feat: Wire LDAIMetrics tool_calls and duration_ms into tracker

packages/sdk/server-ai/tests/test_tracker.py

@@ -909,3 +909,111 @@ def test_client_create_tracker_fails_on_invalid_json():
     result = ai_client.create_tracker(bad_token, context)
     assert not result.is_success()
     assert "Invalid resumption token" in result.error
+
+
+# --- PR 10: LDAIMetrics enrichment + tracker integration ---
+
+
+def test_ldai_metrics_to_dict_includes_tool_calls_and_duration_ms():
+    metrics = LDAIMetrics(
+        success=True,
+        usage=TokenUsage(total=10, input=4, output=6),
+        tool_calls=["search", "lookup"],
+        duration_ms=123,
+    )
+    d = metrics.to_dict()
+    assert d["success"] is True
+    assert d["usage"] == {"total": 10, "input": 4, "output": 6}
+    assert d["toolCalls"] == ["search", "lookup"]
+    assert d["durationMs"] == 123
+
+
+def test_ldai_metrics_to_dict_omits_optional_fields_when_none():
+    metrics = LDAIMetrics(success=False)
+    d = metrics.to_dict()
+    assert d == {"success": False}
+
+
+def test_track_metrics_of_uses_metrics_duration_ms_when_set(client: LDClient):
+    context = Context.create("user-key")
+    tracker = LDAIConfigTracker(
+        ld_client=client, run_id="test-run-id", config_key="config-key",
+        variation_key="variation-key", version=3, model_name="m",
+        provider_name="p", context=context,
+    )
+
+    def fn():
+        return "done"
+
+    def extract(_r):
+        return LDAIMetrics(success=True, duration_ms=999)
+
+    tracker.track_metrics_of(extract, fn)
+    assert tracker.get_summary().duration_ms == 999
+
+
+@pytest.mark.asyncio
+async def test_track_metrics_of_async_uses_metrics_duration_ms_when_set(client: LDClient):
+    context = Context.create("user-key")
+    tracker = LDAIConfigTracker(
+        ld_client=client, run_id="test-run-id", config_key="config-key",
+        variation_key="variation-key", version=3, model_name="m",
+        provider_name="p", context=context,
+    )
+
+    async def fn():
+        return "done"
+
+    def extract(_r):
+        return LDAIMetrics(success=True, duration_ms=42)
+
+    await tracker.track_metrics_of_async(extract, fn)
+    assert tracker.get_summary().duration_ms == 42
+
+
+def test_track_metrics_of_calls_track_tool_calls_when_present(client: LDClient):
+    context = Context.create("user-key")
+    tracker = LDAIConfigTracker(
+        ld_client=client, run_id="test-run-id", config_key="config-key",
+        variation_key="variation-key", version=3, model_name="m",
+        provider_name="p", context=context,
+    )
+
+    def fn():
+        return "done"
+
+    def extract(_r):
+        return LDAIMetrics(success=True, tool_calls=["foo", "bar"])
+
+    tracker.track_metrics_of(extract, fn)
+    summary = tracker.get_summary()
+    assert summary.tool_calls == ["foo", "bar"]
+    # One $ld:ai:tool_call event per tool key.
+    tool_call_events = [
+        c for c in client.track.mock_calls  # type: ignore
+        if c.args[0] == "$ld:ai:tool_call"
+    ]
+    assert len(tool_call_events) == 2
+
+
+def test_track_metrics_of_skips_track_tool_calls_when_absent(client: LDClient):
+    context = Context.create("user-key")
+    tracker = LDAIConfigTracker(
+        ld_client=client, run_id="test-run-id", config_key="config-key",
+        variation_key="variation-key", version=3, model_name="m",
+        provider_name="p", context=context,
+    )
+
+    def fn():
+        return "done"
+
+    def extract(_r):
+        return LDAIMetrics(success=True, usage=None)
+
+    tracker.track_metrics_of(extract, fn)
+    assert tracker.get_summary().tool_calls is None
+    tool_call_events = [
+        c for c in client.track.mock_calls  # type: ignore
+        if c.args[0] == "$ld:ai:tool_call"
+    ]
+    assert tool_call_events == []