Update app.py

app.py

@@ -155,74 +155,97 @@ def safe_calculator(expression: str) -> str:
 class HfAgentWrapper:
     def __init__(self):
         print("Initializing HfAgentWrapper...")
-        model_id_or_path = "bigcode/starcoderbase-1b" # Compatible model
-
+        model_id_or_path = "bigcode/starcoderbase-1b"  # Using a model compatible with transformers 4.36.0
+        
         try:
-            print(f"Attempting to initialize HfAgent with model: {model_id_or_path}")
-
+            print(f"Attempting to initialize HfAgent directly with model: {model_id_or_path}")
+            
             hf_auth_token = os.getenv("HF_AUTH_TOKEN")
             if not hf_auth_token:
-                print("WARNING: HF_AUTH_TOKEN secret not found. Starcoder is gated and requires a token.")
-                # For Starcoder, token is necessary
-                raise ValueError("HF_AUTH_TOKEN secret is missing and is required for bigcode/starcoderbase-1b.")
+                # Starcoderbase might be gated or require login for some operations/configs
+                print("WARNING: HF_AUTH_TOKEN secret not found. This might cause issues if the model requires full authentication.")
+                # For now, we'll let it proceed and see if HfAgent can fetch it without an explicit token here
+                # if it's publicly accessible enough. If not, this will error out.
             else:
                 print(f"HF_AUTH_TOKEN found (length: {len(hf_auth_token)}), will pass it to HfAgent.")
 
             # --- Ensure Tool names are correct ---
-            if not get_current_time_in_timezone.__doc__: raise ValueError("Tool 'get_current_time_in_timezone' is missing a docstring.")
-            if not web_search.__doc__: raise ValueError("Tool 'web_search' is missing a docstring.")
-            if not safe_calculator.__doc__: raise ValueError("Tool 'safe_calculator' is missing a docstring.")
-
-            time_tool_obj = Tool(name=get_current_time_in_timezone.__name__, func=get_current_time_in_timezone, description=get_current_time_in_timezone.__doc__)
-            search_tool_obj = Tool(name=web_search.__name__, func=web_search, description=web_search.__doc__)
-            calculator_tool_obj = Tool(name=safe_calculator.__name__, func=safe_calculator, description=safe_calculator.__doc__)
+            if not get_current_time_in_timezone.__doc__: 
+                raise ValueError("Tool 'get_current_time_in_timezone' is missing a docstring.")
+            if not web_search.__doc__: 
+                raise ValueError("Tool 'web_search' is missing a docstring.")
+            if not safe_calculator.__doc__: 
+                raise ValueError("Tool 'safe_calculator' is missing a docstring.")
+
+            time_tool_obj = Tool(
+                name=get_current_time_in_timezone.__name__,
+                func=get_current_time_in_timezone,
+                description=get_current_time_in_timezone.__doc__
+            )
+            search_tool_obj = Tool(
+                name=web_search.__name__,
+                func=web_search,
+                description=web_search.__doc__
+            )
+            calculator_tool_obj = Tool(
+                name=safe_calculator.__name__,
+                func=safe_calculator,
+                description=safe_calculator.__doc__
+            )
             self.actual_tools_for_agent = [time_tool_obj, search_tool_obj, calculator_tool_obj]
+            
             tool_names_for_log = [tool.name for tool in self.actual_tools_for_agent]
-            print(f"Prepared Tool objects with names: {tool_names_for_log} and descriptions.") # Verify this prints correct names!
+            # This print MUST show your actual tool names, not empty strings
+            print(f"Prepared Tool objects with names: {tool_names_for_log} and descriptions.") 
             # --- End Tool Name Check ---
 
             # Let HfAgent create its own pipeline internally.
-            # Pass the model ID string and the hf_token.
-            # trust_remote_code=True is not needed for HfAgent constructor and not for starcoder with 4.36.0.
+            # Pass model_id_or_path as the FIRST POSITIONAL argument.
+            # Pass hf_token as a keyword argument.
             self.agent = HfAgent(
-                llm_endpoint=model_id_or_path,  # Pass model ID string
+                model_id_or_path,  # <<<--- First argument, NO 'llm_endpoint=' keyword
                 additional_tools=self.actual_tools_for_agent,
                 hf_token=hf_auth_token  # HfAgent uses this for its internal LLMProxy
             )
             print(f"HfAgent successfully instantiated for model {model_id_or_path}.")
 
-            # ... (rest of your Tool object creations - these were correct)
-            if not get_current_time_in_timezone.__doc__: raise ValueError("Tool 'get_current_time_in_timezone' is missing a docstring.")
-            if not web_search.__doc__: raise ValueError("Tool 'web_search' is missing a docstring.")
-            if not safe_calculator.__doc__: raise ValueError("Tool 'safe_calculator' is missing a docstring.")
-
-            time_tool_obj = Tool(name=get_current_time_in_timezone.__name__, func=get_current_time_in_timezone, description=get_current_time_in_timezone.__doc__)
-            search_tool_obj = Tool(name=web_search.__name__, func=web_search, description=web_search.__doc__)
-            calculator_tool_obj = Tool(name=safe_calculator.__name__, func=safe_calculator, description=safe_calculator.__doc__)
-            self.actual_tools_for_agent = [time_tool_obj, search_tool_obj, calculator_tool_obj]
-            tool_names_for_log = [tool.name for tool in self.actual_tools_for_agent]
-            print(f"Prepared Tool objects with names: {tool_names_for_log} and descriptions.")
-
-            # 2. Pass the pre-initialized pipeline object to HfAgent
-            print(f"Initializing HfAgent with pre-initialized pipeline...")
-            self.agent = HfAgent(
-                llm_pipeline,
-                additional_tools=self.actual_tools_for_agent
-            )
-            print(f"HfAgent successfully instantiated with pre-initialized pipeline.")
-
-            # ... (your robust toolbox inspection code - still keep it) ...
-            # ...
+            # --- Robust toolbox inspection (still useful) ---
+            print(f"Inspecting self.agent.toolbox...")
+            if hasattr(self.agent, 'toolbox'):
+                toolbox_attr = self.agent.toolbox
+                print(f"Type of self.agent.toolbox: {type(toolbox_attr)}")
+
+                if isinstance(toolbox_attr, dict):
+                    print(f"Toolbox is a dict. Keys: {list(toolbox_attr.keys())}")
+                    tools_info_from_dict = {}
+                    for key, value in list(toolbox_attr.items())[:5]: 
+                        tool_name_in_dict = key 
+                        if hasattr(value, 'name'): tool_name_in_dict = value.name
+                        elif isinstance(value, dict) and 'name' in value: tool_name_in_dict = value['name']
+                        tools_info_from_dict[key] = {'name_attr': tool_name_in_dict, 'type': str(type(value))}
+                    print(f"Sample of toolbox dict content: {tools_info_from_dict}")
+                    print(f"Names of tools we passed to HfAgent: {[tool.name for tool in self.actual_tools_for_agent]}")
+                elif hasattr(toolbox_attr, 'tools') and callable(toolbox_attr.tools):
+                    try:
+                        tools_in_toolbox = toolbox_attr.tools()
+                        print(f"Toolbox has .tools() method. Tool names: {[tool.name for tool in tools_in_toolbox if hasattr(tool, 'name')]}")
+                    except Exception as e_toolbox_call:
+                        print(f"Error calling or processing self.agent.toolbox.tools(): {e_toolbox_call}")
+                else:
+                    print(f"Toolbox is of type {type(toolbox_attr)} but not a dict or recognized Toolbox object for this debug print.")
+            else:
+                print("self.agent does not have a 'toolbox' attribute (this would be unexpected).")
+            # --- End of robust toolbox inspection ---
 
         except Exception as e:
             print(f"CRITICAL ERROR: Failed to initialize HfAgent: {e}")
+            # import traceback # Already imported at the top of your file
             print("Full traceback of HfAgent initialization error:")
             traceback.print_exc() 
             raise RuntimeError(f"HfAgent initialization failed: {e}") from e
 
     # __call__ method remains the same
     def __call__(self, question: str) -> str:
-        # ... (your existing __call__ method) ...
         print(f"\n--- HfAgentWrapper received question (first 100 chars): {question[:100]}... ---")
         try:
             answer = self.agent.run(question)
@@ -230,6 +253,7 @@ class HfAgentWrapper:
             return str(answer)
         except Exception as e:
             print(f"ERROR: HfAgent execution failed for question '{question[:50]}...': {e}")
+            # import traceback # Already imported at the top of your file
             print("Full traceback of HfAgent execution error:")
             traceback.print_exc()
             return f"Agent Error: Failed to process the question. Details: {e}"