python-code-reviewer

Reviewing Python OpenInference instrumentation packages involves validating test setup, CI configuration, semantic conventions, and span hierarchy to ensure the instrumentor meets project standards before human review.

Validating test setup and CI configuration for OpenInference instrumentors requires checking dependency files like tox.ini and test-requirements.txt to verify accurate library versioning and ensure automated testing patterns are correctly configured.

Semantic conventions and span hierarchy in Python instrumentation code define the standardized naming and parent-child relationships for tracing spans, ensuring consistent telemetry data collection across the OpenInference ecosystem.

Yes, you can use an automated code reviewer to pre-flight check a new OpenInference Python instrumentor pull request, catching potential issues in testing patterns and CI configurations before human review.

Yes, the OpenInference code review process checks for adherence to specific testing patterns, ensuring that Python instrumentors follow project standards for correctness, completeness, and best practices across the ecosystem.

When submitting a pull request for an openinference-instrumentation-openai package, you should check test setup, CI configuration, semantic conventions, and span hierarchy to ensure the code adheres to OpenInference project standards.