191 lines
6.7 KiB
Python
191 lines
6.7 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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提示词构建服务
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负责根据选题信息构建完整的提示词
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"""
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import logging
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from typing import Dict, Any, Optional, Tuple
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from pathlib import Path
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from core.config import ConfigManager, GenerateContentConfig
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from utils.prompts import PromptTemplate
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from api.services.prompt_service import PromptService
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logger = logging.getLogger(__name__)
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class PromptBuilderService:
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"""提示词构建服务类"""
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def __init__(self, config_manager: ConfigManager, prompt_service: PromptService):
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"""
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初始化提示词构建服务
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Args:
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config_manager: 配置管理器
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prompt_service: 提示词服务
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"""
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self.config_manager = config_manager
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self.prompt_service = prompt_service
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self.content_config: GenerateContentConfig = config_manager.get_config('content_gen', GenerateContentConfig)
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def build_content_prompt(self, topic: Dict[str, Any], step: str = "content") -> Tuple[str, str]:
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"""
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构建内容生成提示词
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Args:
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topic: 选题信息
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step: 当前步骤，用于过滤参考内容
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Returns:
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系统提示词和用户提示词的元组
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"""
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# 加载系统提示词和用户提示词模板
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system_prompt_path = self.content_config.content_system_prompt
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user_prompt_path = self.content_config.content_user_prompt
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# 创建提示词模板
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template = PromptTemplate(system_prompt_path, user_prompt_path)
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# 获取风格内容
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style_filename = topic.get("style", "")
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style_content = self.prompt_service.get_style_content(style_filename)
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# 获取目标受众内容
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demand_filename = topic.get("target_audience", "")
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demand_content = self.prompt_service.get_audience_content(demand_filename)
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# 获取景区信息
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object_name = topic.get("object", "")
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object_content = self.prompt_service.get_scenic_spot_info(object_name)
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# 获取产品信息
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product_name = topic.get("product", "")
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product_content = self.prompt_service.get_product_info(product_name)
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# 获取参考内容
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refer_content = self.prompt_service.get_refer_content(step)
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# 构建系统提示词
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system_prompt = template.get_system_prompt()
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# 构建用户提示词
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user_prompt = template.build_user_prompt(
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style_content=f"{style_filename}\n{style_content}",
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demand_content=f"{demand_filename}\n{demand_content}",
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object_content=f"{object_name}\n{object_content}",
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product_content=f"{product_name}\n{product_content}",
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refer_content=refer_content
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)
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return system_prompt, user_prompt
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def build_topic_prompt(self, num_topics: int, month: str) -> Tuple[str, str]:
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"""
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构建选题生成提示词
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Args:
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num_topics: 要生成的选题数量
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month: 月份
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Returns:
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系统提示词和用户提示词的元组
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"""
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# 从配置中获取选题提示词模板路径
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topic_config = self.config_manager.get_config('topic_gen', dict)
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if not topic_config:
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raise ValueError("未找到选题生成配置")
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system_prompt_path = topic_config.get("topic_system_prompt", "")
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user_prompt_path = topic_config.get("topic_user_prompt", "")
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if not system_prompt_path or not user_prompt_path:
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raise ValueError("选题提示词模板路径不完整")
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# 创建提示词模板
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template = PromptTemplate(system_prompt_path, user_prompt_path)
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# 获取风格列表
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styles = self.prompt_service.get_all_styles()
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style_content = "Style文件列表:\n" + "\n".join([f"- {style['name']}" for style in styles])
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# 获取目标受众列表
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audiences = self.prompt_service.get_all_audiences()
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demand_content = "Demand文件列表:\n" + "\n".join([f"- {audience['name']}" for audience in audiences])
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# 获取参考内容
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refer_content = self.prompt_service.get_refer_content("topic")
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# 获取景区信息列表
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spots = self.prompt_service.get_all_scenic_spots()
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object_content = "Object信息:\n" + "\n".join([f"- {spot['name']}" for spot in spots])
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# 构建系统提示词
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system_prompt = template.get_system_prompt()
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# 构建创作资料
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creative_materials = (
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f"你拥有的创作资料如下：\n"
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f"{style_content}\n\n"
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f"{demand_content}\n\n"
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f"{refer_content}\n\n"
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f"{object_content}"
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)
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# 构建用户提示词
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user_prompt = template.build_user_prompt(
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creative_materials=creative_materials,
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num_topics=num_topics,
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month=month
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)
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return system_prompt, user_prompt
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def build_judge_prompt(self, topic: Dict[str, Any], content: Dict[str, Any]) -> Tuple[str, str]:
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"""
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构建内容审核提示词
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Args:
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topic: 选题信息
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content: 生成的内容
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Returns:
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系统提示词和用户提示词的元组
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"""
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# 从配置中获取审核提示词模板路径
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system_prompt_path = self.content_config.judger_system_prompt
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user_prompt_path = self.content_config.judger_user_prompt
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# 创建提示词模板
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template = PromptTemplate(system_prompt_path, user_prompt_path)
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# 获取景区信息
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object_name = topic.get("object", "")
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object_content = self.prompt_service.get_scenic_spot_info(object_name)
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# 获取产品信息
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product_name = topic.get("product", "")
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product_content = self.prompt_service.get_product_info(product_name)
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# 获取参考内容
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refer_content = self.prompt_service.get_refer_content("judge")
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# 构建系统提示词
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system_prompt = template.get_system_prompt()
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# 格式化内容
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import json
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tweet_content = json.dumps(content, ensure_ascii=False, indent=4)
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# 构建用户提示词
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user_prompt = template.build_user_prompt(
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tweet_content=tweet_content,
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object_content=object_content,
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product_content=product_content,
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refer_content=refer_content
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)
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return system_prompt, user_prompt |