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fix(py): add dynamic model listing/resolving #4306
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Summary of ChangesHello @MengqinShen, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed! This pull request modernizes the Google GenAI plugin by transitioning from static model definitions to dynamic discovery directly from the API. This change significantly improves the plugin's adaptability to new models and features, such as the newly integrated Veo text-to-video model. It streamlines how the plugin identifies and configures various AI capabilities, making it more robust and future-proof without requiring code updates for every new model release. Highlights
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Code Review
This pull request introduces dynamic model discovery for the Google GenAI plugin, which is a great improvement over hardcoded model lists. The changes are extensive and touch both the GoogleAI and VertexAI plugin implementations, as well as model definition files and tests.
My review has identified several critical indentation issues throughout google.py that will cause runtime errors. I've also found an opportunity to simplify the long-running operation handling in the new veo.py model implementation. Additionally, there are a few minor suggestions for code cleanup.
Once the critical indentation issues are resolved, this will be a solid contribution.
py/plugins/google-genai/src/genkit/plugins/google_genai/google.py
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| actions = [] | ||
| # Gemini Models | ||
| for name in genai_models.gemini: | ||
| actions.append(self._resolve_model(googleai_name(name))) |
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py/plugins/google-genai/src/genkit/plugins/google_genai/google.py
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py/plugins/google-genai/src/genkit/plugins/google_genai/google.py
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py/plugins/google-genai/src/genkit/plugins/google_genai/google.py
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| gemini: list[str] = [] | ||
| imagen: list[str] = [] | ||
| embedders: list[str] = [] | ||
| veo: list[str] = [] |
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The class attributes gemini, imagen, embedders, and veo are mutable lists initialized at the class level. This is generally discouraged as they are shared across all instances of the class. Although the __init__ method correctly creates instance-specific attributes, the class-level attributes are redundant and can be misleading. It's better to declare the types at the class level without initializing them, and perform initialization only in __init__.
| gemini: list[str] = [] | |
| imagen: list[str] = [] | |
| embedders: list[str] = [] | |
| veo: list[str] = [] | |
| gemini: list[str] | |
| imagen: list[str] | |
| embedders: list[str] | |
| veo: list[str] |
| from typing import Any | ||
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| from google import genai | ||
| from google.genai import types as genai_types | ||
| from pydantic import ValidationError |
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