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Extract structured data from PDFs.
Stop wasting time extracting PDFs.
Transform your PDF documents into structured data with Documind. Simple, powerful and open-source.
Documind is an advanced document processing tool that leverages AI to extract structured data from PDFs. It is built to handle PDF conversions, extract relevant information, and format results as specified by customizable schemas.
RAG that intelligently adapts to your use case, data, and queries.
Streamlined and promptable Fast GraphRAG framework designed for interpretable, high-precision, agent-driven retrieval workflows.
MinerU is a tool that converts PDFs into machine-readable formats (e.g., markdown, JSON), allowing for easy extraction into any format. MinerU was born during the pre-training process of InternLM. We focus on solving symbol conversion issues in scientific literature and hope to contribute to technological development in the era of large models. Compared to well-known commercial products, MinerU is still young. If you encounter any issues or if the results are not as expected, please submit an issue on issue and attach the relevant PDF.
🦛 CHONK your texts with Chonkie ✨ - The no-nonsense RAG chunking library.
The no-nonsense RAG chunking library that's lightweight, lightning-fast, and ready to CHONK your texts
Docling parses documents and exports them to the desired format with ease and speed.
🗂️ Reads popular document formats (PDF, DOCX, PPTX, Images, HTML, AsciiDoc, Markdown) and exports to Markdown and JSON.
🤯 Lobe Chat - an open-source, modern-design AI chat framework. Supports Multi AI Providers( OpenAI / Claude 3 / Gemini / Ollama / Azure / DeepSeek), Knowledge Base (file upload / knowledge management / RAG ), Multi-Modals (Vision/TTS) and plugin system. One-click FREE deployment of your private ChatGPT/ Claude application.
🤖 Chat with your SQL database 📊. Accurate Text-to-SQL Generation via LLMs using RAG 🔄.
Personalized AI SQL Agent. Let Vanna.AI write your SQL for you
The fastest way to get actionable insights from your database just by asking questions.
📦 Repopack is a powerful tool that packs your entire repository into a single, AI-friendly file. Perfect for when you need to feed your codebase to Large Language Models (LLMs) or other AI tools like Claude, ChatGPT, and Gemini.
OmniParse is a platform that ingests/parses any unstructured data into structured, actionable data optimized for GenAI (LLM) applications. Whether working with documents, tables, images, videos, audio files, or web pages, OmniParse prepares your data to be clean, structured and ready for AI applications, such as RAG , fine-tuning and more.
Rank LLMs, RAG systems, and prompts using automated judge evaluation.
An open-source RAG-based tool for chatting with your documents.
An open-source clean & customizable RAG UI for chatting with your documents. Built with both end users and developers in mind.
Text-To-Speech, RAG, and LLMs. All local!
Dot is a standalone, open-source application designed for seamless interaction with documents and files using local LLMs and Retrieval Augmented Generation (RAG). It is inspired by solutions like Nvidia's Chat with RTX, providing a user-friendly interface for those without a programming background. Using the Phi-3 LLM by default, Dot ensures accessibility and simplicity right out of the box.
The GraphRAG project is a data pipeline and transformation suite that is designed to extract meaningful, structured data from unstructured text using the power of LLMs.
GraphRAG is a structured, hierarchical approach to Retrieval Augmented Generation (RAG), as opposed to naive semantic-search approaches using plain text snippets. The GraphRAG process involves extracting a knowledge graph out of raw text, building a community hierarchy, generating summaries for these communities, and then leveraging these structures when perform RAG-based tasks.
A new community-based approach to build truly open-source LLMs.
InstructLab Command-Line Interface. Use this to chat with a model and execute the InstructLab workflow to train a model using custom taxonomy data.
Retrieval Augmented Generation (RAG) chatbot powered by Weaviate.
Welcome to Verba: The Golden RAGtriever, an open-source application designed to offer an end-to-end, streamlined, and user-friendly interface for Retrieval-Augmented Generation (RAG) out of the box. In just a few easy steps, explore your datasets and extract insights with ease, either locally with HuggingFace and Ollama or through LLM providers such as OpenAI, Cohere, and Google.
Infra for RAG apps that work in prod.
You know Postgres. Now you know machine learning.
Index, filter & rank vectors. Create embeddings. Generate real-time, fact-based outputs.
Korvus is a search SDK that unifies the entire RAG pipeline in a single database query. Built on top of Postgres with bindings for Python, JavaScript and Rust, Korvus delivers high-performance, customizable search capabilities with minimal infrastructure concerns.