Kye
1 year ago
parent
b457511bde
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"""
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Swarm of multi modal autonomous agents for manufacturing!
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---------------------------------------------------------
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Health Security agent: Agent that monitors the health of working conditions: input image of factory output: health safety index 0.0 - 1.0 being the highest
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Quality Control agent: Agent that monitors the quality of the product: input image of product output: quality index 0.0 - 1.0 being the highest
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Productivity agent: Agent that monitors the productivity of the factory: input image of factory output: productivity index 0.0 - 1.0 being the highest
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Safety agent: Agent that monitors the safety of the factory: input image of factory output: safety index 0.0 - 1.0 being the highest
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Security agent: Agent that monitors the security of the factory: input image of factory output: security index 0.0 - 1.0 being the highest
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Sustainability agent: Agent that monitors the sustainability of the factory: input image of factory output: sustainability index 0.0 - 1.0 being the highest
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Efficiency agent: Agent that monitors the efficiency of the factory: input image of factory output: efficiency index 0.0 - 1.0 being the highest
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Flow:
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health security agent -> quality control agent -> productivity agent -> safety agent -> security agent -> sustainability agent -> efficiency agent
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"""
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from swarms.structs import Flow, SequentialWorkflow
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import os
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from dotenv import load_dotenv
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from swarms.models import GPT4VisionAPI
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from swarms.prompts.multi_modal_autonomous_instruction_prompt import (
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MULTI_MODAL_AUTO_AGENT_SYSTEM_PROMPT_1,
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)
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load_dotenv()
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api_key = os.getenv("OPENAI_API_KEY")
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llm = GPT4VisionAPI(
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openai_api_key=api_key
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)
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assembly_line = "playground/demos/swarm_of_mma_manufacturing/assembly_line.jpg"
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red_robots = "playground/demos/swarm_of_mma_manufacturing/red_robots.jpg"
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robots = "playground/demos/swarm_of_mma_manufacturing/robots.jpg"
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tesla_assembly_line = "playground/demos/swarm_of_mma_manufacturing/tesla_assembly.jpg"
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# Define detailed prompts for each agent
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tasks = {
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"health_safety": (
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"Analyze the factory's working environment for health safety. Focus on"
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" cleanliness, ventilation, spacing between workstations, and personal"
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" protective equipment availability."
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),
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"productivity": (
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"Review the factory's workflow efficiency, machine utilization, and"
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" employee engagement. Identify operational delays or bottlenecks."
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),
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"safety": (
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"Analyze the factory's safety measures, including fire exits, safety"
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" signage, and emergency response equipment."
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),
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"security": (
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"Evaluate the factory's security systems, entry/exit controls, and"
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" potential vulnerabilities."
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),
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"sustainability": (
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"Inspect the factory's sustainability practices, including waste"
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" management, energy usage, and eco-friendly processes."
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),
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"efficiency": (
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"Assess the manufacturing process's efficiency, considering the layout,"
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" logistics, and automation level."
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),
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}
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# Define prompts for each agent
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health_safety_prompt = tasks["health_safety"]
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productivity_prompt = tasks["productivity"]
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safety_prompt = tasks["safety"]
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security_prompt = tasks["security"]
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sustainability_prompt = tasks["sustainability"]
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efficiency_prompt = tasks["efficiency"]
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# Health security agent
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health_security_agent = Flow(
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llm=llm,
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sop_list=health_safety_prompt,
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max_loops=2,
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multi_modal=True
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)
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# Quality control agent
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productivity_check_agent = Flow(
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llm=llm,
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sop=productivity_prompt,
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max_loops=2,
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multi_modal=True
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)
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# Security agent
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security_check_agent = Flow(
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llm=llm,
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sop=security_prompt,
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max_loops=2,
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multi_modal=True
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)
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# Efficiency agent
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efficiency_check_agent = Flow(
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llm=llm,
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sop=efficiency_prompt,
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max_loops=2,
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multi_modal=True
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)
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# Add the first task to the health_security_agent
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health_check = health_security_agent.run(
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"Analyze the safety of this factory",
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robots
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)
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# Add the third task to the productivity_check_agent
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productivity_check = productivity_check_agent.run(
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health_check, assembly_line
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)
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# Add the fourth task to the security_check_agent
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security_check = security_check_agent.add(
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productivity_check, red_robots
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)
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# Add the fifth task to the efficiency_check_agent
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efficiency_check = efficiency_check_agent.run(
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security_check, tesla_assembly_line
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)
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