Hi team,

I'm currently reviewing this pull request and will have a full review ready in a few minutes. In the meantime, here's a quick summary to get everyone up to speed:

This PR, submitted by bgdnvk, addresses issue #1571. The goal is to fix a problem where the textembedding-gecko model failed to load when specifying the latest version. The documentation also discourages using latest, so this change makes the fix more robust.

Here's a breakdown of the changes:

• File Changed: gemini/use-cases/retrieval-augmented-generation/utils/intro_multimodal_rag_utils.py
• Specific Change: Line 23 of intro_multimodal_rag_utils.py was modified. The text embedding model instantiation was updated to use a specific version (textembedding-gecko@003) instead of textembedding-gecko@latest.

Before:

text_embedding_model = TextEmbeddingModel.from_pretrained("textembedding-gecko@latest")

After:

text_embedding_model = TextEmbeddingModel.from_pretrained("textembedding-gecko@003")

This change ensures that the code uses a known working version of the textembedding-gecko model, improving the reliability and maintainability of the code. No other files were modified.

And now, a little haiku to lighten the mood:

Gecko's version fixed,
Stable code, a joyful sight,
No more loading woes.

This change replaces the "latest" tag for the textembedding-gecko model with the specific version 003. This is a good practice for reproducibility and avoids potential issues with breaking changes in future versions of the model. Pinning the version ensures that the code will continue to work as expected, even if the "latest" tag is updated to a newer, potentially incompatible version. The pull request description clearly explains the reason for the change and links to the related issue, which is helpful for context and traceability.

I studied the codebase to understand the project's coding style and didn't find any explicit style guide, so I'm defaulting to the Google Python Style Guide for my suggestions.

Overall, this is a small but important change that improves the reliability and maintainability of the code.