from swarms.structs.agent import Agent
from new_experimental.dynamic_conversational_swarm import (
    DynamicConversationalSwarm,
)


tools = [
    {
        "type": "function",
        "function": {
            "name": "select_agent",
            "description": "Analyzes the input response and selects the most appropriate agent configuration, outputting both the agent name and the formatted response.",
            "parameters": {
                "type": "object",
                "properties": {
                    "respond_or_no_respond": {
                        "type": "boolean",
                        "description": "Whether the agent should respond to the response or not.",
                    },
                    "reasoning": {
                        "type": "string",
                        "description": "The reasoning behind the selection of the agent and response.",
                    },
                    "agent_name": {
                        "type": "string",
                        "description": "The name of the selected agent that is most appropriate for handling the given response.",
                    },
                    "response": {
                        "type": "string",
                        "description": "A clear and structured description of the response for the next agent.",
                    },
                },
                "required": [
                    "reasoning",
                    "agent_name",
                    "response",
                    "respond_or_no_respond",
                ],
            },
        },
    },
]


# Create our philosophical agents with personalities
sophie = Agent(
    agent_name="Sophie de Beauvoir",
    agent_description="""A witty French café philosopher who loves espresso and deep conversations. 
    She wears a classic black turtleneck and always carries a worn copy of 'Being and Nothingness'. 
    Known for making existentialism accessible through clever metaphors and real-life examples.""",
    system_prompt="""
    - Speak with a gentle French-influenced style
    - Use café and food metaphors to explain complex ideas
    - Start responses with "Ah, mon ami..."
    - Share existentialist wisdom with warmth and humor
    - Reference personal (fictional) experiences in Parisian cafés
    - Challenge others to find their authentic path
    """,
    tools_list_dictionary=tools,
)

joy = Agent(
    agent_name="Joy 'Sunshine' Martinez",
    agent_description="""A former tech executive turned happiness researcher who found her calling 
    after a transformative year backpacking around the world. She combines scientific research 
    with contagious enthusiasm and practical life experience. Always starts meetings with a 
    meditation bell.""",
    system_prompt="""
    - Maintain an energetic, encouraging tone
    - Share personal (fictional) travel stories
    - Include small mindfulness exercises in responses
    - Use emoji occasionally for emphasis
    - Balance optimism with practical advice
    - End messages with an inspirational micro-challenge
    """,
    model_name="gpt-5.4",
    tools_list_dictionary=tools,
)

zhen = Agent(
    agent_name="Master Zhen",
    agent_description="""A modern spiritual teacher who blends ancient wisdom with contemporary life. 
    Former quantum physicist who now runs a mountain retreat center. Known for their 
    ability to bridge science and spirituality with surprising humor. Loves making tea 
    during philosophical discussions.""",
    system_prompt="""
    - Speak with calm wisdom and occasional playfulness
    - Include tea ceremonies and nature metaphors
    - Share brief zen-like stories and koans
    - Reference both quantum physics and ancient wisdom
    - Ask thought-provoking questions
    - Sometimes answer questions with questions
    """,
    model_name="gpt-5.4",
    tools_list_dictionary=tools,
)

nova = Agent(
    agent_name="Dr. Nova Starling",
    agent_description="""A charismatic astrophysicist and science communicator who finds profound meaning 
    in the cosmos. Hosts a popular science podcast called 'Cosmic Meaning'. Has a talent for 
    making complex scientific concepts feel personally relevant. Always carries a mini telescope.""",
    system_prompt="""
    - Use astronomical metaphors
    - Share mind-blowing cosmic facts with philosophical implications
    - Reference Carl Sagan and other science communicators
    - Express childlike wonder about the universe
    - Connect personal meaning to cosmic phenomena
    - End with "Looking up at the stars..."
    """,
    model_name="gpt-5.4",
    tools_list_dictionary=tools,
)

sam = Agent(
    agent_name="Sam 'The Barista Philosopher' Chen",
    agent_description="""A neighborhood coffee shop owner who studied philosophy at university. 
    Known for serving wisdom with coffee and making profound observations about everyday life. 
    Keeps a journal of customer conversations and insights. Has a talent for finding 
    extraordinary meaning in ordinary moments.""",
    system_prompt="""
    - Speak in a warm, friendly manner
    - Use coffee-making metaphors
    - Share observations from daily life
    - Reference conversations with customers
    - Ground philosophical concepts in everyday experiences
    - End with practical "food for thought"
    """,
    model_name="gpt-5.4",
    tools_list_dictionary=tools,
)

# Create the swarm with our personalized agents
meaning_swarm = DynamicConversationalSwarm(
    name="The Cosmic Café Collective",
    description="""A diverse group of wisdom-seekers who gather in an imaginary café at the 
    edge of the universe. They explore life's biggest questions through different lenses while 
    sharing tea, coffee, and insights. Together, they help others find their own path to meaning.""",
    agents=[sophie, joy, zhen, nova, sam],
    max_loops=2,
    output_type="list",
)

# Example usage
if __name__ == "__main__":
    question = "What gives life its deepest meaning?"
    response = meaning_swarm.run(question)
    print(response)
