improve logging
This commit is contained in:
Gaetan Hurel
parent
c20be407d5
commit
ea1519a208
@ -14,6 +14,9 @@ if __name__ == "__main__":
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messages = []
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print("Welcome to the multi-agent sysadmin assistant!")
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print("Type your sysadmin question below. Type 'exit' to quit.")
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print("\n💡 Note: When agents execute shell commands, you may see command output")
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print(" appear between the structured step logs. This is normal behavior.")
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print(" The output belongs to the agent that was most recently active.")
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while True:
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user_input = input("\n📝 User: ")
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if user_input.strip().lower() == 'exit':
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@ -22,27 +25,10 @@ if __name__ == "__main__":
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messages.append({"role": "user", "content": user_input})
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query = {"messages": messages}
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print("\n=== Using invoke() method ===")
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result = supervisor.invoke(query)
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print("\n📊 FINAL RESULT:")
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print("-" * 40)
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print(result["messages"][-1].content)
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print("-" * 40)
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print(f"\n📈 Total messages exchanged: {len(result['messages'])}")
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# Add the assistant's reply to the conversation history
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messages.append({"role": "assistant", "content": result["messages"][-1].content})
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# Ask if the user wants to continue
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cont = input("\nWould you like to continue the conversation? (y/n): ")
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if cont.strip().lower() not in ('y', 'yes'):
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print("Session ended.")
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break
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print("\n=== Using stream() method for detailed step-by-step analysis ===")
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print("\n=== Processing with detailed step-by-step analysis ===")
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step_count = 0
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max_steps = 20 # Prevent infinite loops
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final_result = None
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try:
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chunks_processed = []
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@ -51,21 +37,50 @@ if __name__ == "__main__":
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chunks_processed.append(chunk)
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print_step_info(step_count, chunk)
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# Store the final result for conversation history
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if isinstance(chunk, dict):
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for agent_name, agent_data in chunk.items():
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if 'messages' in agent_data and agent_data['messages']:
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last_msg = agent_data['messages'][-1]
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if hasattr(last_msg, 'content') and last_msg.content:
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final_result = last_msg.content
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# Safety check to prevent infinite loops
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if step_count >= max_steps:
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print(f"\n⚠️ Reached maximum steps ({max_steps}), stopping stream...")
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break
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print(f"\n✅ Streaming completed successfully with {step_count} steps")
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print(f"📊 Total chunks processed: {len(chunks_processed)}")
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print(f"\n✅ Analysis completed with {step_count} steps")
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# Check if the last chunk contains a complete final response
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if chunks_processed:
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last_chunk = chunks_processed[-1]
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print(f"🔍 Last chunk keys: {list(last_chunk.keys()) if isinstance(last_chunk, dict) else type(last_chunk)}")
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# Add the assistant's reply to the conversation history
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if final_result:
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messages.append({"role": "assistant", "content": final_result})
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print(f"\n📊 FINAL SUMMARY:")
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print("-" * 60)
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if final_result:
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print(final_result)
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else:
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print("Analysis completed - check the detailed steps above for results")
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print("-" * 60)
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except Exception as e:
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print(f"\n❌ Streaming error after {step_count} steps: {e}")
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print("💡 The invoke() method worked fine, so the supervisor itself is functional.")
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import traceback
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traceback.print_exc()
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print("💡 Falling back to basic invoke method...")
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try:
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result = supervisor.invoke(query)
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final_result = result["messages"][-1].content
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messages.append({"role": "assistant", "content": final_result})
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print(f"\n📊 FINAL RESULT:")
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print("-" * 40)
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print(final_result)
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print("-" * 40)
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except Exception as fallback_error:
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print(f"❌ Fallback also failed: {fallback_error}")
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continue
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# Ask if the user wants to continue
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cont = input("\nWould you like to continue the conversation? (y/n): ")
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if cont.strip().lower() not in ('y', 'yes'):
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print("Session ended.")
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break
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@ -26,12 +26,12 @@ def explain_supervisor_pattern():
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def print_step_info(step_count: int, chunk):
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"""Print formatted step information during streaming."""
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print(f"\n🔄 STEP {step_count}:")
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print("-" * 30)
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"""Print formatted step information during streaming with clear agent actions."""
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print(f"\n{'='*60}")
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print(f"STEP {step_count}")
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print(f"{'='*60}")
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try:
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# Extract agent information from chunk
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if isinstance(chunk, dict):
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# Look for agent names in the chunk keys
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agent_names = [key for key in chunk.keys() if key in [
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@ -41,102 +41,115 @@ def print_step_info(step_count: int, chunk):
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]]
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if agent_names:
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current_agent = agent_names[0]
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print(f"🤖 ACTIVE AGENT: {current_agent}")
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current_agent = agent_names[0].upper()
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agent_data = chunk[agent_names[0]]
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# Show the messages from this agent
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agent_data = chunk[current_agent]
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if 'messages' in agent_data:
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messages = agent_data['messages']
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if messages:
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last_message = messages[-1]
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# Get message type from the class name
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if 'messages' in agent_data and agent_data['messages']:
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last_message = agent_data['messages'][-1]
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message_type = type(last_message).__name__
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print(f"💬 MESSAGE TYPE: {message_type}")
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# Show content preview if available
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if hasattr(last_message, 'content') and last_message.content:
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content = last_message.content
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content_length = len(content)
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print(f"📏 CONTENT LENGTH: {content_length} characters")
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# Show full content for final AI responses, abbreviated for others
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if message_type == 'AIMessage':
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print(f"📄 FULL CONTENT:")
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print(content)
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print() # Extra line for readability
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# Handle different message types with clear formatting
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if message_type == 'HumanMessage':
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# This is typically the user query or supervisor instruction
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content = getattr(last_message, 'content', '')
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if current_agent == 'SUPERVISOR':
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print(f"[ SUPERVISOR ] received user query: {content[:100]}{'...' if len(content) > 100 else ''}")
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else:
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# Truncate other message types for brevity
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preview = content[:200] + "..." if len(content) > 200 else content
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print(f"📄 CONTENT PREVIEW:")
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print(preview)
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print() # Extra line for readability
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print(f"[ {current_agent} ] received prompt from supervisor: {content[:100]}{'...' if len(content) > 100 else ''}")
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# Show tool calls if any
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if hasattr(last_message, 'tool_calls') and last_message.tool_calls:
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tool_calls = last_message.tool_calls
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print(f"🔧 TOOL CALLS: {len(tool_calls)} tool(s)")
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for i, tool_call in enumerate(tool_calls):
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tool_name = getattr(tool_call, 'name', 'unknown')
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print(f" {i+1}. {tool_name}")
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# Show transfer details for supervisor delegation
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elif message_type == 'ToolMessage':
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# Result of tool execution
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tool_name = getattr(last_message, 'name', 'unknown')
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content = getattr(last_message, 'content', '')
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if "Successfully transferred" in content:
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if tool_name.startswith('transfer_to_'):
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target_agent = tool_name.replace('transfer_to_', '')
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print(f" 🎯 DELEGATING to: {target_agent}")
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# Show the arguments/context being passed
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if hasattr(tool_call, 'args') and tool_call.args:
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print(f" 📋 Context/Args: {tool_call.args}")
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# Show additional info for ToolMessage
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if message_type == 'ToolMessage':
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if hasattr(last_message, 'name'):
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tool_name = last_message.name
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print(f"🔧 TOOL NAME: {tool_name}")
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# Explain what "Successfully transferred" means
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if "transfer" in tool_name and "Successfully transferred" in content:
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if tool_name.startswith('transfer_to_'):
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target_agent = tool_name.replace('transfer_to_', '')
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print(f" ℹ️ EXPLANATION: Supervisor delegated control to {target_agent}")
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print(f" ℹ️ The {target_agent} will now execute its specialized tasks")
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target_agent = tool_name.replace('transfer_to_', '').upper()
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print(f"[ SUPERVISOR ] successfully transferred control to {target_agent}")
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print(f"[ SUPERVISOR ] {target_agent} will now analyze the situation and execute necessary commands")
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print(f"[ SUPERVISOR ] (Any shell command output below belongs to {target_agent})")
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elif tool_name == 'transfer_back_to_supervisor':
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print(f" ℹ️ EXPLANATION: Agent completed its task and returned control to supervisor")
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print(f" ℹ️ Supervisor will decide the next step based on results")
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print(f"[ {current_agent} ] completed analysis and transferred control back to supervisor")
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print(f"[ {current_agent} ] (Any shell command output above was from {current_agent})")
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if hasattr(last_message, 'tool_call_id'):
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print(f"🔧 TOOL CALL ID: {last_message.tool_call_id}")
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# Show conversation context for better understanding
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agent_data = chunk[current_agent]
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# Show the result being sent back to supervisor
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# Look for the last AIMessage before this transfer to get the result
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if 'messages' in agent_data and len(agent_data['messages']) > 1:
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print(f"\n📚 CONVERSATION CONTEXT ({len(agent_data['messages'])} messages):")
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for i, msg in enumerate(agent_data['messages'][-3:], start=max(0, len(agent_data['messages'])-3)):
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msg_type = type(msg).__name__
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if hasattr(msg, 'content') and msg.content:
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preview = msg.content[:100].replace('\n', ' ')
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if len(msg.content) > 100:
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preview += "..."
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print(f" {i+1}. {msg_type}: {preview}")
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elif hasattr(msg, 'tool_calls') and msg.tool_calls:
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tool_names = [getattr(tc, 'name', 'unknown') for tc in msg.tool_calls]
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print(f" {i+1}. {msg_type}: Tool calls: {tool_names}")
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# Look for the most recent AIMessage with content
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for msg in reversed(agent_data['messages'][:-1]): # Exclude current ToolMessage
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if type(msg).__name__ == 'AIMessage' and hasattr(msg, 'content') and msg.content:
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result_content = msg.content
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if len(result_content) > 300:
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preview = result_content[:300] + "..."
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print(f"[ {current_agent} ] sending result to supervisor (preview): {preview}")
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print(f"[ {current_agent} ] (full result length: {len(result_content)} characters)")
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else:
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print(f" {i+1}. {msg_type}: (no content)")
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print(f"[ {current_agent} ] sending result to supervisor: {result_content}")
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break
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else:
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print(f"[ {current_agent} ] sending analysis results to supervisor")
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else:
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print(f"[ {current_agent} ] sending analysis results to supervisor")
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else:
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# Other tool execution result
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if len(content) > 200:
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preview = content[:200] + "..."
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print(f"[ {current_agent} ] tool result preview: {preview}")
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print(f"[ {current_agent} ] (full result length: {len(content)} characters)")
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else:
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print(f"[ {current_agent} ] tool result: {content}")
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elif message_type == 'AIMessage':
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# Agent is responding or making tool calls
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content = getattr(last_message, 'content', '')
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tool_calls = getattr(last_message, 'tool_calls', [])
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if tool_calls:
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for tool_call in tool_calls:
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tool_name = getattr(tool_call, 'name', 'unknown')
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if tool_name.startswith('transfer_to_'):
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target_agent = tool_name.replace('transfer_to_', '').upper()
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args = getattr(tool_call, 'args', {})
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context = str(args)[:150] + "..." if len(str(args)) > 150 else str(args)
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print(f"[ SUPERVISOR ] calling {target_agent} with context: {context}")
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elif tool_name == 'transfer_back_to_supervisor':
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print(f"[ {current_agent} ] completed task, transferring back to supervisor")
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print() # Extra spacing for readability
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else:
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print("📋 CHUNK DATA:")
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# Show first few keys for debugging
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chunk_keys = list(chunk.keys())[:3]
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print(f" Keys: {chunk_keys}")
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print(f"[ {current_agent} ] using tool: {tool_name}")
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args = getattr(tool_call, 'args', {})
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if args:
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args_preview = str(args)[:100] + "..." if len(str(args)) > 100 else str(args)
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print(f"[ {current_agent} ] tool arguments: {args_preview}")
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elif content:
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# Final response from agent
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if len(content) > 200:
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preview = content[:200] + "..."
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print(f"[ {current_agent} ] response preview: {preview}")
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print(f"[ {current_agent} ] (full response length: {len(content)} characters)")
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else:
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print(f"📦 CHUNK TYPE: {type(chunk)}")
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print(f"📄 CONTENT: {str(chunk)[:100]}...")
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print(f"[ {current_agent} ] response: {content}")
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else:
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print(f"[ {current_agent} ] {message_type}: {getattr(last_message, 'content', 'No content')[:100]}")
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else:
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print(f"[ {current_agent} ] no message data available")
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else:
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print("[ SYSTEM ] processing chunk with keys:", list(chunk.keys())[:3])
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else:
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print(f"[ SYSTEM ] received {type(chunk).__name__}: {str(chunk)[:100]}{'...' if len(str(chunk)) > 100 else ''}")
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except Exception as e:
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print(f"❌ Error processing chunk: {e}")
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print(f"📦 CHUNK TYPE: {type(chunk)}")
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print(f"[ ERROR ] processing step {step_count}: {e}")
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print(f"[ DEBUG ] chunk type: {type(chunk)}")
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if hasattr(chunk, '__dict__'):
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print(f"📄 CHUNK ATTRIBUTES: {list(chunk.__dict__.keys())}")
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print(f"[ DEBUG ] chunk attributes: {list(chunk.__dict__.keys())}")
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print("-" * 30)
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print(f"{'='*60}")
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print(f"NOTE: Shell command output may appear below before the next step")
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