Instructor
Python library for structured LLM outputs using Pydantic models. Provides data extraction, validation, and retry logic with support for 15+ LLM providers. Enables type-safe, schema-driven AI integrations.
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Overview
Get structured, validated data from any LLM with Instructor - the #1 library for LLM data extraction. Supports 15+ providers (OpenAI, Anthropic, Google, Ollama, DeepSeek) in 6 languages. Built on type-safe schemas with automatic retries, streaming, and nested object support.
The Verdict
Who Should Use Instructor?
Best For
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What's Great
- Structured Outputs: Define Pydantic models to specify exactly what data you want from your LLM
- Automatic Retries: Built-in retry logic when validation fails - no more manual error handling
- Data Validation: Leverage Pydantic's powerful validation to ensure response quality
- Streaming Support: Real-time processing of partial responses and lists
- Multi-Provider: Works with OpenAI, Anthropic, Google, Mistral, Cohere, Ollama, DeepSeek, and 15+ LLM
Pricing
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Key Features
- Structured Outputs: Define Pydantic models to specify exactly what data you want from your LLM
- Automatic Retries: Built-in retry logic when validation fails - no more manual error handling
- Data Validation: Leverage Pydantic's powerful validation to ensure response quality
- Streaming Support: Real-time processing of partial responses and lists
- Multi-Provider: Works with OpenAI, Anthropic, Google, Mistral, Cohere, Ollama, DeepSeek, and 15+ LLM
- Type Safety: Full IDE support with proper type inference and autocompletion
Platforms
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How It Compares
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