LangExtract is an open-source Python library designed for developers to extract structured information from unstructured text. It utilizes large language models like Gemini and simplifies defining extraction tasks through natural language instructions and examples. Key features include controlled generation for formatted output and linked source text, ensuring transparency. Advanced strategies like text chunking and parallel processing enhance its ability to extract from lengthy documents. LangExtract supports integration with various models, providing flexibility for developers in multiple domains, from healthcare to legal documentation, without needing in-depth machine learning expertise.
LangExtract enables developers to extract structured information from unstructured text using large language models with simple natural language instructions and example data.
LangExtract ensures extracted information is consistently formatted and accurately linked to its original source in the text, enhancing transparency and reliability.
For handling long and complex documents, LangExtract employs strategies like text chunking and parallel processing, improving recall and accuracy in extraction.
LangExtract's flexibility allows integration with various LLMs, making it a valuable tool for developers across multiple domains without needing extensive machine learning expertise.
#langextract #information-extraction #natural-language-processing #machine-learning #large-language-models
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