Langextract: Extracting Structured Information from Unstructured Text with LLMs and Precise Source Grounding
Langextract is a powerful Python library that empowers developers and researchers to extract structured information from unstructured text. Built with Large Language Models (LLMs) at its core, it emphasizes precise source grounding and offers interactive visualization capabilities, making it an invaluable tool for complex NLP tasks.
Key Features:
- LLM-Powered Extraction: Harnesses the advanced capabilities of LLMs for sophisticated text understanding and data extraction.
- Precise Source Grounding: Ensures that extracted information is directly traceable to its source in the original text, enhancing reliability and auditability.
- Interactive Visualization: Provides tools to visualize the extracted information, helping users to better understand relationships and patterns within the data.
Whether you are working on building intelligent chatbots, analyzing large datasets of text, or developing advanced search functionalities, Langextract provides a robust foundation.
Getting Started
This is an open-source project, and contributions are always welcome. Explore the repository to learn more about its architecture, use cases, and how you can get involved.
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