AutoGen Setup and Agent Definition

Initialize AutoGen and define the core agents for the system: a 'UserTopicAnalyzer' (using Gemini 2.5 Flash), an 'AdStrategist', a 'PrivacyAuditor', and a 'FactChecker'. Configure their roles, system messages, and communication patterns. Consider using `ConversableAgent` for custom logic and `AssistantAgent` for LLM integration.

```python
import autogen

config_list = [
    {
        "model": "gemini-2.5-flash",
        "api_key": "YOUR_GEMINI_API_KEY",
        "api_type": "google",
        "base_url": "https://generativelanguage.googleapis.com/v1beta",
    }
    # Add other LLM configurations as needed
]

llm_config = {"config_list": config_list, "temperature": 0.7}

# Define agents
user_proxy = autogen.UserProxyAgent(
    name="admin",
    human_input_mode="TERMINATE",
    max_consecutive_auto_reply=10,
    is_termination_msg=lambda x: x.get("content", "").rstrip().endswith("TERMINATE"),
    code_execution_config={"last_n_messages": 3, "work_dir": "coding"},
)

user_topic_analyzer = autogen.AssistantAgent(
    name="UserTopicAnalyzer",
    llm_config=llm_config,
    system_message="You are an expert at analyzing user conversation data to extract primary topics and interests. Use Gemini 2.5 Flash to quickly identify key themes for ad targeting.",
)

ad_strategist = autogen.AssistantAgent(
    name="AdStrategist",
    llm_config=llm_config, # Or a different LLM config
    system_message="You are an ad campaign manager. Based on user topics, propose a concise ad strategy, including title, target audience, and key phrases. Await privacy review.",
)

# ... continue defining PrivacyAuditor and FactChecker agents
```