Personalized Video Chat AI Backend 🚀

Welcome to the backend repository for the Personalized Video Chat AI project! This backend powers an innovative educational platform that delivers emotionally intelligent, real-time video tutoring using advanced AI technologies. Built with scalability and performance in mind, it integrates seamlessly with the frontend to provide a robust user experience.

🔗 Related Repositories

• Frontend Repository: sam-shubham/video_chat_with_ai_frontend
  The frontend interface for the Personalized Video Chat AI system, built with Next.js and TailwindCSS.

📖 Overview

This repository (sam-shubham/video_chat_with_ai_backend) contains the backend logic for the Personalized Video Chat AI system. It handles API requests, AI model orchestration, database management, and real-time communication services to support interactive video tutoring.

🔗 Frontend Repository: sam-shubham/video_chat_with_ai_frontend

✨ Features

• API Gateway 🌐: Manages communication between frontend and backend services with authentication, routing, and load balancing.
• Large Language Model (LLM) 🧠: Powers conversational abilities with dynamic retraining on custom datasets (e.g., NPTEL courses).
• Vector Database (ChromaDB) 📊: Stores vector embeddings for efficient semantic search across educational content.
• Emotion & Face Recognition 😊: Analyzes facial expressions and identifies users for personalized responses.
• MongoDB Integration 🗄️: Stores user profiles, interaction history, and academic progress.
• Scalable Architecture ⚙️: Deployed on Vercel with Next.js for optimized performance and concurrent user support.

🛠️ Tech Stack

• Framework: Next.js (v13.4.4)
• Database: MongoDB, ChromaDB
• AI Libraries: LangChain, OpenAI, Pinecone
• Other Tools: Axios, Multer, TailwindCSS

📦 Installation

1. Clone the repository:

   git clone https://github.com/sam-shubham/video_chat_with_ai_backend.git
   cd video_chat_with_ai_backend

2. Install dependencies:

   npm install

3. Set up environment variables: Create a .env file in the root directory and add the necessary variables (e.g., database URI, API keys).

4. Run the development server:

   npm run dev

   The server will run on http://localhost:4090.

📝 Usage

• Use the API endpoints to interact with the AI services (e.g., emotion recognition, semantic search).
• Connect the backend with the frontend for a complete video chat experience.
• Deploy the backend on Vercel for production use.

👨‍💻 Author

Sam Shubham
📧 Email: mrshubhamsamrat05@gmail.com
🌐 Website: sam.appambient.com
GitHub: @sam-shubham

📜 License

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

🤝 Contributing

We welcome contributions to enhance the Personalized Video Chat AI backend! Follow these steps to contribute:

1. Fork the repository 🍴.
2. Create a new branch for your feature or bug fix:

   git checkout -b feature/your-feature-name

3. Make your changes and commit them:

   git commit -m "Add your commit message"

4. Push to your fork:

   git push origin feature/your-feature-name

5. Open a Pull Request 📬 with a detailed description of your changes.

Please ensure your code follows the project's coding standards and includes relevant tests.

🌟 Acknowledgments

• Thanks to the team at Lovely Professional University for their support.
• Kudos to the open-source community for providing amazing tools and libraries!

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Happy Coding! 💻
For any queries, feel free to reach out to the author.