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971b4ea | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 | # 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
```
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