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78 lines
2.0 KiB
78 lines
2.0 KiB
from swarms.models.openai_function_caller import OpenAIFunctionCaller
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from pydantic import BaseModel, Field
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from typing import List
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class Observation(BaseModel):
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observation: str = Field(
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...,
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description="What are you seeing in the image?",
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)
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summary_of_observation: str = Field(
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...,
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description="The summary of the observation/ img",
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)
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class Sequence(BaseModel):
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goal: str = Field(
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...,
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description="The goal of the mission",
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)
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observation: List[Observation] = Field(
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...,
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description="The observations of the agent",
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)
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action: str = Field(
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...,
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description="Take an action that leads to the completion of the task.",
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)
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class GoalDecomposer(BaseModel):
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goal: str = Field(
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...,
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description="The goal of the task",
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)
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sub_goals: List[str] = Field(
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...,
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description="The sub goals of the mission",
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)
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# Given the task t, observation o, the sub-goals
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# sequence g1, g2, g3, ..., gn can be formulated as:
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class KGP(BaseModel):
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task: str = Field(
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...,
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description="The task to be accomplished",
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)
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observation: str = Field(
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...,
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description="The observation of the task",
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)
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sequence: List[GoalDecomposer] = Field(
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...,
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description="The sequence of goals to accomplish the task",
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)
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# Example usage:
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# Initialize the function caller
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model = OpenAIFunctionCaller(
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system_prompt="You're an autonomous agent, you're purpose to accomplish a task through understanding your goal, observing the environment, and taking actions that lead to the completion of the task.",
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max_tokens=500,
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temperature=0.5,
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base_model=KGP,
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parallel_tool_calls=False,
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)
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# The OpenAIFunctionCaller class is used to interact with the OpenAI API and make function calls.
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out = model.run(
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"We need to craft a diamond pickaxe to mine the obsidian."
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)
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print(out)
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