import autogen

# 1. Configure the LLM (Azure OpenAI)
config_list = [{
    "model": "gpt-4o",
    "api_type": "azure",
    "base_url": "https://your-resource.openai.azure.com/",
    "api_key": "<YOUR_KEY>",
}]

llm_config = {"config_list": config_list, "temperature": 0.1}

# 2. Create the Assistant Agent (LLM-powered)
assistant = autogen.AssistantAgent(
    name="DataAnalyst",
    llm_config=llm_config,
    system_message="You are an expert data analyst. Write Python code to answer questions."
)

# 3. Create the UserProxy Agent (executes code, approves)
user_proxy = autogen.UserProxyAgent(
    name="User",
    human_input_mode="NEVER",    # fully automated
    max_consecutive_auto_reply=5,
    code_execution_config={
        "work_dir": "workspace",
        "use_docker": False
    }
)

# 4. Start the conversation — agents collaborate until done
user_proxy.initiate_chat(
    assistant,
    message="Load sales.csv, compute monthly totals, and plot a bar chart."
)