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FastAPI LangGraph Agent Template

FastAPI LangGraph Agent Template is a Python repository for building FastAPI services around LangGraph AI agents, with components for stateful conversations, long-term memory, tool calling, authentication, rate limiting and observability.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

FastAPI LangGraph Agent Template — OpenViST project profile in Agent Frameworks.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it when developing an agent API that needs state, tools, memory or service-level monitoring and you intend to configure and run the backend yourself.

Who it is for

  • AI engineers building agent backends in Python
  • Developers who want a code foundation for a stateful, tool-using LangGraph service

Documented uses

  • Create a FastAPI endpoint layer for a LangGraph agent.
  • Maintain conversation state and checkpointing across interactions.
  • Add long-term semantic memory using mem0, PostgreSQL and pgvector.
  • Register LangChain tools with the agent.
  • Instrument LLM calls and service activity with tracing, metrics and structured logs.
Before you choose

Requirements & limits

The repository is public and MIT-licensed. Docker is recommended for the documented quick start but is not required; the README points to a local development setup.

  • The built-in LLMRegistry is described as supporting OpenAI; an OpenAI-compatible Atlas Cloud endpoint is documented as a configurable option.
  • Long-term memory uses self-hosted mem0 with PostgreSQL and pgvector, and requires an OpenAI API key for fact extraction and embeddings.
  • Docker Compose launches the API and PostgreSQL together; Valkey or Redis is an optional cache layer.
  • The repository includes a single agent by default and documents adding custom tools and additional graph nodes.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Start the API and PostgreSQL with Docker

Set up the template and launch its API and PostgreSQL services using the documented quick-start sequence.

Before you start

  • Docker and the repository
  • Configuration values and keys for the .env.development file

Steps

  1. Clone the repository into a working directory and change into it.

  2. Copy .env.example to .env.development and fill in the required keys.

  3. Run make install.

  4. Run make docker-up to start the API and PostgreSQL.

  5. Open http://localhost:8000/docs to view the interactive API documentation.

Expected outcome

The API and PostgreSQL are started through Docker, and the interactive API documentation is available at the documented local address.

Guide limitations

  • The guide documents startup, not successful execution of a particular agent task.
  • A local development path without Docker is linked separately in the repository documentation.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
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Sources checked
11 October 2026
Original website title
wassim249/fastapi-langgraph-agent-production-ready-template · Official homepage title · retained in its source language
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