Gen AI Projects

A collection of AI-powered chatbot applications built with LangChain, Streamlit, and OpenRouter API.

🚀 Projects

1. Q&A Chatbot

Location: Q&A_chatbot/

A simple question-answering chatbot with a clean Streamlit interface.

Features:

• Direct conversational interface
• Powered by free OpenRouter models (Google Gemini Flash, Mistral)
• Clean and intuitive UI
• Configurable response parameters

Files:

• app.py - Main Streamlit application
• test_api.py - API connection testing
• find_free_models.py - Discover available free models
• ollamaapp.py - Ollama integration variant

Run:

cd Q&A_chatbot
streamlit run app.py

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2. RAG Q&A Chatbot

Location: rag_q&a_chatbot/

A Retrieval-Augmented Generation (RAG) chatbot that answers questions from uploaded PDF documents.

Features:

• PDF document upload and processing
• FAISS vector store for efficient retrieval
• Custom embeddings implementation
• Context-aware responses from documents
• Question answering with source context

Files:

• ragapp.py - Main RAG application
• pdfs/ - Directory for PDF documents

Run:

cd rag_q&a_chatbot
streamlit run ragapp.py

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3. Conversational Q&A Chatbot with PDF

Location: conversational_q&a_chatbot/

An advanced conversational chatbot with PDF support and persistent chat history.

Features:

• Upload and query PDF documents
• Session-based chat history
• Conversational memory (remembers previous messages)
• RAG-based responses with context
• Streamlit Cloud ready
• Free AI models via OpenRouter

Files:

• app.py - Main application
• requirements.txt - Python dependencies
• README.md - Project-specific documentation
• DEPLOYMENT.md - Streamlit Cloud deployment guide
• .streamlit/config.toml - Streamlit configuration
• .gitignore - Git exclusions

Run:

cd conversational_q&a_chatbot
streamlit run app.py

Deploy to Streamlit Cloud: See conversational_q&a_chatbot/DEPLOYMENT.md for detailed deployment instructions.

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🛠️ Tech Stack

• Python 3.13.7
• Streamlit - Web UI framework
• LangChain - LLM framework and chains
• OpenRouter - AI model API with free tier
• FAISS - Vector database for embeddings
• PyPDF - PDF document processing
• NumPy - Numerical operations for embeddings
• python-dotenv - Environment variable management

📋 Prerequisites

• Python 3.13 or higher
• OpenRouter API key (get it free at openrouter.ai)
• Virtual environment (recommended)

⚙️ Setup

1. Clone the Repository

git clone https://github.com/itsmeayan45/gen-ai.git
cd gen-ai

2. Create Virtual Environment

python -m venv genvenv
genvenv\Scripts\activate  # Windows

3. Install Dependencies

pip install -r requirements.txt

4. Configure API Key

Create a .env file in the project root:

OPENROUTER_API_KEY=your_openrouter_api_key_here
LANGCHAIN_API_KEY=your_langchain_api_key_here  # Optional

5. Run Any Project

Navigate to the project folder and run:

streamlit run app.py

Or for the RAG chatbot:

streamlit run ragapp.py

🌐 Free AI Models

All projects use free OpenRouter models:

• google/gemini-2.0-flash-exp:free
• mistralai/mistral-7b-instruct:free

No API costs required for basic usage!

📁 Project Structure

Gen-ai-projects/
├── Q&A_chatbot/              # Basic Q&A chatbot
│   ├── app.py
│   ├── test_api.py
│   └── find_free_models.py
├── rag_q&a_chatbot/          # RAG chatbot with PDF
│   ├── ragapp.py
│   └── pdfs/
├── conversational_q&a_chatbot/  # Advanced conversational chatbot
│   ├── app.py
│   ├── requirements.txt
│   ├── README.md
│   ├── DEPLOYMENT.md
│   └── .streamlit/
├── genvenv/                  # Virtual environment
├── .env                      # API keys (not in git)
├── .gitignore
├── LICENSE
├── requirements.txt
└── README.md

🚢 Deployment

The Conversational Q&A Chatbot is ready for deployment on Streamlit Cloud:

1. Push to GitHub
2. Connect to share.streamlit.io
3. Add OPENROUTER_API_KEY in Streamlit secrets
4. Deploy!

See conversational_q&a_chatbot/DEPLOYMENT.md for detailed steps.

🤝 Contributing

Feel free to fork this repository and submit pull requests for improvements!

📄 License

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

👨‍💻 Author

Ayan

• GitHub: @itsmeayan45

🙏 Acknowledgments

• LangChain for the amazing framework
• OpenRouter for free AI model access
• Streamlit for the easy-to-use web framework

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