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core/explainer.py

@@ -2,7 +2,6 @@ import re
 from typing import Any, Dict, List, Tuple
 
 import numpy as np
-import shap
 import torch
 from transformers import DistilBertForSequenceClassification, DistilBertTokenizer
 
@@ -10,6 +9,16 @@ from transformers import DistilBertForSequenceClassification, DistilBertTokenize
 class SHAPExplainer:
     def __init__(self, model_path: str = "."):
         print("🚀 Initializing SHAP Explainer...")
+        # Import shap lazily to avoid triggering optional plotting imports
+        # during app startup (e.g., Spaces reload scanner).
+        try:
+            import shap  # type: ignore
+
+            self._shap = shap
+        except Exception as e:
+            print(f"⚠️ SHAP import failed; falling back to heuristic explainer: {e}")
+            self._shap = None
+
         self.model = DistilBertForSequenceClassification.from_pretrained(model_path)
         self.tokenizer = DistilBertTokenizer.from_pretrained(model_path)
 
@@ -40,9 +49,13 @@ class SHAPExplainer:
 
         self.model_predict = model_predict
 
+        if self._shap is None:
+            self.explainer = None
+            return
+
         try:
-            masker = shap.maskers.Text(tokenizer=self.tokenizer)
-            self.explainer = shap.Explainer(self.model_predict, masker=masker)
+            masker = self._shap.maskers.Text(tokenizer=self.tokenizer)
+            self.explainer = self._shap.Explainer(self.model_predict, masker=masker)
             print("✅ SHAP Explainer initialized successfully!")
         except Exception as e:
             print(f"❌ Error initializing SHAP: {e}")