import os

from dotenv import load_dotenv

# Import the OpenAIChat model and the Agent struct
from swarms import OpenAIChat, Agent, SwarmNetwork

# Load the environment variables
load_dotenv()

# Get the API key from the environment
api_key = os.environ.get("OPENAI_API_KEY")
org_id = os.environ.get("OPENAI_ORG_ID")

# Initialize the language model
llm = OpenAIChat(
    temperature=0.5,
    openai_api_key=api_key,
    openai_org_id=org_id,
)

## Initialize the workflow
agent = Agent(llm=llm, max_loops=1, agent_name="Social Media Manager")
agent2 = Agent(llm=llm, max_loops=1, agent_name=" Product Manager")
agent3 = Agent(llm=llm, max_loops=1, agent_name="SEO Manager")


# Load the swarmnet with the agents
swarmnet = SwarmNetwork(
    agents=[agent, agent2, agent3],
)

# List the agents in the swarm network
out = swarmnet.list_agents()
print(out)

# Run the workflow on a task
out = swarmnet.run_single_agent(
    agent2.id, "Generate a 10,000 word blog on health and wellness."
)
print(out)


# Run all the agents in the swarm network on a task
out = swarmnet.run_many_agents(
    "Generate a 10,000 word blog on health and wellness."
)
print(out)
