🤖 AI Chatbot Starter Kit

A FastAPI-based starter kit for building AI-powered chatbots with OpenAI (or similar) integration, streaming responses, and database persistence. This project provides a robust and scalable foundation for chatbot development, including optional tool calls via the MCP protocol.

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🚀 Overview

🔹 Key Features:

✅ FastAPI-powered REST API for managing Assistants, Chats, and Messages.
✅ PostgreSQL database integration with SQLModel & Alembic for persistence.
✅ Layered architecture separating repositories (data access) from services (business logic).
✅ Seamless OpenAI integration for chat completions and real-time streaming responses.
✅ MCP protocol support to enable external tool calls within conversations.

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🛠️ Core Features

🎯 Assistant Management

Effortlessly create, retrieve, and list AI chat assistants with specific configurations tailored to your needs.

💬 Chat Management

Start new chat sessions, retrieve past conversations, and handle streaming responses from the LLM.

🧠 LLM Integration

Leverage OpenAI (or other compatible LLM services) to power your chatbot with high-quality, context-aware responses.

🛎️ Tool Integration via MCP

Extend your chatbot's functionality by integrating external tools that can be invoked dynamically during interactions.

📦 Database Management

Store and manage chat data, messages, summaries, and assistant configurations using PostgreSQL.

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⚙️ Configuration

This project uses pydantic_settings for managing configurations, loaded via environment variables from a .env file.

🔑 Required Environment Variables:

OPENAI_API_KEY=sk-xxxxxx
MCP_SERVER_COMMAND=uv
MCP_SERVER_ARGS=["run","mcp.servers.example.py"]  
POSTGRES_USER=myuser
POSTGRES_PASSWORD=mysecretpassword
POSTGRES_HOST=localhost
POSTGRES_DB=mydb
POSTGRES_PORT=5432

These variables are automatically wired at startup using Container in container.py.

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🚀 Getting Started

1️⃣ Clone the repository

git clone https://github.com/your-repo/ai-chatbot-starter-kit.git
cd ai-chatbot-starter-kit

2️⃣ Create a virtual environment & install dependencies

uv sync

3️⃣ Set up environment variables Create a .env file in the project root and configure it as shown above.

4️⃣ Run database migrations First you need to spin up the database

docker compose up

Then run the migrations

alembic upgrade head

5️⃣ Start the FastAPI application

uvicorn app.main:app --reload

6️⃣ Access the API documentation FastAPI provides interactive API documentation available at:

• Swagger UI: http://localhost:8000/docs
• Redoc: http://localhost:8000/redoc

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📌 Contributing

Contributions are welcome! Feel free to fork this repo, create a feature branch, and submit a pull request.

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🏆 Credits

Developed and maintained by GonzaData.

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📜 License

This project is licensed under the MIT License. See the LICENSE file for details.

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