A simple PDF AI chatbot which runs locallly on your machine with streamlit UI
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Updated
Dec 22, 2024 - Python
A simple PDF AI chatbot which runs locallly on your machine with streamlit UI
Content Engine is RAG system that analyzes and compares multiple PDF documents, specifically identifying and highlighting their differences. The system will utilize Retrieval Augmented Generation (RAG) techniques to effectively retrieve, assess, and generate insights from the documents.
PDF Chatbot capable of answering your questions from a PDF.
LLM based PDF Chatbot
An LLM-powered augmented generation suite leveraging LangChain, Ollama, and vector databases to enhance response quality through caching, contextual memory, and retrieval-based methods. This collection of Jupyter notebooks showcases modular techniques for building intelligent, memory-efficient generative systems with real-time semantic awareness.
A simple chatbot that answers questions based on a PDF book. It extracts text, stores structured knowledge using Neo4j, and retrieves relevant information using a large language model (LLM).
The Advanced RAG Chatbot is a GPU-powered PDF question-answering system using Mistral (via Ollama), semantic search, and a Streamlit interface for accurate, interactive responses and exportable chat history.
Chat with your PDFs using PDFPal! Built with Streamlit, LangChain, Amazon Bedrock, and S3, this app lets you upload, process, and interact with PDF content using RAG-powered chat. Includes admin and user interfaces, vector storage, and Docker support.
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