A Python library for extracting structured information from unstructured text using LLMs with precise source grounding and interactive visualization.
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🦉 Data Versioning and ML Experiments
- data-science
- machine-learning
- reproducibility
- data-version-control
LLM-Driven Extraction of Unstructured Data — Built for API Deployments & ETL Pipeline Workflows
- ai-agents
- data-engineering
- document-ai
- generative-ai
Hypergraph is more powerful. Transform unstructured text into structured knowledge with LLMs. Graphs, hypergraphs, and spatio-temporal extractions — with one command.
A system for agentic LLM-powered data processing and ETL
Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.
- machine-learning
- convolutional-networks
- embedding-vectors
- embeddings
The Context Layer for unstructured data: typed, versioned datasets over S3, GCS, Azure
- claude-code
- codex
- data-processing
- harness-engineering
🔮 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
- unstructured-data
- low-code
- developer-tools
- etl
Extract structured data and insights from documents using LLMs and decision models
- ai
- data-extraction
- document-intelligence
- generative-ai
An on-premises, OCR-free unstructured data extraction, markdown conversion and benchmarking toolkit. (https://idp-leaderboard.org/)
- document
- document-analysis
- extraction
- llms
Nomic Developer API SDK
- python
- clustering
- duplicate-detection
- embeddings