gemini-code-assist[bot] commented on PR #37306: URL: https://github.com/apache/beam/pull/37306#issuecomment-3750051736
## Summary of Changes Hello @tarun-google, I'm Gemini Code Assist[^1]! 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 cherry-picks a set of changes related to the RateLimiter SDK into the Beam 2.71 release. The primary goal is to refine the rate limiting mechanism by renaming key methods for clarity, enhancing the `EnvoyRateLimiter` for distributed environments through serialization support, and integrating this rate limiting capability directly into the ML inference framework. These updates provide more robust control over external service interactions within Beam pipelines. ### Highlights * **Rate Limiter Method Renaming**: The core rate limiting method has been renamed from `throttle()` to `allow()` across the `RateLimiter` abstract base class and its `EnvoyRateLimiter` implementation. This change clarifies the method's intent, indicating whether a request is permitted rather than just if it's being throttled. * **EnvoyRateLimiter Serialization Support**: Added `__getstate__` and `__setstate__` methods to the `EnvoyRateLimiter` class. This enables proper serialization and deserialization of the rate limiter, which is crucial for Beam's distributed processing where objects might need to be pickled and unpickled across workers. * **Integration with ML Inference Handlers**: The `RemoteModelHandler` in `apache_beam.ml.inference.base` now supports an optional `rate_limiter` parameter. This allows users to apply a global rate limit to inference requests, ensuring that external ML services are not overwhelmed. A new `RateLimitExceeded` exception has also been introduced. * **New Vertex AI Rate Limiter Example**: A new example file, `rate_limiter_vertex_ai.py`, has been added. This example demonstrates how to use the `EnvoyRateLimiter` in conjunction with `VertexAIModelHandlerJSON` to control the rate of inference requests to a Vertex AI endpoint. * **Updated Test Cases**: Existing test cases for the `EnvoyRateLimiter` have been updated to reflect the `throttle()` to `allow()` method rename. Additionally, new test cases have been added to `base_test.py` to validate the integration of the rate limiter within the `RunInference` transform and to test scenarios where rate limits are exceeded. 🧠**New Feature in Public Preview:** You can now enable **Memory** to help **Gemini Code Assist** learn from your team's feedback. 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