feat: Add AIM telemetry support and test it in xai sample

[zarinn3pal]

This PR adds a fix to AIM telemetry implementation . Both traces and metrics are logged and can be seen on the dashboard. Xai sample is modified to showcase the implementation

[gemini-code-assist]

Summary of Changes

Hello @zarinn3pal, 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 significantly enhances the GCP telemetry integration by introducing a new GcpTelemetry class. This centralizes the configuration and lifecycle management of tracing, metrics, and logging, ensuring a more robust and consistent telemetry experience. Key improvements include adjustments to metric export intervals, ensuring valid trace span durations for GCP, standardizing metric aggregation temporality, and enabling better log correlation. The changes are showcased through an updated XAI sample application.

Highlights

• Refactored GCP Telemetry Configuration: The core logic for configuring GCP tracing, metrics, and logging has been consolidated into a new GcpTelemetry class, centralizing management and improving consistency.
• Adjusted Metric Export Interval: The default metric export interval has been increased from 60 seconds to 5 minutes (DEFAULT_METRIC_EXPORT_INTERVAL_MS changed from 60000 to 300000) to potentially reduce export frequency and align with common practices.
• Ensured Valid Trace Span Durations: A new TimeAdjustedSpan class was introduced to guarantee that all trace spans have an end_time strictly greater than their start_time, which is a requirement for proper ingestion by GCP Trace.
• Standardized Metric Aggregation Temporality: The GenkitMetricExporter now explicitly forces AggregationTemporality.DELTA for all OpenTelemetry metric instrument types, ensuring consistent data representation across different telemetry components.
• Enhanced Logging Correlation with Traces: Structlog integration within the GcpTelemetry class now injects GCP-compatible trace context into log entries, enabling better correlation between logs and traces in monitoring tools.
• XAI Sample Integration: The xai-hello sample application has been updated to include the genkit-plugin-google-cloud and demonstrate the new GCP telemetry setup, showcasing both traces and metrics.

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[gemini-code-assist]

Code Review

This pull request introduces a significant and well-executed refactoring of the Google Cloud telemetry implementation. The new GcpTelemetry class effectively encapsulates the configuration and lifecycle management of tracing, metrics, and logging, which greatly improves code organization and maintainability. The changes also include important fixes for compatibility with Google Cloud services, such as adjusting span end times for Cloud Trace and forcing DELTA temporality for Cloud Monitoring. The addition of telemetry to the xai-hello sample is a valuable way to demonstrate and test this new functionality. I've included a couple of suggestions for minor improvements to further enhance the code quality.

[gemini-code-assist]

The deduplication logic for the structlog processor is flawed. The check for _inject_trace_context will not match the function being added, which is named inject_trace_context. This will cause the check to always fail, leading to duplicate processors being added if initialize() is called multiple times. Additionally, the getattr(p, '__self__', None) == self check is not suitable for closures as they don't have a __self__ attribute. A simpler check on the correct function name would be more effective and robust.

Suggested change

	getattr(p, '__name__', '') == '_inject_trace_context' and getattr(p, '__self__', None) == self
	for p in processors
	getattr(p, '__name__', '') == 'inject_trace_context' for p in processors

[gemini-code-assist]

The _log_input_and_output and _project_id attributes are already initialized in the AdjustingTraceExporter superclass via the super().__init__() call. This re-assignment is redundant and can be removed for cleaner code.

[zarinn3pal]