TravelContentCreator/api/services/prompt_builder.py

#!/usr/bin/env python3
# -*- coding: utf-8 -*-

"""
提示词构建服务
负责根据选题信息构建完整的提示词
"""

import logging
from typing import Dict, Any, Optional, Tuple
from pathlib import Path

from core.config import ConfigManager, GenerateContentConfig
from utils.prompts import PromptTemplate
from api.services.prompt_service import PromptService

logger = logging.getLogger(__name__)


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