mirror of
https://github.com/hwchase17/langchain
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33 lines
1.1 KiB
Python
33 lines
1.1 KiB
Python
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from typing import List
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from langchain.base_language import BaseLanguageModel
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from langchain.tools.base import BaseTool
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from langchain_experimental.autonomous_agents.hugginggpt.repsonse_generator import (
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load_response_generator,
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)
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from langchain_experimental.autonomous_agents.hugginggpt.task_executor import (
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TaskExecutor,
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)
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from langchain_experimental.autonomous_agents.hugginggpt.task_planner import (
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load_chat_planner,
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)
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class HuggingGPT:
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def __init__(self, llm: BaseLanguageModel, tools: List[BaseTool]):
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self.llm = llm
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self.tools = tools
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self.chat_planner = load_chat_planner(llm)
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self.response_generator = load_response_generator(llm)
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self.task_executor: TaskExecutor
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def run(self, input: str) -> str:
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plan = self.chat_planner.plan(inputs={"input": input, "hf_tools": self.tools})
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self.task_executor = TaskExecutor(plan)
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self.task_executor.run()
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response = self.response_generator.generate(
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{"task_execution": self.task_executor}
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)
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return response
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