修复了推文的传参

api/main.py

@@ -59,9 +59,9 @@ app.add_middleware(
 from api.routers import tweet, poster, prompt
 
 # 包含路由
-app.include_router(tweet.router, prefix="/api/tweet", tags=["tweet"])
-app.include_router(poster.router, prefix="/api/poster", tags=["poster"])
-app.include_router(prompt.router, prefix="/api/prompt", tags=["prompt"])
+app.include_router(tweet.router, prefix="/api/v1/tweet", tags=["tweet"])
+app.include_router(poster.router, prefix="/api/v1/poster", tags=["poster"])
+app.include_router(prompt.router, prefix="/api/v1/prompt", tags=["prompt"])
 
 @app.get("/")
 async def root():

api/models/tweet.py

@@ -11,18 +11,22 @@ from pydantic import BaseModel, Field
 
 class TopicRequest(BaseModel):
     """选题生成请求模型"""
-    date: str = Field(..., description="选题日期，格式为YYYY-MM-DD")
+    dates: Optional[str] = Field(None, description="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'")
     num_topics: int = Field(5, description="要生成的选题数量", ge=1, le=10)
-    style: Optional[str] = Field(None, description="内容风格，如'旅游攻略'、'亲子游'等")
-    target_audience: Optional[str] = Field(None, description="目标受众，如'年轻人'、'家庭'等")
+    styles: Optional[List[str]] = Field(None, description="风格列表")
+    audiences: Optional[List[str]] = Field(None, description="受众列表")
+    scenic_spots: Optional[List[str]] = Field(None, description="景区列表")
+    products: Optional[List[str]] = Field(None, description="产品列表")
     
     class Config:
         schema_extra = {
             "example": {
-                "date": "2023-07-15",
-                "num_topics": 3,
-                "style": "旅游攻略",
-                "target_audience": "年轻人"
+                "dates": "2023-07-01 to 2023-07-31",
+                "num_topics": 5,
+                "styles": ["旅游攻略", "亲子游"],
+                "audiences": ["年轻人", "家庭"],
+                "scenic_spots": ["故宫", "长城"],
+                "products": ["门票", "导游服务"]
             }
         }
 
@@ -141,19 +145,23 @@ class JudgeResponse(BaseModel):
 
 class PipelineRequest(BaseModel):
     """完整流程请求模型"""
-    date: str = Field(..., description="选题日期，格式为YYYY-MM-DD")
+    dates: Optional[str] = Field(None, description="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'")
     num_topics: int = Field(5, description="要生成的选题数量", ge=1, le=10)
-    style: Optional[str] = Field(None, description="内容风格，如'旅游攻略'、'亲子游'等")
-    target_audience: Optional[str] = Field(None, description="目标受众，如'年轻人'、'家庭'等")
+    styles: Optional[List[str]] = Field(None, description="风格列表")
+    audiences: Optional[List[str]] = Field(None, description="受众列表")
+    scenic_spots: Optional[List[str]] = Field(None, description="景区列表")
+    products: Optional[List[str]] = Field(None, description="产品列表")
     skip_judge: bool = Field(False, description="是否跳过内容审核步骤")
     
     class Config:
         schema_extra = {
             "example": {
-                "date": "2023-07-15",
+                "dates": "2023-07-01 to 2023-07-31",
                 "num_topics": 3,
-                "style": "旅游攻略",
-                "target_audience": "年轻人",
+                "styles": ["旅游攻略", "亲子游"],
+                "audiences": ["年轻人", "家庭"],
+                "scenic_spots": ["故宫", "长城"],
+                "products": ["门票", "导游服务"],
                 "skip_judge": False
             }
         }

api/routers/tweet.py

@@ -60,17 +60,21 @@ async def generate_topics(
     """
     生成选题
     
-    - **date**: 选题日期，格式为YYYY-MM-DD
+    - **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
     - **num_topics**: 要生成的选题数量
-    - **style**: 内容风格，如'旅游攻略'、'亲子游'等
-    - **target_audience**: 目标受众，如'年轻人'、'家庭'等
+    - **styles**: 风格列表
+    - **audiences**: 受众列表
+    - **scenic_spots**: 景区列表
+    - **products**: 产品列表
     """
     try:
         request_id, topics = await tweet_service.generate_topics(
-            date=request.date,
+            dates=request.dates,
             num_topics=request.num_topics,
-            style=request.style,
-            target_audience=request.target_audience
+            styles=request.styles,
+            audiences=request.audiences,
+            scenic_spots=request.scenic_spots,
+            products=request.products
         )
         
         return TopicResponse(
@@ -172,18 +176,22 @@ async def run_pipeline(
     """
     运行完整流水线，包括生成选题、生成内容和审核内容
     
-    - **date**: 选题日期，格式为YYYY-MM-DD
+    - **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
     - **num_topics**: 要生成的选题数量
-    - **style**: 内容风格，如'旅游攻略'、'亲子游'等
-    - **target_audience**: 目标受众，如'年轻人'、'家庭'等
+    - **styles**: 风格列表
+    - **audiences**: 受众列表
+    - **scenic_spots**: 景区列表
+    - **products**: 产品列表
     - **skip_judge**: 是否跳过内容审核步骤
     """
     try:
         request_id, topics, contents, judged_contents = await tweet_service.run_pipeline(
-            date=request.date,
+            dates=request.dates,
             num_topics=request.num_topics,
-            style=request.style,
-            target_audience=request.target_audience,
+            styles=request.styles,
+            audiences=request.audiences,
+            scenic_spots=request.scenic_spots,
+            products=request.products,
             skip_judge=request.skip_judge
         )
         

api/services/prompt_builder.py

@@ -7,7 +7,7 @@
 """
 
 import logging
-from typing import Dict, Any, Optional, Tuple
+from typing import Dict, Any, Optional, Tuple, List
 from pathlib import Path
 
 from core.config import ConfigManager, GenerateContentConfig, GenerateTopicConfig, PosterConfig
@@ -150,13 +150,17 @@ class PromptBuilderService:
         
         return system_prompt, user_prompt
         
-    def build_topic_prompt(self, num_topics: int, month: str) -> Tuple[str, str]:
+    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, num_topics: int = 5) -> 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'
             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
@@ -173,20 +177,51 @@ class PromptBuilderService:
         # 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])
+        # 处理日期
+        if dates:
+            if ' to ' in dates:
+                start_date, end_date = dates.split(' to ')
+                month = f"从 {start_date} 到 {end_date}"
+            elif ',' in dates:
+                month = ', '.join(dates.split(','))
+            else:
+                month = dates
+        else:
+            month = ''
         
-        # 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:
+            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])
+        
+        # 获取受众内容
+        demand_content = ''
+        if audiences:
+            demand_content = '\n'.join([f"{audience}: {self.prompt_service.get_audience_content(audience)}" for audience in audiences])
+        else:
+            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])
         
         # 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])
+        # 获取景区内容
+        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:
+            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])
+        
+        # 获取产品内容
+        product_content = ''
+        if products:
+            product_content = '\n'.join([f"{product}: {self.prompt_service.get_product_info(product)}" for product in products])
+        else:
+            product_content = ''  # 假设没有默认产品列表
         
         # 构建系统提示词
         system_prompt = template.get_system_prompt()
@@ -194,10 +229,11 @@ class PromptBuilderService:
         # 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}"
+            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}"
         )
         
         # 构建用户提示词

api/services/prompt_service.py

@@ -342,12 +342,35 @@ class PromptService:
                     full_path = self._get_full_path(path_str)
                     
                     if full_path.exists() and full_path.is_file():
+                        if full_path.suffix.lower() == '.json':
+                            # 处理JSON文件
+                            with open(full_path, 'r', encoding='utf-8') as f:
+                                data = json.load(f)
+                            if isinstance(data, dict) and 'examples' in data:
+                                examples = data['examples']
+                                if isinstance(examples, list):
+                                    sample_size = max(1, int(len(examples) * ref_item.sampling_rate))
+                                    sampled_examples = random.sample(examples, sample_size)
+                                    sampled_content = json.dumps({'examples': sampled_examples}, ensure_ascii=False, indent=4)
+                            elif isinstance(data, list):
+                                sample_size = max(1, int(len(data) * ref_item.sampling_rate))
+                                sampled_examples = random.sample(data, sample_size)
+                                sampled_content = json.dumps(sampled_examples, ensure_ascii=False, indent=4)
+                            else:
+                                # 如果不是预期结构，按原方式处理
                                 with open(full_path, 'r', encoding='utf-8') as f:
                                     lines = f.readlines()
-                        if lines:
                                 sample_size = max(1, int(len(lines) * ref_item.sampling_rate))
                                 sampled_lines = random.sample(lines, sample_size)
                                 sampled_content = ''.join(sampled_lines)
+                        else:
+                            # 非JSON文件，按原方式处理
+                            with open(full_path, 'r', encoding='utf-8') as f:
+                                lines = f.readlines()
+                            sample_size = max(1, int(len(lines) * ref_item.sampling_rate))
+                            sampled_lines = random.sample(lines, sample_size)
+                            sampled_content = ''.join(sampled_lines)
+                        
                         refer_content += f"--- {full_path.name} (sampled {ref_item.sampling_rate * 100}%) ---\n{sampled_content}\n\n"
                 except Exception as e:
                     logger.error(f"读取或采样参考文件失败 {ref_item.path}: {e}")

api/services/tweet.py

@@ -48,32 +48,41 @@ class TweetService:
         self.prompt_service = PromptService(config_manager)
         self.prompt_builder = PromptBuilderService(config_manager, self.prompt_service)
         
-    async def generate_topics(self, date: str, num_topics: int = 5, 
-                            style: Optional[str] = None, 
-                            target_audience: Optional[str] = None) -> Tuple[str, List[Dict[str, Any]]]:
+    async def generate_topics(self, dates: Optional[str] = None, num_topics: int = 5, 
+                            styles: Optional[List[str]] = None, 
+                            audiences: Optional[List[str]] = None,
+                            scenic_spots: Optional[List[str]] = None,
+                            products: Optional[List[str]] = None) -> Tuple[str, List[Dict[str, Any]]]:
         """
         生成选题
         
         Args:
-            date: 选题日期，格式为YYYY-MM-DD
+            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
             num_topics: 要生成的选题数量
-            style: 内容风格
-            target_audience: 目标受众
+            styles: 风格列表
+            audiences: 受众列表
+            scenic_spots: 景区列表
+            products: 产品列表
             
         Returns:
             请求ID和生成的选题列表
         """
-        logger.info(f"开始生成选题，日期: {date}, 数量: {num_topics}")
+        logger.info(f"开始生成选题，日期: {dates}, 数量: {num_topics}")
         
         # 获取并更新配置
         topic_config = self.config_manager.get_config('topic_gen', GenerateTopicConfig)
-        topic_config.topic.date = date
+        if dates:
+            topic_config.topic.date = dates
         topic_config.topic.num = num_topics
         
         # 使用PromptBuilderService构建提示词
         system_prompt, user_prompt = self.prompt_builder.build_topic_prompt(
-            num_topics=num_topics,
-            month=date
+            products=products,
+            scenic_spots=scenic_spots,
+            styles=styles,
+            audiences=audiences,
+            dates=dates,
+            num_topics=num_topics
         )
         
         # 使用预构建的提示词生成选题
@@ -164,30 +173,34 @@ class TweetService:
         logger.info(f"内容审核完成，请求ID: {request_id}, 选题索引: {topic_index}, 审核结果: {judge_success}")
         return request_id, topic_index, judged_data, judge_success
         
-    async def run_pipeline(self, date: str, num_topics: int = 5, 
-                         style: Optional[str] = None, 
-                         target_audience: Optional[str] = None,
+    async def run_pipeline(self, dates: Optional[str] = None, num_topics: int = 5, 
+                         styles: Optional[List[str]] = None, 
+                         audiences: Optional[List[str]] = None,
+                         scenic_spots: Optional[List[str]] = None,
+                         products: Optional[List[str]] = None,
                          skip_judge: bool = False) -> Tuple[str, List[Dict[str, Any]], Dict[str, Dict[str, Any]], Dict[str, Dict[str, Any]]]:
         """
         运行完整流水线
         
         Args:
-            date: 选题日期，格式为YYYY-MM-DD
+            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
             num_topics: 要生成的选题数量
-            style: 内容风格
-            target_audience: 目标受众
+            styles: 风格列表
+            audiences: 受众列表
+            scenic_spots: 景区列表
+            products: 产品列表
             skip_judge: 是否跳过内容审核步骤
             
         Returns:
             请求ID、生成的选题列表、生成的内容和审核后的内容
         """
-        logger.info(f"开始运行完整流水线，日期: {date}, 数量: {num_topics}")
+        logger.info(f"开始运行完整流水线，日期: {dates}, 数量: {num_topics}")
         
         # 生成请求ID
         request_id = f"pipeline_{datetime.now().strftime('%Y%m%d_%H%M%S')}_{str(uuid.uuid4())[:8]}"
         
         # 步骤1: 生成选题
-        _, topics = await self.generate_topics(date, num_topics, style, target_audience)
+        _, topics = await self.generate_topics(dates, num_topics, styles, audiences, scenic_spots, products)
         if not topics:
             logger.error("未能生成任何选题，流程终止")
             return request_id, [], {}, {}

core/config/models.py

@@ -130,7 +130,7 @@ class GenerateTopicConfig(BaseConfig):
 
 class GenerateContentConfig(BaseConfig):
     """内容生成配置"""
-    content_system_prompt: str = "resource/prompt/generateContent/contentSystem.txt"
+    content_system_prompt: str = "resource/prompt/generateContent/system.txt"
     content_user_prompt: str = "resource/prompt/generateContent/user.txt"
     judger_system_prompt: str = "resource/prompt/judgeContent/system.txt"
     judger_user_prompt: str = "resource/prompt/judgeContent/user.txt"