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LangExtract: Python library for extracting structured data from language models

9 months ago
  • #Python
  • #LLM
  • #Text Extraction
  • LangExtract is a Python library for extracting structured information from unstructured text using LLMs.
  • Key features include precise source grounding, reliable structured outputs, optimized long document processing, interactive visualization, flexible LLM support, and adaptability to any domain.
  • Supports cloud-based models like Google Gemini and local models via Ollama, requiring API keys for cloud models.
  • Quick start involves defining a prompt, providing examples, and running extraction with a few lines of code.
  • Installation is straightforward via pip, with options for development mode and Docker.
  • API key setup can be done via environment variables, .env files, or directly in code (not recommended for production).
  • Examples include processing full texts like Romeo and Juliet and extracting medical information from clinical notes.
  • Contributions are welcome, with guidelines provided in CONTRIBUTING.md.
  • Testing can be done locally with pytest or tox, with instructions for handling dependencies.
  • Disclaimer notes that LangExtract is not an officially supported Google product and is subject to Apache 2.0 License.