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, List
from pathlib import Path

from core.config import ConfigManager, GenerateContentConfig, GenerateTopicConfig, PosterConfig
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
        
    def _ensure_content_config(self) -> GenerateContentConfig:
        """确保内容生成配置已加载"""
        # 按需加载内容生成配置
        if not self.config_manager.load_task_config('content_gen'):
            logger.warning("未找到内容生成配置，将使用默认配置")
            
        return self.config_manager.get_config('content_gen', GenerateContentConfig)
        
    def _ensure_topic_config(self) -> GenerateTopicConfig:
        """确保选题生成配置已加载"""
        # 按需加载选题生成配置
        if not self.config_manager.load_task_config('topic_gen'):
            logger.warning("未找到选题生成配置，将使用默认配置")
            
        return self.config_manager.get_config('topic_gen', GenerateTopicConfig)
    
    def _ensure_poster_config(self) -> PosterConfig:
        """确保海报生成配置已加载"""
        # 按需加载海报生成配置
        if not self.config_manager.load_task_config('poster_gen'):
            logger.warning("未找到海报生成配置，将使用默认配置")
            
        return self.config_manager.get_config('poster_gen', PosterConfig)
        
    def build_content_prompt(self, topic: Dict[str, Any], step: str = "content") -> Tuple[str, str]:
        """
        构建内容生成提示词 (已重构)
        此方法现在依赖于一个预先填充好完整信息的topic对象。
        """
        content_config = self._ensure_content_config()
        template = PromptTemplate(content_config.content_system_prompt, content_config.content_user_prompt)
        
        # 从预填充的topic对象中直接获取信息，不再调用prompt_service
        style_obj = topic.get('style_object', {})
        style_content = f"{style_obj.get('styleName', '')}\n{style_obj.get('description', '')}"

        audience_obj = topic.get('audience_object', {})
        demand_content = f"{audience_obj.get('audienceName', '')}\n{audience_obj.get('description', '')}"

        spot_obj = topic.get('scenic_spot_object', {})
        object_content = f"{spot_obj.get('name', '')}\n{spot_obj.get('description', '')}"

        product_obj = topic.get('product_object', {})
        product_content = f"{product_obj.get('productName', '')}\n{product_obj.get('detailedDescription', '')}"
        
        # 获取通用的参考内容
        refer_content = self.prompt_service.get_refer_content(step)
        
        system_prompt = template.get_system_prompt()
        
        user_prompt = template.build_user_prompt(
            style_content=style_content,
            demand_content=demand_content,
            object_content=object_content,
            product_content=product_content,
            refer_content=refer_content
        )
        
        return system_prompt, user_prompt
    
    def build_content_prompt_with_params(self, topic: Dict[str, Any], 
                                       styles: Optional[List[str]] = None,
                                       audiences: Optional[List[str]] = None,
                                       scenic_spots: Optional[List[str]] = None,
                                       products: Optional[List[str]] = None,
                                       step: str = "content") -> Tuple[str, str]:
        """
        使用额外参数构建内容生成提示词
        
        Args:
            topic: 选题信息
            styles: 风格列表
            audiences: 受众列表
            scenic_spots: 景区列表
            products: 产品列表
            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
        """
        # 获取内容生成配置
        content_config = self._ensure_content_config()
        
        # 加载系统提示词和用户提示词模板
        system_prompt_path = content_config.content_system_prompt
        user_prompt_path = 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_content = ''
        if styles:
            style_content = '\n'.join([f"{style}: {self.prompt_service.get_style_content(style)}" for style in styles])
        else:
            style_filename = topic.get("style", "")
            style_content = f"{style_filename}\n{self.prompt_service.get_style_content(style_filename)}"
        
        # 获取目标受众内容
        demand_content = ''
        if audiences:
            demand_content = '\n'.join([f"{audience}: {self.prompt_service.get_audience_content(audience)}" for audience in audiences])
        else:
            demand_filename = topic.get("targetAudience", "")
            demand_content = f"{demand_filename}\n{self.prompt_service.get_audience_content(demand_filename)}"
        
        # 获取景区信息
        object_content = ''
        if scenic_spots:
            object_content = '\n'.join([f"{spot}: {self.prompt_service.get_scenic_spot_info(spot)}" for spot in scenic_spots])
        else:
            object_name = topic.get("object", "")
            object_content = f"{object_name}\n{self.prompt_service.get_scenic_spot_info(object_name)}"
        
        # 获取产品信息
        product_content = ''
        if products:
            product_content = '\n'.join([f"{product}: {self.prompt_service.get_product_info(product)}" for product in products])
        else:
            product_name = topic.get("product", "")
            product_content = f"{product_name}\n{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=style_content,
            demand_content=demand_content,
            object_content=object_content,
            product_content=product_content,
            refer_content=refer_content
        )
        
        return system_prompt, user_prompt
    
    def build_poster_prompt(self, topic: Dict[str, Any], content: Dict[str, Any]) -> Tuple[str, str]:
        """
        构建海报生成提示词
        
        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
        """
        # 获取海报生成配置
        poster_config = self._ensure_poster_config()
        
        # 从配置中获取海报提示词模板路径
        system_prompt_path = poster_config.poster_system_prompt
        user_prompt_path = poster_config.poster_user_prompt
        
        if not system_prompt_path or not user_prompt_path:
            raise ValueError("海报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)
        
        # 获取景区信息
        object_name = topic.get("object", "")
        object_content = self.prompt_service.get_scenic_spot_info(object_name)
        
        # 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(
            content=content.get("content", ""),
            title=content.get("title", ""),
            object_name=object_name,
            object_content=object_content
        )
        
        return system_prompt, user_prompt
        
    def build_topic_prompt(self, products: Optional[List[str]] = None,
                             scenic_spots: Optional[List[str]] = None,
                             styles: Optional[List[str]] = None,
                             audiences: Optional[List[str]] = None,
                             dates: Optional[str] = None, numTopics: int = 5,
                             style_objects: Optional[List[Dict[str, Any]]] = None,
                             audience_objects: Optional[List[Dict[str, Any]]] = None,
                             scenic_spot_objects: Optional[List[Dict[str, Any]]] = None,
                             product_objects: Optional[List[Dict[str, Any]]] = None) -> Tuple[str, str]:
        """
        构建选题生成提示词
        
        Args:
            products: 产品列表
            scenic_spots: 景区列表
            styles: 风格列表
            audiences: 受众列表
            dates: 日期字符串，可能为单个日期、多个日期用逗号分隔或范围如'2023-01-01 to 2023-01-31'
            numTopics: 要生成的选题数量
            
        Returns:
            系统提示词和用户提示词的元组
        """
        # 获取选题生成配置
        topic_config = self._ensure_topic_config()
            
        system_prompt_path = topic_config.topic_system_prompt
        user_prompt_path = topic_config.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")
        
        template = PromptTemplate(system_prompt_path, user_prompt_path)
        
        month = dates or ''
        if dates and ' to ' in dates:
                start_date, end_date = dates.split(' to ')
                month = f"从 {start_date} 到 {end_date}"
        elif dates and ',' in dates:
                month = ', '.join(dates.split(','))

        # 使用传入的完整对象构建内容，避免重复查询
        if style_objects:
            style_content = '\n'.join([f"{obj['styleName']}: {obj.get('description', '')}" for obj in style_objects])
        elif styles:
            style_content = '\n'.join([f"{style}: {self.prompt_service.get_style_content(style)}" for style in styles])
        else:
            all_styles = self.prompt_service.get_all_styles()
            style_content = "Style文件列表:\n" + "\n".join([f"- {style['name']}" for style in all_styles])
        
        if audience_objects:
            demand_content = '\n'.join([f"{obj['audienceName']}: {obj.get('description', '')}" for obj in audience_objects])
        elif audiences:
            demand_content = '\n'.join([f"{audience}: {self.prompt_service.get_audience_content(audience)}" for audience in audiences])
        else:
            all_audiences = self.prompt_service.get_all_audiences()
            demand_content = "Demand文件列表:\n" + "\n".join([f"- {audience['name']}" for audience in all_audiences])
        
        if scenic_spot_objects:
            object_content = '\n'.join([f"{obj['name']}: {obj.get('description', '')}" for obj in scenic_spot_objects])
        elif scenic_spots:
            object_content = '\n'.join([f"{spot}: {self.prompt_service.get_scenic_spot_info(spot)}" for spot in scenic_spots])
        else:
            all_spots = self.prompt_service.get_all_scenic_spots()
            object_content = "Object信息:\n" + "\n".join([f"- {spot['name']}" for spot in all_spots])
        
        if product_objects:
            product_content = '\n'.join([f"{obj['productName']}: {obj.get('detailedDescription', '')}" for obj in product_objects])
        elif products:
            product_content = '\n'.join([f"{product}: {self.prompt_service.get_product_info(product)}" for product in products])
        else:
            product_content = ''
        
        refer_content = self.prompt_service.get_refer_content("topic")
        system_prompt = template.get_system_prompt()
        
        creative_materials = (
            f"你拥有的创作资料如下：\n"
            f"风格信息:\n{style_content}\n\n"
            f"受众信息:\n{demand_content}\n\n"
            f"参考内容:\n{refer_content}\n\n"
            f"景区信息:\n{object_content}\n\n"
            f"产品信息:\n{product_content}"
        )
        
        user_prompt = template.build_user_prompt(
            creative_materials=creative_materials,
            numTopics=numTopics,
            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 (已重构)
        此方法现在依赖于一个预先填充好完整信息的topic对象。
        """
        content_config = self._ensure_content_config()
        template = PromptTemplate(content_config.judger_system_prompt, content_config.judger_user_prompt)
        
        # 从预填充的topic对象中直接获取信息
        spot_obj = topic.get('scenic_spot_object', {})
        object_content = f"{spot_obj.get('name', '')}\n{spot_obj.get('description', '')}"

        product_obj = topic.get('product_object', {})
        product_content = f"{product_obj.get('productName', '')}\n{product_obj.get('detailedDescription', '')}"

        refer_content = self.prompt_service.get_refer_content("judge")
        system_prompt = template.get_system_prompt()
        
        import json
        tweet_content = json.dumps(content, ensure_ascii=False, indent=4)
        
        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 

    def build_judge_prompt_with_params(self, topic: Dict[str, Any], content: Dict[str, Any],
                                     styles: Optional[List[str]] = None,
                                     audiences: Optional[List[str]] = None,
                                     scenic_spots: Optional[List[str]] = None,
                                     products: Optional[List[str]] = None) -> Tuple[str, str]:
        """
        使用额外参数构建内容审核提示词
        
        Args:
            topic: 选题信息
            content: 生成的内容
            styles: 风格列表
            audiences: 受众列表
            scenic_spots: 景区列表
            products: 产品列表
            
        Returns:
            系统提示词和用户提示词的元组
        """
        # 获取内容生成配置
        content_config = self._ensure_content_config()
        
        # 从配置中获取审核提示词模板路径
        system_prompt_path = content_config.judger_system_prompt
        user_prompt_path = 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_content = ''
        if scenic_spots:
            object_content = '\n'.join([f"{spot}: {self.prompt_service.get_scenic_spot_info(spot)}" for spot in scenic_spots])
        else:
            object_name = topic.get("object", "")
            object_content = f"{object_name}\n{self.prompt_service.get_scenic_spot_info(object_name)}"
        
        # 获取产品信息
        product_content = ''
        if products:
            product_content = '\n'.join([f"{product}: {self.prompt_service.get_product_info(product)}" for product in products])
        else:
            product_name = topic.get("product", "")
            product_content = f"{product_name}\n{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 

    def build_judge_prompt_simple(self, topic: Dict[str, Any], content: Dict[str, Any]) -> Tuple[str, str]:
        """
        构建简化的内容审核提示词（只需要产品信息、景区信息和文章）
        
        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
        """
        # 获取内容生成配置
        content_config = self._ensure_content_config()
        
        # 从配置中获取审核提示词模板路径
        system_prompt_path = content_config.judger_system_prompt
        user_prompt_path = 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)
        
        # 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（简化版，不包含参考内容）
        user_prompt = template.build_user_prompt(
            tweet_content=tweet_content,
            object_content=object_content,
            product_content=product_content,
            refer_content=""  # 简化版不使用参考内容
        )
        
        return system_prompt, user_prompt