eyurtsev/kor

Health v2 · maintenance only

Adoption not part of the score

1685 stars · 93 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Kor is a Python library for extracting structured data from text using large language models. Users define a schema (Kor-style or Pydantic) with examples, and Kor generates prompts, sends them to an LLM, and parses the output into structured data.

Use cases

• extract structured data from unstructured text with an llm
• parse entities like songs and artists from user commands
• build information extraction pipelines for legacy llms without tool calling
• convert free-form text into using a schema
• extract fields from documents using prompt-based parsing

When to choose

• you use older LLMs that lack native tool calling or JSON mode
• you want a schema-and-examples driven parsing approach integrated with LangChain
• you need extraction that works across any good-enough LLM

When to avoid

• your chat model supports native tool calling APIs (use those instead)
• you need a production-grade, actively developed extraction solution
• you want guaranteed extraction accuracy without providing good examples

Facets

library · maturity maintenance

nlp llm-inference parser prompt-engineering large-language-models artificial-intelligence python information-extraction structured-output langchain schema-extraction text-parsing natural-language-processing

Member repositories

For agents

markdown · JSON · MCP: product_card(name="eyurtsev/kor")