翻译前置语言判断

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 = get_translation_from_llama3("[" + request_data.text + "]")
+        data = get_translation_from_llama3(request_data.text)
         logger.info(f"prompt_generation response @@@@@@:{data}")
     except Exception as e:
         logger.warning(f"prompt_generation Run Exception @@@@@@:{e}")

app/service/chat_robot/script/prompt.py

@@ -69,3 +69,5 @@ TOOLS_FUNCTIONS_SUFFIX = (
 )
 
 TUTORIAL_TOOL_RETURN = "Commencing the systematic tutorial guide now."
+
+GET_LANGUAGE_PREFIX = "Please identify the language. Only output the language name"

app/service/chat_robot/script/service/CallQWen.py

@@ -8,7 +8,8 @@ from urllib3.exceptions import NewConnectionError
 from app.core.config import *
 from app.service.chat_robot.script.callbacks.qwen_callback_handler import QWenCallbackHandler
 from app.service.chat_robot.script.database import CustomDatabase
-from app.service.chat_robot.script.prompt import FASHION_CHAT_BOT_PREFIX, TOOLS_FUNCTIONS_SUFFIX, TUTORIAL_TOOL_RETURN
+from app.service.chat_robot.script.prompt import FASHION_CHAT_BOT_PREFIX, TOOLS_FUNCTIONS_SUFFIX, TUTORIAL_TOOL_RETURN, \
+    GET_LANGUAGE_PREFIX
 from app.service.search_image_with_text.service import query
 
 get_database_table_description = "Input is an empty string, output is a comma separated list of tables in the database."
@@ -300,5 +301,23 @@ def tutorial_tool():
     return TUTORIAL_TOOL_RETURN
 
 
+def get_language(message: str) -> str:
+    messages = [
+        {
+            "content": message,  # 用户message
+            "role": "user"
+        },
+        {
+            "content": GET_LANGUAGE_PREFIX,  # ai message
+            "role": "assistant"
+        }
+    ]
+
+    first_response = get_response(messages)
+    assistant_output = first_response.output.choices[0].message.content
+    logging.info(f"大模型输出信息：{first_response}\n判断用户输入的语言为：{assistant_output}")
+    return assistant_output
+
+
 if __name__ == '__main__':
-    call_with_messages()
+    get_language("")

app/service/prompt_generation/chatgpt_for_translation.py

@@ -8,6 +8,7 @@ from requests import RequestException
 from retry import retry
 
 from app.core.config import QWEN_API_KEY
+from app.service.chat_robot.script.service.CallQWen import get_language
 
 logger = logging.getLogger(__name__)
 
@@ -93,7 +94,13 @@ def get_translation_from_llama3(text):
 
     # prompt = f"System: {prefix_for_llama}\nUser:[{text}]"
 
-    # 创建请求的负载
+    # 先获取用户输入文本的语言
+    language = get_language(text)
+
+    if 'English' in language:
+        return text
+
+    # 创建请求的负载 translator是自定义的翻译模型
     payload = {
         "model": "translator",
         "prompt": f"[{text}]",
@@ -117,6 +124,26 @@ def get_translation_from_llama3(text):
         print(response.text)
 
 
+# 在llama3中创建一个翻译模型
+# def create_model_with_llama(text):
+#     url = "http://localhost:11434/api/create"
+#     # url = "http://10.1.1.240:1143/api/generate"
+#
+#     # prompt = f"System: {prefix_for_llama}\nUser:[{text}]"
+#
+#     # 创建翻译器的配置文件
+#     payload = {
+#         "model": "translator",
+#         "modelfile": "FROM llama3\nSYSTEM Translate everything within the brackets [] into English."
+#                      "Never translate or modify any English input."
+#                      "The input must be fully translated into coherent English sentences."
+#     }
+#
+#     # 将负载转换为 JSON 格式
+#     headers = {'Content-Type': 'application/json'}
+#     response = requests.post(url, data=json.dumps(payload), headers=headers)
+
+
 def main():
     """Main function"""
     text = get_translation_from_llama3("[火焰]")