189 lines
15 KiB
JSON
189 lines
15 KiB
JSON
{
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"file_path": "tweet/topic_generator.py",
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"file_size": 4849,
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"line_count": 148,
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"functions": [
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{
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"name": "__init__",
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"line_start": 26,
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"line_end": 40,
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"args": [
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{
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"name": "self"
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},
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{
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"name": "ai_agent",
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"type_hint": "AIAgent"
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},
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{
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"name": "config_manager",
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"type_hint": "ConfigManager"
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},
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{
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"name": "output_manager",
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"type_hint": "OutputManager"
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}
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],
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"return_type": null,
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"docstring": "初始化选题生成器\n\nArgs:\n ai_agent: AI代理\n config_manager: 配置管理器\n output_manager: 输出管理器",
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"is_async": false,
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"decorators": [],
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"code": " def __init__(self, ai_agent: AIAgent, config_manager: ConfigManager, output_manager: OutputManager):\n \"\"\"\n 初始化选题生成器\n\n Args:\n ai_agent: AI代理\n config_manager: 配置管理器\n output_manager: 输出管理器\n \"\"\"\n self.ai_agent = ai_agent\n self.config_manager = config_manager\n self.config = config_manager.get_config('topic_gen', GenerateTopicConfig)\n self.output_manager = output_manager\n self.prompt_builder = TopicPromptBuilder(config_manager)\n self.parser = TopicParser()",
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"code_hash": "8de8e887e9258010481e9e668326b0d6"
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}
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],
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"classes": [
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{
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"name": "TopicGenerator",
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"line_start": 20,
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"line_end": 146,
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"bases": [],
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"methods": [
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{
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"name": "__init__",
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"line_start": 26,
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"line_end": 40,
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"args": [
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{
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"name": "self"
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},
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{
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"name": "ai_agent",
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"type_hint": "AIAgent"
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},
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{
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"name": "config_manager",
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"type_hint": "ConfigManager"
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},
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{
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"name": "output_manager",
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"type_hint": "OutputManager"
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}
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],
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"return_type": null,
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"docstring": "初始化选题生成器\n\nArgs:\n ai_agent: AI代理\n config_manager: 配置管理器\n output_manager: 输出管理器",
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"is_async": false,
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"decorators": [],
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"code": " def __init__(self, ai_agent: AIAgent, config_manager: ConfigManager, output_manager: OutputManager):\n \"\"\"\n 初始化选题生成器\n\n Args:\n ai_agent: AI代理\n config_manager: 配置管理器\n output_manager: 输出管理器\n \"\"\"\n self.ai_agent = ai_agent\n self.config_manager = config_manager\n self.config = config_manager.get_config('topic_gen', GenerateTopicConfig)\n self.output_manager = output_manager\n self.prompt_builder = TopicPromptBuilder(config_manager)\n self.parser = TopicParser()",
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"code_hash": "8de8e887e9258010481e9e668326b0d6"
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},
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{
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"name": "generate_topics",
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"line_start": 42,
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"line_end": 92,
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"args": [
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{
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"name": "self"
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}
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],
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"return_type": "Optional[List[Dict[str, Any]]]",
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"docstring": "执行完整的选题生成流程：构建提示 -> 调用AI -> 解析结果 -> 保存产物",
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"is_async": true,
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"decorators": [],
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"code": " async def generate_topics(self) -> Optional[List[Dict[str, Any]]]:\n \"\"\"\n 执行完整的选题生成流程：构建提示 -> 调用AI -> 解析结果 -> 保存产物\n \"\"\"\n logger.info(\"开始执行选题生成流程...\")\n\n # 1. 构建提示\n system_prompt = self.prompt_builder.get_system_prompt()\n user_prompt = self.prompt_builder.build_user_prompt(\n numTopics=self.config.topic.num,\n month=self.config.topic.date\n )\n self.output_manager.save_text(system_prompt, \"topic_system_prompt.txt\")\n self.output_manager.save_text(user_prompt, \"topic_user_prompt.txt\")\n \n # 获取模型参数\n model_params = {}\n if hasattr(self.config, 'model') and isinstance(self.config.model, dict):\n model_params = {\n 'temperature': self.config.model.get('temperature'),\n 'top_p': self.config.model.get('top_p'),\n 'presence_penalty': self.config.model.get('presence_penalty')\n }\n # 移除None值\n model_params = {k: v for k, v in model_params.items() if v is not None}\n \n # 2. 调用AI生成\n try:\n raw_result, _, _, _ = await self.ai_agent.generate_text(\n system_prompt=system_prompt,\n user_prompt=user_prompt,\n use_stream=True, # 选题生成通常不需要流式输出\n stage=\"选题生成\",\n **model_params\n )\n self.output_manager.save_text(raw_result, \"topics_raw_response.txt\")\n except Exception as e:\n logger.critical(f\"AI调用失败，无法生成选题: {e}\", exc_info=True)\n return None\n\n # 3. 解析结果\n topics = self.parser.parse(raw_result)\n if not topics:\n logger.error(\"未能从AI响应中解析出任何有效选题\")\n return None\n \n # 4. 保存结果\n self.output_manager.save_json(topics, \"topics.json\")\n logger.info(f\"成功生成并保存 {len(topics)} 个选题\")\n \n return topics",
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"code_hash": "8bfc34aad972e35422d8ee4b9ab9bd9b"
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},
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{
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"name": "generate_topics_with_prompt",
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"line_start": 94,
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"line_end": 146,
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"args": [
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{
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"name": "self"
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},
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{
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"name": "system_prompt",
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"type_hint": "str"
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},
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{
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"name": "user_prompt",
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"type_hint": "str"
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}
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],
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"return_type": "Optional[List[Dict[str, Any]]]",
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"docstring": "使用预构建的提示词生成选题\n\nArgs:\n system_prompt: 已构建好的系统提示词\n user_prompt: 已构建好的用户提示词\n \nReturns:\n 生成的选题列表，如果失败则返回None",
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"is_async": true,
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"decorators": [],
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"code": " async def generate_topics_with_prompt(self, system_prompt: str, user_prompt: str) -> Optional[List[Dict[str, Any]]]:\n \"\"\"\n 使用预构建的提示词生成选题\n \n Args:\n system_prompt: 已构建好的系统提示词\n user_prompt: 已构建好的用户提示词\n \n Returns:\n 生成的选题列表，如果失败则返回None\n \"\"\"\n logger.info(\"使用预构建提示词开始执行选题生成流程...\")\n \n # 保存提示以供调试\n self.output_manager.save_text(system_prompt, \"topic_system_prompt.txt\")\n self.output_manager.save_text(user_prompt, \"topic_user_prompt.txt\")\n \n # 获取模型参数\n model_params = {}\n if hasattr(self.config, 'model') and isinstance(self.config.model, dict):\n model_params = {\n 'temperature': self.config.model.get('temperature'),\n 'top_p': self.config.model.get('top_p'),\n 'presence_penalty': self.config.model.get('presence_penalty')\n }\n # 移除None值\n model_params = {k: v for k, v in model_params.items() if v is not None}\n \n # 调用AI生成\n try:\n raw_result, _, _, _ = await self.ai_agent.generate_text(\n system_prompt=system_prompt,\n user_prompt=user_prompt,\n use_stream=True,\n stage=\"选题生成\",\n **model_params\n )\n self.output_manager.save_text(raw_result, \"topics_raw_response.txt\")\n except Exception as e:\n logger.critical(f\"AI调用失败，无法生成选题: {e}\", exc_info=True)\n return None\n \n # 解析结果\n topics = self.parser.parse(raw_result)\n if not topics:\n logger.error(\"未能从AI响应中解析出任何有效选题\")\n return None\n \n # 保存结果\n self.output_manager.save_json(topics, \"topics.json\")\n logger.info(f\"成功生成并保存 {len(topics)} 个选题\")\n \n return topics",
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"code_hash": "6768f97a84285f1a10cfd586d1a925af"
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}
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],
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"docstring": "选题生成器\n负责生成旅游相关的选题",
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"decorators": [],
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"code": "class TopicGenerator:\n \"\"\"\n 选题生成器\n 负责生成旅游相关的选题\n \"\"\"\n\n def __init__(self, ai_agent: AIAgent, config_manager: ConfigManager, output_manager: OutputManager):\n \"\"\"\n 初始化选题生成器\n\n Args:\n ai_agent: AI代理\n config_manager: 配置管理器\n output_manager: 输出管理器\n \"\"\"\n self.ai_agent = ai_agent\n self.config_manager = config_manager\n self.config = config_manager.get_config('topic_gen', GenerateTopicConfig)\n self.output_manager = output_manager\n self.prompt_builder = TopicPromptBuilder(config_manager)\n self.parser = TopicParser()\n\n async def generate_topics(self) -> Optional[List[Dict[str, Any]]]:\n \"\"\"\n 执行完整的选题生成流程：构建提示 -> 调用AI -> 解析结果 -> 保存产物\n \"\"\"\n logger.info(\"开始执行选题生成流程...\")\n\n # 1. 构建提示\n system_prompt = self.prompt_builder.get_system_prompt()\n user_prompt = self.prompt_builder.build_user_prompt(\n numTopics=self.config.topic.num,\n month=self.config.topic.date\n )\n self.output_manager.save_text(system_prompt, \"topic_system_prompt.txt\")\n self.output_manager.save_text(user_prompt, \"topic_user_prompt.txt\")\n \n # 获取模型参数\n model_params = {}\n if hasattr(self.config, 'model') and isinstance(self.config.model, dict):\n model_params = {\n 'temperature': self.config.model.get('temperature'),\n 'top_p': self.config.model.get('top_p'),\n 'presence_penalty': self.config.model.get('presence_penalty')\n }\n # 移除None值\n model_params = {k: v for k, v in model_params.items() if v is not None}\n \n # 2. 调用AI生成\n try:\n raw_result, _, _, _ = await self.ai_agent.generate_text(\n system_prompt=system_prompt,\n user_prompt=user_prompt,\n use_stream=True, # 选题生成通常不需要流式输出\n stage=\"选题生成\",\n **model_params\n )\n self.output_manager.save_text(raw_result, \"topics_raw_response.txt\")\n except Exception as e:\n logger.critical(f\"AI调用失败，无法生成选题: {e}\", exc_info=True)\n return None\n\n # 3. 解析结果\n topics = self.parser.parse(raw_result)\n if not topics:\n logger.error(\"未能从AI响应中解析出任何有效选题\")\n return None\n \n # 4. 保存结果\n self.output_manager.save_json(topics, \"topics.json\")\n logger.info(f\"成功生成并保存 {len(topics)} 个选题\")\n \n return topics\n \n async def generate_topics_with_prompt(self, system_prompt: str, user_prompt: str) -> Optional[List[Dict[str, Any]]]:\n \"\"\"\n 使用预构建的提示词生成选题\n \n Args:\n system_prompt: 已构建好的系统提示词\n user_prompt: 已构建好的用户提示词\n \n Returns:\n 生成的选题列表，如果失败则返回None\n \"\"\"\n logger.info(\"使用预构建提示词开始执行选题生成流程...\")\n \n # 保存提示以供调试\n self.output_manager.save_text(system_prompt, \"topic_system_prompt.txt\")\n self.output_manager.save_text(user_prompt, \"topic_user_prompt.txt\")\n \n # 获取模型参数\n model_params = {}\n if hasattr(self.config, 'model') and isinstance(self.config.model, dict):\n model_params = {\n 'temperature': self.config.model.get('temperature'),\n 'top_p': self.config.model.get('top_p'),\n 'presence_penalty': self.config.model.get('presence_penalty')\n }\n # 移除None值\n model_params = {k: v for k, v in model_params.items() if v is not None}\n \n # 调用AI生成\n try:\n raw_result, _, _, _ = await self.ai_agent.generate_text(\n system_prompt=system_prompt,\n user_prompt=user_prompt,\n use_stream=True,\n stage=\"选题生成\",\n **model_params\n )\n self.output_manager.save_text(raw_result, \"topics_raw_response.txt\")\n except Exception as e:\n logger.critical(f\"AI调用失败，无法生成选题: {e}\", exc_info=True)\n return None\n \n # 解析结果\n topics = self.parser.parse(raw_result)\n if not topics:\n logger.error(\"未能从AI响应中解析出任何有效选题\")\n return None\n \n # 保存结果\n self.output_manager.save_json(topics, \"topics.json\")\n logger.info(f\"成功生成并保存 {len(topics)} 个选题\")\n \n return topics",
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"code_hash": "d9772082007b323b17a00ad5360872d6"
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}
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],
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"imports": [
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{
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"type": "import",
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"modules": [
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"logging"
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],
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"aliases": []
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},
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{
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"type": "from_import",
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"module": "typing",
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"names": [
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"Dict",
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"Any",
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"List",
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"Optional",
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"Tuple"
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],
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"aliases": [],
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"level": 0
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},
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{
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"type": "from_import",
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"module": "core.ai",
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"names": [
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"AIAgent"
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],
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"aliases": [],
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"level": 0
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},
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{
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"type": "from_import",
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"module": "core.config",
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"names": [
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"ConfigManager",
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"GenerateTopicConfig"
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],
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"aliases": [],
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"level": 0
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},
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{
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"type": "from_import",
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"module": "utils.prompts",
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"names": [
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"TopicPromptBuilder"
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],
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"aliases": [],
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"level": 0
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},
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{
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"type": "from_import",
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"module": "utils.file_io",
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"names": [
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"OutputManager",
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"process_llm_json_text"
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],
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"aliases": [],
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"level": 0
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},
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{
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"type": "from_import",
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"module": "topic_parser",
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"names": [
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"TopicParser"
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],
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"aliases": [],
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"level": 1
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}
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],
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"constants": [],
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"docstring": "选题生成模块",
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"content_hash": "a72f82d4171671649a5ed42732953412"
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} |