Update app.py

app.py

@@ -131,8 +131,15 @@ class CustomRagRetriever:
         # Load PCA if it exists
         pca_path = os.path.join(os.path.dirname(model_path), "pca_model.pkl")
         if os.path.exists(pca_path):
-            with open(pca_path, 'rb') as f:
-                self.pca = pickle.load(f)
+            try:
+                with open(pca_path, 'rb') as f:
+                    self.pca = pickle.load(f)
+            except ModuleNotFoundError:
+                print("Warning: Could not load PCA model due to numpy version mismatch. Continuing without PCA.")
+                self.pca = None
+            except Exception as e:
+                print(f"Warning: Error loading PCA model: {str(e)}. Continuing without PCA.")
+                self.pca = None
 
     def retrieve(self, query, top_k=10):
         print(f"Retrieving properties for query: {query}")
@@ -145,11 +152,15 @@ class CustomRagRetriever:
                     device=device,
                     normalize_embeddings=True
                 )
-                # Convert to FP16 after encoding
+                # Convert to FP32
                 query_embedding = query_embedding.astype(np.float32)
 
+            # Only apply PCA if it was successfully loaded
             if self.pca is not None:
-                query_embedding = self.pca.transform(query_embedding)
+                try:
+                    query_embedding = self.pca.transform(query_embedding)
+                except Exception as e:
+                    print(f"Warning: Error applying PCA transformation: {str(e)}")
 
             distances, indices = self.index.search(query_embedding, top_k)