LangGraph Platform Quickstart

Get your agent deployed to LangGraph Platform in 2 minutes

Deploy in 3 Steps

1. Install CLI

   uv tool install langgraph-cli
   
2. Login to LangChain

   langgraph login
   

   This will prompt for your LangSmith API key. Get it from smith.langchain.com/settings.

3. Deploy

   langgraph deploy
   

   Your agent is now live on LangGraph Platform!

Deployment complete! Your agent is now running on LangGraph Platform with automatic scaling and built-in LangSmith tracing.

What Happens During Deployment

When you run langgraph deploy, the CLI:

1. Packages your code - Bundles your agent and dependencies
2. Uploads to platform - Securely transfers to LangGraph Platform
3. Provisions infrastructure - Creates serverless compute resources
4. Deploys your graph - Makes your agent available via API
5. Returns endpoint URL - Gives you the deployment URL

Test Your Deployment

Via CLI

langgraph deployment invoke my-agent \
  --input '{"messages": [{"role": "user", "content": "Hello!"}]}'

Via HTTP

curl -X POST https://your-deployment.langchain.com/invoke \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "input": {
      "messages": [{"role": "user", "content": "Hello!"}]
    }
  }'

Via Python SDK

from langgraph_sdk import get_client

client = get_client(url="https://your-deployment.langchain.com")
response = client.runs.stream(
    assistant_id="agent",
    input={"messages": [{"role": "user", "content": "Hello!"}]}
)

for chunk in response:
    print(chunk)

View Traces in LangSmith

All invocations are automatically traced in LangSmith:

1. Go to smith.langchain.com
2. Select your project
3. See all traces with full LLM details

Local Testing First

Test locally before deploying:

## Start local dev server
langgraph dev

## In another terminal, test
langgraph deployment invoke --local \
  --input '{"messages": [{"role": "user", "content": "Test"}]}'

Deployment Commands

Deploy with custom name

langgraph deploy my-agent-prod

Deploy with tag

langgraph deploy my-agent-prod --tag v1.0.0

List deployments

langgraph deployment list

View logs

langgraph deployment logs my-agent-prod --follow

Rollback

langgraph deployment rollback my-agent-prod --revision 3

Delete deployment

langgraph deployment delete my-agent-prod

Next Steps

Configuration

Configure your deployment settings

Secrets Management

Manage API keys and secrets

Monitoring

Monitor with LangSmith

CI/CD

Automate deployments

Troubleshooting

Login fails

Solution: Ensure you’re using a valid LangSmith API key from smith.langchain.com/settings.

# Re-login
langgraph logout
langgraph login

Deployment fails

Common causes:

• Missing dependencies in langgraph/requirements.txt
• Invalid langgraph.json configuration
• Graph import errors

Solution: Test locally first with langgraph dev

Graph not found error

Solution: Verify langgraph.json has correct graph path:

{
  "graphs": {
    "agent": "./langgraph/agent.py:graph"
  }
}

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Need help? Check the full deployment guide or visit LangChain docs.