{"library":"instructor","type":"library","category":null,"description":"Structured data extraction from LLMs via Pydantic models. Patches or wraps provider clients (OpenAI, Anthropic, Gemini, Cohere, Mistral, Groq, Ollama, and 15+ others) to add response_model, automatic validation, and retry logic. Uses tool-calling or JSON mode depending on provider. Core interface: client.chat.completions.create(response_model=MyModel, ...) returns a validated Pydantic instance. Maintained by Jason Liu / jxnl.","language":"python","status":"active","version":"1.14.5","tags":["instructor","structured-outputs","pydantic","openai","anthropic","gemini","extraction","validation","llm","tool-calling"],"last_verified":"Tue Jun 09","install":[{"cmd":"pip install instructor","imports":["import instructor; import openai; client = instructor.from_openai(openai.OpenAI())","import instructor; client = instructor.from_provider('openai/gpt-4o')"]},{"cmd":"pip install 'instructor[anthropic]'","imports":[]},{"cmd":"pip install 'instructor[google-genai]'","imports":[]},{"cmd":"pip install 'instructor[groq]'","imports":[]},{"cmd":"pip install 'instructor[litellm]'","imports":[]}],"homepage":"https://python.useinstructor.com","github":"https://github.com/instructor-ai/instructor","docs":null,"changelog":null,"pypi":"https://pypi.org/project/instructor/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":50,"avg_install_s":11.9,"avg_import_s":null,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/instructor/compatibility"}}