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- **Do** match the interpreter requirement declared in `pyproject.toml` (Python ≥ 3.12) and install `requirements.txt` plus `requirements-dev.txt` before running tools.
- Optimized PR diff processing by introducing caching for diff files, reducing the number of API calls.
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A beginner-friendly introduction to using Instructor for structured outputs from LLMs
Discover why Instructor is the simplest, most reliable way to get structured outputs from LLMs.
Learn the structure of the Instructor repository and the purpose of each major directory.
Get notified about AI tips, blog posts, and research. Stay informed with Instructor's latest features and community insights.
Compare different modes available in Instructor and understand when to use each
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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.
Learn how to install Instructor and its dependencies using pip for Python 3.9+. Simple setup guide included.
Explore key resources for getting help with Instructor, including Discord, blog, concepts, cookbooks, and GitHub discussions.
A step-by-step guide to getting started with Instructor for structured outputs from LLMs
Common questions and answers about using Instructor
Join us in enhancing the Instructor library with evals, report issues, and submit pull requests on GitHub. Collaborate and contribute!
Learn how to debug Instructor applications with hooks, logging, and exception handling. Practical techniques for inspecting inputs, outputs, and retries.
Learn about the internal architecture and design decisions of the Instructor library
Explore the comprehensive API reference with details on instructors, validation, iteration, and function calls.
Internal guide for maintaining and improving Instructor documentation
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