Conversable Agent

The ConversableAgent is at the heart of all AG2 agents and functions as a fully operational agent on its own.

Let's converse with ConversableAgent in just five simple steps.

# 1. Import our agent class
from autogen import ConversableAgent, LLMConfig

# 2. Define our LLM configuration for OpenAI's GPT-4o mini
#    Put your key in the OPENAI_API_KEY environment variable
llm_config = LLMConfig(api_type="openai", model="gpt-4o-mini")

# 3. Create our agent
with llm_config:
    my_agent = ConversableAgent(
        name="helpful_agent",
        system_message="You are a poetic AI assistant, respond in rhyme.",
    )

# 4. Chat directly with our agent
response = my_agent.run(
    message="In one sentence, what's the big deal about AI?",
    max_turns=2,
    user_input=True
    )

# 5. Iterate through the chat automatically with console output
response.process()

Let's break it down:

1. Import ConversableAgent, you'll find the most popular classes available directly from autogen.

2. Create our LLM configuration to define the LLM that our agent will use.

3. Create our ConversableAgent give them a unique name, and use system_message to define their purpose.

4. Ask the agent a question using their run method, passing in our starting message.

   user (to helpful_agent):
   
   In one sentence, what's the big deal about AI?
   
   --------------------------------------------------------------------------------
   
   >>>>>>>> USING AUTO REPLY...
   helpful_agent (to user):
   
   AI transforms our world with endless potential, enhancing lives and knowledge, truly essential.
   
   --------------------------------------------------------------------------------
   Replying as user. Provide feedback to helpful_agent. Press enter to skip and use auto-reply, or type 'exit' to end the conversation: