567-labs/instructor

Health v2 · maintenance only

Adoption not part of the score

13782 stars · 1205 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Instructor is a Python library that patches LLM clients to return validated, type-safe structured data using Pydantic models, with automatic retries and streaming. It supports 15+ providers including OpenAI, Anthropic, Google Gemini, Mistral, Cohere, and local models via Ollama and llama.cpp.

Use cases

• extract structured data from llm responses
• get validated from gpt-4 or claude
• parse resumes or documents into pydantic models with an llm
• retry llm calls automatically when validation fails
• stream partial structured outputs from a language model
• use function calling across multiple llm providers with one interface

When to choose

• you need schema-first structured extraction from any LLM with type safety
• you want Pydantic validation and automatic reasking on failed outputs
• you need a unified interface across OpenAI, Anthropic, Gemini, and other providers

When to avoid

• you need full agent frameworks with tools, traces, and observability (consider PydanticAI)
• you want raw unstructured LLM text generation
• you are not working in Python or another supported language runtime

Facets

library · maturity stable

llm-inference serialization sdk middleware large-language-models artificial-intelligence developer-tools python cross-platform structured-outputs pydantic openai function-calling data-extraction validation retries multi-provider natural-language-processing

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