mirror of
https://github.com/FoundationAgents/MetaGPT.git
synced 2026-06-08 15:05:17 +02:00
refine a lot of code, fix pylint, use actionnode include ui, action _aask_v1, detail_mining, prepare_interview, etc.
This commit is contained in:
geekan
parent
8a1237460e
commit
f0fd5ac59b
12 changed files with 163 additions and 216 deletions
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@ -6,19 +6,26 @@
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@File : action.py
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"""
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from __future__ import annotations
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from abc import ABC
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from typing import Optional
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from tenacity import retry, stop_after_attempt, wait_random_exponential
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from metagpt.actions.action_output import ActionOutput
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from metagpt.actions.action_node import ActionNode
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from metagpt.llm import LLM
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from metagpt.logs import logger
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from metagpt.provider.postprecess.llm_output_postprecess import llm_output_postprecess
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from metagpt.utils.common import OutputParser, general_after_log
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from metagpt.schema import BaseContext
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class Action(ABC):
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"""Action abstract class, requiring all inheritors to provide a series of standard capabilities"""
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name: str
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llm: LLM
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context: dict | BaseContext | str | None
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prefix: str
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desc: str
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node: ActionNode | None
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def __init__(self, name: str = "", context=None, llm: LLM = None):
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self.name: str = name
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if llm is None:
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@ -27,7 +34,7 @@ class Action(ABC):
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self.context = context
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self.prefix = "" # aask*时会加上prefix，作为system_message
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self.desc = "" # for skill manager
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self.nodes = ...
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self.node = None
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def set_prefix(self, prefix):
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"""Set prefix for later usage"""
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@ -47,33 +54,6 @@ class Action(ABC):
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system_msgs.append(self.prefix)
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return await self.llm.aask(prompt, system_msgs)
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@retry(
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wait=wait_random_exponential(min=1, max=60),
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stop=stop_after_attempt(6),
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after=general_after_log(logger),
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)
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async def _aask_v1(
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self,
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prompt: str,
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output_class_name: str,
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output_data_mapping: dict,
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system_msgs: Optional[list[str]] = None,
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format="markdown", # compatible to original format
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) -> ActionOutput:
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content = await self.llm.aask(prompt, system_msgs)
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logger.debug(f"llm raw output:\n{content}")
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output_class = ActionOutput.create_model_class(output_class_name, output_data_mapping)
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if format == "json":
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parsed_data = llm_output_postprecess(output=content, schema=output_class.schema(), req_key="[/CONTENT]")
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else: # using markdown parser
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parsed_data = OutputParser.parse_data_with_mapping(content, output_data_mapping)
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logger.debug(f"parsed_data:\n{parsed_data}")
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instruct_content = output_class(**parsed_data)
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return ActionOutput(content, instruct_content)
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async def run(self, *args, **kwargs):
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"""Run action"""
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raise NotImplementedError("The run method should be implemented in a subclass.")
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@ -6,17 +6,15 @@
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@File : action_node.py
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"""
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import json
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import re
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from typing import Any, Dict, List, Optional, Type
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from typing import Dict, Generic, List, Optional, Type, TypeVar
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from pydantic import BaseModel, create_model, root_validator, validator
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from tenacity import retry, stop_after_attempt, wait_random_exponential
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from metagpt.actions import ActionOutput
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from metagpt.llm import BaseGPTAPI
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from metagpt.logs import logger
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from metagpt.utils.common import OutputParser
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from metagpt.utils.custom_decoder import CustomDecoder
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from metagpt.provider.postprecess.llm_output_postprecess import llm_output_postprecess
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from metagpt.utils.common import OutputParser, general_after_log
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CONSTRAINT = """
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- Language: Please use the same language as the user input.
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@ -43,14 +41,17 @@ Fill in the above nodes based on the format example.
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"""
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def dict_to_markdown(d, prefix="###", postfix="\n"):
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def dict_to_markdown(d, prefix="-", postfix="\n"):
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markdown_str = ""
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for key, value in d.items():
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markdown_str += f"{prefix} {key}: {value}{postfix}"
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return markdown_str
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class ActionNode:
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T = TypeVar("T")
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class ActionNode(Generic[T]):
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"""ActionNode is a tree of nodes."""
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mode: str
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@ -65,7 +66,7 @@ class ActionNode:
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expected_type: Type # such as str / int / float etc.
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# context: str # everything in the history.
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instruction: str # the instructions should be followed.
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example: Any # example for In Context-Learning.
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example: T # example for In Context-Learning.
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# Action Output
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content: str
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@ -76,7 +77,7 @@ class ActionNode:
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key: str,
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expected_type: Type,
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instruction: str,
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example: str,
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example: T,
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content: str = "",
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children: dict[str, "ActionNode"] = None,
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):
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@ -148,29 +149,6 @@ class ActionNode:
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new_class.__root_validator_check_missing_fields = classmethod(check_missing_fields)
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return new_class
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@classmethod
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def create_model_class_v2(cls, class_name: str, mapping: Dict[str, Type]):
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"""基于pydantic v2的模型动态生成，用来检验结果类型正确性，待验证"""
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new_class = create_model(class_name, **mapping)
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@model_validator(mode="before")
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def check_missing_fields(data):
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required_fields = set(mapping.keys())
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missing_fields = required_fields - set(data.keys())
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if missing_fields:
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raise ValueError(f"Missing fields: {missing_fields}")
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return data
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@field_validator("*")
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def check_name(v: Any, field: str) -> Any:
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if field not in mapping.keys():
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raise ValueError(f"Unrecognized block: {field}")
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return v
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new_class.__model_validator_check_missing_fields = classmethod(check_missing_fields)
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new_class.__field_validator_check_name = classmethod(check_name)
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return new_class
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def create_children_class(self):
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"""使用object内有的字段直接生成model_class"""
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class_name = f"{self.key}_AN"
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@ -245,6 +223,7 @@ class ActionNode:
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"""
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# FIXME: json instruction会带来格式问题，如："Project name": "web_2048 # 项目名称使用下划线",
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# compile example暂时不支持markdown
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self.instruction = self.compile_instruction(to="markdown", mode=mode)
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self.example = self.compile_example(to=to, tag="CONTENT", mode=mode)
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prompt = template.format(
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@ -252,36 +231,32 @@ class ActionNode:
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)
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return prompt
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@retry(wait=wait_random_exponential(min=1, max=10), stop=stop_after_attempt(6))
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@retry(
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wait=wait_random_exponential(min=1, max=60),
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stop=stop_after_attempt(6),
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after=general_after_log(logger),
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)
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async def _aask_v1(
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self,
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prompt: str,
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output_class_name: str,
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output_data_mapping: dict,
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system_msgs: Optional[list[str]] = None,
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format="markdown", # compatible to original format
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) -> ActionOutput:
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schema="markdown", # compatible to original format
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) -> (str, BaseModel):
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"""Use ActionOutput to wrap the output of aask"""
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content = await self.llm.aask(prompt, system_msgs)
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logger.debug(content)
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output_class = ActionOutput.create_model_class(output_class_name, output_data_mapping)
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if format == "json":
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pattern = r"\[CONTENT\](\s*\{.*?\}\s*)\[/CONTENT\]"
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matches = re.findall(pattern, content, re.DOTALL)
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for match in matches:
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if match:
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content = match
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break
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parsed_data = CustomDecoder(strict=False).decode(content)
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logger.debug(f"llm raw output:\n{content}")
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output_class = self.create_model_class(output_class_name, output_data_mapping)
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if schema == "json":
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parsed_data = llm_output_postprecess(output=content, schema=output_class.schema(), req_key="[/CONTENT]")
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else: # using markdown parser
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parsed_data = OutputParser.parse_data_with_mapping(content, output_data_mapping)
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logger.debug(parsed_data)
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logger.debug(f"parsed_data:\n{parsed_data}")
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instruct_content = output_class(**parsed_data)
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return ActionOutput(content, instruct_content)
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return content, instruct_content
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def get(self, key):
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return self.instruct_content.dict()[key]
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@ -302,9 +277,9 @@ class ActionNode:
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mapping = self.get_mapping(mode)
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class_name = f"{self.key}_AN"
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output = await self._aask_v1(prompt, class_name, mapping, format=to)
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self.content = output.content
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self.instruct_content = output.instruct_content
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content, scontent = await self._aask_v1(prompt, class_name, mapping, schema=to)
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self.content = content
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self.instruct_content = scontent
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return self
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async def fill(self, context, llm, to="json", mode="auto", strgy="simple"):
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@ -50,7 +50,7 @@ class WriteDesign(Action):
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"clearly and in detail."
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)
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async def run(self, with_messages, format=CONFIG.prompt_format):
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async def run(self, with_messages, schema=CONFIG.prompt_schema):
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# Use `git diff` to identify which PRD documents have been modified in the `docs/prds` directory.
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prds_file_repo = CONFIG.git_repo.new_file_repository(PRDS_FILE_REPO)
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changed_prds = prds_file_repo.changed_files
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@ -80,13 +80,13 @@ class WriteDesign(Action):
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# leaving room for global optimization in subsequent steps.
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return ActionOutput(content=changed_files.json(), instruct_content=changed_files)
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async def _new_system_design(self, context, format=CONFIG.prompt_format):
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node = await DESIGN_API_NODE.fill(context=context, llm=self.llm, to=format)
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async def _new_system_design(self, context, schema=CONFIG.prompt_schema):
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node = await DESIGN_API_NODE.fill(context=context, llm=self.llm, to=schema)
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return node
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async def _merge(self, prd_doc, system_design_doc, format=CONFIG.prompt_format):
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async def _merge(self, prd_doc, system_design_doc, schema=CONFIG.prompt_schema):
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context = NEW_REQ_TEMPLATE.format(old_design=system_design_doc.content, context=prd_doc.content)
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node = await DESIGN_API_NODE.fill(context=context, llm=self.llm, to=format)
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node = await DESIGN_API_NODE.fill(context=context, llm=self.llm, to=schema)
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system_design_doc.content = node.instruct_content.json(ensure_ascii=False)
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return system_design_doc
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@ -5,47 +5,31 @@
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@Author : fisherdeng
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@File : detail_mining.py
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"""
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from metagpt.actions import Action, ActionOutput
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from metagpt.actions import Action
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from metagpt.actions.action_node import ActionNode
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PROMPT_TEMPLATE = """
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##TOPIC
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CONTEXT_TEMPLATE = """
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## TOPIC
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{topic}
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##RECORD
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## RECORD
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{record}
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##Format example
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{format_example}
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-----
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Task: Refer to the "##TOPIC" (discussion objectives) and "##RECORD" (discussion records) to further inquire about the details that interest you, within a word limit of 150 words.
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Special Note 1: Your intention is solely to ask questions without endorsing or negating any individual's viewpoints.
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Special Note 2: This output should only include the topic "##OUTPUT". Do not add, remove, or modify the topic. Begin the output with '##OUTPUT', followed by an immediate line break, and then proceed to provide the content in the specified format as outlined in the "##Format example" section.
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Special Note 3: The output should be in the same language as the input.
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"""
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FORMAT_EXAMPLE = """
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##
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##OUTPUT
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...(Please provide the specific details you would like to inquire about here.)
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##
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##
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"""
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OUTPUT_MAPPING = {
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"OUTPUT": (str, ...),
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}
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QUESTIONS = ActionNode(
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key="Questions",
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expected_type=list[str],
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instruction="Task: Refer to the context to further inquire about the details that interest you, within a word limit"
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" of 150 words. Please provide the specific details you would like to inquire about here",
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example=["1. What ...", "2. How ...", "3. ..."],
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)
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class DetailMining(Action):
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"""This class allows LLM to further mine noteworthy details based on specific "##TOPIC"(discussion topic) and "##RECORD" (discussion records), thereby deepening the discussion."""
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"""This class allows LLM to further mine noteworthy details based on specific "##TOPIC"(discussion topic) and
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"##RECORD" (discussion records), thereby deepening the discussion."""
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def __init__(self, name="", context=None, llm=None):
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super().__init__(name, context, llm)
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async def run(self, topic, record) -> ActionOutput:
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prompt = PROMPT_TEMPLATE.format(topic=topic, record=record, format_example=FORMAT_EXAMPLE)
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rsp = await self._aask_v1(prompt, "detail_mining", OUTPUT_MAPPING)
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async def run(self, topic, record):
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context = CONTEXT_TEMPLATE.format(topic=topic, record=record)
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rsp = await QUESTIONS.fill(context=context, llm=self.llm)
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return rsp
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@ -6,35 +6,18 @@
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@File : prepare_interview.py
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"""
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from metagpt.actions import Action
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from metagpt.actions.action_node import ActionNode
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PROMPT_TEMPLATE = """
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# Context
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{context}
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## Format example
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---
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Q1: question 1 here
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References:
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- point 1
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- point 2
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Q2: question 2 here...
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---
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-----
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Role: You are an interviewer of our company who is well-knonwn in frontend or backend develop;
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QUESTIONS = ActionNode(
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key="Questions",
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expected_type=list[str],
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instruction="""Role: You are an interviewer of our company who is well-knonwn in frontend or backend develop;
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Requirement: Provide a list of questions for the interviewer to ask the interviewee, by reading the resume of the interviewee in the context.
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Attention: Provide as markdown block as the format above, at least 10 questions.
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"""
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# prepare for a interview
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Attention: Provide as markdown block as the format above, at least 10 questions.""",
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example=["1. What ...", "2. How ..."],
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)
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class PrepareInterview(Action):
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def __init__(self, name, context=None, llm=None):
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super().__init__(name, context, llm)
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async def run(self, context):
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prompt = PROMPT_TEMPLATE.format(context=context)
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question_list = await self._aask_v1(prompt)
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return question_list
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return await QUESTIONS.fill(context=context, llm=self.llm)
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|
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@ -42,7 +42,7 @@ class WriteTasks(Action):
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def __init__(self, name="CreateTasks", context=None, llm=None):
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super().__init__(name, context, llm)
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async def run(self, with_messages, format=CONFIG.prompt_format):
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async def run(self, with_messages, schema=CONFIG.prompt_schema):
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system_design_file_repo = CONFIG.git_repo.new_file_repository(SYSTEM_DESIGN_FILE_REPO)
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changed_system_designs = system_design_file_repo.changed_files
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@ -89,16 +89,16 @@ class WriteTasks(Action):
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await self._save_pdf(task_doc=task_doc)
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return task_doc
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async def _run_new_tasks(self, context, format=CONFIG.prompt_format):
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node = await PM_NODE.fill(context, self.llm, format)
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async def _run_new_tasks(self, context, schema=CONFIG.prompt_schema):
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node = await PM_NODE.fill(context, self.llm, schema)
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# prompt_template, format_example = get_template(templates, format)
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# prompt = prompt_template.format(context=context, format_example=format_example)
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# rsp = await self._aask_v1(prompt, "task", OUTPUT_MAPPING, format=format)
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return node
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async def _merge(self, system_design_doc, task_doc, format=CONFIG.prompt_format) -> Document:
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async def _merge(self, system_design_doc, task_doc, schema=CONFIG.prompt_schema) -> Document:
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context = NEW_REQ_TEMPLATE.format(context=system_design_doc.content, old_tasks=task_doc.content)
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node = await PM_NODE.fill(context, self.llm, format)
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node = await PM_NODE.fill(context, self.llm, schema)
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task_doc.content = node.instruct_content.json(ensure_ascii=False)
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return task_doc
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@ -111,7 +111,7 @@ class WritePRD(Action):
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# optimization in subsequent steps.
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return ActionOutput(content=change_files.json(), instruct_content=change_files)
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async def _run_new_requirement(self, requirements, format=CONFIG.prompt_format) -> ActionOutput:
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async def _run_new_requirement(self, requirements, schema=CONFIG.prompt_schema) -> ActionOutput:
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# sas = SearchAndSummarize()
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# # rsp = await sas.run(context=requirements, system_text=SEARCH_AND_SUMMARIZE_SYSTEM_EN_US)
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# rsp = ""
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@ -121,7 +121,7 @@ class WritePRD(Action):
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# logger.info(rsp)
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project_name = CONFIG.project_name if CONFIG.project_name else ""
|
||||
context = CONTEXT_TEMPLATE.format(requirements=requirements, project_name=project_name)
|
||||
node = await WRITE_PRD_NODE.fill(context=context, llm=self.llm, to=format)
|
||||
node = await WRITE_PRD_NODE.fill(context=context, llm=self.llm, to=schema)
|
||||
await self._rename_workspace(node)
|
||||
return node
|
||||
|
||||
|
|
@ -130,11 +130,11 @@ class WritePRD(Action):
|
|||
node = await WP_IS_RELATIVE_NODE.fill(context, self.llm)
|
||||
return node.get("is_relative") == "YES"
|
||||
|
||||
async def _merge(self, new_requirement_doc, prd_doc, format=CONFIG.prompt_format) -> Document:
|
||||
async def _merge(self, new_requirement_doc, prd_doc, schema=CONFIG.prompt_schema) -> Document:
|
||||
if not CONFIG.project_name:
|
||||
CONFIG.project_name = Path(CONFIG.project_path).name
|
||||
prompt = NEW_REQ_TEMPLATE.format(requirements=new_requirement_doc.content, old_prd=prd_doc.content)
|
||||
node = await WRITE_PRD_NODE.fill(context=prompt, llm=self.llm, to=format)
|
||||
node = await WRITE_PRD_NODE.fill(context=prompt, llm=self.llm, to=schema)
|
||||
prd_doc.content = node.instruct_content.json(ensure_ascii=False)
|
||||
await self._rename_workspace(node)
|
||||
return prd_doc
|
||||
|
|
|
|||
|
|
@ -143,7 +143,7 @@ class Config(metaclass=Singleton):
|
|||
self.pyppeteer_executable_path = self._get("PYPPETEER_EXECUTABLE_PATH", "")
|
||||
|
||||
self.repair_llm_output = self._get("REPAIR_LLM_OUTPUT", False)
|
||||
self.prompt_format = self._get("PROMPT_FORMAT", "json")
|
||||
self.prompt_schema = self._get("PROMPT_FORMAT", "json")
|
||||
self.workspace_path = Path(self._get("WORKSPACE_PATH", DEFAULT_WORKSPACE_ROOT))
|
||||
self._ensure_workspace_exists()
|
||||
|
||||
|
|
|
|||
|
|
@ -8,10 +8,10 @@
|
|||
from metagpt.config import CONFIG
|
||||
|
||||
|
||||
def get_template(templates, format=CONFIG.prompt_format):
|
||||
selected_templates = templates.get(format)
|
||||
def get_template(templates, schema=CONFIG.prompt_schema):
|
||||
selected_templates = templates.get(schema)
|
||||
if selected_templates is None:
|
||||
raise ValueError(f"Can't find {format} in passed in templates")
|
||||
raise ValueError(f"Can't find {schema} in passed in templates")
|
||||
|
||||
# Extract the selected templates
|
||||
prompt_template = selected_templates["PROMPT_TEMPLATE"]
|
||||
|
|
|
|||
|
|
@ -19,5 +19,5 @@ async def test_detail_mining():
|
|||
rsp = await detail_mining.run(topic=topic, record=record)
|
||||
logger.info(f"{rsp.content=}")
|
||||
|
||||
assert "##OUTPUT" in rsp.content
|
||||
assert "蛋糕" in rsp.content
|
||||
assert "Questions" in rsp.content
|
||||
assert "1." in rsp.content
|
||||
|
|
|
|||
21
tests/metagpt/actions/test_prepare_interview.py
Normal file
21
tests/metagpt/actions/test_prepare_interview.py
Normal file
|
|
@ -0,0 +1,21 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
@Time : 2023/9/13 00:26
|
||||
@Author : fisherdeng
|
||||
@File : test_detail_mining.py
|
||||
"""
|
||||
import pytest
|
||||
|
||||
from metagpt.actions.prepare_interview import PrepareInterview
|
||||
from metagpt.logs import logger
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_prepare_interview():
|
||||
action = PrepareInterview()
|
||||
rsp = await action.run("I just graduated and hope to find a job as a Python engineer")
|
||||
logger.info(f"{rsp.content=}")
|
||||
|
||||
assert "Questions" in rsp.content
|
||||
assert "1." in rsp.content
|
||||
|
|
@ -10,6 +10,7 @@ from importlib import import_module
|
|||
from metagpt.actions import Action, ActionOutput, WritePRD
|
||||
|
||||
# from metagpt.const import WORKSPACE_ROOT
|
||||
from metagpt.actions.action_node import ActionNode
|
||||
from metagpt.config import CONFIG
|
||||
from metagpt.logs import logger
|
||||
from metagpt.roles import Role
|
||||
|
|
@ -17,44 +18,38 @@ from metagpt.schema import Message
|
|||
from metagpt.tools.sd_engine import SDEngine
|
||||
|
||||
PROMPT_TEMPLATE = """
|
||||
# Context
|
||||
{context}
|
||||
|
||||
## Format example
|
||||
{format_example}
|
||||
-----
|
||||
Role: You are a UserInterface Designer; the goal is to finish a UI design according to PRD, give a design description, and select specified elements and UI style.
|
||||
Requirements: Based on the context, fill in the following missing information, provide detailed HTML and CSS code
|
||||
Attention: Use '##' to split sections, not '#', and '## <SECTION_NAME>' SHOULD WRITE BEFORE the code and triple quote.
|
||||
|
||||
## UI Design Description:Provide as Plain text, place the design objective here
|
||||
## Selected Elements:Provide as Plain text, up to 5 specified elements, clear and simple
|
||||
## HTML Layout:Provide as Plain text, use standard HTML code
|
||||
## CSS Styles (styles.css):Provide as Plain text,use standard css code
|
||||
## Anything UNCLEAR:Provide as Plain text. Try to clarify it.
|
||||
|
||||
## Role
|
||||
You are a UserInterface Designer; the goal is to finish a UI design according to PRD, give a design description, and select specified elements and UI style.
|
||||
"""
|
||||
|
||||
FORMAT_EXAMPLE = """
|
||||
UI_DESIGN_DESC = ActionNode(
|
||||
key="UI Design Desc",
|
||||
expected_type=str,
|
||||
instruction="place the design objective here",
|
||||
example="Snake games are classic and addictive games with simple yet engaging elements. Here are the main elements"
|
||||
" commonly found in snake games",
|
||||
)
|
||||
|
||||
## UI Design Description
|
||||
```Snake games are classic and addictive games with simple yet engaging elements. Here are the main elements commonly found in snake games ```
|
||||
SELECTED_ELEMENTS = ActionNode(
|
||||
key="Selected Elements",
|
||||
expected_type=list[str],
|
||||
instruction="up to 5 specified elements, clear and simple",
|
||||
example=[
|
||||
"Game Grid: The game grid is a rectangular...",
|
||||
"Snake: The player controls a snake that moves across the grid...",
|
||||
"Food: Food items (often represented as small objects or differently colored blocks)",
|
||||
"Score: The player's score increases each time the snake eats a piece of food. The longer the snake becomes, the higher the score.",
|
||||
"Game Over: The game ends when the snake collides with itself or an obstacle. At this point, the player's final score is displayed, and they are given the option to restart the game.",
|
||||
],
|
||||
)
|
||||
|
||||
## Selected Elements
|
||||
|
||||
Game Grid: The game grid is a rectangular...
|
||||
|
||||
Snake: The player controls a snake that moves across the grid...
|
||||
|
||||
Food: Food items (often represented as small objects or differently colored blocks)
|
||||
|
||||
Score: The player's score increases each time the snake eats a piece of food. The longer the snake becomes, the higher the score.
|
||||
|
||||
Game Over: The game ends when the snake collides with itself or an obstacle. At this point, the player's final score is displayed, and they are given the option to restart the game.
|
||||
|
||||
|
||||
## HTML Layout
|
||||
<!DOCTYPE html>
|
||||
HTML_LAYOUT = ActionNode(
|
||||
key="HTML Layout",
|
||||
expected_type=str,
|
||||
instruction="use standard HTML code",
|
||||
example="""<!DOCTYPE html>
|
||||
<html lang="en">
|
||||
<head>
|
||||
<meta charset="UTF-8">
|
||||
|
|
@ -71,9 +66,14 @@ Game Over: The game ends when the snake collides with itself or an obstacle. At
|
|||
</div>
|
||||
</body>
|
||||
</html>
|
||||
""",
|
||||
)
|
||||
|
||||
## CSS Styles (styles.css)
|
||||
body {
|
||||
CSS_STYLES = ActionNode(
|
||||
key="CSS Styles",
|
||||
expected_type=str,
|
||||
instruction="use standard css code",
|
||||
example="""body {
|
||||
display: flex;
|
||||
justify-content: center;
|
||||
align-items: center;
|
||||
|
|
@ -121,19 +121,25 @@ body {
|
|||
color: #ff0000;
|
||||
display: none;
|
||||
}
|
||||
""",
|
||||
)
|
||||
|
||||
## Anything UNCLEAR
|
||||
There are no unclear points.
|
||||
ANYTHING_UNCLEAR = ActionNode(
|
||||
key="Anything UNCLEAR",
|
||||
expected_type=str,
|
||||
instruction="Mention any aspects of the project that are unclear and try to clarify them.",
|
||||
example="...",
|
||||
)
|
||||
|
||||
"""
|
||||
NODES = [
|
||||
UI_DESIGN_DESC,
|
||||
SELECTED_ELEMENTS,
|
||||
HTML_LAYOUT,
|
||||
CSS_STYLES,
|
||||
ANYTHING_UNCLEAR,
|
||||
]
|
||||
|
||||
OUTPUT_MAPPING = {
|
||||
"UI Design Description": (str, ...),
|
||||
"Selected Elements": (str, ...),
|
||||
"HTML Layout": (str, ...),
|
||||
"CSS Styles (styles.css)": (str, ...),
|
||||
"Anything UNCLEAR": (str, ...),
|
||||
}
|
||||
UI_DESIGN_NODE = ActionNode.from_children("UI_DESIGN", NODES)
|
||||
|
||||
|
||||
def load_engine(func):
|
||||
|
|
@ -223,10 +229,8 @@ class UIDesign(Action):
|
|||
css_file_path = save_dir / "ui_design.css"
|
||||
html_file_path = save_dir / "ui_design.html"
|
||||
|
||||
with open(css_file_path, "w") as css_file:
|
||||
css_file.write(css_content)
|
||||
with open(html_file_path, "w") as html_file:
|
||||
html_file.write(html_content)
|
||||
css_file_path.write_text(css_content)
|
||||
html_file_path.write_text(html_content)
|
||||
|
||||
async def run(self, requirements: list[Message], *args, **kwargs) -> ActionOutput:
|
||||
"""Run the UI Design action."""
|
||||
|
|
@ -234,9 +238,9 @@ class UIDesign(Action):
|
|||
context = requirements[-1].content
|
||||
ui_design_draft = self.parse_requirement(context=context)
|
||||
# todo: parse requirements str
|
||||
prompt = PROMPT_TEMPLATE.format(context=ui_design_draft, format_example=FORMAT_EXAMPLE)
|
||||
prompt = PROMPT_TEMPLATE.format(context=ui_design_draft)
|
||||
logger.info(prompt)
|
||||
ui_describe = await self._aask_v1(prompt, "ui_design", OUTPUT_MAPPING)
|
||||
ui_describe = await UI_DESIGN_NODE.fill(prompt)
|
||||
logger.info(ui_describe.content)
|
||||
logger.info(ui_describe.instruct_content)
|
||||
css = self.parse_css_code(context=ui_describe.content)
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue