Update project and configurations

intelligent_cabin/archive/tests/test_joint_nlu_integration.py

@@ -0,0 +1,93 @@
+from __future__ import annotations
+
+import unittest
+
+from app.schemas.intent import IntentDefinition
+from app.services.classifier import JointBertIntentClassifier
+from app.services.planner import HeuristicWorkflowPlanner
+from app.services.router import JointBertSlotExtractor
+
+
+class FakeJointNLU:
+    def __init__(self) -> None:
+        self._predictions = {
+            "把空调调到22度": {
+                "intent_id": "cabin_set_ac",
+                "intent_score": 0.93,
+                "candidates": [("cabin_set_ac", 0.93), ("cabin_ac_on", 0.04)],
+                "slots": {"temperature": 22},
+            },
+            "导航去公司，然后把空调调到22度": {
+                "intent_id": "cabin_nav_to",
+                "intent_score": 0.88,
+                "candidates": [("cabin_nav_to", 0.88), ("cabin_set_ac", 0.72)],
+                "slots": {"destination": "公司"},
+            },
+        }
+        self._slot_predictions = {
+            ("把空调调到22度", "cabin_set_ac"): {"temperature": 22},
+            ("导航去公司", "cabin_nav_to"): {"destination": "公司"},
+            ("把空调调到22度", "cabin_set_ac"): {"temperature": 22},
+        }
+
+    def warmup(self, sample_text: str = "打开车窗") -> bool:
+        _ = sample_text
+        return True
+
+    def predict(self, text: str, intents: list[IntentDefinition]):
+        from app.services.joint_nlu import JointCandidate, JointNluResult
+
+        raw = self._predictions[text]
+        candidates = [JointCandidate(intent_id=intent_id, score=score) for intent_id, score in raw["candidates"]]
+        return JointNluResult(
+            intent_id=raw["intent_id"],
+            intent_score=raw["intent_score"],
+            candidates=candidates,
+            slots=dict(raw["slots"]),
+        )
+
+    def extract_slots(self, text: str, intent: IntentDefinition):
+        return dict(self._slot_predictions.get((text, intent.intent_id), {}))
+
+    def extract_slots_by_intent_id(self, text: str, intent_id: str, required_slots=None):
+        _ = required_slots
+        return dict(self._slot_predictions.get((text, intent_id), {}))
+
+
+class JointNLUIntegrationTests(unittest.TestCase):
+    def setUp(self) -> None:
+        self.intents = [
+            IntentDefinition(intent_id="cabin_set_ac", plugin_id="x", domain="cabin", required_slots=["temperature"]),
+            IntentDefinition(intent_id="cabin_nav_to", plugin_id="x", domain="cabin", required_slots=["destination"]),
+            IntentDefinition(intent_id="cabin_ac_on", plugin_id="x", domain="cabin"),
+        ]
+        self.fake_nlu = FakeJointNLU()
+
+    def test_joint_classifier_uses_joint_nlu_intent_head(self) -> None:
+        classifier = JointBertIntentClassifier(self.fake_nlu, threshold=0.3, top_k=2)
+
+        result = classifier.predict("把空调调到22度", self.intents)
+
+        self.assertIsNotNone(result.intent)
+        self.assertEqual(result.intent.intent_id, "cabin_set_ac")
+        self.assertEqual(result.raw_candidates[0]["intent_id"], "cabin_set_ac")
+
+    def test_joint_slot_extractor_uses_joint_nlu_slots(self) -> None:
+        extractor = JointBertSlotExtractor(self.fake_nlu)
+
+        slots = extractor.extract("把空调调到22度", self.intents[0])
+
+        self.assertEqual(slots, {"temperature": 22})
+
+    def test_planner_prefers_joint_nlu_slots_for_each_clause(self) -> None:
+        planner = HeuristicWorkflowPlanner(joint_nlu=self.fake_nlu)
+
+        result = planner.plan("导航去公司，然后把空调调到22度", self.intents)
+
+        self.assertTrue(result.accepted)
+        self.assertEqual(result.steps[0].slots, {"destination": "公司"})
+        self.assertEqual(result.steps[1].slots, {"temperature": 22})
+
+
+if __name__ == "__main__":
+    unittest.main()