From 86df6db3af7ef337b5fa30f00d10a774637d54de Mon Sep 17 00:00:00 2001
From: salimlaimeche <laimeche160@gmail.com>
Date: Fri, 29 May 2026 04:38:26 +0200
Subject: [PATCH] chore(ci): add training regression smoke

---
 scripts/ci-smoke.mjs | 213 +++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 213 insertions(+)

diff --git a/scripts/ci-smoke.mjs b/scripts/ci-smoke.mjs
index fcad0c3..99abc2e 100644
--- a/scripts/ci-smoke.mjs
+++ b/scripts/ci-smoke.mjs
@@ -16,6 +16,7 @@ const results = [
   runGridWorldSmoke(),
   await runDqnSmoke(),
   runDroneTargetSmoke(),
+  runTrainingRegressionSmoke(),
 ];
 
 console.log(
@@ -832,6 +833,142 @@ async function runDqnSmoke() {
   });
 }
 
+function runTrainingRegressionSmoke() {
+  return withProjectDir("ignitionrl-training-regression-smoke-", (projectDir) => {
+    const gridProjectDir = join(projectDir, "grid-world.ignitionrl");
+    const droneProjectDir = join(projectDir, "drone-target.ignitionrl");
+
+    runCli(["init", "grid-world", gridProjectDir, "--json"]);
+    const gridTrain = runCli([
+      "train",
+      gridProjectDir,
+      "GridWorld-v0",
+      "--learner",
+      "tabular-q",
+      "--episodes",
+      "12",
+      "--max-steps",
+      "20",
+      "--seed",
+      "ci-training-regression-grid",
+      "--run-id",
+      "grid-world-training-regression",
+      "--checkpoint-id",
+      "final",
+      "--json",
+    ]);
+    const gridMetrics = runCli([
+      "metrics",
+      gridProjectDir,
+      "totalReward",
+      "--run-id",
+      "grid-world-training-regression",
+      "--json",
+    ]);
+    const gridMetricPoints = metricPointCount(
+      gridMetrics,
+      "grid-world-training-regression",
+      "totalReward",
+    );
+
+    assertTrainingRun(gridTrain, {
+      environmentId: "GridWorld-v0",
+      learner: "tabular-q",
+      runId: "grid-world-training-regression",
+    });
+    assertTrainingMetricListed(gridTrain, "learner.transitions");
+    assertTrainingMetricAtLeast(
+      gridTrain,
+      "summary.successRate",
+      gridTrain.summary.successRate,
+      0.8,
+    );
+    assertTrainingMetricAtLeast(
+      gridTrain,
+      "summary.totalReward",
+      gridTrain.summary.totalReward,
+      100,
+    );
+    assertTrainingMetricAtLeast(gridTrain, "metricPoints.totalReward", gridMetricPoints, 1);
+
+    runCli(["init", "drone-target", droneProjectDir, "--json"]);
+    const droneTrain = runCli([
+      "train",
+      droneProjectDir,
+      "DroneTarget-v0",
+      "--learner",
+      "linear-policy-search",
+      "--episodes",
+      "2",
+      "--max-steps",
+      "12",
+      "--seed",
+      "ci-training-regression-drone",
+      "--run-id",
+      "drone-target-training-regression",
+      "--checkpoint-id",
+      "final",
+      "--json",
+    ]);
+    const droneMetrics = runCli([
+      "metrics",
+      droneProjectDir,
+      "learner.bestReward",
+      "--run-id",
+      "drone-target-training-regression",
+      "--json",
+    ]);
+    const droneMetricPoints = metricPointCount(
+      droneMetrics,
+      "drone-target-training-regression",
+      "learner.bestReward",
+    );
+
+    assertTrainingRun(droneTrain, {
+      environmentId: "DroneTarget-v0",
+      learner: "linear-policy-search",
+      runId: "drone-target-training-regression",
+    });
+    assertTrainingMetricListed(droneTrain, "learner.bestReward");
+    assertTrainingMetricAtLeast(
+      droneTrain,
+      "summary.successRate",
+      droneTrain.summary.successRate,
+      0.5,
+    );
+    assertTrainingMetricAtLeast(
+      droneTrain,
+      "summary.bestReward",
+      droneTrain.summary.bestReward,
+      20,
+    );
+    assertTrainingMetricAtLeast(
+      droneTrain,
+      "metricPoints.learner.bestReward",
+      droneMetricPoints,
+      1,
+    );
+
+    return {
+      name: "TrainingRegression",
+      runs: [gridTrain.runId, droneTrain.runId],
+      doctorChecks: 0,
+      evalChecks: 5,
+      environments: 2,
+      environmentRuns: 2,
+      historyRows: 0,
+      studioSelectedRun: droneTrain.runId,
+      runDetailArtifacts: 0,
+      artifacts: 0,
+      episodes: gridTrain.summary.episodes + droneTrain.summary.episodes,
+      metricPoints: gridMetricPoints + droneMetricPoints,
+      rewardTerms: 0,
+      checkpoints: 2,
+      checkpointSource: `${gridTrain.runId}, ${droneTrain.runId}`,
+    };
+  });
+}
+
 function withProjectDir(prefix, fn) {
   const projectDir = mkdtempSync(join(tmpdir(), prefix));
 
@@ -879,3 +1016,79 @@ function assert(condition, message) {
     throw new Error(message);
   }
 }
+
+function assertTrainingRun(result, expected) {
+  assert(
+    result.command === "train",
+    "training regression command returned an unexpected payload",
+  );
+  assert(
+    result.environmentId === expected.environmentId,
+    `training regression selected wrong environment: run=${result.runId} expected=${expected.environmentId} actual=${result.environmentId}`,
+  );
+  assert(
+    result.learner === expected.learner,
+    `training regression selected wrong learner: run=${result.runId} expected=${expected.learner} actual=${result.learner}`,
+  );
+  assert(
+    result.runId === expected.runId,
+    `training regression selected wrong run: expected=${expected.runId} actual=${result.runId}`,
+  );
+  assert(
+    result.checkpoint?.id === "final",
+    `training regression did not persist final checkpoint: run=${result.runId}`,
+  );
+}
+
+function assertTrainingMetricListed(result, metric) {
+  if (!result.metricNames.includes(metric)) {
+    throw new Error(
+      [
+        "Training regression failed:",
+        `run=${result.runId}`,
+        `environment=${result.environmentId}`,
+        `learner=${result.learner}`,
+        `metric=${metric}`,
+        "reason=missing_metric_name",
+      ].join(" "),
+    );
+  }
+}
+
+function assertTrainingMetricAtLeast(result, metric, actual, expected) {
+  if (typeof actual !== "number" || !Number.isFinite(actual) || actual < expected) {
+    throw new Error(
+      [
+        "Training regression failed:",
+        `run=${result.runId}`,
+        `environment=${result.environmentId}`,
+        `learner=${result.learner}`,
+        `metric=${metric}`,
+        `actual=${String(actual)}`,
+        `expected>=${String(expected)}`,
+      ].join(" "),
+    );
+  }
+}
+
+function metricPointCount(result, runId, metric) {
+  assert(
+    result.command === "metrics",
+    "training regression metrics command returned an unexpected payload",
+  );
+
+  const run = result.runs.find((entry) => entry.id === runId);
+
+  if (run === undefined) {
+    throw new Error(
+      [
+        "Training regression failed:",
+        `run=${runId}`,
+        `metric=${metric}`,
+        "reason=missing_metric_run",
+      ].join(" "),
+    );
+  }
+
+  return run.points.length;
+}