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49 lines
1.1 KiB
49 lines
1.1 KiB
import os
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from dotenv import load_dotenv
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# Import the OpenAIChat model and the Agent struct
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from swarms.models import OpenAIChat
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from swarms.structs import Agent
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from swarms.structs.swarm_net import SwarmNetwork
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# Load the environment variables
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load_dotenv()
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# Get the API key from the environment
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api_key = os.environ.get("OPENAI_API_KEY")
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# Initialize the language model
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llm = OpenAIChat(
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temperature=0.5,
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openai_api_key=api_key,
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)
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## Initialize the workflow
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agent = Agent(llm=llm, max_loops=1, agent_name="Social Media Manager")
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agent2 = Agent(llm=llm, max_loops=1, agent_name=" Product Manager")
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agent3 = Agent(llm=llm, max_loops=1, agent_name="SEO Manager")
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# Load the swarmnet with the agents
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swarmnet = SwarmNetwork(
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agents=[agent, agent2, agent3],
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)
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# List the agents in the swarm network
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out = swarmnet.list_agents()
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print(out)
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# Run the workflow on a task
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out = swarmnet.run_single_agent(
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agent2.id, "Generate a 10,000 word blog on health and wellness."
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)
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print(out)
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# Run all the agents in the swarm network on a task
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out = swarmnet.run_many_agents(
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"Generate a 10,000 word blog on health and wellness."
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)
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print(out)
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