🤖 AI PDF Chatbot

An AI-powered PDF Question Answering application built using Retrieval-Augmented Generation (RAG). Upload one or multiple PDF documents, ask questions in natural language, and receive context-aware answers powered by Google Gemini, LangChain, and FAISS.

🌐 Live Demo: https://ai-pdf-chatbot-2639.streamlit.app/

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✨ Features

• 📄 Upload and chat with multiple PDF documents
• 🤖 AI-powered question answering using Google Gemini
• 🔍 Semantic search with FAISS vector database
• 🧠 Retrieval-Augmented Generation (RAG) pipeline
• 💬 Supports follow-up questions with conversational query rewriting
• 📚 Displays the source pages used to generate answers
• ⚡ Fast document retrieval using LangChain
• 🎨 Clean and responsive Streamlit interface
• 🔒 Secure API key management using Streamlit Secrets

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🖼️ Screenshots

Home Page

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Uploading PDFs

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AI Answer

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Source References

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🛠️ Tech Stack

Category	Technology
Language	Python
Frontend	Streamlit
LLM	Google Gemini
Framework	LangChain
Vector Database	FAISS
PDF Parsing	PyMuPDF
Embeddings	Google Gemini Embeddings
Environment	python-dotenv

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📂 Project Structure

AI_PDF_Chatbot/
│
├── app.py
├── requirements.txt
├── .gitignore
├── README.md
│
├── assets/
│   ├── home.png
│   ├── upload.png
│   ├── chat.png
│   └── sources.png
│
└── utils/
    ├── chatbot.py
    ├── embeddings.py
    ├── pdf_reader.py
    ├── renderer.py
    ├── retriever.py
    ├── text_splitter.py
    └── vector_store.py

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⚙️ How It Works

PDF Upload
      │
      ▼
Extract Text (PyMuPDF)
      │
      ▼
Text Chunking
      │
      ▼
Gemini Embeddings
      │
      ▼
FAISS Vector Store
      │
      ▼
Similarity Search
      │
      ▼
Relevant Chunks Retrieved
      │
      ▼
Google Gemini
      │
      ▼
AI Answer + Source References

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🚀 Installation

1. Clone the repository

git clone https://github.com/Vansh2639/AI_PDF_Chatbot.git

cd AI_PDF_Chatbot

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2. Install dependencies

pip install -r requirements.txt

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3. Create a .env file

GOOGLE_API_KEY=YOUR_API_KEY

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4. Run the application

streamlit run app.py

The application will open at:

http://localhost:8501

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🌐 Deployment

This project is deployed using Streamlit Community Cloud.

Live Application

https://ai-pdf-chatbot-2639.streamlit.app/

To deploy your own version:

1. Fork this repository.
2. Connect it to Streamlit Community Cloud.
3. Add your API key under App Settings → Secrets:

GOOGLE_API_KEY = "YOUR_API_KEY"

4. Deploy.

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📚 Example Questions

Try asking:

• What is Object Destructuring?
• Explain Object Destructuring in detail.
• Give me an example of Object Destructuring.
• Summarize this document.
• What are the key points discussed?
• Explain this topic like I'm a beginner.
• What is the difference between dot notation and bracket notation?
• List the important concepts in this chapter.

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🔮 Future Improvements

• OCR support for scanned PDFs
• Highlight answer text inside PDFs
• Export chat history
• Multi-model support
• Citation highlighting
• Dark/Light theme toggle
• Voice input
• Streaming token generation
• Document summarization
• PDF comparison

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📦 Requirements

Some of the major libraries used:

• streamlit
• langchain
• faiss-cpu
• pymupdf
• google-genai
• python-dotenv

Install everything with:

pip install -r requirements.txt

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👨‍💻 Author

Vansh Garg

Computer Science Student | AI/ML Enthusiast

GitHub: https://github.com/Vansh2639

LinkedIn: https://www.linkedin.com/in/vansh-garg-2850b332a/

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⭐ Support

If you found this project useful:

• ⭐ Star the repository
• 🍴 Fork it
• 🐞 Report issues
• 💡 Suggest new features

Contributions are always welcome!

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📄 License

This project is licensed under the MIT License.