openai-cookbook is a repository containing example code, tutorials, and guidance for how to build real applications on top of the OpenAI API. It covers a wide range of use cases: prompt engineering, embeddings and semantic search, fine-tuning, agent architectures, function calling, working with images, chat workflows, and more. The content is primarily in Python (notebooks, scripts), but the conceptual guidance is applicable across languages. The repository is kept up to date and often expanded, and its examples are intended to serve both beginners and intermediate users of the API. It also includes deployment recipes, integration snippets (e.g. with GitHub Actions), and production considerations. Because OpenAI’s API evolves rapidly, the Cookbook acts as a living, community-curated reference to show “how to do X with the API” rather than only reprinting documentation.
Features
- Example notebooks and code for a wide spectrum of OpenAI API use cases
- Recipes for embeddings, semantic search, fine-tuning, and prompt engineering
- Integration examples (e.g. GitHub Actions, API pipelines)
- Function calling, agents, and multistep workflows tutorials
- Frequently updated content aligned with new API features
- Community contributions and curated guidance for production usage