README.md

---
title: Gemma AI Assistant
emoji: 🤖
colorFrom: indigo
colorTo: purple
sdk: docker
sdk_version: "1.0"
app_file: app.py
pinned: false
---

# Gemma AI Assistant Space

This Space hosts the backend API for the Gemma AI Assistant, a conversational AI that combines local LLM processing using HuggingFace Transformers and real-time chat capabilities with Google's Gemini API.

## Features

- FastAPI backend with async support
- Local LLM using `mradermacher/Huihui-gemma-3n-E4B-it-abliterated-GGUF`
- Gemini API integration for real-time chat
- Supabase integration for data persistence
- Containerized deployment

## API Endpoints

### POST /api/chat
Process chat messages using either the local LLM or Gemini API.

**Request Body:**
```json
{
  "messages": [
    {
      "role": "user",
      "content": "Hello, how are you?"
    }
  ],
  "use_gemini": true,
  "temperature": 0.7
}
```

**Response:**
```json
{
  "response": "I'm doing well, thank you! How can I help you today?"
}
```

## Environment Variables Required

- `GOOGLE_AI_STUDIO_KEY`: Your Google AI Studio API key
- `SUPABASE_URL`: Your Supabase project URL
- `SUPABASE_SERVICE_KEY`: Your Supabase service role key
- `HF_MODEL_ID`: HuggingFace model ID (default: mradermacher/Huihui-gemma-3n-E4B-it-abliterated-GGUF)

## Local Development

1. Install dependencies:
```bash
pip install -r requirements.txt
```

2. Run the server:
```bash
uvicorn app:app --reload --port 7860
```

## Testing

Run the tests using pytest:
```bash
pytest test_app.py -v
```