Update app.py

app.py

@@ -34,7 +34,7 @@ model_names=['financial_rating','legal_rating']
 
 
 FHE_MODEL_PATH = "deployment/financial_rating"
-FHE_LEGAL_PATH = "deployment/legal_rating"
+#FHE_LEGAL_PATH = "deployment/legal_rating"
 #FHE_LEGAL_PATH="deployment/legal_rating"
 
 print("Loading the transformer model...")
@@ -169,19 +169,9 @@ def keygen(selected_tasks):
 def encode_quantize_encrypt(text, user_id):
     if not user_id:
         raise gr.Error("You need to generate FHE keys first.")
-    if "legal_rating" in model_names:
-        fhe_api = FHEModelClient(FHE_LEGAL_PATH, f".fhe_keys/{user_id}")
-        encodings =vectorizer.fit_transform([text]).toarray()
-        if encodings.shape[1] < 1736:
-            # 在后面填充零
-            padding = np.zeros((1, 1736 - encodings.shape[1]))
-            encodings = np.hstack((encodings, padding))
-        elif encodings.shape[1] > 1736:
-            # 截取前1736列
-            encodings = encodings[:, :1736]
-    else:
-        fhe_api = FHEModelClient(FHE_MODEL_PATH, f".fhe_keys/{user_id}")
-        encodings = transformer_vectorizer.transform([text])
+
+    fhe_api = FHEModelClient(FHE_MODEL_PATH, f".fhe_keys/{user_id}")
+    encodings = transformer_vectorizer.transform([text])
     
     fhe_api.load()
     quantized_encodings = fhe_api.model.quantize_input(encodings).astype(numpy.uint8)