翻译接口优化

app/api/api_prompt_generation.py

@@ -26,7 +26,7 @@ def prompt_generation(request_data: PromptGenerationImageModel):
     """
     try:
         logger.info(f"prompt_generation request item is : @@@@@@:{request_data}")
-        data = translate_to_en(request_data.text)
+        data = translate_to_en("[" + request_data.text + "]")
         logger.info(f"prompt_generation response @@@@@@:{data}")
     except Exception as e:
         logger.warning(f"prompt_generation Run Exception @@@@@@:{e}")

app/service/prompt_generation/chatgpt_for_translation.py

@@ -25,27 +25,38 @@ def translate_to_en(text):
         output the input text exactly as it is without any modifications or additions.
         If there are grammatical errors, correct them and then output the sentence."""
     )
+
+    prefix = (
+        """
+        Translate everything within the brackets [] into English.
+        Never translate or modify any English input.
+        The input must be fully translated into coherent English sentences.
+        Never present the translation results in the format 
+        "The translation of \"Material suave\" into English would be \"Smooth material.\"". Instead, directly output "Smooth material".
+        """
+    )
     messages = [
-        {
-            "content": template,  # 系统message
-            "role": "system"
-        },
+        # {
+        # Translate the entire text and ensure the output is a complete and coherent sentence in English.
+        #     "content": template,  # 系统message
+        #     "role": "system"
+        # },
         {
             # "content": input('请输入：'),  # 用户message
-            "content": text,  # 用户message
+            "content": prefix + text,  # 用户message
             "role": "user"
         }
     ]
     first_response = get_response(messages)
     assistant_output = first_response.output.choices[0].message
-    print("translate result : {}".format(assistant_output))
+    print("input : {}, translate result : {}".format(text, assistant_output.content))
     return assistant_output.content
 
 
 @retry(exceptions=RequestException, tries=3, delay=1)
 def get_response(messages):
     response = Generation.call(
-        model='qwen-max',
+        model='qwen-turbo',
         api_key= QWEN_API_KEY,
         messages=messages,
         # seed=random.randint(1, 10000),  # 设置随机数种子seed，如果没有设置，则随机数种子默认为1234