- Migrate the MVP into kotaemon. - Preliminary include the pipeline within chatbot interface. - Organize MVP as an application. Todo: - Add an info panel to view the planning of agents -> Fix streaming agents' output. Resolve: #60 Resolve: #61 Resolve: #62
33 lines
916 B
Python
33 lines
916 B
Python
from typing import AnyStr, Optional, Type
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from pydantic import BaseModel, Field
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from kotaemon.llms import BaseLLM
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from .base import BaseTool, ToolException
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class LLMArgs(BaseModel):
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query: str = Field(..., description="a search question or prompt")
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class LLMTool(BaseTool):
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name: str = "llm"
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description: str = (
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"A pretrained LLM like yourself. Useful when you need to act with "
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"general world knowledge and common sense. Prioritize it when you "
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"are confident in solving the problem "
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"yourself. Input can be any instruction."
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)
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llm: BaseLLM
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args_schema: Optional[Type[BaseModel]] = LLMArgs
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def _run_tool(self, query: AnyStr) -> str:
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output = None
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try:
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response = self.llm(query)
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except ValueError:
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raise ToolException("LLM Tool call failed")
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output = response.text
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return output
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