tool & is llm message for xml tool adds

backend/agent/prompt.py

@@ -82,4 +82,5 @@ def get_system_prompt():
     '''
     Returns the system prompt with XML tool usage instructions.
     '''
-    return SYSTEM_PROMPT + RESPONSE_FORMAT
+    return SYSTEM_PROMPT 
+#+ RESPONSE_FORMAT

backend/agent/run.py

@@ -56,8 +56,8 @@ Current development environment workspace state:
         llm_temperature=0.1,
         llm_max_tokens=8000,
         processor_config=ProcessorConfig(
-            xml_tool_calling=True,
+            xml_tool_calling=False,
-            native_tool_calling=False,
+            native_tool_calling=True,
             execute_tools=True,
             execute_on_stream=True,
             tool_execution_strategy="sequential",
@@ -126,6 +126,7 @@ async def test_agent():
         
         chunk_counter = 0
         current_response = ""
+        tool_call_counter = 0  # Track number of tool calls
         
         async for chunk in run_agent(thread_id=thread_id, stream=True, thread_manager=thread_manager):
             chunk_counter += 1
@@ -139,9 +140,47 @@ async def test_agent():
                 print(f"🛠️ Tool Result: {chunk.get('function_name', 'Unknown Tool')}")
                 print(f"📝 {chunk.get('result', chunk)}")
                 print("="*50 + "\n")
+            elif chunk.get('type') == 'tool_call_chunk':
+                # Display native tool call chunks as they arrive
+                tool_call = chunk.get('tool_call', {})
+                
+                # Check if it's a meaningful part of the tool call to display
+                if tool_call.get('function', {}).get('arguments'):
+                    args = tool_call.get('function', {}).get('arguments', '')
+                    
+                    # Only show when we have substantial arguments or a function name
+                    should_display = (
+                        len(args) > 3 or  # More than just '{}'
+                        tool_call.get('function', {}).get('name')  # Or we have a name
+                    )
+                    
+                    if should_display:
+                        tool_call_counter += 1
+                        print("\n" + "-"*50)
+                        print(f"🔧 Tool Call #{tool_call_counter}: {tool_call.get('function', {}).get('name', 'Building...')}")
+                        
+                        # Try to parse and pretty print the arguments if they're JSON
+                        try:
+                            # Check if it's complete JSON or just a fragment
+                            if args.strip().startswith('{') and args.strip().endswith('}'):
+                                args_obj = json.loads(args)
+                                print(f"📋 Arguments: {json.dumps(args_obj, indent=2)}")
+                            else:
+                                print(f"📋 Arguments (partial): {args}")
+                        except json.JSONDecodeError:
+                            print(f"📋 Arguments (building): {args}")
+                            
+                        print("-"*50)
+                        
+                        # Return to the current content display
+                        if current_response:
+                            print("\nContinuing response:", flush=True)
+                            print(current_response, end='', flush=True)
         
         print("\n" + "="*50)
         print(f"✅ Agent completed. Processed {chunk_counter} chunks.")
+        if tool_call_counter > 0:
+            print(f"🔧 Found {tool_call_counter} native tool calls.")
         print("="*50 + "\n")
     
     print("\n" + "="*50)

backend/agentpress/response_processor.py

@@ -175,6 +175,37 @@ class ResponseProcessor:
                     # Process native tool calls
                     if config.native_tool_calling and delta and hasattr(delta, 'tool_calls') and delta.tool_calls:
                         for tool_call in delta.tool_calls:
+                            # Yield the raw tool call chunk directly to the stream
+                            # Safely extract tool call data even if model_dump isn't available
+                            tool_call_data = {}
+                            
+                            if hasattr(tool_call, 'model_dump'):
+                                # Use model_dump if available (OpenAI client)
+                                tool_call_data = tool_call.model_dump()
+                            else:
+                                # Manual extraction if model_dump not available
+                                if hasattr(tool_call, 'id'):
+                                    tool_call_data['id'] = tool_call.id
+                                if hasattr(tool_call, 'index'):
+                                    tool_call_data['index'] = tool_call.index
+                                if hasattr(tool_call, 'type'):
+                                    tool_call_data['type'] = tool_call.type
+                                if hasattr(tool_call, 'function'):
+                                    tool_call_data['function'] = {}
+                                    if hasattr(tool_call.function, 'name'):
+                                        tool_call_data['function']['name'] = tool_call.function.name
+                                    if hasattr(tool_call.function, 'arguments'):
+                                        tool_call_data['function']['arguments'] = tool_call.function.arguments
+                            
+                            # Yield the chunk data
+                            yield {
+                                "type": "tool_call_chunk", 
+                                "tool_call": tool_call_data
+                            }
+                            
+                            # Log the tool call chunk for debugging
+                            logger.debug(f"Yielded native tool call chunk: {tool_call_data}")
+                            
                             if not hasattr(tool_call, 'function'):
                                 continue
                                 
@@ -988,9 +1019,9 @@ class ResponseProcessor:
             }
             await self.add_message(
                 thread_id=thread_id, 
-                type=result_role if result_role == "assistant" else "user",
+                type="tool",
                 content=result_message,
-                is_llm_message=(result_role == "assistant")
+                is_llm_message=True
             )
         except Exception as e:
             logger.error(f"Error adding tool result: {str(e)}", exc_info=True)
@@ -1002,7 +1033,7 @@ class ResponseProcessor:
                 }
                 await self.add_message(
                     thread_id=thread_id, 
-                    type="user", 
+                    type="tool", 
                     content=fallback_message,
                     is_llm_message=True
                 )

backend/agentpress/thread_manager.py

@@ -187,14 +187,14 @@ class ThreadManager:
             logger.debug(f"Processor config: XML={processor_config.xml_tool_calling}, Native={processor_config.native_tool_calling}, " 
                    f"Execute tools={processor_config.execute_tools}, Strategy={processor_config.tool_execution_strategy}")
 
-            # Check if native_tool_calling is enabled and throw an error if it is
+            # # Check if native_tool_calling is enabled and throw an error if it is
-            if processor_config.native_tool_calling:
+            # if processor_config.native_tool_calling:
-                error_message = "Native tool calling is not supported in this version"
+            #     error_message = "Native tool calling is not supported in this version"
-                logger.error(error_message)
+            #     logger.error(error_message)
-                return {
+            #     return {
-                    "status": "error",
+            #         "status": "error",
-                    "message": error_message
+            #         "message": error_message
-                }
+            #     }
 
             # 4. Prepare tools for LLM call
             openapi_tool_schemas = None