Update app.py

app.py

@@ -89,13 +89,13 @@ def key_gen_fn() -> Dict:
 
     if not evaluation_key_path.is_file():
         error_message = (
-            f"Error Encountered While generating the evaluation {evaluation_key_path.is_file()=}"
+            f"生成密钥时发生异常 {evaluation_key_path.is_file()=}"
         )
         print(error_message)
         return {gen_key_btn: gr.update(value=error_message)}
     else:
         print("Keys have been generated ✅")
-        return {gen_key_btn: gr.update(value="Keys have been generated ✅")}
+        return {gen_key_btn: gr.update(value="密钥生成成功！ ✅")}
 
 
 def encrypt_doc_fn(doc):
@@ -103,7 +103,7 @@ def encrypt_doc_fn(doc):
     print(f"\n------------ Step 2.1: Doc encryption: {doc=}")
 
     if not (KEYS_DIR / f"{USER_ID}/evaluation_key").is_file():
-        return {encrypted_doc_box: gr.update(value="Error ❌: Please generate the key first!", lines=10)}
+        return {encrypted_doc_box: gr.update(value="Error ❌: 请先生成密钥！", lines=10)}
 
     # Retrieve the client API
     client = FHEModelClient(path_dir=DEPLOYMENT_DIR, key_dir=KEYS_DIR / f"{USER_ID}")
@@ -138,14 +138,13 @@ def encrypt_query_fn(query):
     print(f"\n------------ Step 2: Query encryption: {query=}")
 
     if not (KEYS_DIR / f"{USER_ID}/evaluation_key").is_file():
-        return {output_encrypted_box: gr.update(value="Error ❌: Please generate the key first!", lines=8)}
+        return {output_encrypted_box: gr.update(value="Error ❌: 请先生成密钥！", lines=8)}
 
     if is_user_query_valid(query):
         return {
             query_box: gr.update(
                 value=(
-                    "Unable to process ❌: The request exceeds the length limit or falls "
-                    "outside the scope of this document. Please refine your query."
+                    "不能执行 ❌: 请求超过了长度限制。修改查询后重试。 "
                 )
             )
         }
@@ -174,7 +173,7 @@ def encrypt_query_fn(query):
 
         encrypted_tokens.append(encrypted_x)
 
-    print("Data encrypted ✅ on Client Side")
+    print("数据已在客户端加密。 ✅")
 
     assert len({len(token) for token in encrypted_tokens}) == 1
 
@@ -203,15 +202,15 @@ def send_input_fn(query) -> Dict:
 
     if not evaluation_key_path.is_file():
         error_message = (
-            "Error Encountered While Sending Data to the Server: "
-            f"The key has been generated correctly - {evaluation_key_path.is_file()=}"
+            "发送数据到服务器时发生异常："
+            f"密钥已经正常生成 - {evaluation_key_path.is_file()=}"
         )
         return {anonymized_query_output: gr.update(value=error_message)}
 
     if not encrypted_input_path.is_file():
         error_message = (
-            "Error Encountered While Sending Data to the Server: The data has not been encrypted "
-            f"correctly on the client side - {encrypted_input_path.is_file()=}"
+            "发送数据到服务器时发生异常： 数据没有加密"
+            f"在客户端正确 - {encrypted_input_path.is_file()=}"
         )
         return {anonymized_query_output: gr.update(value=error_message)}
 
@@ -232,7 +231,7 @@ def send_input_fn(query) -> Dict:
         data=data,
         files=files,
     ) as resp:
-        print("Data sent to the server ✅" if resp.ok else "Error ❌ in sending data to the server")
+        print("数据发送到服务器。 ✅" if resp.ok else "发送到服务器时出现错误。 ❌ ")
 
 
 def run_fhe_in_server_fn() -> Dict:
@@ -278,7 +277,7 @@ def run_fhe_in_server_fn() -> Dict:
             }
         else:
             time.sleep(1)
-            print(f"The query anonymization was computed in {response.json():.2f} s per token.")
+            print(f"匿名化查询在以每句柄{response.json():.2f} 秒的速率执行。")
 
 
 def get_output_fn() -> Dict:
@@ -310,7 +309,7 @@ def get_output_fn() -> Dict:
         data=data,
     ) as response:
         if response.ok:
-            print("Data received ✅ from the remote Server")
+            print("数据从远程服务器接收到。 ✅")
             response_data = response.json()
             encrypted_output_base64 = response_data["encrypted_output"]
             length_encrypted_output_base64 = response_data["length"]
@@ -397,7 +396,7 @@ def decrypt_fn(text) -> Dict:
     else:
         identified_df = pd.DataFrame(columns=["Identified Words", "Probability"])
 
-    print("Decryption done ✅ on Client Side")
+    print("在客户端完成了解密。  ✅")
 
     return anonymized_text, identified_df