Orchestrate Agent Conversation and Evaluation

Orchestrate the AutoGen agents' conversation flow, ensuring they communicate effectively to process an ad strategy from topic analysis to privacy audit and fact-checking. Set up a simple execution loop and prepare the final output in the required JSON format for evaluation.

```python
# Example of initiating a group chat
# groupchat = autogen.GroupChat(agents=[user_topic_analyzer, ad_strategist, privacy_auditor, fact_checker], messages=[], max_round=10)
# manager = autogen.GroupChatManager(groupchat=groupchat, llm_config=llm_config)

# user_proxy.initiate_chat(manager, message="Analyze user data for ad strategy and audit: {'user_topics': ..., 'ad_proposal': ..., 'privacy_policy': ...}")

# Ensure the final output is in the specified JSON format after the agents complete their tasks.
# This might involve a final agent or the user_proxy formatting the results.
```