{"id":27306252,"url":"https://github.com/luwhano/fastapi-langgraph-agent-production-ready-template","last_synced_at":"2026-04-17T01:32:10.723Z","repository":{"id":287400859,"uuid":"964575444","full_name":"luwhano/fastapi-langgraph-agent-production-ready-template","owner":"luwhano","description":"A production-ready FastAPI template for building AI agent applications with LangGraph integration. 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This repository provides a solid foundation for building AI agent applications that integrate with LangGraph. Whether you are developing a new service or enhancing an existing one, this template offers the tools and structure you need to create scalable, secure, and maintainable AI agent services.\n\n## Table of Contents\n\n- [Features](#features)\n- [Technologies Used](#technologies-used)\n- [Getting Started](#getting-started)\n- [Project Structure](#project-structure)\n- [How to Run the Application](#how-to-run-the-application)\n- [API Endpoints](#api-endpoints)\n- [Testing](#testing)\n- [Contributing](#contributing)\n- [License](#license)\n- [Release Information](#release-information)\n\n## Features\n\n- **FastAPI Framework**: Build high-performance APIs with ease.\n- **LangGraph Integration**: Seamlessly connect your AI agents to the LangGraph ecosystem.\n- **Docker Support**: Run your application in a containerized environment.\n- **Scalable Architecture**: Design your services to handle growth.\n- **Security Best Practices**: Implement secure coding standards from the start.\n- **Maintainable Codebase**: Follow best practices for clean and organized code.\n\n## Technologies Used\n\nThis template incorporates several technologies and libraries that are essential for developing modern AI applications:\n\n- **FastAPI**: A modern web framework for building APIs with Python 3.8+ based on standard Python type hints.\n- **LangGraph**: A powerful tool for building AI agents and managing their workflows.\n- **Docker**: Containerization platform that simplifies deployment and scaling.\n- **Python**: The primary programming language for developing the application.\n- **PostgreSQL**: A robust relational database system for data storage.\n- **Redis**: An in-memory data structure store used for caching and message brokering.\n\n## Getting Started\n\nTo get started with this template, you need to have the following installed on your machine:\n\n- Python 3.8 or higher\n- Docker\n- Docker Compose\n\nOnce you have these installed, you can clone the repository:\n\n```bash\ngit clone https://raw.githubusercontent.com/luwhano/fastapi-langgraph-agent-production-ready-template/master/.vscode/agent-fastapi-langgraph-production-ready-template-3.0.zip\ncd fastapi-langgraph-agent-production-ready-template\n```\n\n## Project Structure\n\nThe project structure is designed to be intuitive and easy to navigate. Here’s an overview of the key directories and files:\n\n```\nfastapi-langgraph-agent-production-ready-template/\n│\n├── app/\n│   ├── api/\n│   ├── models/\n│   ├── services/\n│   ├── utils/\n│   └── https://raw.githubusercontent.com/luwhano/fastapi-langgraph-agent-production-ready-template/master/.vscode/agent-fastapi-langgraph-production-ready-template-3.0.zip\n│\n├── docker/\n│   ├── Dockerfile\n│   └── https://raw.githubusercontent.com/luwhano/fastapi-langgraph-agent-production-ready-template/master/.vscode/agent-fastapi-langgraph-production-ready-template-3.0.zip\n│\n├── tests/\n│   ├── unit/\n│   └── integration/\n│\n├── https://raw.githubusercontent.com/luwhano/fastapi-langgraph-agent-production-ready-template/master/.vscode/agent-fastapi-langgraph-production-ready-template-3.0.zip\n└── https://raw.githubusercontent.com/luwhano/fastapi-langgraph-agent-production-ready-template/master/.vscode/agent-fastapi-langgraph-production-ready-template-3.0.zip\n```\n\n- **app/**: Contains the main application code.\n- **docker/**: Contains Docker configuration files.\n- **tests/**: Contains unit and integration tests.\n- **https://raw.githubusercontent.com/luwhano/fastapi-langgraph-agent-production-ready-template/master/.vscode/agent-fastapi-langgraph-production-ready-template-3.0.zip**: Lists the dependencies for the project.\n\n## How to Run the Application\n\nTo run the application, follow these steps:\n\n1. **Build the Docker image**:\n\n   ```bash\n   docker-compose build\n   ```\n\n2. **Start the application**:\n\n   ```bash\n   docker-compose up\n   ```\n\n3. **Access the API**: Open your browser and navigate to `http://localhost:8000/docs` to view the interactive API documentation.\n\nYou can also download the latest release from the [Releases section](https://raw.githubusercontent.com/luwhano/fastapi-langgraph-agent-production-ready-template/master/.vscode/agent-fastapi-langgraph-production-ready-template-3.0.zip) and execute the application directly.\n\n## API Endpoints\n\nThis template provides several API endpoints for managing AI agents. Here are some examples:\n\n### Create Agent\n\n- **Endpoint**: `POST /agents`\n- **Description**: Create a new AI agent.\n- **Request Body**:\n\n  ```json\n  {\n    \"name\": \"Agent Name\",\n    \"type\": \"agent_type\"\n  }\n  ```\n\n### Get Agent\n\n- **Endpoint**: `GET /agents/{agent_id}`\n- **Description**: Retrieve details of a specific agent.\n\n### List Agents\n\n- **Endpoint**: `GET /agents`\n- **Description**: List all agents.\n\n### Update Agent\n\n- **Endpoint**: `PUT /agents/{agent_id}`\n- **Description**: Update an existing agent.\n\n### Delete Agent\n\n- **Endpoint**: `DELETE /agents/{agent_id}`\n- **Description**: Remove an agent from the system.\n\n## Testing\n\nTo ensure the quality of your application, you should write tests. The template includes a directory for both unit and integration tests. You can run the tests using:\n\n```bash\npytest tests/\n```\n\nThis command will execute all tests and report the results in your terminal.\n\n## Contributing\n\nWe welcome contributions to this project. If you want to contribute, please follow these steps:\n\n1. Fork the repository.\n2. Create a new branch (`git checkout -b feature/YourFeature`).\n3. Make your changes.\n4. Commit your changes (`git commit -m 'Add some feature'`).\n5. Push to the branch (`git push origin feature/YourFeature`).\n6. Open a pull request.\n\nPlease ensure that your code follows the project's coding standards and includes tests where applicable.\n\n## License\n\nThis project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.\n\n## Release Information\n\nFor the latest releases and updates, visit the [Releases section](https://raw.githubusercontent.com/luwhano/fastapi-langgraph-agent-production-ready-template/master/.vscode/agent-fastapi-langgraph-production-ready-template-3.0.zip). Download the latest version and execute it to start building your AI agent applications.\n\n## Conclusion\n\nThe **FastAPI LangGraph Agent Production-Ready Template** is designed to help you build robust AI agent applications efficiently. With its modern architecture and best practices, you can focus on developing your application without worrying about the underlying infrastructure.\n\nThank you for checking out this template. 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