Integrate LangSmith for Multi-Agent Tracing

Integrate LangSmith into your AutoGen multi-agent system to trace the entire conversation and tool execution flow. Configure the `LANGCHAIN_API_KEY` and `LANGCHAIN_TRACING_V2` environment variables. Demonstrate how LangSmith visualizes the interactions between different agents, LLM calls, and tool uses, which is critical for debugging complex multi-agent reasoning. Provide a code snippet showing how to enable LangSmith for your AutoGen `GroupChat` or individual agents. 

```python
import os

os.environ["LANGCHAIN_API_KEY"] = "YOUR_LANGSMITH_API_KEY"
os.environ["LANGCHAIN_TRACING_V2"] = "true"
os.environ["LANGCHAIN_PROJECT"] = "AutoGen_CRE_Analysis"

# (After defining agents and tools)
# groupchat = autogen.GroupChat(agents=[user_proxy, analyst_agent], messages=[], max_round=12)
# manager = autogen.GroupChatManager(groupchat=groupchat, llm_config={"config_list": config_list_claude})

# (Then initiate the conversation)
# user_proxy.initiate_chat(manager, message="Analyze the retail property market in Austin, TX.")
```