#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ 文字内容API路由 """ import logging from typing import List, Dict, Any, Optional from fastapi import APIRouter, Depends, HTTPException from api.models.tweet import ( TopicRequest, TopicResponse, ContentRequest, ContentResponse, JudgeRequest, JudgeResponse, PipelineRequest, PipelineResponse ) from api.services.tweet import TweetService from api.services.database_service import DatabaseService from api.dependencies import get_tweet_service, get_database_service # 创建一个新的模型用于接收预构建提示词的请求 from pydantic import BaseModel, Field class ContentWithPromptRequest(BaseModel): """带有预构建提示词的内容生成请求模型""" topic: Dict[str, Any] = Field(..., description="选题信息") system_prompt: str = Field(..., description="系统提示词") user_prompt: str = Field(..., description="用户提示词") class Config: schema_extra = { "example": { "topic": { "index": "1", "date": "2023-07-15", "object": "北京故宫", "product": "故宫门票", "style": "旅游攻略", "targetAudience": "年轻人", "logic": "暑期旅游热门景点推荐" }, "system_prompt": "你是一位专业的旅游内容创作者...", "user_prompt": "请为以下景点创作一篇旅游文章..." } } logger = logging.getLogger(__name__) router = APIRouter( tags=["tweet"], responses={404: {"description": "Not found"}}, ) def _resolve_ids_to_names_with_mapping(db_service: DatabaseService, styleIds: Optional[List[int]] = None, audienceIds: Optional[List[int]] = None, scenicSpotIds: Optional[List[int]] = None, productIds: Optional[List[int]] = None) -> tuple: """ 将ID列表转换为名称列表，并返回ID到名称的映射关系 Args: db_service: 数据库服务 styleIds: 风格ID列表 audienceIds: 受众ID列表 scenicSpotIds: 景区ID列表 productIds: 产品ID列表 Returns: (styles, audiences, scenic_spots, products, id_name_mappings) 名称列表和映射关系元组 """ styles = [] audiences = [] scenic_spots = [] products = [] # 建立ID到名称的映射字典 id_name_mappings = { 'style_mapping': {}, # {name: id} 'audience_mapping': {}, # {name: id} 'scenic_spot_mapping': {}, # {name: id} 'product_mapping': {} # {name: id} } # 如果数据库服务不可用，返回空列表 if not db_service or not db_service.is_available(): logger.warning("数据库服务不可用，无法解析ID") return styles, audiences, scenic_spots, products, id_name_mappings # 解析风格ID if styleIds: style_records = db_service.get_styles_by_ids(styleIds) for record in style_records: style_name = record['styleName'] styles.append(style_name) id_name_mappings['style_mapping'][style_name] = record['id'] # 解析受众ID if audienceIds: audience_records = db_service.get_audiences_by_ids(audienceIds) for record in audience_records: audience_name = record['audienceName'] audiences.append(audience_name) id_name_mappings['audience_mapping'][audience_name] = record['id'] # 解析景区ID if scenicSpotIds: spot_records = db_service.get_scenic_spots_by_ids(scenicSpotIds) for record in spot_records: spot_name = record['name'] scenic_spots.append(spot_name) id_name_mappings['scenic_spot_mapping'][spot_name] = record['id'] # 解析产品ID if productIds: product_records = db_service.get_products_by_ids(productIds) for record in product_records: product_name = record['productName'] # 修改这里，从name改为productName products.append(product_name) id_name_mappings['product_mapping'][product_name] = record['id'] return styles, audiences, scenic_spots, products, id_name_mappings def _resolve_ids_to_names(db_service: DatabaseService, styleIds: Optional[List[int]] = None, audienceIds: Optional[List[int]] = None, scenicSpotIds: Optional[List[int]] = None, productIds: Optional[List[int]] = None) -> tuple: """ 将ID列表转换为名称列表（保持向后兼容） Args: db_service: 数据库服务 styleIds: 风格ID列表 audienceIds: 受众ID列表 scenicSpotIds: 景区ID列表 productIds: 产品ID列表 Returns: (styles, audiences, scenic_spots, products) 名称列表元组 """ styles, audiences, scenic_spots, products, _ = _resolve_ids_to_names_with_mapping( db_service, styleIds, audienceIds, scenicSpotIds, productIds ) return styles, audiences, scenic_spots, products def _add_ids_to_topics(topics: List[Dict[str, Any]], id_name_mappings: Dict[str, Dict[str, int]]) -> List[Dict[str, Any]]: """ 为每个topic添加对应的ID字段 Args: topics: 生成的选题列表 id_name_mappings: 名称到ID的映射字典 Returns: 包含ID字段的选题列表 """ enriched_topics = [] for topic in topics: # 复制原topic enriched_topic = topic.copy() # 添加ID字段 enriched_topic['styleIds'] = [] enriched_topic['audienceIds'] = [] enriched_topic['scenicSpotIds'] = [] enriched_topic['productIds'] = [] # 根据topic中的name查找对应的ID if 'style' in topic and topic['style']: style_name = topic['style'] if style_name in id_name_mappings['style_mapping']: enriched_topic['styleIds'] = [id_name_mappings['style_mapping'][style_name]] if 'targetAudience' in topic and topic['targetAudience']: audience_name = topic['targetAudience'] if audience_name in id_name_mappings['audience_mapping']: enriched_topic['audienceIds'] = [id_name_mappings['audience_mapping'][audience_name]] if 'object' in topic and topic['object']: spot_name = topic['object'] if spot_name in id_name_mappings['scenic_spot_mapping']: enriched_topic['scenicSpotIds'] = [id_name_mappings['scenic_spot_mapping'][spot_name]] if 'product' in topic and topic['product']: product_name = topic['product'] if product_name in id_name_mappings['product_mapping']: enriched_topic['productIds'] = [id_name_mappings['product_mapping'][product_name]] enriched_topics.append(enriched_topic) return enriched_topics @router.post("/topics", response_model=TopicResponse, summary="生成选题") async def generate_topics( request: TopicRequest, tweet_service: TweetService = Depends(get_tweet_service), db_service: DatabaseService = Depends(get_database_service) ): """ 生成选题 - **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 - **numTopics**: 要生成的选题数量 - **styleIds**: 风格ID列表 - **audienceIds**: 受众ID列表 - **scenicSpotIds**: 景区ID列表 - **productIds**: 产品ID列表 """ try: # 将ID转换为名称，并获取映射关系 styles, audiences, scenic_spots, products, id_name_mappings = _resolve_ids_to_names_with_mapping( db_service, request.styleIds, request.audienceIds, request.scenicSpotIds, request.productIds ) request_id, topics = await tweet_service.generate_topics( dates=request.dates, numTopics=request.numTopics, styles=styles, audiences=audiences, scenic_spots=scenic_spots, products=products ) # 为topics添加ID字段 enriched_topics = _add_ids_to_topics(topics, id_name_mappings) return TopicResponse( requestId=request_id, topics=enriched_topics ) except Exception as e: logger.error(f"生成选题失败: {e}", exc_info=True) raise HTTPException(status_code=500, detail=f"生成选题失败: {str(e)}") @router.post("/content", response_model=ContentResponse, summary="生成内容") async def generate_content( request: ContentRequest, tweet_service: TweetService = Depends(get_tweet_service), db_service: DatabaseService = Depends(get_database_service) ): """ 生成内容 - **topic**: 选题信息 - **styleIds**: 风格ID列表 - **audienceIds**: 受众ID列表 - **scenicSpotIds**: 景区ID列表 - **productIds**: 产品ID列表 - **autoJudge**: 是否自动进行内容审核 """ try: # 将ID转换为名称 styles, audiences, scenic_spots, products = _resolve_ids_to_names( db_service, request.styleIds, request.audienceIds, request.scenicSpotIds, request.productIds ) request_id, topic_index, content = await tweet_service.generate_content( topic=request.topic, styles=styles, audiences=audiences, scenic_spots=scenic_spots, products=products, autoJudge=request.autoJudge ) # 提取judgeSuccess字段，从content中移除以避免重复 judge_success = None if isinstance(content, dict) and 'judgeSuccess' in content: judge_success = content.pop('judgeSuccess') return ContentResponse( requestId=request_id, topicIndex=topic_index, content=content, judgeSuccess=judge_success ) except Exception as e: logger.error(f"生成内容失败: {e}", exc_info=True) raise HTTPException(status_code=500, detail=f"生成内容失败: {str(e)}") @router.post("/content-with-prompt", response_model=ContentResponse, summary="使用预构建提示词生成内容") async def generate_content_with_prompt( request: ContentWithPromptRequest, tweet_service: TweetService = Depends(get_tweet_service) ): """ 使用预构建的提示词为选题生成内容 - **topic**: 选题信息 - **system_prompt**: 系统提示词 - **user_prompt**: 用户提示词 """ try: request_id, topic_index, content = await tweet_service.generate_content_with_prompt( topic=request.topic, system_prompt=request.system_prompt, user_prompt=request.user_prompt ) return ContentResponse( requestId=request_id, topicIndex=topic_index, content=content, judgeSuccess=None ) except Exception as e: logger.error(f"使用预构建提示词生成内容失败: {e}", exc_info=True) raise HTTPException(status_code=500, detail=f"使用预构建提示词生成内容失败: {str(e)}") @router.post("/judge", response_model=JudgeResponse, summary="审核内容") async def judge_content( request: JudgeRequest, tweet_service: TweetService = Depends(get_tweet_service), db_service: DatabaseService = Depends(get_database_service) ): """ 审核内容 - **topic**: 选题信息 - **content**: 要审核的内容 - **styleIds**: 风格ID列表 - **audienceIds**: 受众ID列表 - **scenicSpotIds**: 景区ID列表 - **productIds**: 产品ID列表 """ try: # 将ID转换为名称 styles, audiences, scenic_spots, products = _resolve_ids_to_names( db_service, request.styleIds, request.audienceIds, request.scenicSpotIds, request.productIds ) request_id, topic_index, judged_content, judge_success = await tweet_service.judge_content( topic=request.topic, content=request.content, styles=styles, audiences=audiences, scenic_spots=scenic_spots, products=products ) return JudgeResponse( requestId=request_id, topicIndex=topic_index, content=judged_content, judgeSuccess=judge_success ) except Exception as e: logger.error(f"审核内容失败: {e}", exc_info=True) raise HTTPException(status_code=500, detail=f"审核内容失败: {str(e)}") @router.post("/pipeline", response_model=PipelineResponse, summary="运行完整流水线") async def run_pipeline( request: PipelineRequest, tweet_service: TweetService = Depends(get_tweet_service), db_service: DatabaseService = Depends(get_database_service) ): """ 运行完整流水线：生成选题 → 生成内容 → 审核内容 - **dates**: 日期范围 - **numTopics**: 要生成的选题数量 - **styleIds**: 风格ID列表 - **audienceIds**: 受众ID列表 - **scenicSpotIds**: 景区ID列表 - **productIds**: 产品ID列表 - **skip_judge**: 是否跳过内容审核步骤 - **autoJudge**: 是否在内容生成时进行内嵌审核 """ try: # 将ID转换为名称 styles, audiences, scenic_spots, products = _resolve_ids_to_names( db_service, request.styleIds, request.audienceIds, request.scenicSpotIds, request.productIds ) request_id, topics, contents, judged_contents = await tweet_service.run_pipeline( dates=request.dates, numTopics=request.numTopics, styles=styles, audiences=audiences, scenic_spots=scenic_spots, products=products, skipJudge=request.skipJudge, autoJudge=request.autoJudge ) return PipelineResponse( requestId=request_id, topics=topics, contents=contents, judgedContents=judged_contents ) except Exception as e: logger.error(f"运行流水线失败: {e}", exc_info=True) raise HTTPException(status_code=500, detail=f"运行流水线失败: {str(e)}")