OpenAI Cookbook - Examples and Guides for the OpenAI API
The official OpenAI Cookbook is a comprehensive collection of examples, guides, and best practices for using the OpenAI API. Covers GPT-4, ChatGPT, embeddings, fine-tuning, and more.
OpenAI Cookbook#
The OpenAI Cookbook is the official repository of examples and guides for using the OpenAI API. With over 73,000 GitHub stars, it is the most comprehensive reference for developers building with OpenAI models.
What You Will Find#
- Getting Started Guides: Step-by-step tutorials for making your first API calls, handling authentication, and understanding the request/response format
- GPT-4 and GPT-4o Examples: Practical code samples for text generation, function calling, structured outputs, and multi-turn conversations
- Embeddings Guide: How to generate and use embeddings for semantic search, clustering, and classification
- Fine-tuning Walkthrough: Complete guide to fine-tuning models on your own data for better performance on specific tasks
- Vision Examples: Using GPT-4o and GPT-5 models with images for visual understanding tasks
- Best Practices: Tips for prompt engineering, token management, rate limiting, and cost optimization
Key Sections#
Text Generation
Learn how to use the Chat Completions API for generating text, handling conversations, and implementing function calling. Includes examples for streaming responses, managing context windows, and using structured outputs.
Embeddings and Search
Comprehensive guide to using OpenAI embeddings for semantic search, similarity comparison, and clustering. Includes recipes for building search engines with pgvector and other vector databases.
Fine-tuning
Step-by-step instructions for fine-tuning GPT-4o-mini and other models on custom datasets. Covers data preparation, training configuration, evaluation, and deployment.
Image Understanding
Examples for using vision-capable models to analyze images, extract text, describe scenes, and answer questions about visual content.
Cost Optimization
Strategies for reducing API costs including prompt caching, batch API usage, token-efficient prompting, and choosing the right model for each task.
Getting Started#
Visit the cookbook at cookbook.openai.com or clone the GitHub repository to run examples locally. Most examples are Jupyter notebooks that you can run with minimal setup.
git clone https://github.com/openai/openai-cookbook.git cd openai-cookbook pip install -r requirements.txt
Who Should Use This#
- Developers new to the OpenAI API who want structured learning paths
- Experienced developers looking for best practices and advanced patterns
- Teams building production applications who need reliable reference implementations
- Researchers exploring OpenAI model capabilities
Related Resources#
- OpenAI API Documentation: The official API reference
- OpenAI Developer Forum: Community support and discussions
- OpenAI Status Page: Real-time API status and incident reports