Add a guide for MLflow observability integration with Gemini

[TomeHirata]

Description of the feature request:

Hi, team. I'm a core maintainer of MLFlow, one of the most popular tools for ML workflow management.
We have recently introduced a new tracing integration with the google-generativeai Python ADK and we would be grateful if we could add a guide for the integration to the Cookbook. The guide will include example codes for using the MLflow tracing integration and links to the relevant documentation.
Please refer to https://mlflow.org/docs/latest/llms/tracing/index.html for the tracing integration.

What problem are you trying to solve with this feature?

With the guide, users can easily get started with MLflow integration for Gemini and gain observability of their agents or applications using Gemini API.

Any other information you'd like to share?

No response

[markmcd]

Sounds great. I think MLFlow meets the contribution guidelines, so I'd be happy to have something added in here.

If you have any early drafts or an outline, feel free to share. Generally we like guides to be pretty specific, but you can create multiple if you need (e.g. examples/mlflow/basic_observability.ipynb, examples/mlflow/complex_something_something.ipynb). Let me know if you need a less public channel to share.

We're also in the progress of migrating our examples and content to use the new SDK (google-genai) - can you use that too?

[TomeHirata]

Hi, @markmcd. Thank you so much for your reply. It sounds like we should integrate with the new SDK and then add the examples and guides. For our reference, do you plan to maintain google-generativeai or do you think it's ok to stop supporting this package and fully migrate our integration to the new SDK google-genai?

[markmcd]

Long-term, we don't intend to have 2 SDKs for the same API. Short-term though, google-generative still gets almost 1M downloads/week so there may be a user base you want to cover there, but that's your call.