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google-cla bot commented Aug 26, 2025

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Summary of Changes

Hello @ShaharKatz, 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 PR refactors the evaluation process to ensure that the session ID generated during inference is consistently returned and utilized. This is particularly important for services like Vertex AI, where the session ID might be generated externally and needs to be propagated for accurate evaluation tracking.

Highlights

  • Function Signature Change: The _generate_inferences_from_root_agent function now explicitly returns the session ID alongside the inference results.
  • Session ID Propagation: Updates were made to cli_eval.py and local_eval_service.py to correctly capture and use this returned session ID in evaluation flows.
  • Vertex AI Integration: Specific handling for VertexAiSessionService was introduced to retrieve the session ID from the created session object, ensuring compatibility with external session management.
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adk-bot commented Aug 26, 2025

Response from ADK Triaging Agent

Hello @ShaharKatz, thank you for your contribution!

Before we can proceed with the review, could you please address the following points from our contribution guidelines:

  • Contributor License Agreement (CLA): It appears that the CLA has not been signed. Please sign the Google CLA so we can accept your contribution.
  • Associated Issue: For changes like this, we require an associated GitHub issue. Could you please create one and link it in the PR description?
  • Testing Plan: Please add a "testing plan" section to your PR description to explain how you've tested these changes.

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Code Review

This pull request updates the evaluation logic to support services like VertexAiSessionService that generate their own session IDs. The changes correctly propagate the returned session_id through the evaluation flow. My review includes suggestions to improve the implementation's robustness and clarity. Specifically, I've pointed out a problematic top-level import for an optional dependency that should be localized, suggested simplifying some logic by relying on type contracts instead of hasattr, and noted a minor code clarity issue with variable shadowing along with a typo in a comment.

@@ -28,6 +28,7 @@
from ..memory.in_memory_memory_service import InMemoryMemoryService
from ..runners import Runner
from ..sessions.base_session_service import BaseSessionService
from ..sessions.vertex_ai_session_service import VertexAiSessionService # TODO: some users won't have this dependency.

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high

As the TODO comment correctly points out, this top-level import can cause a ModuleNotFoundError for users who haven't installed the optional dependencies required by VertexAiSessionService. This can break the application on startup.

To ensure this dependency remains optional, the import should be moved into the _generate_inferences_from_root_agent method, where VertexAiSessionService is used. This is typically done within a try...except ImportError block to handle cases where the module isn't available.

Comment on lines +233 to +234
# TODO: this overrides the seesion_id that was generated locally in the prefix format.
inference_result, session_id = (

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medium

The TODO comment has a typo ('seesion_id').

More importantly, the variable shadowing on line 234 for session_id can be confusing. The session_id generated on line 231 is passed to the function, and then the same variable name is used to capture the returned session ID, which might be different (e.g., when using VertexAiSessionService). This makes the code harder to follow.

To improve clarity, consider renaming the variable to avoid shadowing, though this would require changes outside the current diff.

Suggested change
# TODO: this overrides the seesion_id that was generated locally in the prefix format.
inference_result, session_id = (
# TODO: this overrides the session_id that was generated locally in the prefix format.
inference_result, session_id = (

Comment on lines +170 to +173
if hasattr(vertex_session, "id"):
session_id = vertex_session.id
else:
raise ValueError("Session ID was not returned by the Vertex AI session service during session creation.")

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medium

The create_session method is type-hinted to return a Session object, which should have an id attribute according to its definition. Using hasattr to check for the attribute is less idiomatic and can mask underlying type issues. It's better to directly access vertex_session.id and rely on the type contract. If an implementation of create_session violates this contract, an AttributeError will be raised, which provides a clearer and faster failure signal.

      session_id = vertex_session.id

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