Private chat with local GPT with document, images, video, etc. 100% private, Apache 2.0. Supports oLLaMa, Mixtral, llama.cpp, and more. Demo: https://gpt.h2o.ai/ https://gpt-docs.h2o.ai/
AIxplora is a open-source tool which let's you query all kind of files not limited to any length or format.
Using Langchain's ideas to build SpringBoot AI applications | 用langchain的思想，构建SpringBoot AI应用
Discover and converse with advanced AI models like Mistral, LLAMA2, and GPT-3.5 from leading sources like OLLAMA, Hugging Face, and OpenAI. Easily extract insights from PDFs, web pages, and YouTube videos with our intuitive interface. Unlock the power of knowledge with seamless chat interactions.
Chat with your docs in PDF/PPTX/DOCX format, using LangChain and GPT4/ChatGPT from both Azure OpenAI Service and OpenAI
Using LlamaIndex, Redis, and OpenAI to chat with PDF documents. Supplementary material for blog post on Microsoft Developer Blog
📚 Local PDF-Integrated Chat Bot: Secure Conversations and Document Assistance with LLM-Powered Privacy
Upload your files and ask questions about them. Open-source RAG app with LangChain & Streamlit, built before ChatGPT had file uploads. Works with Anthropic & OpenRouter. Easy to extend. The newest release is a functioning tribute and future development ideas are in consideration.
🧠 Quivr Chatbot extension - Instantly access Quivr, dump your files and chat with them using your Generative AI Second Brain using LLMs ( GPT 3.5/4, Private, Anthropic, VertexAI ) & Embeddings 🧠
Chatbot for Indian Law using Llama-7B-chat using Langchain integration and Streamlit UI.
Explore Multiple Vector Databases and chat with documents on Multiple LLM models, private LLM models
Ask question over your Notion Database! A naive Retrieval-Augmented Generation (RAG) pipeline backed by Langchain and Streamlit
AIGC 知识库问答系统快速搭建，便于企业级定制化，支持文档上传，向量存储，聊天式问答。
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Using Hugging Face Hub Embeddings with Langchain document loaders to do some query answering
[ACL 2025] NeuSym-RAG: Hybrid Neural Symbolic Retrieval with Multiview Structuring for PDF Question Answering
Rust-based retrieval system with hybrid search (vector + BM25), async ingestion, and gRPC-first API
Integrated LLM-based document and data Q&A with knowledge graph visualization
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