Update project and configurations

intelligent_cabin/archive/scripts/test_local_bert_intent.py

@@ -0,0 +1,97 @@
+from __future__ import annotations
+
+import argparse
+import json
+import sys
+from pathlib import Path
+
+PROJECT_ROOT = Path(__file__).resolve().parents[1]
+if str(PROJECT_ROOT) not in sys.path:
+    sys.path.insert(0, str(PROJECT_ROOT))
+
+from app.core.config import settings
+from app.core.bootstrap import build_intent_registry
+from app.services.classifier import BertIntentClassifier
+from app.services.router import build_matcher_pipeline
+
+
+DEFAULT_MODEL_DIR = PROJECT_ROOT / "models/local_bert_intent"
+DEFAULT_LABEL_MAP = DEFAULT_MODEL_DIR / "label_map.json"
+
+
+def build_classifier(threshold: float, top_k: int) -> BertIntentClassifier:
+    return BertIntentClassifier(
+        model_path=str(DEFAULT_MODEL_DIR),
+        threshold=threshold,
+        label_map_path=str(DEFAULT_LABEL_MAP),
+        fallback=None,
+        top_k=top_k,
+    )
+
+
+def predict_once(text: str, threshold: float, top_k: int) -> dict[str, object]:
+    classifier = build_classifier(threshold=threshold, top_k=top_k)
+    registry = build_intent_registry()
+    intents = registry.list()
+    result = classifier.predict(text, intents)
+    matcher = build_matcher_pipeline(
+        registry,
+        ["classifier"],
+        classifier=classifier,
+        route_to_cloud_threshold=settings.local_route_to_cloud_threshold,
+        clarify_margin_threshold=settings.local_clarify_margin_threshold,
+    )
+    route_result = matcher.match(text)
+    fusion_stage = next((stage for stage in reversed(route_result.debug.stages) if stage.stage == "fusion"), None)
+    return {
+        "text": text,
+        "predicted_intent": result.intent.intent_id if result.intent is not None else None,
+        "score": round(result.score, 4),
+        "model_name": result.model_name,
+        "backend": result.backend_name,
+        "raw_label": result.raw_label,
+        "fallback_reason": result.fallback_reason,
+        "error_message": result.error_message,
+        "decision": route_result.debug.decision,
+        "decision_reason": route_result.debug.decision_reason,
+        "confidence_grade": route_result.debug.confidence_grade,
+        "unknown_detected": route_result.debug.unknown_detected,
+        "fusion_top_score": round(fusion_stage.score, 4) if fusion_stage is not None else None,
+        "top_candidates": [
+            {"intent_id": intent.intent_id, "score": round(score, 4)}
+            for intent, score in (result.candidates or [])
+        ],
+    }
+
+
+def interactive_loop(threshold: float, top_k: int) -> None:
+    print("本地 BERT 意图测试已启动，输入一句话直接查看预测结果，输入 exit 退出。")
+    while True:
+        try:
+            text = input("\n请输入问题> ").strip()
+        except EOFError:
+            print()
+            break
+        if not text:
+            continue
+        if text.lower() in {"exit", "quit", "q"}:
+            break
+        result = predict_once(text, threshold=threshold, top_k=top_k)
+        print(json.dumps(result, ensure_ascii=False, indent=2))
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description="本地 BERT 意图识别测试脚本")
+    parser.add_argument("--text", type=str, default="", help="单次测试文本")
+    parser.add_argument("--threshold", type=float, default=0.0, help="BERT 置信度阈值")
+    parser.add_argument("--top-k", type=int, default=3, help="返回候选数量")
+    args = parser.parse_args()
+
+    if args.text.strip():
+        print(json.dumps(predict_once(args.text.strip(), threshold=args.threshold, top_k=args.top_k), ensure_ascii=False, indent=2))
+        return
+    interactive_loop(threshold=args.threshold, top_k=args.top_k)
+
+
+if __name__ == "__main__":
+    main()