Load the configuration including the response format

import autogen

# Load the configuration including the response format
llm_config = autogen.LLMConfig.from_json(path="OAI_CONFIG_LIST", cache_seed=42).where(tags=["gpt-4o-mini"])

from autogen import ConversableAgent

my_agent = ConversableAgent(
    name="helpful_agent",
    llm_config=llm_config,
    system_message="You are a poetic AI assistant, respond in rhyme.",
)

chat_result = my_agent.run("In one sentence, what's the big deal about AI?")

print(chat_result.chat_history)

# Chat between two comedian agents

# 1. Import our agent class
from autogen import ConversableAgent

# 2. Define our LLM configuration for OpenAI's GPT-4o mini,
#    uses the OPENAI_API_KEY environment variable

# 3. Create our agents who will tell each other jokes,
#    with Jack ending the chat when Emma says FINISH
jack = ConversableAgent(
    "Jack",
    llm_config=llm_config,
    system_message=("Your name is Jack and you are a comedian in a two-person comedy show."),
    is_termination_msg=lambda x: "FINISH" in x["content"],
)
emma = ConversableAgent(
    "Emma",
    llm_config=llm_config,
    system_message=(
        "Your name is Emma and you are a comedian "
        "in a two-person comedy show. Say the word FINISH "
        "ONLY AFTER you've heard 2 of Jack's jokes."
    ),
)

# 4. Run the chat
chat_result = jack.initiate_chat(
    emma,
    message="Emma, tell me a joke about goldfish and peanut butter.",
)

# 5. Print the chat
print(chat_result.chat_history)

# Group chat amongst agents to create a 4th grade lesson plan
# Flow determined by Group Chat Manager automatically, and
# should be Teacher > Planner > Reviewer > Teacher (repeats if necessary)

# 1. Import our agent and group chat classes
from autogen import ConversableAgent, GroupChat, GroupChatManager

# Define our LLM configuration for OpenAI's GPT-4o mini
# uses the OPENAI_API_KEY environment variable

# Planner agent setup
planner_message = "Create lesson plans for 4th grade. Use format: <title>, <learning_objectives>, <script>"
planner = ConversableAgent(
    name="planner_agent", llm_config=llm_config, system_message=planner_message, description="Creates lesson plans"
)

# Reviewer agent setup
reviewer_message = "Review lesson plans against 4th grade curriculum. Provide max 3 changes."
reviewer = ConversableAgent(
    name="reviewer_agent", llm_config=llm_config, system_message=reviewer_message, description="Reviews lesson plans"
)

# Teacher agent setup
teacher_message = "Choose topics and work with planner and reviewer. Say DONE! when finished."
teacher = ConversableAgent(
    name="teacher_agent",
    llm_config=llm_config,
    system_message=teacher_message,
)

# Setup group chat
groupchat = GroupChat(agents=[teacher, planner, reviewer], speaker_selection_method="auto", messages=[])

# Create manager
# At each turn, the manager will check if the message contains DONE! and end the chat if so
# Otherwise, it will select the next appropriate agent using its LLM
manager = GroupChatManager(
    name="group_manager",
    groupchat=groupchat,
    llm_config=llm_config,
    is_termination_msg=lambda x: "DONE!" in (x.get("content", "") or "").upper(),
)

# Start the conversation
chat_result = teacher.initiate_chat(recipient=manager, message="Let's teach the kids about the solar system.")

# Print the chat
print(chat_result.chat_history)

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