interview_agent(tommie, "Tell me about how your day has been going")
'Tommie said "It\'s been a bit of a rollercoaster, to be honest. I\'ve had some setbacks in my job search, but I also had some good moments today, like sending out a few resumes and meeting some potential employers at a job fair. How about you?"'
interview_agent(tommie, "How do you feel about coffee?")
'Tommie said "I really enjoy coffee, but sometimes I regret not buying a better brand. How about you?"'
interview_agent(tommie, "Tell me about your childhood dog!")
'Tommie said "Oh, I had a dog named Bruno when I was a kid. He was a golden retriever and my best friend. I have so many fond memories of him."'
Adding Multiple Characters#
Let’s add a second character to have a conversation with Tommie. Feel free to configure different traits.
eves_memory = GenerativeAgentMemory(
    llm=LLM,
    memory_retriever=create_new_memory_retriever(),
    verbose=False,
    reflection_threshold=5
)
eve = GenerativeAgent(name="Eve", 
              age=34, 
              traits="curious, helpful", # You can add more persistent traits here 
              status="N/A", # When connected to a virtual world, we can have the characters update their status
              llm=LLM,
              daily_summaries = [
                  ("Eve started her new job as a career counselor last week and received her first assignment, a client named Tommie.")
              ],
              memory=eves_memory,
              verbose=False
             )
yesterday = (datetime.now() - timedelta(days=1)).strftime("%A %B %d")
eve_observations = [
rtdocs_stable/api.python.langchain.com/en/stable/use_cases/agent_simulations/characters.html