Update main.py

main.py

@@ -849,7 +849,8 @@ async def _call_groq(text: str, summary_type: str) -> Tuple[Optional[str], Optio
 
 async def _call_gemini(text: str, summary_type: str, model_name: str) -> Tuple[Optional[str], Optional[str]]:
     """Internal function to call Gemini API. Returns (summary, error_message)."""
-    global _gemini_api_enabled, HarmCategory, HarmBlockThreshold, genai, google # Add google to global if needed, though import should make it available
+    # Make sure globals are accessible if needed (import should suffice)
+    global _gemini_api_enabled, HarmCategory, HarmBlockThreshold, genai, google
     if not _gemini_api_enabled:
         logger.error(f"[Gemini {model_name}] Called but API is disabled.");
         return None, f"Error: AI service (Gemini API) not configured/available."
@@ -859,11 +860,6 @@ async def _call_gemini(text: str, summary_type: str, model_name: str) -> Tuple[O
          logger.error(f"[Gemini {model_name}] SDK or safety types (HarmCategory/HarmBlockThreshold) are None/unavailable.")
          return None, f"Sorry, an internal configuration error occurred with the AI service ({model_name}). SDK components missing."
 
-    # Also check if the google exceptions module loaded - needed for specific error handling
-    if google is None or not hasattr(google, 'api_core') or not hasattr(google.api_core, 'exceptions'):
-         logger.warning(f"[Gemini {model_name}] google.api_core.exceptions not available for specific error handling. Will use general exceptions.")
-         # We can proceed but error handling might be less specific
-
     logger.info(f"[Gemini {model_name}] Generating {summary_type} summary using {model_name}. Input length: {len(text)}")
 
     prompt = PROMPT_PARAGRAPH if summary_type == "paragraph" else PROMPT_POINTS
@@ -892,7 +888,7 @@ async def _call_gemini(text: str, summary_type: str, model_name: str) -> Tuple[O
         logger.error(f"[Gemini {model_name}] Unexpected error defining safety settings ({type(e).__name__}): {e}.", exc_info=True)
         return None, f"Sorry, an internal error occurred configuring the AI service ({model_name}). Safety settings definition failed."
 
-    if not safety_settings: # Should not happen if base categories exist
+    if not safety_settings:
         logger.error(f"[Gemini {model_name}] Failed to define any safety settings.")
         return None, f"Sorry, an internal error occurred configuring the AI service ({model_name}). No safety settings defined."
 
@@ -945,47 +941,53 @@ async def _call_gemini(text: str, summary_type: str, model_name: str) -> Tuple[O
             if finish_reason_str == 'SAFETY': return None, f"Sorry, the AI model ({model_name}) response was blocked by safety filters."
             return None, f"Sorry, the AI model ({model_name}) did not provide a summary (Finish Reason: {finish_reason_str})."
 
-    # --- Exception Handling (Refined) ---
-    except AttributeError as ae: # Error within response processing
+    # --- Exception Handling (Corrected Syntax) ---
+    except AttributeError as ae:
          logger.error(f"[Gemini {model_name}] AttributeError during Gemini response processing: {ae}. SDK/response structure issue.", exc_info=True);
          return None, f"Sorry, there was an issue processing the response from the AI service ({model_name}). Attribute error."
 
-    # Check if specific exceptions are available before trying to catch them
-    except google.api_core.exceptions.NotFound as nfe if google and hasattr(google.api_core, 'exceptions') else None:
-        # Specific handling for the 404 error
+    # --- Specific Google API Error Handling (Only if google.api_core.exceptions was imported) ---
+    # Attempt to catch specific errors if the 'google' object and submodules are available
+    except google.api_core.exceptions.NotFound as nfe:
         logger.error(f"[Gemini {model_name}] Model Not Found error from Gemini API: {nfe}", exc_info=False)
         user_message = f"Sorry, the AI model '{model_name}' was not found by the API service. It might be unavailable or spelled incorrectly."
         return None, user_message
-    except google.api_core.exceptions.InvalidArgument as iae if google and hasattr(google.api_core, 'exceptions') else None:
+    except google.api_core.exceptions.InvalidArgument as iae:
          logger.error(f"[Gemini {model_name}] Invalid Argument error from Gemini API: {iae}", exc_info=False)
          error_detail = str(iae)
          user_message = f"Sorry, the AI service ({model_name}) reported an invalid argument."
          if "API key not valid" in error_detail: user_message = f"Error: The API key for the AI service ({model_name}) is invalid."
-         # Add other specific InvalidArgument checks if needed
          return None, user_message
-    except google.api_core.exceptions.PermissionDenied as pde if google and hasattr(google.api_core, 'exceptions') else None:
+    except google.api_core.exceptions.PermissionDenied as pde:
         logger.error(f"[Gemini {model_name}] Permission Denied error from Gemini API: {pde}", exc_info=False)
         user_message = f"Error: Access denied for the AI service ({model_name}). Check API key permissions."
         return None, user_message
-    except google.api_core.exceptions.ResourceExhausted as ree if google and hasattr(google.api_core, 'exceptions') else None:
+    except google.api_core.exceptions.ResourceExhausted as ree:
         logger.error(f"[Gemini {model_name}] Resource Exhausted (Quota/Rate Limit) error from Gemini API: {ree}", exc_info=False)
         user_message = f"Sorry, the AI model ({model_name}) is busy or quota exceeded. Please try again later."
         return None, user_message
-    except google.api_core.exceptions.GoogleAPIError as gae if google and hasattr(google.api_core, 'exceptions') else None:
-        # Catch other Google API errors
+    except google.api_core.exceptions.GoogleAPIError as gae:
         logger.error(f"[Gemini {model_name}] Google API error during Gemini call: {gae}", exc_info=False)
         status_code = getattr(gae, 'code', 'Unknown')
         user_message = f"Sorry, the AI service ({model_name}) encountered an API error (Code: {status_code})."
         if status_code == 500: user_message = f"Sorry, the AI service ({model_name}) had an internal server error."
-        # Add other status codes if needed
         return None, user_message
+
+    # --- General Exception Catch-all ---
     except Exception as e:
-        # General catch-all
-        logger.error(f"[Gemini {model_name}] Unexpected error during Gemini API call: {e}", exc_info=True);
-        error_msg = f"Sorry, an unexpected error occurred while using the AI service ({model_name})."
-        # Check if it's the specific NameError we saw before, indicating an issue loading the exceptions module
-        if isinstance(e, NameError) and 'google' in str(e):
-             error_msg = f"Sorry, an internal configuration error occurred with the AI service ({model_name}). Exception handling module missing."
+        # Check if 'google' was defined during import, if not, specific catches above would have failed with NameError
+        google_exceptions_available = 'google' in globals() and google and hasattr(google, 'api_core') and hasattr(google.api_core, 'exceptions')
+
+        # Log the error appropriately
+        if isinstance(e, NameError) and 'google' in str(e) and not google_exceptions_available:
+             # This specifically means the import failed and we tried to use a google.api_core exception type
+             logger.error(f"[Gemini {model_name}] Failed to import google.api_core.exceptions. Cannot catch specific API errors. Fallback error: {e}", exc_info=True);
+             error_msg = f"Sorry, an internal configuration error occurred with the AI service ({model_name}). Cannot handle specific API errors."
+        else:
+             # General unexpected error
+             logger.error(f"[Gemini {model_name}] Unexpected error during Gemini API call: {e}", exc_info=True);
+             error_msg = f"Sorry, an unexpected error occurred while using the AI service ({model_name})."
+
         return None, error_msg