..

app.py

@@ -780,7 +780,6 @@ class GaiaLevel1Agent:
 
         if genai and GOOGLE_GEMINI_API_KEY:
             try:
-                # Corrected: Initialize client explicitly with the GOOGLE_GEMINI_API_KEY
                 self.genai_client = genai.Client(api_key=GOOGLE_GEMINI_API_KEY)
                 gaia_logger.info(f"Google GenAI Client initialized successfully with GOOGLE_GEMINI_API_KEY. Will use model '{self.llm_model_name}'.")
             except Exception as e:
@@ -1150,8 +1149,13 @@ class GaiaLevel1Agent:
 
 
         try:
-            current_gen_config_obj = types.GenerationConfig(temperature=0.1, top_p=0.95, max_output_tokens=1024)
-            
+            # Corrected: Define generation and safety settings directly for GenerateContentConfig
+            # generation_config parameters
+            temp = 0.1
+            top_p_val = 0.95
+            max_tokens = 1024
+
+            # safety_settings parameters
             current_safety_settings_list_of_dicts = [
                 {"category": types.HarmCategory.HARM_CATEGORY_HARASSMENT, "threshold": types.HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE},
                 {"category": types.HarmCategory.HARM_CATEGORY_HATE_SPEECH, "threshold": types.HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE},
@@ -1160,9 +1164,11 @@ class GaiaLevel1Agent:
             ]
             sdk_safety_settings = [types.SafetySetting(category=s["category"], threshold=s["threshold"]) for s in current_safety_settings_list_of_dicts]
             
-            # Main config object for generate_content, now as types.GenerateContentConfig
+            # Create the main config object for the generate_content call
             api_call_config = types.GenerateContentConfig(
-                generation_config=current_gen_config_obj,
+                temperature=temp,
+                top_p=top_p_val,
+                max_output_tokens=max_tokens,
                 safety_settings=sdk_safety_settings
             )
             
@@ -1211,17 +1217,9 @@ class GaiaLevel1Agent:
             gaia_logger.info(f"LLM Raw Full Answer (first 200 chars): {llm_answer_text[:200]}...")
             return self._parse_llm_output(llm_answer_text)
 
-        except ValueError as ve:
-            if "finish_reason" in str(ve).lower() and ("part" in str(ve).lower() or "candidate" in str(ve).lower()):
-                gaia_logger.error(f"ValueError accessing Google GenAI response.text, likely due to non-STOP finish_reason not caught explicitly: {ve}", exc_info=False)
-                fr_from_ex = "Unknown (from ValueError)"
-                match_fr = re.search(r"finish_reason.*?is\s*(\w+)", str(ve), re.IGNORECASE)
-                if match_fr: fr_from_ex = match_fr.group(1)
-                return {"model_answer": "LLM Error: Invalid response state",
-                        "reasoning_trace": f"Could not parse LLM response. Finish reason possibly {fr_from_ex}. Details: {str(ve)[:150]}"}
-            else: 
-                gaia_logger.error(f"ValueError during Google GenAI call or processing: {ve}", exc_info=True)
-                return {"model_answer": "LLM Error: Value error", "reasoning_trace": f"A value error occurred: {str(ve)}"}
+        except ValueError as ve: # Catch pydantic.ValidationError specifically if possible, or broader ValueError
+            gaia_logger.error(f"ValueError during Google GenAI call or processing: {ve}", exc_info=True) # Log with full traceback
+            return {"model_answer": "LLM Error: Value error in config", "reasoning_trace": f"A value error occurred: {str(ve)}"}
         except Exception as e:
             gaia_logger.error(f"Error calling Google GenAI API: {e}", exc_info=True)
             error_type_name = type(e).__name__
@@ -1468,5 +1466,4 @@ if __name__ == "__main__":
 
 
     print("-"*(60 + len(" GAIA Level 1 Agent - RAG, FileProc, Video Analysis ")) + "\n")
-    # Removed ssr=False as it was causing a TypeError with the Gradio version in the environment
     demo.launch(server_name="0.0.0.0", server_port=7860, debug=False, share=False)