........

app.py

@@ -19,12 +19,10 @@ import tempfile
 
 try:
     import google.genai as genai
-    from google.genai import types # Import types directly for GenerateContentConfig, SafetySetting etc.
-    # Specific types are referenced via types.GenerationConfig etc. later
+    from google.genai import types 
 except ImportError:
     genai = None
-    types = None # Ensure types is None if genai fails to import
-    # Individual type hints will be set to None if types is None
+    types = None 
     GenerationConfig = None
     HarmCategory = None
     HarmBlockThreshold = None
@@ -32,14 +30,13 @@ except ImportError:
     HarmProbability = None
     print("WARNING: google-genai library not found. Install with: pip install google-genai")
 
-# Assign specific types if 'types' was imported successfully, else None
 if types:
     GenerationConfig = types.GenerationConfig
     HarmCategory = types.HarmCategory
     HarmBlockThreshold = types.HarmBlockThreshold
     FinishReason = types.FinishReason
     HarmProbability = types.HarmProbability
-else: # Redundant if already None, but ensures clarity
+else: 
     GenerationConfig = None
     HarmCategory = None
     HarmBlockThreshold = None
@@ -120,9 +117,9 @@ gaia_logger = logging.getLogger('gaia_agent_llm')
 
 DEFAULT_API_URL = os.getenv("SCORING_API_URL", "https://agents-course-unit4-scoring.hf.space")
 
-GOOGLE_CUSTOM_SEARCH_API_KEY = os.getenv("GOOGLE_API_KEY") # Used for Google Custom Search
+GOOGLE_CUSTOM_SEARCH_API_KEY = os.getenv("GOOGLE_API_KEY") 
 GOOGLE_CUSTOM_SEARCH_CSE_ID = os.getenv("GOOGLE_CSE_ID")
-GOOGLE_GEMINI_API_KEY = os.getenv("GOOGLE_GEMINI_API_KEY") # Used for Google GenAI (Gemini models)
+GOOGLE_GEMINI_API_KEY = os.getenv("GOOGLE_GEMINI_API_KEY") 
 TAVILY_API_KEY = os.getenv("TAVILY_API_KEY")
 
 AGENT_DEFAULT_TIMEOUT = 15
@@ -132,7 +129,6 @@ MAX_FILE_SIZE = 5 * 1024 * 1024
 CSV_SAMPLE_ROWS = 10
 MAX_FILE_CONTEXT_LENGTH = 10000
 
-# Global instances for video analysis pipelines
 video_object_detector_pipeline: Optional[Any] = None
 video_vqa_pipeline: Optional[Any] = None 
 
@@ -180,7 +176,6 @@ DEFAULT_RAG_CONFIG = {
     'results': {'total_limit': 3, 'enrich_count': 2 }
 }
 
-# --- Helper functions for initializing video pipelines ---
 def _get_video_object_detector():
     global video_object_detector_pipeline, VIDEO_ANALYSIS_DEVICE
     if video_object_detector_pipeline is None and hf_transformers_pipeline and torch:
@@ -780,13 +775,12 @@ class GaiaLevel1Agent:
     def __init__(self, api_url: str = DEFAULT_API_URL):
         self.api_url = api_url
         self.genai_client: Optional[Any] = None
-        self.llm_model_name: str = 'gemini-2.5-flash-preview-05-20' # Using a newer model name
+        self.llm_model_name: str = 'gemini-2.5-flash-preview-05-20' 
         self.rag_pipeline = GeneralRAGPipeline(DEFAULT_RAG_CONFIG)
 
         if genai and GOOGLE_GEMINI_API_KEY:
             try:
                 # Corrected: Initialize client explicitly with the GOOGLE_GEMINI_API_KEY
-                # Remove genai.configure() as it's from the old SDK.
                 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:
@@ -898,7 +892,7 @@ class GaiaLevel1Agent:
                 'format': 'bestvideo[height<=480][ext=mp4]+bestaudio[ext=m4a]/bestvideo[height<=480][ext=webm]+bestaudio[ext=webm]/best[height<=480][ext=mp4]/best[height<=480][ext=webm]/best[height<=480]',
                 'outtmpl': os.path.join(temp_dir, '%(id)s.%(ext)s'),
                 'quiet': True,
-                'max_filesize': 75 * 1024 * 1024, # 75MB limit for video downloads
+                'max_filesize': 75 * 1024 * 1024, 
                 'overwrites': True, 'noprogress': True, 'noplaylist': True, 'socket_timeout': 20,
                 'merge_output_format': 'mp4',
             }
@@ -1081,7 +1075,6 @@ class GaiaLevel1Agent:
         default_model_answer = "Information not available in provided context"
         default_reasoning = "LLM processing failed or context insufficient."
 
-        # Check if genai client and necessary types are available
         if not self.genai_client or not types or not GenerationConfig or not FinishReason or not HarmCategory or not HarmBlockThreshold:
             gaia_logger.warning("Google GenAI Client or necessary types (GenerationConfig, HarmCategory, etc.) not available for answer formulation.")
             reasoning = "Google GenAI Client or its configuration components (types) not available for answer formulation."
@@ -1157,32 +1150,26 @@ class GaiaLevel1Agent:
 
 
         try:
-            # Prepare GenerationConfig (already an object from earlier in the script)
-            current_gen_config_obj = GenerationConfig(temperature=0.1, top_p=0.95, max_output_tokens=1024)
+            current_gen_config_obj = types.GenerationConfig(temperature=0.1, top_p=0.95, max_output_tokens=1024)
             
-            # Prepare SafetySettings (list of types.SafetySetting objects)
             current_safety_settings_list_of_dicts = [
-                {"category": HarmCategory.HARM_CATEGORY_HARASSMENT, "threshold": HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE},
-                {"category": HarmCategory.HARM_CATEGORY_HATE_SPEECH, "threshold": HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE},
-                {"category": HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT, "threshold": HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE},
-                {"category": HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT, "threshold": HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE},
+                {"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},
+                {"category": types.HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT, "threshold": types.HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE},
+                {"category": types.HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT, "threshold": types.HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE},
             ]
-            sdk_safety_settings = []
-            if types and HarmCategory and HarmBlockThreshold: # Ensure types are available
-                for setting_dict in current_safety_settings_list_of_dicts:
-                    sdk_safety_settings.append(types.SafetySetting(category=setting_dict["category"], threshold=setting_dict["threshold"]))
+            sdk_safety_settings = [types.SafetySetting(category=s["category"], threshold=s["threshold"]) for s in current_safety_settings_list_of_dicts]
             
-            # Create the main config object for the generate_content call
-            # This uses types.GenerateContentConfig from the new SDK
-            tool_config_for_api = types.GenerateContentConfig(
+            # Main config object for generate_content, now as types.GenerateContentConfig
+            api_call_config = types.GenerateContentConfig(
                 generation_config=current_gen_config_obj,
                 safety_settings=sdk_safety_settings
             )
             
             response = self.genai_client.models.generate_content(
-                model=self.llm_model_name, # Corrected: no "models/" prefix
-                contents=[final_prompt],    # Correct: contents is a list
-                config=tool_config_for_api  # Corrected: pass the GenerateContentConfig object
+                model=self.llm_model_name, 
+                contents=[final_prompt],    
+                config=api_call_config 
             )
 
             if hasattr(response, 'prompt_feedback') and response.prompt_feedback.block_reason:
@@ -1196,11 +1183,10 @@ class GaiaLevel1Agent:
                 return {"model_answer": "LLM Error: No response", "reasoning_trace": "LLM did not provide any response candidates."}
 
             candidate = response.candidates[0]
-            # Ensure FinishReason enum is available for comparison
             if types and FinishReason and candidate.finish_reason != FinishReason.STOP:
                 reason_name = candidate.finish_reason.name if hasattr(candidate.finish_reason, 'name') else str(candidate.finish_reason)
                 safety_ratings_str = ""
-                if candidate.safety_ratings and types and HarmProbability: # Ensure types are available
+                if candidate.safety_ratings and types and HarmProbability: 
                     relevant_ratings = [
                         f"{sr.category.name.split('_')[-1] if hasattr(sr.category, 'name') else 'CAT?'}: {(sr.probability.name if hasattr(sr.probability, 'name') else 'PROB?')}"
                         for sr in candidate.safety_ratings if (hasattr(sr,'blocked') and sr.blocked) or (hasattr(sr,'probability') and sr.probability.value >= HarmProbability.MEDIUM.value)
@@ -1217,7 +1203,7 @@ class GaiaLevel1Agent:
                     "model_answer": user_message,
                     "reasoning_trace": f"LLM generation stopped. Reason: {reason_name}. " + (f"Details: {safety_ratings_str}" if safety_ratings_str else "")
                 }
-            elif not (types and FinishReason): # Fallback if types were not imported
+            elif not (types and FinishReason): 
                  gaia_logger.warning("FinishReason type not available, cannot check candidate finish reason properly.")
 
 
@@ -1482,4 +1468,6 @@ if __name__ == "__main__":
 
 
     print("-"*(60 + len(" GAIA Level 1 Agent - RAG, FileProc, Video Analysis ")) + "\n")
-    demo.launch(server_name="0.0.0.0", server_port=7860, debug=False, share=False, ssr=False) 
+    # 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) 
+-