.....

app.py

@@ -18,8 +18,8 @@ from collections import defaultdict
 import tempfile
 
 try:
-    import google.generativeai as genai
-    from google.generativeai.types import GenerationConfig, HarmCategory, HarmBlockThreshold, FinishReason, HarmProbability
+    import google.genai as genai # Corrected: Import the new SDK package
+    from google.genai.types import GenerationConfig, HarmCategory, HarmBlockThreshold, FinishReason, HarmProbability # Corrected: Types from the new SDK
 except ImportError:
     genai = None
     GenerationConfig = None
@@ -27,7 +27,7 @@ except ImportError:
     HarmBlockThreshold = None
     FinishReason = None
     HarmProbability = None
-    print("WARNING: google-genai library not found. Install with: pip install google-genai")
+    print("WARNING: google-genai library not found. Install with: pip install google-genai") # This warning is correct
 
 try:
     from duckduckgo_search import DDGS
@@ -761,24 +761,31 @@ class GeneralRAGPipeline:
 class GaiaLevel1Agent:
     def __init__(self, api_url: str = DEFAULT_API_URL):
         self.api_url = api_url
-        # Changed self.llm_model to self.genai_client and store model name separately
         self.genai_client: Optional[Any] = None
         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:
-                genai.configure(api_key=GOOGLE_GEMINI_API_KEY) # Configure API key globally
-                self.genai_client = genai.Client() # Initialize the GenAI Client
+                # The genai.configure call is no longer needed if GOOGLE_API_KEY env var is set,
+                # or if the API key is passed directly to genai.Client()
+                # However, keeping it for now as it doesn't hurt if GOOGLE_GEMINI_API_KEY is set.
+                # If GOOGLE_API_KEY (the generic one) is intended for the client, it's often picked up automatically.
+                # For clarity, if GOOGLE_GEMINI_API_KEY is specific and different, ensure Client uses it.
+                # The new SDK typically uses GOOGLE_API_KEY from env.
+                # If GOOGLE_GEMINI_API_KEY is specifically for GenAI and different from a general GOOGLE_API_KEY,
+                # it should be passed to Client() if the client supports an api_key argument,
+                # or ensure genai.configure(api_key=GOOGLE_GEMINI_API_KEY) correctly sets it for the client.
+                # The migration guide implies genai.configure() still works or the client picks it up.
+                genai.configure(api_key=GOOGLE_GEMINI_API_KEY) 
+                self.genai_client = genai.Client() 
                 gaia_logger.info(f"Google GenAI Client initialized. Will use model '{self.llm_model_name}'.")
             except Exception as e:
-                # Updated error message to reflect client initialization
                 gaia_logger.error(f"Error initializing Google GenAI Client or configuring for model '{self.llm_model_name}': {e}", exc_info=True)
-                self.genai_client = None # Ensure it's None on failure
+                self.genai_client = None
         else:
-            gaia_logger.warning("Google GenAI library (google.generativeai) or GOOGLE_GEMINI_API_KEY missing. LLM capabilities will be unavailable.")
+            gaia_logger.warning("Google GenAI library (google.genai) or GOOGLE_GEMINI_API_KEY missing. LLM capabilities will be unavailable.")
 
-        # Updated check for genai_client availability
         if not self.genai_client:
             gaia_logger.warning("Google GenAI Client unavailable. LLM capabilities limited/unavailable.")
 
@@ -1061,9 +1068,7 @@ class GaiaLevel1Agent:
         default_model_answer = "Information not available in provided context"
         default_reasoning = "LLM processing failed or context insufficient."
 
-        # Updated check to use self.genai_client
         if not self.genai_client or not genai or not GenerationConfig or not FinishReason or not HarmCategory or not HarmBlockThreshold:
-            # Updated warning message
             gaia_logger.warning("Google GenAI Client or necessary enums/configs not available for answer formulation.")
             reasoning = "Google GenAI Client or its configuration components not available for answer formulation."
             answer_val = default_model_answer
@@ -1146,11 +1151,9 @@ class GaiaLevel1Agent:
                 {"category": HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT, "threshold": HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE},
             ]
             
-            # Updated LLM call to use self.genai_client.models.generate_content
-            # Model name is prefixed with "models/" and contents is a list.
             response = self.genai_client.models.generate_content(
-                model=f"models/{self.llm_model_name}", # Pass the fully qualified model name
-                contents=[final_prompt], # Contents should be a list
+                model=f"models/{self.llm_model_name}", 
+                contents=[final_prompt], 
                 generation_config=gen_config,
                 safety_settings=safety_settings
             )
@@ -1158,12 +1161,10 @@ class GaiaLevel1Agent:
             if hasattr(response, 'prompt_feedback') and response.prompt_feedback.block_reason:
                 reason_text = response.prompt_feedback.block_reason.name
                 block_details = "; ".join([f"{sr.category.name}: {sr.probability.name}" for sr in response.prompt_feedback.safety_ratings if hasattr(sr, 'blocked') and sr.blocked])
-                # Updated log message for clarity
                 gaia_logger.warning(f"Google GenAI prompt blocked. Reason: {reason_text}. Details: {block_details}")
                 return {"model_answer": "LLM Error: Prompt blocked", "reasoning_trace": f"My input was blocked by the LLM provider (Reason: {reason_text}). Details: {block_details}"}
 
             if not response.candidates:
-                # Updated log message
                 gaia_logger.warning("Google GenAI response has no candidates.")
                 return {"model_answer": "LLM Error: No response", "reasoning_trace": "LLM did not provide any response candidates."}
 
@@ -1177,7 +1178,6 @@ class GaiaLevel1Agent:
                         for sr in candidate.safety_ratings if (hasattr(sr,'blocked') and sr.blocked) or (hasattr(sr,'probability') and HarmProbability and sr.probability.value >= HarmProbability.MEDIUM.value)
                     ]
                     if relevant_ratings: safety_ratings_str = "; ".join(relevant_ratings)
-                # Updated log message
                 gaia_logger.warning(f"Google GenAI candidate did not finish successfully. Reason: {reason_name}. Safety Ratings: {safety_ratings_str if safety_ratings_str else 'N/A'}")
 
                 user_message = "LLM Error: Response incomplete"
@@ -1195,7 +1195,6 @@ class GaiaLevel1Agent:
             return self._parse_llm_output(llm_answer_text)
 
         except ValueError as ve:
-            # Updated log message
             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)"
@@ -1203,11 +1202,10 @@ class GaiaLevel1Agent:
                 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: # General ValueError
+            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 Exception as e:
-            # Updated log and error messages
             gaia_logger.error(f"Error calling Google GenAI API: {e}", exc_info=True)
             error_type_name = type(e).__name__
             error_message = str(e)
@@ -1335,12 +1333,11 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     except Exception as e: return f"Error fetching questions: {e}", None
 
     results_log_for_gradio, answers_for_api_submission = [], []
-    GEMINI_RPM_LIMIT = int(os.getenv("GEMINI_RPM_LIMIT", "10")) # Defaulting to 10 RPM if not set
-    # Ensuring sleep_llm calculation is robust, e.g. GEMINI_RPM_LIMIT can't be 0.
+    GEMINI_RPM_LIMIT = int(os.getenv("GEMINI_RPM_LIMIT", "10")) 
     if GEMINI_RPM_LIMIT <= 0:
         gaia_logger.warning(f"GEMINI_RPM_LIMIT is {GEMINI_RPM_LIMIT}, which is invalid. Defaulting to 1 RPM for safety (60s sleep).")
-        GEMINI_RPM_LIMIT = 1 # Fallback to a safe low rate
-    sleep_llm = (60.0 / GEMINI_RPM_LIMIT) + 0.5 # Added 0.5s buffer
+        GEMINI_RPM_LIMIT = 1 
+    sleep_llm = (60.0 / GEMINI_RPM_LIMIT) + 0.5 
     gaia_logger.info(f"Using Gemini RPM limit: {GEMINI_RPM_LIMIT}, LLM call sleep: {sleep_llm:.2f}s")
 
 
@@ -1403,12 +1400,13 @@ with gr.Blocks(title="GAIA RAG Agent - Advanced") as demo:
         2.  Click 'Run Evaluation & Submit All Answers' to process all questions from the GAIA benchmark and submit them.
         ---
         This agent utilizes Retrieval-Augmented Generation (RAG) with multiple search providers, advanced file processing (CSV, JSON, Excel, PDF, Audio Transcription), and experimental video analysis capabilities (bird species identification/counting in YouTube videos) via Hugging Face Transformers. Answers are formulated by a Large Language Model (Google GenAI).
-        """ # Updated LLM name
+        """ 
     )
     gr.LoginButton()
     run_button = gr.Button("Run Evaluation & Submit All Answers", variant="primary")
     status_output = gr.Textbox(label="Status / Submission Result", lines=5, interactive=False)
-    results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True, height=500) # Removed max_rows
+    # Removed height argument from gr.DataFrame as it's causing a TypeError
+    results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True) 
     run_button.click(fn=run_and_submit_all, inputs=[], outputs=[status_output, results_table])
 
 if __name__ == "__main__":
@@ -1427,7 +1425,8 @@ if __name__ == "__main__":
         ("librosa", librosa), ("openpyxl", openpyxl), ("pdfplumber", pdfplumber),
         ("yt_dlp", yt_dlp), ("cv2 (opencv-python)", cv2), ("BeautifulSoup", BeautifulSoup),
         ("duckduckgo_search", DDGS), ("googleapiclient", build_google_search_service),
-        ("tavily", TavilyClient), ("genai (google-generativeai)", genai)
+        ("tavily", TavilyClient), 
+        ("google.genai", genai) # Corrected library name in check
     ]
     for lib_name, lib_var in libraries_to_check:
         print(f"✅ {lib_name} lib found." if lib_var else f"⚠️ WARNING: {lib_name} lib missing (functionality may be impaired).")
@@ -1435,14 +1434,14 @@ if __name__ == "__main__":
     if missing_keys: print(f"\n--- PLEASE SET MISSING ENV VARS FOR FULL FUNCTIONALITY: {', '.join(missing_keys)} ---\n")
     else: print("\n--- All major API Key Environment Variables found. ---")
 
-    gemini_rpm_env = os.getenv("GEMINI_RPM_LIMIT", "10") # Default to "10" string
+    gemini_rpm_env = os.getenv("GEMINI_RPM_LIMIT", "10") 
     try:
         gemini_rpm_val = int(gemini_rpm_env)
-        if gemini_rpm_val <= 0: gemini_rpm_val = 10 # Fallback for invalid int
+        if gemini_rpm_val <= 0: gemini_rpm_val = 10 
     except ValueError:
-        gemini_rpm_val = 10 # Fallback for non-integer string
+        gemini_rpm_val = 10 
         gaia_logger.warning(f"GEMINI_RPM_LIMIT ('{gemini_rpm_env}') is not a valid integer. Defaulting to {gemini_rpm_val} RPM.")
-    print(f"--- Using GEMINI_RPM_LIMIT: {gemini_rpm_val} (Ensure this matches your Google GenAI API plan limits) ---") # Updated LLM name
+    print(f"--- Using GEMINI_RPM_LIMIT: {gemini_rpm_val} (Ensure this matches your Google GenAI API plan limits) ---") 
 
 
     print("-"*(60 + len(" GAIA Level 1 Agent - RAG, FileProc, Video Analysis ")) + "\n")