Popular GitHub Repositories for Unstructured Data

? Data Versioning and ML Experiments

Neo4j graph construction from unstructured data using LLMs

? Instill Core is a full-stack AI infrastructure tool for data, model and pipeline orchestration, designed to streamline every aspect of building versatile AI-first applications

Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video analysis, question and answer systems, NLP, etc.

Interact, analyze and structure massive text, image, embedding, audio and video datasets

Curate better data for LLMs

Enterprise-grade and API-first LLM workspace for unstructured documents, including data extraction, redaction, rights management, prompt playground, and more!

Embedding Studio is a framework which allows you transform your Vector Database into a feature-rich Search Engine.

Enforce structured output from LLMs 100% of the time

Home of the AI workforce - Multi-agent system, AI agents & tools

Structured Data Extractor for AI Agents. Search your documents or the web for specific data and get it back in JSON or Markdown in a single tool call.

RAG-QA-Generator 是一个用于检索增强生成（RAG）系统的自动化知识库构建与管理工具。该工具通过读取文档数据，利用大规模语言模型生成高质量的问答对（QA对），并将这些数据插入数据库中，实现RAG系统知识库的自动化构建和管理。

How to construct knowledge graphs from unstructured data sources

An on-premises unstructured data extraction tool powered by vision language models.

A System for (Optimized) Semantic Computation

ContextGem: Easier and faster way to build LLM extraction workflows through powerful abstractions

Demo of knowledge graph creation and Graph RAG with BAML and Kuzu

The Indox Ecosystem offers integrated AI tools for data workflows. Our four components (IndoxArcg, IndoxMiner, IndoxJudge, and IndoxGen) enhance AI applications with advanced retrieval, extraction, evaluation, and generation capabilities, supporting multiple document formats and LLM providers.

⚗️ Instill Model contains components for AI model orchestration

Unstract's interface to LLMs, Embeddings and VectorDBs.