Work-around slow import issue for google-adk

[dagardner-nv]

Description

• Reduce test runtime by 60s by importing google-adk early.

Explanation:
google-adk has a known slow import issue (google/adk-python#2433), where the library takes ~8 seconds to import. However since we run the tests in the packages dir last (after tests and examples), the ADK related tests run close to last. For some reason when ADK is imported late, it takes 60-70s.

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• When the PR is ready for review, new or existing tests cover these changes.
• When the PR is ready for review, the documentation is up to date with these changes.

Summary by CodeRabbit

• Tests
  • Added a session-scoped, automatically applied test fixture that attempts an early ADK import during test collection/run and silently ignores ImportError when ADK is not present, improving test initialization stability and reliability without affecting outcomes if ADK is absent.

[coderabbitai]

Walkthrough

Adds an autouse, session-scoped pytest fixture import_adk_early that attempts to import google.adk during test session setup and silently suppresses ImportError so test collection/run proceeds whether ADK is present or not.

Changes

Cohort / File(s)	Change Summary
Test Plugin Fixture Addition packages/nvidia_nat_test/src/nat/test/plugin.py	Adds autouse session-scoped pytest fixture import_adk_early() which tries import google.adk and ignores ImportError (early ADK import workaround).

Sequence Diagram(s)

sequenceDiagram
    autonumber
    participant Pytest as Pytest (session start)
    participant Fixture as import_adk_early fixture
    participant ADK as google.adk
    participant Tests as Tests (collection & run)

    rect rgb(240,248,255)
    Pytest->>Fixture: invoke at session start (autouse)
    end

    rect rgb(240,255,240)
    Fixture->>ADK: try import google.adk
    alt import succeeds
        ADK-->>Fixture: module loaded
    else ImportError
        ADK-->>Fixture: raises ImportError (caught & suppressed)
    end
    end

    Fixture-->>Pytest: fixture completes
    Pytest->>Tests: continue collection & run

Loading

Estimated code review effort

🎯 1 (Trivial) | ⏱️ ~3 minutes

• Single-file, small try/except fixture addition.
• Files to inspect: packages/nvidia_nat_test/src/nat/test/plugin.py (verify fixture scope/autouse and import handling).

Pre-merge checks and finishing touches

✅ Passed checks (3 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The title clearly and concisely describes the main change: adding a work-around for a slow google-adk import issue, matching the actual implementation of an early import fixture.
Docstring Coverage	✅ Passed	Docstring coverage is 100.00% which is sufficient. The required threshold is 80.00%.

✨ Finishing touches

• 📝 Generate docstrings

🧪 Generate unit tests (beta)

• Create PR with unit tests
• Post copyable unit tests in a comment

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Reviewing files that changed from the base of the PR and between 321381e and fa36991.

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• packages/nvidia_nat_test/src/nat/test/plugin.py (1 hunks)

🧰 Additional context used

📓 Path-based instructions (2)

**/*

⚙️ CodeRabbit configuration file

**/*: # Code Review Instructions

• Ensure the code follows best practices and coding standards. - For Python code, follow
  PEP 20 and
  PEP 8 for style guidelines.
• Check for security vulnerabilities and potential issues. - Python methods should use type hints for all parameters and return values.
  Example:

  def my_function(param1: int, param2: str) -> bool:
      pass

• For Python exception handling, ensure proper stack trace preservation:
  • When re-raising exceptions: use bare raise statements to maintain the original stack trace,
    and use logger.error() (not logger.exception()) to avoid duplicate stack trace output.
  • When catching and logging exceptions without re-raising: always use logger.exception()
    to capture the full stack trace information.

Documentation Review Instructions - Verify that documentation and comments are clear and comprehensive. - Verify that the documentation doesn't contain any TODOs, FIXMEs or placeholder text like "lorem ipsum". - Verify that the documentation doesn't contain any offensive or outdated terms. - Verify that documentation and comments are free of spelling mistakes, ensure the documentation doesn't contain any

words listed in the ci/vale/styles/config/vocabularies/nat/reject.txt file, words that might appear to be
spelling mistakes but are listed in the ci/vale/styles/config/vocabularies/nat/accept.txt file are OK.

Misc. - All code (except .mdc files that contain Cursor rules) should be licensed under the Apache License 2.0,

and should contain an Apache License 2.0 header comment at the top of each file.

• Confirm that copyright years are up-to date whenever a file is changed.

Files:

• packages/nvidia_nat_test/src/nat/test/plugin.py

packages/**/*

⚙️ CodeRabbit configuration file

packages/**/*: - This directory contains optional plugin packages for the toolkit, each should contain a pyproject.toml file. - The pyproject.toml file should declare a dependency on nvidia-nat or another package with a name starting
with nvidia-nat-. This dependency should be declared using ~=<version>, and the version should be a two
digit version (ex: ~=1.0).

• Not all packages contain Python code, if they do they should also contain their own set of tests, in a
  tests/ directory at the same level as the pyproject.toml file.

Files:

• packages/nvidia_nat_test/src/nat/test/plugin.py

🪛 Ruff (0.14.5)

packages/nvidia_nat_test/src/nat/test/plugin.py

833-833: Unused noqa directive (non-enabled: F401)

Remove unused noqa directive

(RUF100)

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Actionable comments posted: 1

📜 Review details

Configuration used: Path: .coderabbit.yaml

Review profile: CHILL

Plan: Pro

📥 Commits

Reviewing files that changed from the base of the PR and between cb6c9d8 and 321381e.

📒 Files selected for processing (1)

• packages/nvidia_nat_test/src/nat/test/plugin.py (1 hunks)

🧰 Additional context used

📓 Path-based instructions (2)

**/*

⚙️ CodeRabbit configuration file

**/*: # Code Review Instructions

• Ensure the code follows best practices and coding standards. - For Python code, follow
  PEP 20 and
  PEP 8 for style guidelines.
• Check for security vulnerabilities and potential issues. - Python methods should use type hints for all parameters and return values.
  Example:

  def my_function(param1: int, param2: str) -> bool:
      pass

• For Python exception handling, ensure proper stack trace preservation:
  • When re-raising exceptions: use bare raise statements to maintain the original stack trace,
    and use logger.error() (not logger.exception()) to avoid duplicate stack trace output.
  • When catching and logging exceptions without re-raising: always use logger.exception()
    to capture the full stack trace information.

Documentation Review Instructions - Verify that documentation and comments are clear and comprehensive. - Verify that the documentation doesn't contain any TODOs, FIXMEs or placeholder text like "lorem ipsum". - Verify that the documentation doesn't contain any offensive or outdated terms. - Verify that documentation and comments are free of spelling mistakes, ensure the documentation doesn't contain any

words listed in the ci/vale/styles/config/vocabularies/nat/reject.txt file, words that might appear to be
spelling mistakes but are listed in the ci/vale/styles/config/vocabularies/nat/accept.txt file are OK.

Misc. - All code (except .mdc files that contain Cursor rules) should be licensed under the Apache License 2.0,

and should contain an Apache License 2.0 header comment at the top of each file.

• Confirm that copyright years are up-to date whenever a file is changed.

Referenced Documentation Contents

ci/vale/styles/config/vocabularies/nat/reject.txt:
Contains regex patterns (case-insensitive) for terms we want to reject (e.g., Agent-IQ, blacklist, TODO). Actio...

Files:

• packages/nvidia_nat_test/src/nat/test/plugin.py

packages/**/*

⚙️ CodeRabbit configuration file

packages/**/*: - This directory contains optional plugin packages for the toolkit, each should contain a pyproject.toml file. - The pyproject.toml file should declare a dependency on nvidia-nat or another package with a name starting
with nvidia-nat-. This dependency should be declared using ~=<version>, and the version should be a two
digit version (ex: ~=1.0).

• Not all packages contain Python code, if they do they should also contain their own set of tests, in a
  tests/ directory at the same level as the pyproject.toml file.

Files:

• packages/nvidia_nat_test/src/nat/test/plugin.py

🧠 Learnings (2)

📚 Learning: 2025-11-14T20:33:53.944Z

Learnt from: AnuradhaKaruppiah
Repo: NVIDIA/NeMo-Agent-Toolkit PR: 1181
File: packages/nvidia_nat_test/tests/test_test_llm.py:419-484
Timestamp: 2025-11-14T20:33:53.944Z
Learning: The NVIDIA NeMo-Agent-Toolkit project uses pytest-asyncio in strict mode (the default), which requires pytest.mark.asyncio decorator on all async test functions. All async tests in packages/nvidia_nat_test/tests/test_test_llm.py consistently follow this pattern.

Applied to files:

• packages/nvidia_nat_test/src/nat/test/plugin.py

📚 Learning: 2025-10-09T22:21:15.944Z

Learnt from: onkkul
Repo: NVIDIA/NeMo-Agent-Toolkit PR: 859
File: packages/nvidia_nat_autogen/src/nat/plugins/autogen/tool_wrapper.py:115-118
Timestamp: 2025-10-09T22:21:15.944Z
Learning: In `packages/nvidia_nat_autogen/src/nat/plugins/autogen/tool_wrapper.py`, when extracting parameters from input_schema at line 136, the code must handle both dataclasses (standard and Pydantic) and Pydantic BaseModels differently. Pydantic dataclasses have `__pydantic_fields__` (not `model_fields`), so use `dataclasses.fields()` for dataclasses and `model_fields` for BaseModels to properly extract function parameters.

Applied to files:

• packages/nvidia_nat_test/src/nat/test/plugin.py

[dagardner-nv]

/merge