Instructor
Structured outputs from LLMs using Pydantic — patches OpenAI/Anthropic/Cohere/etc. clients to return validated typed objects with retries.
llm-gateway-frameworksNew to PyRadar
74
Hero Score
Popularity
74
Performance
85
Ecosystem
75
Maturity
61
Dev Experience
75
⭐ 13,078 stars⬇ 3.0M downloads/wkFirst release: Jul 2023Last release: Apr 2026
Async Support: YesPlugin Extensions: HighSpeed: FastDoc Quality: HighLearning Curve: Easy
Pros
- • Type-safe LLM outputs via Pydantic response_model — validated objects, not strings
- • Automatic retries with parsing errors fed back to the model
- • Multi-provider — patches OpenAI, Anthropic, Cohere, Gemini, Mistral, and more
Cons
- • Works by patching client libraries, which can feel implicit and surprising
- • response_model feature coverage and reliability vary by underlying provider
- • Adds parsing/validation latency compared to raw streaming