feat: Update OpenAI graph runner to return AgentGraphRunnerResult with GraphMetrics#155
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…h GraphMetrics Remove all direct LaunchDarkly tracker calls from OpenAIAgentGraphRunner. The runner now collects per-node metrics via _NodeMetricsAccumulator (a lightweight accumulator replacing the per-node LDAIConfigTracker) and returns AgentGraphRunnerResult with populated GraphMetrics (path, duration_ms, usage, node_metrics). Graph-level and per-node tracking events are emitted by ManagedAgentGraph._flush_graph_tracking() from the result. ManagedAgentGraph._flush_graph_tracking() is extended to also drive per-node tracking from result.metrics.node_metrics using the graph definition's node tracker factories. Integration tests in test_tracking_openai_agents.py are updated to run through the full ManagedAgentGraph pipeline (ManagedAgentGraph.run()) so tracking events are emitted by the managed layer as intended. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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Summary
OpenAIAgentGraphRunner_NodeMetricsAccumulator— a lightweight per-node metrics collector replacingLDAIConfigTrackerinside the runnerAgentGraphRunnerResultwith populatedGraphMetrics(path,duration_ms,usage,node_metrics)ManagedAgentGraph._flush_graph_tracking()from the result metricsManagedAgentGraph._flush_graph_tracking()extended to drive per-node tracking fromresult.metrics.node_metricsusing graph node tracker factoriesManagedAgentGraph.run()pipeline (tracking events now come from the managed layer)track_handoff_success()calls removed (per spec:pathfield is sufficient; handoffs are not inGraphMetrics)Depends on
Test plan
uv run pytest packages/ai-providers/server-ai-openai/tests/)test_openai_agent_graph_runner.py: runner returns new shape, no tracker createdtest_tracking_openai_agents.py: graph-level and per-node events emitted through managed layer🤖 Generated with Claude Code