title	app_file	sdk	sdk_version
TalentTalk	app.py	gradio	5.31.0

TalentTalk 🤖

A personalized AI chatbot that acts as a digital representative for professional networking and career discussions. Built with OpenAI's GPT-4 and Gradio for a seamless web interface.

🌟 Features

• Personalized AI Agent: Acts as a digital representative using your LinkedIn profile and personal summary
• Interactive Chat Interface: Clean, modern web interface built with Gradio
• Lead Capture: Automatically records interested users' contact information
• Question Tracking: Logs unanswered questions for follow-up
• Push Notifications: Real-time notifications via Pushover when users engage
• PDF Integration: Automatically processes LinkedIn profile from PDF

🚀 Quick Start

Prerequisites

• Python 3.8 or higher
• OpenAI API key
• Pushover account (optional, for notifications)

Installation

1. Clone the repository

   git clone <your-repo-url>
   cd TalentTalk

2. Install dependencies

   pip install -r requirements.txt

3. Set up environment variables Create a .env file in the project root:

   OPENAI_API_KEY=your_openai_api_key_here
   PUSHOVER_TOKEN=your_pushover_token_here
   PUSHOVER_USER=your_pushover_user_key_here

4. Add your personal information

   • Place your LinkedIn profile PDF in the me/ directory as linkedin.pdf
   • Update me/summary.txt with your personal summary

5. Run the application

   python app.py

6. Access the interface Open your browser and navigate to the URL displayed in the terminal (typically http://localhost:7860)

📁 Project Structure

TalentTalk/
├── app.py              # Main application file
├── requirements.txt    # Python dependencies
├── README.md          # This file
├── .env              # Environment variables (create this)
└── me/               # Personal information directory
    ├── linkedin.pdf   # LinkedIn profile PDF
    └── summary.txt    # Personal summary

🔧 Configuration

Environment Variables

• OPENAI_API_KEY: Your OpenAI API key (required)
• PUSHOVER_TOKEN: Pushover app token (optional)
• PUSHOVER_USER: Pushover user key (optional)

Personal Information Setup

1. LinkedIn Profile: Export your LinkedIn profile as PDF and save it as me/linkedin.pdf
2. Personal Summary: Create a comprehensive summary in me/summary.txt including:
   • Professional background
   • Key skills and expertise
   • Career highlights
   • Contact preferences

💬 Usage

Once the application is running:

1. Start a conversation: Users can ask questions about your background, skills, or experience
2. Automatic lead capture: When users show interest, the AI will request their email
3. Real-time notifications: You'll receive Pushover notifications for new interactions
4. Question tracking: Unanswered questions are automatically logged for follow-up

🛠️ Technical Details

Core Components

• Me Class: Main chatbot implementation with OpenAI integration
• Tool System: Custom functions for lead capture and question tracking
• Gradio Interface: Web-based chat interface
• PDF Processing: Automatic LinkedIn profile extraction

Dependencies

• openai: OpenAI API client
• gradio: Web interface framework
• pypdf: PDF text extraction
• python-dotenv: Environment variable management
• requests: HTTP requests for notifications

🔒 Privacy & Security

• All conversations are processed through OpenAI's API
• User data is only collected when explicitly provided
• Pushover notifications are sent securely
• No data is stored locally beyond the session

🤝 Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🆘 Support

If you encounter any issues or have questions:

1. Check the Issues page
2. Create a new issue with detailed information
3. Contact the maintainer directly

🔄 Updates

Stay updated with the latest features and improvements by:

• Watching the repository
• Following the release notes
• Checking the changelog

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Built with ❤️ using OpenAI GPT-4 and Gradio