refactor: enhance logging and refine language analysis process in MatMaster agent for improved clarity and accuracy

Author: Rasic2

agents/matmaster_agent/callback.py

@@ -1,3 +1,4 @@
+import inspect
 import json
 import logging
 import uuid
@@ -50,7 +51,7 @@ async def matmaster_set_lang(callback_context: CallbackContext) -> Optional[type
     response = litellm.completion(model='azure/gpt-4o', messages=[{'role': 'user', 'content': prompt}],
                                   response_format=UserContent)
     result: dict = json.loads(response.choices[0].message.content)
-    logger.info(f"[matmaster_prepare_state] user_content = {result}")
+    logger.info(f"[{inspect.currentframe().f_code.co_name}] result = {result}")
     language = str(result.get('language', 'zh'))
     callback_context.state['target_language'] = language
 

agents/matmaster_agent/prompt.py

@@ -804,13 +804,30 @@ def get_params_check_info_prompt():
 
 def get_user_content_lang():
     return """
-You are a professional assistant responsible for analysing language of user_content.
+You are a professional linguistic analyst. Your task is to identify the primary language used in the user content provided.
 
 User Content:
 {user_content}
 
-Provide your analysis in the following JSON format:
+Analyze the text and determine the most likely language from the following predefined options:
+- English
+- Chinese
+- Spanish
+- French
+- German
+- Japanese
+- Korean
+- Russian
+- Arabic
+- Portuguese
+- Italian
+- Dutch
+- Other
+
+If the language does not clearly match any of the above options or is a mix of multiple languages, classify it as "Other".
+
+Provide your analysis in the following strict JSON format:
 {{
-    "language": <string>
+    "language": "<string>"
 }}
 """