AI suite powered by state-of-the-art models and providing advanced AI/AGI functions. Includes AI personas, AGI functions, world-class Beam multi-model chats, text-to-image, voice, response streaming, code highlighting and execution, PDF import, presets for developers, much more. Deploy on-prem or in the cloud.

Meet MultiPDF 📚 Chat AI App! 🚀 Chat seamlessly with Multiple PDFs using Langchain, Google Gemini Pro & FAISS Vector DB with Seamless Streamlit Deployment. Get instant, accurate responses from Awesome Google Gemini OpenSource language Model. 📚💬 Transform your PDF experience now! 🔥✨

Langchain Chatbot with Multiple PDF Support using OpenAI and Hugging Face Models

Python Streamlit web app allowing the user to upload multiple files and then utilizing the OpenAI API GPT 3.5 Turbo language models, the user is able to have a conversation about the uploaded documents. The user is also allowed to specify the language model and the temperature of the model. Also presented with a drop down for PDF analytics.

The Multi-PDF's Chat Agent is a Streamlit-based web application designed to facilitate interactive conversations with a chatbot. The app allows users to upload multiple PDF documents, extract text information from them, and train a chatbot using this extracted content. Users can then engage in real-time conversations with the chatbot.

This script is a chat application that allows users to ask questions about multiple PDF documents implemented with meta's LLAMA2

A dual-mode AI application combining chat and rich-text AI editing, powered by Vue 3.5 + TypeScript. Features streaming Markdown rendering, Mermaid diagrams, Quill 2.0 rich-text editor, Monaco diff view, multi-format export (PDF/DOCX/Markdown/HTML), and offline-first IndexedDB storage.

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This project is a Streamlit-based web app that lets you upload multiple PDF documents and interact with them in natural language. It uses Google Gemini (via LangChain) for embeddings and question-answering, along with FAISS as the vector store for efficient document retrieval.

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Chat with Multiple PDFs Using Gemini API

This project allows you to engage in interactive conversations with your PDF documents using LangChain, ChromaDB, and OpenAI's API. With this powerful combination, you can extract valuable insights and information from your PDFs through dynamic chat-based interactions.

User-friendly chatbot that summarizes and interacts with content fromuser-uploaded PDFs using RAG with Ensemble Retriever

The project is a Streamlit-based app that allows users to upload PDF files, processes the text into chunks, stores it in a FAISS vector store using Google Generative AI embeddings, and enables conversational Q&A with the documents using Google Generative AI’s chat model for answers.

A sophisticated conversational AI application built with Chainlit and Ollama, featuring multi-modal document processing, MCP (Model Context Protocol) tool integration, and persistent chat sessions. Supports voice input, file analysis (PDF, DOCX, images), and seamless LLM model switching through customizable chat profiles.

Interact with multiple PDFs via an AI chatbot! Upload your documents, ask questions, and get intelligent, real-time responses based on the PDF content.

In the dynamic field of artificial intelligence (AI), our recent project stands out as a significant achievement. We developed an advanced AI-powered system utilizing Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) techniques, interfacing with the Gemini API to create a sophisticated question-answering platform.

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Gemini-Powered-MultiPDF-Chatbot is a Streamlit application that leverages Google Generative AI Gemini and LangChain for conversational question-answering based on PDF documents. This chatbot allows users to ask questions related to the content of uploaded PDF files.

A Langchain app that allows you to chat with multiple PDFs

In this project, I created an application using Google Gemini Pro and Langchain to process multiple PDF documents. We will use FAISS vector embeddings to enhance document processing capabilities.

Python-based MultiPDF Chatbot using Hugging Face and StreamLit

Use a large language model like the META Llama 2 13B and Chat with PDF files locally on your machine.

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This app is used easyrtc, whiteboard, pdf share, image share, video share and multi/single chat function by nodejs and expres framework with ejs

An intelligent PDF chatbot powered by Groq LLMs and HuggingFace embeddings. Upload a PDF and ask questions in natural language — the app retrieves answers contextually and remembers previous chat history for coherent multi-turn conversations.

Slidepad adds a sidebar browser panel to your Mac, enabling quick access to web apps, PDFs, docs or chats without switching windows. Features include an omnibox, global shortcut, notifications, dark mode, multi-monitor support. Ideal for multitaskers and anyone who wants apps at hand.

An app built using langchain and streamlit which allows to chat with multiple PDFs and can be run locally with GPUs.