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112 lines
2.4 KiB
112 lines
2.4 KiB
import os
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from dotenv import load_dotenv
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from examples.demos.plant_biologist_swarm.prompts import (
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diagnoser_agent,
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disease_detector_agent,
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growth_predictor_agent,
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harvester_agent,
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treatment_recommender_agent,
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)
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from swarms import Agent, ConcurrentWorkflow
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from swarm_models.gpt_o import GPT4VisionAPI
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# Load the OpenAI API key from the .env file
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load_dotenv()
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# Initialize the OpenAI API key
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api_key = os.environ.get("OPENAI_API_KEY")
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# GPT4VisionAPI
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llm = GPT4VisionAPI(
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max_tokens=4000,
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)
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# Initialize Diagnoser Agent
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diagnoser_agent = Agent(
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agent_name="Diagnoser Agent",
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system_prompt=diagnoser_agent(),
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llm=llm,
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max_loops=1,
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dashboard=False,
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streaming_on=True,
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verbose=True,
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# saved_state_path="diagnoser.json",
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multi_modal=True,
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autosave=True,
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)
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# Initialize Harvester Agent
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harvester_agent = Agent(
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agent_name="Harvester Agent",
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system_prompt=harvester_agent(),
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llm=llm,
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max_loops=1,
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dashboard=False,
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streaming_on=True,
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verbose=True,
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# saved_state_path="harvester.json",
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multi_modal=True,
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autosave=True,
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)
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# Initialize Growth Predictor Agent
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growth_predictor_agent = Agent(
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agent_name="Growth Predictor Agent",
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system_prompt=growth_predictor_agent(),
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llm=llm,
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max_loops=1,
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dashboard=False,
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streaming_on=True,
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verbose=True,
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# saved_state_path="growth_predictor.json",
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multi_modal=True,
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autosave=True,
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)
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# Initialize Treatment Recommender Agent
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treatment_recommender_agent = Agent(
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agent_name="Treatment Recommender Agent",
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system_prompt=treatment_recommender_agent(),
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llm=llm,
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max_loops=1,
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dashboard=False,
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streaming_on=True,
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verbose=True,
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# saved_state_path="treatment_recommender.json",
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multi_modal=True,
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autosave=True,
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)
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# Initialize Disease Detector Agent
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disease_detector_agent = Agent(
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agent_name="Disease Detector Agent",
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system_prompt=disease_detector_agent(),
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llm=llm,
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max_loops=1,
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dashboard=False,
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streaming_on=True,
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verbose=True,
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# saved_state_path="disease_detector.json",
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multi_modal=True,
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autosave=True,
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)
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agents = [
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diagnoser_agent,
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disease_detector_agent,
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treatment_recommender_agent,
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growth_predictor_agent,
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harvester_agent,
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]
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# Create the Concurrent workflow
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workflow = ConcurrentWorkflow(
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agents=agents,
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max_loops=1,
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)
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workflow.run("Diagnose the plant disease.")
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