README.md

# FastAPI RAG Chatbot Backend

This project implements a FastAPI backend for a Retrieval-Augmented Generation (RAG) chatbot. It integrates with OpenAI for chat completions and embeddings, Neon Serverless Postgres for persistent data, and Qdrant Cloud for vector storage.

## Project Structure

```
backend/
├── app/
│   ├── __init__.py
│   ├── main.py
│   ├── config.py
│   ├── database.py
│   ├── qdrant_client.py
│   ├── models/
│   │   ├── __init__.py
│   │   ├── user.py
│   │   └── chat.py
│   ├── schemas/
│   │   ├── __init__.py
│   │   └── chat.py
│   ├── routes/
│   │   ├── __init__.py
│   │   ├── chat.py
│   │   └── health.py
│   └── services/
│       ├── __init__.py
│       ├── rag_service.py
│       ├── embeddings_service.py
│       └── openai_service.py
├── scripts/
│   └── ingest_content.py
├── .env.example
├── requirements.txt
├── README.md
└── .gitignore
```

## Setup Instructions

1.  **Clone the repository**:

    ```bash
    git clone <repository-url>
    cd robotic
    ```

2.  **Navigate to the backend directory**:

    ```bash
    cd backend
    ```

3.  **Set up the Python virtual environment and install dependencies**:

    On Windows, run:
    ```bash
    .\setup.bat
    ```

    On Linux/macOS, run:
    ```bash
    python3 -m venv venv
    source venv/bin/activate
    pip install -r requirements.txt
    ```

4.  **Configure Environment Variables**:

    Create a `.env` file in the `backend/` directory by copying `.env.example` and filling in your credentials:

    ```bash
    copy .env.example .env
    # or for Linux/macOS
    cp .env.example .env
    ```

    Edit the `.env` file with your actual API keys and database URLs:

    ```
    OPENAI_API_KEY=your_openai_api_key_here
    NEON_DATABASE_URL=your_neon_postgres_connection_string_here
    QDRANT_URL=your_qdrant_cluster_url_here
    QDRANT_API_KEY=your_qdrant_api_key_here
    ```

## Running the Application

1.  **Activate your virtual environment**:

    On Windows:
    ```bash
    .\venv\Scripts\activate
    ```

    On Linux/macOS:
    ```bash
    source venv/bin/activate
    ```

2.  **Start the FastAPI server**:

    On Windows, run:
    ```bash
    .\run.bat
    ```

    On Linux/macOS, run:
    ```bash
    uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload
    ```

    The API will be accessible at `http://localhost:8000`.

## API Endpoints

*(Note: Detailed API documentation will be available at `/docs` once the server is running)*

### Health Check

-   **GET `/health`**
    -   Returns the health status of the backend and its integrated services.

### Chatbot Interaction

-   **POST `/chat/`**
    -   **Description**: Sends a user query to the RAG chatbot and receives a generated response.
    -   **Request Body Example**:

        ```json
        {
            "query": "What is the main topic of the book?"
        }
        ```
    -   **Response Body Example**:

        ```json
        {
            "response": "The main topic of the book is ..."
        }
        ```

## Content Ingestion Script

-   **`scripts/ingest_content.py`**
    -   This script is responsible for reading MDX files from `../physical-ai-humanoid-robotics/docs/`, chunking the text, generating OpenAI embeddings, and storing them in Qdrant.
    -   **Usage**:

        ```bash
        python scripts/ingest_content.py
        ```