feat: Add ManagedGraphResult, GraphMetricSummary, and AgentGraphRunnerResult types#151
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…nnerResult - OpenAIModelRunner.run() implements the unified Runner protocol; returns RunnerResult with content, metrics (LDAIMetrics), raw, and parsed fields. Structured output is supported via the output_type parameter. - OpenAIAgentRunner.run() updated to return RunnerResult; populates tool_calls in LDAIMetrics from observed openai-agents ToolCallItems. - Legacy invoke_model() and invoke_structured_model() retained as deprecated adapters that delegate to run() and wrap results into ModelResponse / StructuredResponse for backward compatibility. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
… RunnerResult - LangChainModelRunner.run() implements the unified Runner protocol; returns RunnerResult with content, metrics (LDAIMetrics), raw, and parsed fields. Structured output is supported via the output_type parameter. - LangChainAgentRunner.run() updated to return RunnerResult; populates tool_calls in LDAIMetrics from observed tool_calls in message responses. - Legacy invoke_model() and invoke_structured_model() retained as deprecated adapters that delegate to run() and wrap results into ModelResponse / StructuredResponse for backward compatibility. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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…rResult types - Add GraphMetrics dataclass (runner-layer return type for graph runs) - Add GraphMetricSummary dataclass (managed-layer metrics, analogous to LDAIMetricSummary for single-model invocations) - Add ManagedGraphResult dataclass (managed-layer return type from ManagedAgentGraph) - Add AgentGraphRunnerResult dataclass (future runner return type, no evaluations field) - ManagedAgentGraph.run() now returns ManagedGraphResult with GraphMetricSummary built from the runner's AgentGraphResult metrics - Export all new types from ldai package Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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Apr 29, 2026
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| Delegates to the underlying AgentGraphRunner, which handles | ||
| execution and all auto-tracking internally. | ||
| Delegates to the underlying AgentGraphRunner, builds a |
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This seems redundant given the parm and return docs below.
| content=result.output, | ||
| metrics=summary, | ||
| raw=result.raw, | ||
| evaluations=None, |
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This will be added in a follow up PR #153
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Summary
Adds the managed-layer return type and metric summary for agent graph execution, mirroring the per-config types introduced in PR 8.
GraphMetrics— runner-layer metrics (success, path, duration_ms, usage, node_metrics).GraphMetricSummary— managed-layer summary, analogous toLDAIMetricSummary(adds resumption_token).ManagedGraphResult— return type ofManagedAgentGraph.run()(content, metrics, raw, evaluations task).AgentGraphRunnerResult— pure runner-layer return type (noevaluationsfield).ManagedAgentGraph.run()now returnsManagedGraphResultand builds aGraphMetricSummaryfrom the underlying runner'sLDAIMetrics(path/node_metrics will be populated once graph runners migrate in PR 11).Stack
PR 7 → PR 8 → PR 8-openai → PR 8-langchain → PR 9 (this) → PR 10 → PR 11 → PR 11-openai → PR 11-langchain → PR 12
Test plan
make test— 261 tests pass (server-ai 140, langchain 81, openai 40)make lint— mypy clean🤖 Generated with Claude Code