e0cc11647f
- 在多个规划引擎文件中添加中文响应的语言要求说明 - 将操作相关的提示文本从英文翻译为中文 - 确保代理协作中的所有解释和推理使用中文输出 - 保持代理名称等标识符的原始格式不变
101 lines
3.3 KiB
Python
101 lines
3.3 KiB
Python
from AgentCoord.util.converter import read_LLM_Completion
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from typing import List
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from pydantic import BaseModel
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import json
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PROMPT_PLAN_OUTLINE_GENERATION = """
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## Instruction
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Based on "Output Format Example", "General Goal", and "Initial Key Object List", output a formatted "Plan_Outline".
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**IMPORTANT LANGUAGE REQUIREMENT: You must respond in Chinese (中文) for all content, including StepName, TaskContent, and OutputObject fields.**
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## Initial Key Object List (Specify the list of initial key objects available, each initial key object should be the input object of at least one Step)
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{InitialObject_List}
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## General Goal (Specify the general goal for the collaboration plan)
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{General_Goal}
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## Output Format Example (Specify the output format)
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```json
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{{
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"Plan_Outline": [
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{{
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"StepName": "Love Element Brainstorming",
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"TaskContent": "Decide the main love element in the love story.",
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"InputObject_List": [],
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"OutputObject": "Love Element"
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}},
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{{
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"StepName": "Story World Buiding",
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"TaskContent": "Build the world setting for the story.",
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"InputObject_List": [],
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"OutputObject": "World Setting"
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}},
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{{
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"StepName": "Story Outline Drafting",
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"TaskContent": "Draft the story outline for the story.",
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"InputObject_List": ["Love Element", "World Setting"],
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"OutputObject": "Story Outline"
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}},
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{{
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"StepName": "Final Story Writing",
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"TaskContent": "Writing the final story.",
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"InputObject_List": [],
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"OutputObject": "Completed Story"
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}}
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]
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}}
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```
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## Format Explaination (Explain the Output Format):
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StepName: Provide a CONCISE and UNIQUE name for this step, smartly summarize what this step is doing.
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TaskContent: Describe the task of the current step.
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InputObject_List: The list of the input obejects that will be used in current step.
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OutputObject: The name of the final output object of current step.
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"""
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class Step(BaseModel):
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StepName: str
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TaskContent: str
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InputObject_List: List[str]
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OutputObject: str
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class PlanOutline(BaseModel):
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Plan_Outline: List[Step]
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class Config:
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extra = "allow"
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def generate_PlanOutline(InitialObject_List, General_Goal):
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messages = [
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{
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"role": "system",
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"content": "You are a recipe database that outputs recipes in JSON.\n"
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f" The JSON object must use the schema: {json.dumps(PlanOutline.model_json_schema(), indent=2)}",
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},
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{
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"role": "system",
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"content": PROMPT_PLAN_OUTLINE_GENERATION.format(
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InitialObject_List=str(InitialObject_List),
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General_Goal=General_Goal,
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),
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},
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]
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result = read_LLM_Completion(messages)
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if isinstance(result, dict) and "Plan_Outline" in result:
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return result["Plan_Outline"]
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else:
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# 如果格式不正确，返回默认的计划大纲
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return [
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{
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"StepName": "Default Step",
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"TaskContent": "Generated default plan step due to format error",
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"InputObject_List": [],
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"OutputObject": "Default Output"
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}
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]
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