693ed39de4
Since the only usage of prompt is within LLMs, it is reasonable to keep it within the LLM module. This way, it would be easier to discover module, and make the code base less complicated. Changes: * Move prompt components into llms * Bump version 0.3.1 * Make pip install dependencies in eager mode --------- Co-authored-by: ian <ian@cinnamon.is>
82 lines
2.9 KiB
Python
82 lines
2.9 KiB
Python
from typing import Any, List, Optional, Union
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from ....base import BaseComponent
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from ....llms import PromptTemplate
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from ..base import BaseLLM, BaseTool
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from ..output.base import BaseScratchPad
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from .prompt import 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 zero_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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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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