foundationagents/metagpt/prompts

from typing import Optional
from abc import ABC
from metagpt.llm import LLM # Large language model, similar to GPT
class Action(ABC):
    def __init__(self, name='', context=None, llm: LLM = LLM()):
        self.name = name
        self.llm = llm
        self.context = context
        self.prefix = ""
        self.desc = ""
    def set_prefix(self, prefix):
        """Set prefix for subsequent use"""
        self.prefix = prefix
    async def _aask(self, prompt: str, system_msgs: Optional[list[str]] = None):
        """Use prompt with the default prefix"""
        if not system_msgs:
            system_msgs = []
        system_msgs.append(self.prefix)
        return await self.llm.aask(prompt, system_msgs)
    async def run(self, *args, **kwargs):
        """Execute action"""
        raise NotImplementedError("The run method should be implemented in a subclass.")
PROMPT_TEMPLATE = """
# Requirements
{requirements}
# PRD
Create a product requirement document (PRD) based on the requirements and fill in the blanks below:
Product/Function Introduction:
Goals:
Users and Usage Scenarios:
Requirements:
Constraints and Limitations:
Performance Metrics:
"""
class WritePRD(Action):
    def __init__(self, name="", context=None, llm=None):
        super().__init__(name, context, llm)
    async def run(self, requirements, *args, **kwargs):
        prompt = PROMPT_TEMPLATE.format(requirements=requirements)
        prd = await self._aask(prompt)
        return prd