AutoGen

# Install AutoGen
# pip install autogen-agentchat

from autogen import AssistantAgent, UserProxyAgent
import os

# Configure LLM
llm_config = {
    "config_list": [{
        "model": "gpt-4o-mini",
        "api_key": os.getenv("OPENAI_API_KEY")
    }]
}

# Create assistant agent
assistant = AssistantAgent(
    name="assistant",
    llm_config=llm_config,
    system_message="You are a helpful AI assistant."
)

# Create user proxy (can execute code)
user_proxy = UserProxyAgent(
    name="user",
    human_input_mode="TERMINATE",  # or "ALWAYS" for human approval
    code_execution_config={"use_docker": False}
)

# Start conversation
user_proxy.initiate_chat(
    assistant,
    message="Write a Python function to calculate factorial."
)

from autogen import AssistantAgent, UserProxyAgent, GroupChat, GroupChatManager

# Create specialized agents
planner = AssistantAgent(
    name="planner",
    system_message="You break down tasks into steps. Don't write code.",
    llm_config=llm_config
)

coder = AssistantAgent(
    name="coder",
    system_message="You write Python code based on plans.",
    llm_config=llm_config
)

reviewer = AssistantAgent(
    name="reviewer",
    system_message="You review code for bugs and improvements.",
    llm_config=llm_config
)

executor = UserProxyAgent(
    name="executor",
    human_input_mode="NEVER",
    code_execution_config={"use_docker": False}
)

# Create group chat
group_chat = GroupChat(
    agents=[planner, coder, reviewer, executor],
    messages=[],
    max_round=10
)

# Manager orchestrates the conversation
manager = GroupChatManager(groupchat=group_chat, llm_config=llm_config)

# Start the team
executor.initiate_chat(manager, message="Build a REST API endpoint for user registration.")

from autogen import AssistantAgent, UserProxyAgent, register_function

# Define a tool function
def get_weather(city: str) -> str:
    """Get weather for a city."""
    # In production, call real API
    return f"Weather in {city}: 22°C, Sunny"

def search_web(query: str) -> str:
    """Search the web for information."""
    return f"Search results for '{query}': [result 1, result 2]"

# Create agents
assistant = AssistantAgent(name="assistant", llm_config=llm_config)
user = UserProxyAgent(name="user", human_input_mode="NEVER")

# Register functions for both agents
register_function(
    get_weather,
    caller=assistant,      # Agent that suggests tool calls
    executor=user,         # Agent that executes tools
    description="Get current weather for a city"
)

register_function(
    search_web,
    caller=assistant,
    executor=user,
    description="Search the web for information"
)

# The assistant will now use these tools
user.initiate_chat(assistant, message="What's the weather in London?")