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Add a cookbook on RAG observability instrumentation with MLflow #1668

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Summary

This PR adds a cookbook on instrumenting observability in a RAG chain using MLflow Tracing, an observability tool that automatically instruments traces.

Motivation

Why are these changes necessary? How do they improve the cookbook?

We think this will be useful for users building more complex apps with OpenAI. Gen AI apps are getting increasingly complex, with lots of layers of abstraction, and it can be difficult for people to figure out what's going wrong in the end-to-end execution. Observability tools help people move forward with confidence, as they can inspect each intermediate step and make sure the inputs / outputs are as they expect.


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When contributing new content, read through our contribution guidelines, and mark the following action items as completed:

  • I have added a new entry in registry.yaml (and, optionally, in authors.yaml) so that my content renders on the cookbook website.
  • I have conducted a self-review of my content based on the contribution guidelines:
    • Relevance: This content is related to building with OpenAI technologies and is useful to others.
    • Uniqueness: I have searched for related examples in the OpenAI Cookbook, and verified that my content offers new insights or unique information compared to existing documentation.
    • Spelling and Grammar: I have checked for spelling or grammatical mistakes.
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@daniellok-db
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Hi @phundal-openai, I saw you reviewed some other cookbooks in the repo, do you have the time to take a look at this one as well?

Signed-off-by: Daniel Lok <[email protected]>
Signed-off-by: Daniel Lok <[email protected]>
Signed-off-by: Daniel Lok <[email protected]>
Signed-off-by: Daniel Lok <[email protected]>
Signed-off-by: Daniel Lok <[email protected]>
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