# openai/openai-cookbook

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74,196 stars · 12,563 forks · Jupyter Notebook · MIT

## Links

- GitHub: https://github.com/openai/openai-cookbook
- Homepage: https://cookbook.openai.com
- awesome-repositories: https://awesome-repositories.com/repository/openai-openai-cookbook.md

## Topics

`chatgpt` `gpt-4` `openai` `openai-api`

## Description

This project is a technical learning resource and developer knowledge base focused on the integration of large language models into software applications. It provides a structured collection of guides and code examples designed to teach developers how to implement intelligent features using proven patterns and best practices.

The repository distinguishes itself through a library of functional demonstrations that cover complex topics such as retrieval-augmented generation, function calling, and prompt engineering workflows. These materials are organized into a modular structure, allowing for the rapid development and testing of prototypes and proof-of-concept applications before moving toward production-ready software.

The content is delivered as a version-controlled knowledge base, utilizing markdown-based documentation and executable code blocks. These resources are designed to be copied directly into external development environments or cloud-based notebooks for hands-on experimentation. The entire collection is compiled into a static site to ensure consistent accessibility and navigation.

## Tags

### Artificial Intelligence & ML

- [Artificial Intelligence Tooling](https://awesome-repositories.com/f/artificial-intelligence-ml/artificial-intelligence-tooling.md) — Demonstrates technical patterns and best practices for embedding large language models into production software environments.
- [LLM Integration Patterns](https://awesome-repositories.com/f/artificial-intelligence-ml/multi-agent-orchestration-systems/llm-integration-patterns.md) — Implements architectural strategies like retrieval-augmented generation to connect language models with external data sources.
- [Prompt Engineering Toolkits](https://awesome-repositories.com/f/artificial-intelligence-ml/language-model-orchestration/prompt-engineering-toolkits.md) — Guides developers through the design, testing, and refinement of natural language instructions to optimize model output consistency.
- [AI Prototype Development](https://awesome-repositories.com/f/artificial-intelligence-ml/artificial-intelligence-tooling/platforms-and-runtime-environments/ai-prototype-development.md) — Accelerates the validation of AI concepts by offering functional proof-of-concept implementations for rapid prototyping.
- [Artificial Intelligence Research](https://awesome-repositories.com/f/artificial-intelligence-ml/artificial-intelligence-research.md) — Curates practical code examples and research-backed guides to advance developer understanding of language model capabilities.

### Content Management & Publishing

- [Version-Controlled Knowledge Bases](https://awesome-repositories.com/f/content-management-publishing/content-management-systems/content-architecture-modeling/document-architectures/version-controlled-knowledge-bases.md) — Leverages distributed version control to track community contributions and maintain a transparent history of educational documentation.
- [Static Site Generators](https://awesome-repositories.com/f/content-management-publishing/static-site-document-generators/static-site-generators.md) — Compiles technical documentation into static HTML files to ensure fast loading and high availability.
- [Markdown Documentation](https://awesome-repositories.com/f/content-management-publishing/content-management-systems/content-architecture-modeling/documentation-tooling/authoring-editing/markdown-documentation.md) — Maintains technical content in plain text files that render into a structured, readable web interface.

### Part of an Awesome List

- [Learning and Prompt Engineering](https://awesome-repositories.com/f/awesome-lists/ai/learning-and-prompt-engineering.md) — Practical examples and guides for implementing the API.
- [LLM Development and Research](https://awesome-repositories.com/f/awesome-lists/ai/llm-development-and-research.md) — Examples and guides for utilizing the OpenAI API.
- [Prompt Engineering Resources](https://awesome-repositories.com/f/awesome-lists/ai/prompt-engineering-resources.md) — Official recipes for prompts, RAG, and evaluation techniques.
- [AI Development Resources](https://awesome-repositories.com/f/awesome-lists/devtools/ai-development-resources.md) — Official examples and best practices for using OpenAI APIs.
- [Developer Tools and Infrastructure](https://awesome-repositories.com/f/awesome-lists/devtools/developer-tools-and-infrastructure.md) — Examples and guides for using OpenAI APIs.
- [Prompt Engineering](https://awesome-repositories.com/f/awesome-lists/devtools/prompt-engineering.md) — Official examples and best practices for using language model APIs.
- [Prompt Engineering Guides](https://awesome-repositories.com/f/awesome-lists/devtools/prompt-engineering-guides.md) — Official collection of code recipes for building LLM-powered applications.
- [Educational Guides](https://awesome-repositories.com/f/awesome-lists/learning/educational-guides.md) — Official examples and best practices for using language model APIs.
- [Educational Resources](https://awesome-repositories.com/f/awesome-lists/learning/educational-resources.md) — Official examples and best practices for using model APIs.
- [Learning Resources](https://awesome-repositories.com/f/awesome-lists/learning/learning-resources.md) — Examples and guides for using OpenAI APIs.

### Education & Learning Resources

- [Educational Resources](https://awesome-repositories.com/f/education-learning-resources/educational-resources.md) — Supplies a library of executable scripts and documentation that provide hands-on experience with complex technical concepts.