraph.app)
LANGSMITH_API_KEY Yes* Required when agent is on LangGraph Platform (sent as x-api-key)
RATE_LIMIT_ENABLED No Set to true to enable per-IP rate limiting
RATE_LIMIT_WINDOW_MS No Rate limit window in ms (default: 60000)
RATE_LIMIT_MAX No Max requests per window (default: 40)
SKIP_INSTALL_DEPS No Set to true to skip redundant installs

*Not required if the agent is self-hosted on a private network without auth.

Deploy

  1. Fork the repository
  2. Create a new Blueprint on Render
  3. Connect your forked repo
  4. In the Render dashboard, set LANGGRAPH_DEPLOYMENT_URL to your agent's URL
  5. Set LANGSMITH_API_KEY to your LangSmith API key
  6. Deploy

Render reads render.yaml and creates the frontend service.

LangGraph Platform (LangSmith Cloud)

The agent can be deployed as a managed service on LangGraph Platform using the langgraph deploy CLI. The platform provides built-in Postgres persistence, tracing, streaming, and auto-scaling.

Prerequisites

  • A LangSmith account (Plus plan or higher)
  • LangSmith API key (LANGSMITH_API_KEY)
  • The langgraph CLI: pip install langgraph-cli
  • Docker installed and running (Apple Silicon users need Docker Buildx)

Deploy

cd apps/agent
langgraph deploy --name open-generative-ui-agent

The CLI reads langgraph.json, builds a Docker image, and pushes it to the managed registry. Auth is via LANGSMITH_API_KEY env var or --api-key flag.

After deployment, configure environment variables in the LangSmith dashboard:

Variable Required Notes
OPENAI_API_KEY Yes Your OpenAI API key
LANGGRAPH_CLOUD Yes Set to true — skips local checkpointer in favor of platform-managed Postgres
LLM_MODEL No Defaults to gpt-5.4-2026-03-05
LANGCHAIN_TRACING_V2 No Set to true for built-in tracing
LANGCHAIN_PROJECT No Project name for organizing traces

Note the deployment URL (e.g., https://<id>.default.us.langgraph.app).

Other CLI Commands

Command Description
langgraph deploy list List all deployments
langgraph deploy logs Fetch runtime or build logs
langgraph deploy revisions list <id> Show revision history
langgraph dev Local dev server (no Docker)

Split Deployment: Render + LangGraph Platform

The recommended production setup runs the frontend on Render and the agent on LangGraph Platform. This gives you managed scaling and Postgres persistence for the agent, with familiar Node hosting for the frontend.

Architecture

┌──────────────────────┐       HTTPS + x-api-key       ┌─────────────────────────┐
│  Render (Frontend)   │  ──────────────────────────▶  │  LangGraph Platform     │
│  Next.js on Node 22  │                               │  (LangSmith Cloud)      │
│  /api/copilotkit     │  ◀──────────────────────────  │  Python agent           │
└──────────────────────┘       SSE / streaming          └─────────────────────────┘

Step-by-Step

  1. Deploy the agent on LangGraph Platform:

    cd apps/agent
langgraph deploy --name open-generative-ui-agent

    Then set OPENAI_API_KEY and LANGGRAPH_CLOUD=true in the LangSmith dashboard. Note the deployment URL.

  2. Deploy the frontend on Render following the Render section. In the Render dashboard, set:

    • LANGGRAPH_DEPLOYMENT_URL = your LangGraph Platform URL (e.g., https://<id>.default.us.langgraph.app)
    • LANGSMITH_API_KEY = your LangSmith API key (starts with lsv2_)

  3. Verify by hitting GET /api/health on the frontend and sending a test message through the UI.

How Auth Works

The frontend's API route (/api/copilotkit) reads LANGSMITH_API_KEY from the environment and sends it as an x-api-key header on every request to the agent. LangGraph Platform validates this key. The API key is never exposed to the browser — it stays server-side in the Next.js API route.

Self-Hosted vs. LangGraph Platform

Concern Self-Hosted LangGraph Platform
Checkpointer BoundedMemorySaver (in-memory) Managed Postgres (automatic)
HTTP serving FastAPI + uvicorn Platform-managed
Health checks /health endpoint Platform-managed
Tracing Optional (LANGSMITH_API_KEY) Built-in
Scaling Manual / render.yaml Platform-managed
Auth None (private network) LANGSMITH_API_KEY required

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