Update README.md

README.md

@@ -1,234 +1,12 @@
-# LinkedIn Profile Enhancer
-
-An AI-powered tool that analyzes LinkedIn profiles and provides personalized enhancement suggestions to improve professional visibility and job matching.
-
-## Features
-
-- 🔍 **Profile Analysis**: Comprehensive analysis of LinkedIn profile completeness and quality
-- 🎯 **Job Matching**: Smart matching against job descriptions with skill gap analysis
-- ✍️ **Content Generation**: AI-powered suggestions for headlines, about sections, and experience descriptions
-- 💾 **Memory Management**: Session and persistent storage for tracking improvements over time
-- 🌐 **Web Interface**: User-friendly Gradio interface for easy interaction
-
-## Project Structure
-
-```
-linkedin_enhancer/
-├── app.py                 # Main Gradio application
-├── agents/
-│   ├── __init__.py
-│   ├── orchestrator.py    # Main agent coordinator
-│   ├── scraper_agent.py   # LinkedIn data extraction
-│   ├── analyzer_agent.py  # Profile analysis
-│   └── content_agent.py   # Content generation
-├── memory/
-│   ├── __init__.py
-│   └── memory_manager.py  # Session & persistent memory
-├── utils/
-│   ├── __init__.py
-│   ├── linkedin_parser.py # Parse scraped data
-│   └── job_matcher.py     # Job matching logic
-├── prompts/
-│   └── agent_prompts.py   # All agent prompts
-├── requirements.txt
-└── README.md
-```
-
-## Installation
-
-1. Clone the repository:
-```bash
-git clone <repository-url>
-cd linkedin_enhancer
-```
-
-2. Create a virtual environment:
-```bash
-python -m venv venv
-source venv/bin/activate  # On Windows: venv\Scripts\activate
-```
-
-3. Install dependencies:
-```bash
-pip install -r requirements.txt
-```
-
-4. Set up environment variables:
-```bash
-# Create .env file with your API keys
-OPENAI_API_KEY=your_openai_key_here
-APIFY_API_TOKEN=your_apify_token_here
-```
-
-## API Keys Setup
-
-### Required Services:
-
-1. **OpenAI API** (for AI content generation):
-   - Sign up at [OpenAI Platform](https://platform.openai.com/)
-   - Create an API key in your dashboard
-   - Add to `.env` file: `OPENAI_API_KEY=sk-...`
-
-2. **Apify API** (for LinkedIn scraping):
-   - Sign up at [Apify](https://apify.com/)
-   - Rent the "curious_coder/linkedin-profile-scraper" actor
-   - Get your API token from account settings
-   - Add to `.env` file: `APIFY_API_TOKEN=apify_api_...`
-
-## Usage
-
-### Running the Application
-
-Start the Gradio interface:
-```bash
-python app.py
-```
-
-The application will launch a web interface where you can:
-1. Input a LinkedIn profile URL
-2. Optionally provide a job description for tailored suggestions
-3. Get comprehensive analysis and enhancement recommendations
-
-### Core Components
-
-#### 1. Profile Orchestrator (`agents/orchestrator.py`)
-The main coordinator that manages the entire enhancement workflow:
-- Coordinates between scraper, analyzer, and content generation agents
-- Manages data flow and session storage
-- Formats final output for user presentation
-
-#### 2. Scraper Agent (`agents/scraper_agent.py`)
-Handles LinkedIn profile data extraction using Apify:
-- **Real LinkedIn Scraping**: Uses Apify's `curious_coder/linkedin-profile-scraper`
-- **Comprehensive Data**: Extracts experience, education, skills, connections, etc.
-- **Fallback Support**: Uses mock data if scraping fails
-- **Rate Limiting**: Built-in delays to respect LinkedIn's terms
-
-#### 3. Analyzer Agent (`agents/analyzer_agent.py`)
-Performs comprehensive profile analysis:
-- Calculates profile completeness score
-- Analyzes keyword optimization
-- Identifies strengths and weaknesses
-- Assesses content quality
-- Provides job matching scores
-
-#### 4. Content Agent (`agents/content_agent.py`)
-Generates enhancement suggestions using AI:
-- **AI-Powered Content**: Uses OpenAI GPT models for content generation
-- **Smart Headlines**: AI-generated LinkedIn headline suggestions
-- **About Section**: AI-crafted professional summaries
-- **Experience Optimization**: Enhanced job descriptions with metrics
-- **Fallback Logic**: Traditional rule-based suggestions if AI unavailable
-
-#### 5. Memory Manager (`memory/memory_manager.py`)
-Handles data persistence:
-- Session data storage
-- User preferences
-- Analysis history tracking
-- Data export functionality
-
-#### 6. Utility Classes
-- **LinkedIn Parser** (`utils/linkedin_parser.py`): Cleans and standardizes profile data
-- **Job Matcher** (`utils/job_matcher.py`): Calculates job compatibility scores
-
-## Key Features
-
-### Profile Analysis
-- **Completeness Score**: Measures profile completeness (0-100%)
-- **Keyword Analysis**: Identifies missing keywords for target roles
-- **Content Quality**: Assesses use of action words and quantified achievements
-- **Strengths/Weaknesses**: Identifies areas of improvement
-
-### Job Matching
-- **Skills Gap Analysis**: Compares profile skills with job requirements
-- **Match Scoring**: Weighted scoring across skills, experience, keywords, and education
-- **Improvement Recommendations**: Specific suggestions to increase match scores
-
-### Content Enhancement
-- **Smart Suggestions**: Context-aware recommendations for each profile section
-- **Template Generation**: Provides templates and examples for better content
-- **Keyword Optimization**: Natural integration of relevant keywords
-
-## Development
-
-### Adding New Features
-
-1. **New Analysis Criteria**: Extend `AnalyzerAgent` with additional analysis methods
-2. **Enhanced Scraping**: Improve `ScraperAgent` with better data extraction (requires LinkedIn API setup)
-3. **AI Integration**: Add LLM calls in `ContentAgent` for more sophisticated suggestions
-4. **Additional Matching Logic**: Extend `JobMatcher` with more sophisticated algorithms
-
-### Configuration
-
-The system uses configurable weights for job matching in `utils/job_matcher.py`:
-```python
-weight_config = {
-    'skills': 0.4,
-    'experience': 0.3, 
-    'keywords': 0.2,
-    'education': 0.1
-}
-```
-
-## Limitations & Considerations
-
-### Current Capabilities
-- ✅ **Real LinkedIn Scraping**: Uses Apify's professional scraper
-- ✅ **AI Content Generation**: OpenAI GPT-powered suggestions
-- ✅ **Job Matching**: Advanced compatibility scoring
-- ✅ **Memory Management**: Session tracking and persistent storage
-
-### Production Ready Features
-- **API Integration**: Full OpenAI and Apify integration
-- **Error Handling**: Graceful fallbacks and error recovery
-- **Rate Limiting**: Respects API limits and LinkedIn terms
-- **Data Validation**: Input validation and sanitization
-
-### Production Considerations
-- **Rate Limiting**: Built-in API rate limiting and respect for service terms
-- **Data Privacy**: Secure handling of profile data and API keys
-- **Scalability**: Modular architecture supports high-volume usage
-- **Monitoring**: API connection testing and error tracking
-
-## Testing the Setup
-
-After setting up your API keys, test the connections:
-
-```python
-# Test Apify connection
-python -c "from agents.scraper_agent import ScraperAgent; ScraperAgent().test_apify_connection()"
-
-# Test OpenAI connection  
-python -c "from agents.content_agent import ContentAgent; ContentAgent().test_openai_connection()"
-```
-
-## Future Enhancements
-
-- 📊 **Analytics Dashboard**: Track improvement metrics over time
-- 🔄 **A/B Testing**: Test different enhancement strategies
-- 🌐 **Multi-language Support**: Support for profiles in different languages
-- 📱 **Mobile App**: React Native or Flutter mobile application
-- 🔗 **LinkedIn Integration**: Direct LinkedIn API partnership for real-time updates
-- 🎯 **Industry-specific Templates**: Tailored suggestions for different industries
-- 📈 **Performance Tracking**: Monitor profile view increases after optimizations
-
-## Contributing
-
-1. Fork the repository
-2. Create a feature branch
-3. Make your changes
-4. Add tests if applicable
-5. Submit a pull request
-
-## License
-
-This project is licensed under the MIT License - see the LICENSE file for details.
-
-## Support
-
-For questions or support, please open an issue in the repository or contact the development team.
-
+---
+title: Linked_in_Enhancer_gradio
+emoji: 🌖
+colorFrom: red
+colorTo: pink
+sdk: gradio
+sdk_version: 5.34.2
+app_file: app.py
+pinned: false
 ---
 
-**Note**: This tool is for educational and professional development purposes. Always respect LinkedIn's terms of service and data privacy regulations when using profile data.
-# linked_profile_enhancer
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference