Added Space configuration and metadata

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.py text eol=lf
+*.txt text eol=lf
+*.md text eol=lf
+.gitattributes text eol=lf
+.gitignore text eol=lf

README.md

@@ -1,66 +1,43 @@
-# ML/AI Models API Service
+---
+title: Oversai Text Analyzer
+emoji: 📝
+colorFrom: blue
+colorTo: indigo
+sdk: gradio
+sdk_version: 4.19.2
+app_file: app.py
+pinned: false
+---
 
-A centralized service that hosts various machine learning and AI models using Gradio interfaces, exposed via REST APIs for external frontend clients.
+# Oversai Text Analyzer
 
-## Features
-
-- Multiple ML/AI model endpoints
-- Gradio interfaces for each model
-- FastAPI backend for API exposure
-- Easy model management and deployment
-- Scalable architecture
-
-## Setup
+A powerful text analysis tool that uses BERT-based models to analyze and classify text.
 
-1. Create a virtual environment:
-```bash
-python -m venv venv
-source venv/bin/activate  # On Windows: venv\Scripts\activate
-```
+## Features
 
-2. Install dependencies:
-```bash
-pip install -r requirements.txt
-```
+- Text Classification
+- Sentiment Analysis
+- Easy-to-use Interface
 
-3. Create a `.env` file:
-```bash
-cp .env.example .env
-```
+## Usage
 
-4. Run the development server:
-```bash
-python src/main.py
-```
+1. Enter your text in the input box
+2. Click submit
+3. View the analysis results
 
-## Project Structure
+## Technical Details
 
-```
-├── src/
-│   ├── main.py              # Main application entry point
-│   ├── config.py            # Configuration settings
-│   ├── models/              # ML/AI model implementations
-│   │   ├── __init__.py
-│   │   └── base.py         # Base model class
-│   ├── interfaces/          # Gradio interfaces
-│   │   └── __init__.py
-│   └── api/                 # FastAPI routes
-│       └── __init__.py
-├── tests/                   # Test files
-├── .env.example            # Example environment variables
-├── requirements.txt        # Project dependencies
-└── README.md              # This file
-```
+Built with:
+- Gradio 4.19.2
+- Transformers 4.38.2
+- PyTorch 2.2.1
+- BERT-tiny model
 
-## Adding New Models
+## License
 
-1. Add your model implementation in `src/models/`
-2. Create a Gradio interface in `src/interfaces/`
-3. Add API endpoints in `src/api/`
-4. Register the model in `src/main.py`
+MIT License
 
-## API Documentation
+## Setup
 
-Once the server is running, visit:
-- API documentation: `http://localhost:8000/docs`
-- Gradio interfaces: `http://localhost:8000/gradio` 
+1. Create a virtual environment:
+```