Extracting Structured Data with LangExtract: A Deep Dive into LLM-Orchestrated Workflows

LangExtract is an orchestration engine designed to improve structured data extraction from LLM workflows. It addresses common issues such as fact omission, schema misalignment, and the difficulties of manual prompt fine-tuning across different models. The library automatically chunks large documents, fine-tunes prompts to match the specific LLM's style, and manages the extraction process to ensure outputs are complete and correctly formatted. The workflow involves defining examples and schemas, which LangExtract uses to guide the LLM and post-process the results. A hands-on example demonstrates its application by parsing tech news RSS feeds to extract structured information.