Easily deployable and scalable backend server that efficiently converts various document formats (pdf, docx, pptx, html, images, etc) into Markdown. With support for both CPU and GPU processing, it is Ideal for large-scale workflows, it offers text/table extraction, OCR, and batch processing with sync/async endpoints.

Chat with your PDF files using LlamaIndex, Astra DB (Apache Cassandra), and Gradient's open-source models, including LLama2 and Streamlit, all designed for seamless interaction with PDF files.

PDFwhisper allows you to have a conversation with your PDF docs. Finding info on PDF files is now easier than ever. 🚀🔥 Most secure authentication measures using Passkeys🔑

AgenticRAG is an advanced AI-powered retrieval-augmented generation (RAG) Agent designed to provide users with an interactive and intelligent conversational experience

An AI chat bot which can answer queries based on any PDF file

DocChat - Chat with a PDF using GenAI Capabilities.

Noto.ai is a local AI-powered PDF assistant that lets you chat with documents, ask questions, and get instant summaries—all offline using LLaMA 3 via Ollama. Built with Python and Kivy, it offers a clean desktop interface for students, researchers, and professionals who want to extract insights from complex PDFs efficiently and privately.

🚀 Transform Any PDF into an AI-Powered Q&A Chatbot!

A RAG pipeline using LangChain, OpenAI API, Gradio to chat with your PDFs!

Chat with your documents using LangChain and Chainlit.

A chatbot assistant app that allows you to talk to a pdf using gemini api

A PDF Chatbot to query information out of the selected PDFs you upload.

A private, local RAG (Retrieval-Augmented Generation) system using Flowise, Ollama, and open-source LLMs to chat with your documents securely and offline.

Quill redefines PDF interaction with intelligent conversations. Upload PDFs seamlessly, chat naturally, and receive instant insights.

A privacy-focused local LLM chatbot for chatting with healthcare PDFs using FAISS + FLAN-T5.

An intelligent chatbot that allows you to have a conversation with your PDF documents, powered by Streamlit, LangChain, and Google Generative AI.

End-to-end intelligent document Q&A system using LangChain, OpenAI, and vector databases. Upload PDFs and get GPT-powered answers instantly.

Create your own Retrieval-Augmented Generation (RAG) chatbot for PDFs. This project uses LangChain, Flask, and an LLM (IBM WatsonX/Hugging Face) to build a conversational AI that understands your documents.

RAG Embed chatbot with Cohere API