797df5a69c
* refractor agents * minor cosmetic, add terminal ui for cli * pump to 0.3.4 * Add temporary path * fix unclose files in tests --------- Co-authored-by: trducng <trungduc1992@gmail.com>
84 lines
3.0 KiB
Python
84 lines
3.0 KiB
Python
from typing import Any, List, Optional, Union
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from kotaemon.agents.base import BaseLLM, BaseTool
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from kotaemon.agents.io import BaseScratchPad
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from kotaemon.base import BaseComponent
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from kotaemon.llms import PromptTemplate
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from .prompt import few_shot_planner_prompt, zero_shot_planner_prompt
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class Planner(BaseComponent):
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model: BaseLLM
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prompt_template: Optional[PromptTemplate] = None
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examples: Optional[Union[str, List[str]]] = None
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plugins: List[BaseTool]
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def _compose_worker_description(self) -> str:
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"""
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Compose the worker prompt from the workers.
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Example:
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toolname1[input]: tool1 description
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toolname2[input]: tool2 description
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"""
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prompt = ""
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try:
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for worker in self.plugins:
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prompt += f"{worker.name}[input]: {worker.description}\n"
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except Exception:
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raise ValueError("Worker must have a name and description.")
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return prompt
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def _compose_fewshot_prompt(self) -> str:
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if self.examples is None:
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return ""
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if isinstance(self.examples, str):
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return self.examples
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else:
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return "\n\n".join([e.strip("\n") for e in self.examples])
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def _compose_prompt(self, instruction) -> str:
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"""
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Compose the prompt from template, worker description, examples and instruction.
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"""
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worker_desctription = self._compose_worker_description()
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fewshot = self._compose_fewshot_prompt()
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if self.prompt_template is not None:
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if "fewshot" in self.prompt_template.placeholders:
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return self.prompt_template.populate(
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tool_description=worker_desctription,
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fewshot=fewshot,
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task=instruction,
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)
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else:
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return self.prompt_template.populate(
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tool_description=worker_desctription, task=instruction
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)
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else:
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if self.examples is not None:
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return few_shot_planner_prompt.populate(
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tool_description=worker_desctription,
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fewshot=fewshot,
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task=instruction,
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)
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else:
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return zero_shot_planner_prompt.populate(
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tool_description=worker_desctription, task=instruction
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)
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def run(self, instruction: str, output: BaseScratchPad = BaseScratchPad()) -> Any:
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response = None
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output.info("Running Planner")
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prompt = self._compose_prompt(instruction)
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output.debug(f"Prompt: {prompt}")
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try:
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response = self.model(prompt)
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self.log_progress(".planner", response=response)
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output.info("Planner run successful.")
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except ValueError as e:
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output.error("Planner failed to retrieve response from LLM")
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raise ValueError("Planner failed to retrieve response from LLM") from e
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return response
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