OpenAI Cookbook Github Repository: how to approach studying it

[gaunt trail]

I came across the OpenAI cookbook. I know there is a nice website with blog posts arranged in reverse chronological order, https://cookbook.openai.com ; and there's a related github repository. https://github.com/openai/openai-cookbook which I have downloaded and looked at.

I am puzzled, I think there is just too much material of different quality.

Here are my questions: Is there a table of contents, or a keyword index? What about deprecated models? There are blog posts doing things with LLM versions which are no longer available. Older blog posts can occur anywhere in the folder structure.

How do I approach reading/studying the cookbook material? Is the cookbook essential reading or should power users focus on reading the official documentation first, reading it thoroughly, and then rely on the cookbook only as a fallback solution?
Are there repository maintainers who flag older examples as deprecated (by editing the text, or by moving the files such as deprecated notebooks into differently labeled directories?) .

[paper owl]

Hi @gaunt trail. I'm kapa.ai, your friendly support bot. I will try to answer your question by searching through the knowledge base. :wave:

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The OpenAI Cookbook is a valuable resource, but your questions about navigating it and handling deprecated content are important. Here’s what the knowledge sources say:

Table of Contents & Index

• The OpenAI Cookbook website is organized by examples and guides, with a clear structure and table of contents for each section. For instance, example pages like Azure RAG Quickstart and GCP BigQuery Vector Search have their own tables of contents. However, there is no mention of a global keyword index or a comprehensive table of contents for the entire repository in the knowledge sources.

Handling Deprecated Models & Content

• Some older articles are explicitly marked as archived and may contain outdated information. For example, the fine-tuned Q&A examples state:

  "This article has been archived and may contain outdated information. It reflects approaches, models, or technologies that were current at the time of writing but may no longer represent best practices or the latest developments. Some of the code below may rely on deprecated API endpoints"
  This suggests that maintainers do flag deprecated content by editing the text, but there is no mention of moving files to separate directories for deprecated content. You may encounter older blog posts or notebooks anywhere in the folder structure, so always check for such notices at the top of each file or notebook you read Fine-Tuned Q&A - collect data, Fine-Tuned Q&A - create Q&A, Fine-Tuned Q&A - train.

Approach to Studying the Cookbook

• The Cookbook is designed to be broadly helpful, with an emphasis on clear, simple explanations and practical, self-contained code examples. It is not meant to replace the official documentation, but to complement it with real-world examples and guides. The About page states that most code examples are in Python, and the contributing guide encourages users to suggest improvements or flag issues.
• For best results, start with the official OpenAI documentation for authoritative, up-to-date information on models, endpoints, and best practices. Use the Cookbook for practical examples, inspiration, and solutions to specific problems. If you encounter an example using a deprecated model, check the OpenAI deprecations page for recommended replacements.

Summary

• There is no global index, but each section/example often has its own table of contents.
• Deprecated content is sometimes flagged in the text, but not always moved to a separate directory.
• Start with the official docs for fundamentals; use the Cookbook for practical examples and as a supplement.
• Always check for deprecation notices in the examples you use.

If you want to contribute or suggest improvements, you can do so via the GitHub issues page Contributing.

Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:

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