Configure AutoGen Multi-Agent Team for Vehicle Simulation

Your first task is to set up an AutoGen multi-agent team for autonomous vehicle simulation. Define at least three agent roles: `SensorInterpreter`, `PathPlanner`, and `DecisionMaker`. Configure them to use GPT-5 Pro and Claude 4 Sonnet for their respective reasoning tasks. The `SensorInterpreter` should relay raw sensor data to the `PathPlanner`. ```python
import autogen
from autogen import AssistantAgent, UserProxyAgent # Configure models for AutoGen
config_list_autogen = [ {"model": "gpt-5-pro", "api_key": "YOUR_OPENAI_KEY"}, {"model": "claude-4-sonnet", "api_key": "YOUR_ANTHROPIC_KEY"},
] # Initialize agents
sensor_interpreter = AssistantAgent( name="SensorInterpreter", llm_config={"config_list": config_list_autogen, "temperature": 0.3, "model": "claude-4-sonnet"}, system_message="You interpret raw sensor data (e.g., lidar, camera) into structured observations about the environment."
) path_planner = AssistantAgent( name="PathPlanner", llm_config={"config_list": config_list_autogen, "temperature": 0.7, "model": "gpt-5-pro"}, system_message="You receive environmental observations and generate optimal, safe driving paths to a destination."
) decision_maker = AssistantAgent( name="DecisionMaker", llm_config={"config_list": config_list_autogen, "temperature": 0.5, "model": "claude-4-sonnet"}, system_message="You receive planned paths and sensor data, making real-time tactical driving decisions like braking, accelerating, or steering."
) # User proxy agent to initiate conversations (simulating human input or environment)
user_proxy = UserProxyAgent( name="HumanDriver", human_input_mode="NEVER", is_termination_msg=lambda x: "TERMINATE" in x.get("content", ""), code_execution_config={"last_n_messages": 3, "work_dir": "coding"},
) # Define group chat and start conversation
# groupchat = autogen.GroupChat(agents=[sensor_interpreter, path_planner, decision_maker, user_proxy], messages=[], max_round=20)
# manager = autogen.GroupChatManager(groupchat=groupchat, llm_config={"config_list": config_list_autogen})
# user_proxy.initiate_chat(manager, message="Initial sensor data: traffic light red at intersection X. Destination: Y.")
```