Minimal Space config for testing

README.md

@@ -1,158 +1,13 @@
 ---
-title: Local Inference
-emoji: 👀
-colorFrom: pink
+title: Local Inference Hub
+emoji: 🤖
+colorFrom: purple
 colorTo: gray
 sdk: docker
 pinned: false
+app_port: 7860
 ---
 
-# AI Chat & Summarization Web App 🤖
+# Local Inference Hub
 
-A beautiful web-based AI application featuring **Chat Generation** and **Text Summarization** powered by Hugging Face models.
-
-## Features ✨
-
-- 💬 **Chat Generation**: Interactive AI chat using Qwen/Qwen1.5-0.5B-Chat
-- 📝 **Text Summarization**: Summarize long texts using DistilBART model
-- 🎨 **Beautiful UI**: Modern gradient design with smooth animations
-- 🌐 **Accessible**: Publicly deployable and accessible to everyone
-- ⚡ **Fast**: Lightweight models optimized for quick responses
-
-## Models Used
-
-- **Chat**: `Qwen/Qwen1.5-0.5B-Chat` - Lightweight conversational AI
-- **Summarization**: `sshleifer/distilbart-cnn-6-6` - Efficient text summarization
-
-## Local Development
-
-### Prerequisites
-- Python 3.12+
-- pip
-
-### Installation
-
-1. Clone the repository:
-```bash
-git clone https://github.com/DiegoAdame13322/LocalInference.git
-cd LocalInference
-```
-
-2. Install dependencies:
-```bash
-pip install -r requirements.txt
-```
-
-3. Run the server:
-```bash
-python server.py
-```
-
-4. Open your browser to `http://localhost:8000`
-
-## Deploy Options
-
-### Option 1: Hugging Face Spaces (Docker)
-
-See [DEPLOY_TO_SPACES.md](DEPLOY_TO_SPACES.md) for detailed instructions.
-
-### Option 2: Render Manual Deploy
-
-1. Go to [Render Dashboard](https://dashboard.render.com/)
-2. Click "New +" → "Web Service"
-3. Connect your repository
-4. Configure:
-   - **Name**: `ai-chat-summarization`
-   - **Environment**: `Python`
-   - **Build Command**: `pip install -r requirements.txt`
-   - **Start Command**: `python server.py`
-   - **Instance Type**: Free or Starter (Starter recommended for better performance)
-
-5. Click "Create Web Service"
-
-### Important Notes for Deployment
-
-- ⚠️ **First startup takes 5-10 minutes** as models download (1.5GB+)
-- 💾 **Disk space**: Free tier has 512MB, models need ~1.5GB. Use **Starter plan** or higher
-- 🔄 **Auto-sleep**: Free tier sleeps after 15min of inactivity, takes ~30s to wake up
-- 🎯 **Recommendation**: Use **Starter plan** for:
-  - More disk space
-  - Better performance
-  - No auto-sleep
-
-## API Endpoints
-
-### Chat Generation
-```bash
-POST /api/chat
-Content-Type: application/json
-
-{
-  "message": "What is machine learning?",
-  "max_new_tokens": 150,
-  "temperature": 0.7
-}
-```
-
-### Text Summarization
-```bash
-POST /api/summarize
-Content-Type: application/json
-
-{
-  "text": "Your long text here...",
-  "max_length": 130,
-  "min_length": 30
-}
-```
-
-### Health Check
-```bash
-GET /api/health
-```
-
-## Project Structure
-
-```
-LocalInference/
-├── server.py              # FastAPI backend with model loading
-├── static/
-│   └── index.html        # Frontend web interface
-├── requirements.txt      # Python dependencies
-├── render.yaml          # Render deployment config
-├── runtime.txt          # Python version specification
-└── README.md           # This file
-```
-
-## Tech Stack
-
-- **Backend**: FastAPI, PyTorch, Transformers
-- **Frontend**: HTML5, CSS3, JavaScript (Vanilla)
-- **Models**: Hugging Face Transformers
-- **Deployment**: Hugging Face Spaces, Render
-
-## Troubleshooting
-
-### Models not loading
-- Check disk space in deployment platform
-- Check logs in platform dashboard
-
-### Slow first response
-- Models load on first request, subsequent requests are faster
-- Consider keeping the service warm with periodic requests
-
-### Out of memory errors
-- Reduce `max_new_tokens` in chat requests
-- Use plan with more RAM
-
-## License
-
-MIT License - feel free to use and modify!
-
-## Contributing
-
-Pull requests are welcome! For major changes, please open an issue first.
-
----
-
-Made with ❤️ using Hugging Face Transformers
+A simple FastAPI application for AI chat and summarization.