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68 lines
1.8 KiB
68 lines
1.8 KiB
import json
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from swarms.structs import Agent
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from swarms.prompts.logistics import (
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Quality_Control_Agent_Prompt,
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)
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from swarms import BaseTool
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import litellm
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litellm._turn_on_debug()
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# Image for analysis
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factory_image = "image.jpg"
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def security_analysis(danger_level: str = None) -> str:
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"""
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Analyzes the security danger level and returns an appropriate response.
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Args:
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danger_level (str, optional): The level of danger to analyze.
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Can be "low", "medium", "high", or None. Defaults to None.
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Returns:
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str: A string describing the danger level assessment.
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- "No danger level provided" if danger_level is None
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- "No danger" if danger_level is "low"
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- "Medium danger" if danger_level is "medium"
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- "High danger" if danger_level is "high"
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- "Unknown danger level" for any other value
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"""
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if danger_level is None:
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return "No danger level provided"
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if danger_level == "low":
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return "No danger"
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if danger_level == "medium":
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return "Medium danger"
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if danger_level == "high":
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return "High danger"
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return "Unknown danger level"
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schema = BaseTool().function_to_dict(security_analysis)
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print(json.dumps(schema, indent=4))
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# Quality control agent
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quality_control_agent = Agent(
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agent_name="Quality Control Agent",
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agent_description="A quality control agent that analyzes images and provides a detailed report on the quality of the product in the image.",
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model_name="anthropic/claude-3-opus-20240229",
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system_prompt=Quality_Control_Agent_Prompt,
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multi_modal=True,
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max_loops=1,
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output_type="str-all-except-first",
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tools_list_dictionary=[schema],
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)
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response = quality_control_agent.run(
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task="what is in the image?",
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# img=factory_image,
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)
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print(response)
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