refactor: streamline language instruction handling across prompts

surfsense_backend/app/agents/researcher/prompts.py

@@ -1,10 +1,11 @@
 import datetime
 
-
-def get_answer_outline_system_prompt(language: str | None = None) -> str:
-    language_instruction = ""
+def _build_language_instruction(language: str | None = None):
     if language:
-        language_instruction = f"\n\nIMPORTANT: Please respond in {language} language. All your responses, explanations, and analysis should be written in {language}."
+        return f"\n\nIMPORTANT: Please respond in {language} language. All your responses, explanations, and analysis should be written in {language}."
+    return ""
+def get_answer_outline_system_prompt(language: str | None = None) -> str:
+    language_instruction = _build_language_instruction(language)
 
     return f"""
 Today's date: {datetime.datetime.now().strftime("%Y-%m-%d")}

surfsense_backend/app/agents/researcher/qna_agent/prompts.py

@@ -1,5 +1,5 @@
 import datetime
-
+from ..prompts import _build_language_instruction
 
 def get_qna_citation_system_prompt(chat_history: str | None = None, language: str | None = None):
     chat_history_section = (
@@ -17,10 +17,7 @@ NO CHAT HISTORY PROVIDED
     )
     
     # Add language instruction if specified
-    language_instruction = ""
-    if language:
-        language_instruction = f"\n\nIMPORTANT: Please respond in {language} language. All your responses, explanations, and analysis should be written in {language}."
-
+    language_instruction = _build_language_instruction(language)
     return f"""
 Today's date: {datetime.datetime.now().strftime("%Y-%m-%d")}
 You are SurfSense, an advanced AI research assistant that provides detailed, well-researched answers to user questions by synthesizing information from multiple personal knowledge sources.{language_instruction}
@@ -170,9 +167,7 @@ NO CHAT HISTORY PROVIDED
     )
     
     # Add language instruction if specified
-    language_instruction = ""
-    if language:
-        language_instruction = f"\n\nIMPORTANT: Please respond in {language} language. All your responses, explanations, and analysis should be written in {language}."
+    language_instruction = _build_language_instruction(language)
 
     return f"""
 Today's date: {datetime.datetime.now().strftime("%Y-%m-%d")}

surfsense_backend/app/agents/researcher/sub_section_writer/prompts.py

@@ -1,6 +1,5 @@
 import datetime
-
-
+from ..prompts import _build_language_instruction
 def get_citation_system_prompt(chat_history: str | None = None, language: str | None = None):
     chat_history_section = (
         f"""
@@ -17,9 +16,7 @@ NO CHAT HISTORY PROVIDED
     )
     
     # Add language instruction if specified
-    language_instruction = ""
-    if language:
-        language_instruction = f"\n\nIMPORTANT: Please respond in {language} language. All your responses, explanations, and analysis should be written in {language}."
+    language_instruction = _build_language_instruction(language)
 
     return f"""
 Today's date: {datetime.datetime.now().strftime("%Y-%m-%d")}
@@ -177,9 +174,7 @@ NO CHAT HISTORY PROVIDED
     )
     
     # Add language instruction if specified
-    language_instruction = ""
-    if language:
-        language_instruction = f"\n\nIMPORTANT: Please respond in {language} language. All your responses, explanations, and analysis should be written in {language}."
+    language_instruction = _build_language_instruction(language)
 
     return f"""
 Today's date: {datetime.datetime.now().strftime("%Y-%m-%d")}

surfsense_backend/app/routes/chats_routes.py

@@ -75,33 +75,29 @@ async def handle_chat_data(
             )
         )
         user_preference = language_result.scalars().first()
-        print("UserSearchSpacePreference:", user_preference)
+        # print("UserSearchSpacePreference:", user_preference)
         
         language = None
         if user_preference and user_preference.search_space and user_preference.search_space.llm_configs:
             llm_configs = user_preference.search_space.llm_configs
-            # print(f"Found {len(llm_configs)} LLM Configs")
-            # for i, config in enumerate(llm_configs):
-                # print(f"  Config {i+1}: name={config.name}, provider={config.provider}, language={getattr(config, 'language', None)}")
             
             
             for preferred_llm in [user_preference.fast_llm, user_preference.long_context_llm, user_preference.strategic_llm]:
                 if preferred_llm and getattr(preferred_llm, 'language', None):
                     language = preferred_llm.language
-                    # print(f"Using language from preferred LLM: {preferred_llm.name} -> {language}")
                     break
             
-            # no preferred llM has language use first available LLM config
-            if not language:
-                first_llm_config = llm_configs[0]
-                language = getattr(first_llm_config, 'language', None)
-                # print(f"Using language from first LLM config: {first_llm_config.name} -> {language}")
+            
+        if not language:
+            first_llm_config = llm_configs[0]
+            language = getattr(first_llm_config, 'language', None)
+            
             
     except HTTPException:
         raise HTTPException(
             status_code=403, detail="You don't have access to this search space"
         ) from None
-    # print("Language selected:", language)
+    
     langchain_chat_history = []
     for message in messages[:-1]:
         if message["role"] == "user":