chore(experiments): remove dead paths from the AI summary tool

frontend/snapshots.yml

@@ -6337,7 +6337,7 @@ snapshots:
     scenes-app-experiments--experiment-frequentist-two-variants--light:
         hash: v1.k794b7964.ec64583fd2debf87822296f1c9fc10e73c1c6b7e31fe55f0ca974d3920f8bd14.Ch64gBgjo0wR0Ypvkhap6047UPjXBaWSQCNoKDOiNHc
     scenes-app-experiments--experiment-stopped-with-conclusion--dark:
-        hash: v1.k794b7964.37e8127d5a33175889cf1da00e80998b1858fd3713fe5c0c1ec42ff0bb1da220.oIA6fAIpYfvfCAh_6TQs-uqDeMEONwTb3luZF1rzBs4
+        hash: v1.k794b7964.e347bbe9e217d7cbd915b09b362a9d995285c1f6492229235ce3dcef74e49f30.5xV99CaEDXp-xFACHoS4M9vQ6zFGOjestb-iW79F5Q4
     scenes-app-experiments--experiment-stopped-with-conclusion--light:
         hash: v1.k794b7964.793a4b6109b2c0ab65b07d9eaefd1c8862f12bfc7f33b2f452ad20044396b2a7.6B0Meq7yO75vBEoBmuP2dNl2oKTugzzr_IKTcJHhEi0
     scenes-app-experiments--experiment-with-funnel-metric--dark:

frontend/src/scenes/experiments/components/SummarizeExperimentButton.tsx

@@ -24,33 +24,18 @@ import { isLaunched } from '../experimentsLogic'
 interface MinimalExperimentSummaryContext {
     experiment_id: number | string
     experiment_name: string
-    /** ISO8601 timestamp of when the frontend last refreshed the data */
-    frontend_last_refresh: string | null
 }
 
 function useExperimentSummaryMaxTool(): ReturnType<typeof useMaxTool> {
-    const { experiment, orderedPrimaryMetricsWithResults, primaryMetricsResults, secondaryMetricsResults } =
-        useValues(experimentLogic)
-
-    // Get the most recent last_refresh timestamp from metric results
-    const frontendLastRefresh = useMemo(() => {
-        const allResults = [...(primaryMetricsResults || []), ...(secondaryMetricsResults || [])]
-        const timestamps = allResults
-            .map((r) => r?.last_refresh)
-            .filter((t): t is string => typeof t === 'string')
-            .sort()
-            .reverse()
-        return timestamps[0] || null
-    }, [primaryMetricsResults, secondaryMetricsResults])
+    const { experiment, orderedPrimaryMetricsWithResults } = useValues(experimentLogic)
 
     // Simplified context - backend will fetch full data using experiment_id
     const maxToolContext = useMemo(
         (): MinimalExperimentSummaryContext => ({
             experiment_id: experiment.id,
             experiment_name: experiment.name || 'Unnamed experiment',
-            frontend_last_refresh: frontendLastRefresh,
         }),
-        [experiment.id, experiment.name, frontendLastRefresh]
+        [experiment.id, experiment.name]
     )
 
     const shouldShowMaxSummaryTool = useMemo(() => {

products/experiments/backend/experiment_summary_data_service.py

@@ -2,7 +2,6 @@
 from dataclasses import dataclass
 from datetime import datetime
 from typing import Any, TypeIs, Union
-from zoneinfo import ZoneInfo
 
 from django.conf import settings
 
@@ -57,12 +56,6 @@ class ExposureQueryResult:
 
 MAX_CONCURRENT_EXPERIMENT_SUMMARY_QUERIES = 10
 
-# This threshold is just to avoid minor discrepancies in timestamps.
-# The check itself compares the frontend timestamp with the last
-# backend refresh timestamp. So leaving the browser open while not
-# having any new data on the backend will not trigger a warning.
-FRESHNESS_THRESHOLD_SECONDS = 60
-
 ExperimentMetricType = Union[
     ExperimentMeanMetric, ExperimentFunnelMetric, ExperimentRatioMetric, ExperimentRetentionMetric
 ]
@@ -398,32 +391,3 @@ def process_metric_results(
             pending_calculation=pending_calculation,
             omitted_metric_count=omitted_metric_count,
         )
-
-    def check_data_freshness(
-        self, frontend_last_refresh: str | None, backend_last_refresh: datetime | None
-    ) -> str | None:
-        """
-        Check if there's a significant difference between frontend and backend data freshness.
-        Returns a warning message if data might have changed, None otherwise.
-        """
-        if not frontend_last_refresh or not backend_last_refresh:
-            return None
-
-        try:
-            frontend_time = datetime.fromisoformat(frontend_last_refresh.replace("Z", "+00:00"))
-            if frontend_time.tzinfo is None:
-                frontend_time = frontend_time.replace(tzinfo=ZoneInfo("UTC"))
-            if backend_last_refresh.tzinfo is None:
-                backend_last_refresh = backend_last_refresh.replace(tzinfo=ZoneInfo("UTC"))
-
-            time_diff = abs((backend_last_refresh - frontend_time).total_seconds())
-            if time_diff > FRESHNESS_THRESHOLD_SECONDS:
-                return (
-                    f"**Note:** The experiment data has been updated since you loaded this page "
-                    f"(approximately {int(time_diff / 60)} minutes ago). "
-                    f"The summary below reflects the most current data."
-                )
-        except (ValueError, TypeError):
-            pass
-
-        return None

products/experiments/backend/max_tools.py

@@ -6,8 +6,6 @@
 from pydantic import BaseModel, Field
 from rest_framework.exceptions import ValidationError
 
-from posthog.schema import MaxExperimentMetricResult
-
 from posthog.clickhouse.query_tagging import Product, tags_context
 from posthog.event_usage import EventSource
 from posthog.session_recordings.session_recording_api import list_recordings_from_query
@@ -214,7 +212,7 @@ def create_experiment() -> Experiment:
 class ExperimentSummaryArgs(BaseModel):
     experiment_id: int | None = Field(
         default=None,
-        description="The ID of the experiment to summarize. Only required when results context is not already available (e.g. when the user asks about an experiment from chat).",
+        description="The ID of the experiment to summarize. Not needed when the user is viewing an experiment (taken from context).",
     )
 
 
@@ -239,14 +237,6 @@ async def _arun_impl(self, experiment_id: int | None = None) -> tuple[str, dict[
 
             resolved_experiment_id = int(resolved_experiment_id)
 
-            # When frontend context has metrics data, use it directly
-            if (
-                context.get("primary_metrics_results") is not None
-                or context.get("secondary_metrics_results") is not None
-            ):
-                return await self._format_from_context(resolved_experiment_id, context)
-
-            # Otherwise, fetch data via the data service (agent-initiated call)
             return await self._fetch_and_format(resolved_experiment_id)
 
         except MaxToolAccessDeniedError:
@@ -262,40 +252,6 @@ async def _arun_impl(self, experiment_id: int | None = None) -> tuple[str, dict[
             )
             return f"Failed to summarize experiment: {str(e)}", {"error": "summary_failed", "details": str(e)}
 
-    async def _format_from_context(self, experiment_id: int, context: dict) -> tuple[str, dict[str, Any]]:
-        """Format experiment data using pre-computed context from the frontend."""
-        experiment_context = ExperimentContext(team=self._team, experiment_id=experiment_id)
-        experiment = await experiment_context.aget_experiment()
-        if experiment is None:
-            return f"Experiment {experiment_id} not found", {"error": "not_found"}
-
-        await self.check_object_access(experiment, "viewer", resource="experiment", action="read")
-
-        try:
-            primary_metrics = [MaxExperimentMetricResult(**m) for m in context.get("primary_metrics_results", [])]
-            secondary_metrics = [MaxExperimentMetricResult(**m) for m in context.get("secondary_metrics_results", [])]
-        except Exception as e:
-            capture_exception(
-                e,
-                properties={
-                    "team_id": self._team.id,
-                    "user_id": self._user.id,
-                    "experiment_id": experiment_id,
-                },
-            )
-            return f"Invalid experiment context: {str(e)}", {"error": "invalid_context", "details": str(e)}
-
-        exposures = context.get("exposures")
-
-        formatted_data = await experiment_context.format_experiment_results_data(
-            experiment,
-            exposures=exposures,
-            primary_metrics_results=primary_metrics,
-            secondary_metrics_results=secondary_metrics,
-        )
-
-        return self._build_result(experiment, formatted_data, primary_metrics, secondary_metrics)
-
     async def _fetch_and_format(self, experiment_id: int) -> tuple[str, dict[str, Any]]:
         """Fetch experiment data from query runners and format it."""
         experiment_context = ExperimentContext(team=self._team, experiment_id=experiment_id)

products/experiments/backend/test/test_experiment_summary_tool.py

@@ -248,59 +248,6 @@ async def acreate_experiment(self, name="test-experiment", feature_flag=None, wi
             metrics_secondary=[],
         )
 
-    @freeze_time("2020-01-10T12:00:00Z")
-    async def test_check_data_freshness_no_warning_when_recent(self):
-        data_service = ExperimentSummaryDataService(self.team, self.user)
-
-        # 30 seconds difference - well within the 1 minute threshold
-        frontend_refresh = "2020-01-10T11:59:00Z"
-        backend_refresh = datetime(2020, 1, 10, 11, 59, 30, tzinfo=ZoneInfo("UTC"))
-
-        warning = data_service.check_data_freshness(frontend_refresh, backend_refresh)
-        self.assertIsNone(warning)
-
-    @freeze_time("2020-01-10T12:00:00Z")
-    async def test_check_data_freshness_warning_when_stale(self):
-        data_service = ExperimentSummaryDataService(self.team, self.user)
-
-        frontend_refresh = "2020-01-10T10:00:00Z"
-        backend_refresh = datetime(2020, 1, 10, 11, 30, tzinfo=ZoneInfo("UTC"))
-
-        warning = data_service.check_data_freshness(frontend_refresh, backend_refresh)
-        assert warning is not None
-        self.assertIn("data has been updated", warning)
-
-    @freeze_time("2020-01-10T12:00:00Z")
-    async def test_check_data_freshness_warning_at_threshold_boundary(self):
-        data_service = ExperimentSummaryDataService(self.team, self.user)
-
-        # 61 seconds difference - just over the 1 minute (60 second) threshold
-        frontend_refresh = "2020-01-10T11:58:00Z"
-        backend_refresh = datetime(2020, 1, 10, 11, 59, 1, tzinfo=ZoneInfo("UTC"))
-
-        warning = data_service.check_data_freshness(frontend_refresh, backend_refresh)
-        assert warning is not None
-        self.assertIn("data has been updated", warning)
-
-    @freeze_time("2020-01-10T12:00:00Z")
-    async def test_check_data_freshness_no_warning_at_threshold_boundary(self):
-        data_service = ExperimentSummaryDataService(self.team, self.user)
-
-        # Exactly 60 seconds - at the threshold (not over), should NOT trigger warning
-        frontend_refresh = "2020-01-10T11:58:00Z"
-        backend_refresh = datetime(2020, 1, 10, 11, 59, 0, tzinfo=ZoneInfo("UTC"))
-
-        warning = data_service.check_data_freshness(frontend_refresh, backend_refresh)
-        self.assertIsNone(warning)
-
-    @freeze_time("2020-01-10T12:00:00Z")
-    async def test_check_data_freshness_handles_none_values(self):
-        data_service = ExperimentSummaryDataService(self.team, self.user)
-
-        self.assertIsNone(data_service.check_data_freshness(None, None))
-        self.assertIsNone(data_service.check_data_freshness("2020-01-10T10:00:00Z", None))
-        self.assertIsNone(data_service.check_data_freshness(None, datetime.now(ZoneInfo("UTC"))))
-
     @freeze_time("2020-01-10T12:00:00Z")
     async def test_fetch_experiment_data_with_mocked_query_runners(self):
         experiment = await self.acreate_experiment(name="query-runner-test", with_metrics=True)