LangGraph OpenAI Serve

Serve LangGraph graphs through an OpenAI-compatible /v1 API so existing OpenAI SDKs, Chainlit, Open WebUI, and similar clients can call them without a project-specific protocol.

Install

uv add langgraph-openai-serve
# or
pip install langgraph-openai-serve

The package contains the OpenAI-compatible server integration, not a built-in LLM graph. Applications register their own graphs; repository demo graph dependencies are kept in the demo dependency group.

Quick Demo

From this repository:

docker compose up -d postgres
make run-demo-api

Then call the demo with the OpenAI Python client:

from openai import OpenAI

client = OpenAI(base_url="http://localhost:8000/v1", api_key="DUMMY")

response = client.chat.completions.create(
    model="custom-input-output-context",
    messages=[{"role": "user", "content": "Show me custom schemas."}],
    user="demo-user",
)

print(response.choices[0].message.content)

Use curl http://localhost:8000/v1/models only as a diagnostic to inspect the registered demo graph names.

Use In FastAPI

from fastapi import FastAPI
from langgraph_openai_serve import GraphConfig, GraphRegistry, LanggraphOpenaiServe
from your_graphs import my_graph

app = FastAPI()
graphs = GraphRegistry(
    registry={
        "my-graph": GraphConfig(
            graph=my_graph,
            streamable_node_names=["generate"],
        )
    }
)

LanggraphOpenaiServe(app=app, graphs=graphs).bind_openai_api()

The default base URL is {host}/v1. Register graph names become OpenAI model values.

Docs

• Start here: docs/index.md
• Runnable demo: docs/tutorials/getting-started.md
• OpenAI clients: docs/tutorials/openai-clients.md
• Custom graphs: docs/tutorials/custom-graphs.md
• API and configuration: docs/reference.md
• Compatibility contract: docs/explanation/openai-compatibility.md