{
  "file_path": "travel-algorithms/travel_algorithms/content_generation/topic_parser.py",
  "file_size": 6727,
  "line_count": 205,
  "functions": [
    {
      "name": "__init__",
      "line_start": 23,
      "line_end": 29,
      "args": [
        {
          "name": "self"
        }
      ],
      "return_type": null,
      "docstring": "初始化解析器",
      "is_async": false,
      "decorators": [],
      "code": "    def __init__(self):\n        \"\"\"初始化解析器\"\"\"\n        self.json_pattern = re.compile(r'```json\\s*(.*?)\\s*```', re.DOTALL)\n        self.fallback_patterns = [\n            re.compile(r'\\{.*\\}', re.DOTALL),  # 匹配JSON对象\n            re.compile(r'\\[.*\\]', re.DOTALL),  # 匹配JSON数组\n        ]",
      "code_hash": "2f157d84e962e5b08cd0c5789ec1e2c4"
    },
    {
      "name": "parse",
      "line_start": 31,
      "line_end": 58,
      "args": [
        {
          "name": "self"
        },
        {
          "name": "raw_content",
          "type_hint": "str"
        }
      ],
      "return_type": "List[Dict[str, Any]]",
      "docstring": "解析主题内容\n\nArgs:\n    raw_content: AI生成的原始内容\n\nReturns:\n    解析后的主题列表",
      "is_async": false,
      "decorators": [],
      "code": "    def parse(self, raw_content: str) -> List[Dict[str, Any]]:\n        \"\"\"\n        解析主题内容\n\n        Args:\n            raw_content: AI生成的原始内容\n\n        Returns:\n            解析后的主题列表\n        \"\"\"\n        if not raw_content or not raw_content.strip():\n            logger.warning(\"输入内容为空\")\n            return []\n\n        # 尝试多种解析方法\n        topics = (\n            self._parse_json_block(raw_content) or\n            self._parse_direct_json(raw_content) or\n            self._parse_structured_text(raw_content) or\n            []\n        )\n\n        if topics:\n            logger.info(f\"成功解析出 {len(topics)} 个主题\")\n            return self._validate_topics(topics)\n        else:\n            logger.error(\"未能解析出任何有效主题\")\n            return []",
      "code_hash": "fd6289431a9b868b63cb71ea21fd73b7"
    },
    {
      "name": "_parse_json_block",
      "line_start": 60,
      "line_end": 79,
      "args": [
        {
          "name": "self"
        },
        {
          "name": "content",
          "type_hint": "str"
        }
      ],
      "return_type": "Optional[List[Dict[str, Any]]]",
      "docstring": "解析```json```代码块中的JSON",
      "is_async": false,
      "decorators": [],
      "code": "    def _parse_json_block(self, content: str) -> Optional[List[Dict[str, Any]]]:\n        \"\"\"解析```json```代码块中的JSON\"\"\"\n        try:\n            matches = self.json_pattern.findall(content)\n            if matches:\n                json_str = matches[0].strip()\n                data = json.loads(json_str)\n                \n                if isinstance(data, list):\n                    return data\n                elif isinstance(data, dict):\n                    # 如果是字典，尝试提取topics字段\n                    if 'topics' in data:\n                        return data['topics']\n                    else:\n                        return [data]\n            return None\n        except (json.JSONDecodeError, Exception) as e:\n            logger.debug(f\"JSON代码块解析失败: {e}\")\n            return None",
      "code_hash": "a70c065e9c40432ae3e59cc2e73d486a"
    },
    {
      "name": "_parse_direct_json",
      "line_start": 81,
      "line_end": 108,
      "args": [
        {
          "name": "self"
        },
        {
          "name": "content",
          "type_hint": "str"
        }
      ],
      "return_type": "Optional[List[Dict[str, Any]]]",
      "docstring": "直接解析JSON内容",
      "is_async": false,
      "decorators": [],
      "code": "    def _parse_direct_json(self, content: str) -> Optional[List[Dict[str, Any]]]:\n        \"\"\"直接解析JSON内容\"\"\"\n        try:\n            # 尝试直接解析整个内容\n            data = json.loads(content.strip())\n            \n            if isinstance(data, list):\n                return data\n            elif isinstance(data, dict):\n                if 'topics' in data:\n                    return data['topics']\n                else:\n                    return [data]\n            return None\n        except (json.JSONDecodeError, Exception):\n            # 尝试使用fallback patterns\n            for pattern in self.fallback_patterns:\n                matches = pattern.findall(content)\n                for match in matches:\n                    try:\n                        data = json.loads(match)\n                        if isinstance(data, list) and len(data) > 0:\n                            return data\n                        elif isinstance(data, dict):\n                            return [data]\n                    except json.JSONDecodeError:\n                        continue\n            return None",
      "code_hash": "bbc1f94feb212a1b0ee92114f9c95bc5"
    },
    {
      "name": "_parse_structured_text",
      "line_start": 110,
      "line_end": 159,
      "args": [
        {
          "name": "self"
        },
        {
          "name": "content",
          "type_hint": "str"
        }
      ],
      "return_type": "Optional[List[Dict[str, Any]]]",
      "docstring": "解析结构化文本格式",
      "is_async": false,
      "decorators": [],
      "code": "    def _parse_structured_text(self, content: str) -> Optional[List[Dict[str, Any]]]:\n        \"\"\"解析结构化文本格式\"\"\"\n        try:\n            topics = []\n            lines = content.split('\\n')\n            current_topic = {}\n            \n            for line in lines:\n                line = line.strip()\n                if not line:\n                    continue\n                \n                # 检测主题开始（数字编号）\n                if re.match(r'^\\d+[\\.\\)]\\s*', line):\n                    if current_topic:\n                        topics.append(current_topic)\n                    current_topic = {}\n                    title = re.sub(r'^\\d+[\\.\\)]\\s*', '', line)\n                    current_topic['title'] = title\n                \n                # 检测字段\n                elif ':' in line and current_topic:\n                    key, value = line.split(':', 1)\n                    key = key.strip().lower()\n                    value = value.strip()\n                    \n                    # 映射中文字段到英文\n                    field_mapping = {\n                        '标题': 'title',\n                        '主题': 'title', \n                        '目标': 'target',\n                        '目标人群': 'target',\n                        '内容': 'content',\n                        '描述': 'content',\n                        '关键词': 'keywords',\n                        '标签': 'tags'\n                    }\n                    \n                    mapped_key = field_mapping.get(key, key)\n                    current_topic[mapped_key] = value\n            \n            # 添加最后一个主题\n            if current_topic:\n                topics.append(current_topic)\n            \n            return topics if topics else None\n            \n        except Exception as e:\n            logger.debug(f\"结构化文本解析失败: {e}\")\n            return None",
      "code_hash": "826c5e5160fe9b910eb34e70e657c661"
    },
    {
      "name": "_validate_topics",
      "line_start": 161,
      "line_end": 193,
      "args": [
        {
          "name": "self"
        },
        {
          "name": "topics",
          "type_hint": "List[Dict[str, Any]]"
        }
      ],
      "return_type": "List[Dict[str, Any]]",
      "docstring": "验证和标准化主题数据",
      "is_async": false,
      "decorators": [],
      "code": "    def _validate_topics(self, topics: List[Dict[str, Any]]) -> List[Dict[str, Any]]:\n        \"\"\"验证和标准化主题数据\"\"\"\n        validated_topics = []\n        \n        for i, topic in enumerate(topics):\n            if not isinstance(topic, dict):\n                logger.warning(f\"主题 {i+1} 不是字典格式，跳过\")\n                continue\n            \n            # 确保必需字段存在\n            validated_topic = {\n                'id': topic.get('id', f\"topic_{i+1}\"),\n                'title': topic.get('title', topic.get('主题', f\"主题{i+1}\")),\n                'content': topic.get('content', topic.get('描述', topic.get('内容', ''))),\n                'target': topic.get('target', topic.get('目标人群', '通用')),\n                'keywords': topic.get('keywords', topic.get('关键词', [])),\n                'tags': topic.get('tags', topic.get('标签', [])),\n                'metadata': topic.get('metadata', {})\n            }\n            \n            # 确保keywords和tags是列表\n            if isinstance(validated_topic['keywords'], str):\n                validated_topic['keywords'] = [kw.strip() for kw in validated_topic['keywords'].split(',')]\n            if isinstance(validated_topic['tags'], str):\n                validated_topic['tags'] = [tag.strip() for tag in validated_topic['tags'].split(',')]\n            \n            # 只保留有标题的主题\n            if validated_topic['title']:\n                validated_topics.append(validated_topic)\n            else:\n                logger.warning(f\"主题 {i+1} 缺少标题，跳过\")\n        \n        return validated_topics",
      "code_hash": "3dfeb3356b59c3101937584477962a06"
    },
    {
      "name": "parse_single_topic",
      "line_start": 195,
      "line_end": 206,
      "args": [
        {
          "name": "self"
        },
        {
          "name": "content",
          "type_hint": "str"
        }
      ],
      "return_type": "Optional[Dict[str, Any]]",
      "docstring": "解析单个主题\n\nArgs:\n    content: 主题内容\n\nReturns:\n    解析后的主题字典",
      "is_async": false,
      "decorators": [],
      "code": "    def parse_single_topic(self, content: str) -> Optional[Dict[str, Any]]:\n        \"\"\"\n        解析单个主题\n\n        Args:\n            content: 主题内容\n\n        Returns:\n            解析后的主题字典\n        \"\"\"\n        topics = self.parse(content)\n        return topics[0] if topics else None ",
      "code_hash": "4b6e0b313fdf155b6f375314ae7da82b"
    }
  ],
  "classes": [
    {
      "name": "TopicParser",
      "line_start": 17,
      "line_end": 206,
      "bases": [],
      "methods": [
        {
          "name": "__init__",
          "line_start": 23,
          "line_end": 29,
          "args": [
            {
              "name": "self"
            }
          ],
          "return_type": null,
          "docstring": "初始化解析器",
          "is_async": false,
          "decorators": [],
          "code": "    def __init__(self):\n        \"\"\"初始化解析器\"\"\"\n        self.json_pattern = re.compile(r'```json\\s*(.*?)\\s*```', re.DOTALL)\n        self.fallback_patterns = [\n            re.compile(r'\\{.*\\}', re.DOTALL),  # 匹配JSON对象\n            re.compile(r'\\[.*\\]', re.DOTALL),  # 匹配JSON数组\n        ]",
          "code_hash": "2f157d84e962e5b08cd0c5789ec1e2c4"
        },
        {
          "name": "parse",
          "line_start": 31,
          "line_end": 58,
          "args": [
            {
              "name": "self"
            },
            {
              "name": "raw_content",
              "type_hint": "str"
            }
          ],
          "return_type": "List[Dict[str, Any]]",
          "docstring": "解析主题内容\n\nArgs:\n    raw_content: AI生成的原始内容\n\nReturns:\n    解析后的主题列表",
          "is_async": false,
          "decorators": [],
          "code": "    def parse(self, raw_content: str) -> List[Dict[str, Any]]:\n        \"\"\"\n        解析主题内容\n\n        Args:\n            raw_content: AI生成的原始内容\n\n        Returns:\n            解析后的主题列表\n        \"\"\"\n        if not raw_content or not raw_content.strip():\n            logger.warning(\"输入内容为空\")\n            return []\n\n        # 尝试多种解析方法\n        topics = (\n            self._parse_json_block(raw_content) or\n            self._parse_direct_json(raw_content) or\n            self._parse_structured_text(raw_content) or\n            []\n        )\n\n        if topics:\n            logger.info(f\"成功解析出 {len(topics)} 个主题\")\n            return self._validate_topics(topics)\n        else:\n            logger.error(\"未能解析出任何有效主题\")\n            return []",
          "code_hash": "fd6289431a9b868b63cb71ea21fd73b7"
        },
        {
          "name": "_parse_json_block",
          "line_start": 60,
          "line_end": 79,
          "args": [
            {
              "name": "self"
            },
            {
              "name": "content",
              "type_hint": "str"
            }
          ],
          "return_type": "Optional[List[Dict[str, Any]]]",
          "docstring": "解析```json```代码块中的JSON",
          "is_async": false,
          "decorators": [],
          "code": "    def _parse_json_block(self, content: str) -> Optional[List[Dict[str, Any]]]:\n        \"\"\"解析```json```代码块中的JSON\"\"\"\n        try:\n            matches = self.json_pattern.findall(content)\n            if matches:\n                json_str = matches[0].strip()\n                data = json.loads(json_str)\n                \n                if isinstance(data, list):\n                    return data\n                elif isinstance(data, dict):\n                    # 如果是字典，尝试提取topics字段\n                    if 'topics' in data:\n                        return data['topics']\n                    else:\n                        return [data]\n            return None\n        except (json.JSONDecodeError, Exception) as e:\n            logger.debug(f\"JSON代码块解析失败: {e}\")\n            return None",
          "code_hash": "a70c065e9c40432ae3e59cc2e73d486a"
        },
        {
          "name": "_parse_direct_json",
          "line_start": 81,
          "line_end": 108,
          "args": [
            {
              "name": "self"
            },
            {
              "name": "content",
              "type_hint": "str"
            }
          ],
          "return_type": "Optional[List[Dict[str, Any]]]",
          "docstring": "直接解析JSON内容",
          "is_async": false,
          "decorators": [],
          "code": "    def _parse_direct_json(self, content: str) -> Optional[List[Dict[str, Any]]]:\n        \"\"\"直接解析JSON内容\"\"\"\n        try:\n            # 尝试直接解析整个内容\n            data = json.loads(content.strip())\n            \n            if isinstance(data, list):\n                return data\n            elif isinstance(data, dict):\n                if 'topics' in data:\n                    return data['topics']\n                else:\n                    return [data]\n            return None\n        except (json.JSONDecodeError, Exception):\n            # 尝试使用fallback patterns\n            for pattern in self.fallback_patterns:\n                matches = pattern.findall(content)\n                for match in matches:\n                    try:\n                        data = json.loads(match)\n                        if isinstance(data, list) and len(data) > 0:\n                            return data\n                        elif isinstance(data, dict):\n                            return [data]\n                    except json.JSONDecodeError:\n                        continue\n            return None",
          "code_hash": "bbc1f94feb212a1b0ee92114f9c95bc5"
        },
        {
          "name": "_parse_structured_text",
          "line_start": 110,
          "line_end": 159,
          "args": [
            {
              "name": "self"
            },
            {
              "name": "content",
              "type_hint": "str"
            }
          ],
          "return_type": "Optional[List[Dict[str, Any]]]",
          "docstring": "解析结构化文本格式",
          "is_async": false,
          "decorators": [],
          "code": "    def _parse_structured_text(self, content: str) -> Optional[List[Dict[str, Any]]]:\n        \"\"\"解析结构化文本格式\"\"\"\n        try:\n            topics = []\n            lines = content.split('\\n')\n            current_topic = {}\n            \n            for line in lines:\n                line = line.strip()\n                if not line:\n                    continue\n                \n                # 检测主题开始（数字编号）\n                if re.match(r'^\\d+[\\.\\)]\\s*', line):\n                    if current_topic:\n                        topics.append(current_topic)\n                    current_topic = {}\n                    title = re.sub(r'^\\d+[\\.\\)]\\s*', '', line)\n                    current_topic['title'] = title\n                \n                # 检测字段\n                elif ':' in line and current_topic:\n                    key, value = line.split(':', 1)\n                    key = key.strip().lower()\n                    value = value.strip()\n                    \n                    # 映射中文字段到英文\n                    field_mapping = {\n                        '标题': 'title',\n                        '主题': 'title', \n                        '目标': 'target',\n                        '目标人群': 'target',\n                        '内容': 'content',\n                        '描述': 'content',\n                        '关键词': 'keywords',\n                        '标签': 'tags'\n                    }\n                    \n                    mapped_key = field_mapping.get(key, key)\n                    current_topic[mapped_key] = value\n            \n            # 添加最后一个主题\n            if current_topic:\n                topics.append(current_topic)\n            \n            return topics if topics else None\n            \n        except Exception as e:\n            logger.debug(f\"结构化文本解析失败: {e}\")\n            return None",
          "code_hash": "826c5e5160fe9b910eb34e70e657c661"
        },
        {
          "name": "_validate_topics",
          "line_start": 161,
          "line_end": 193,
          "args": [
            {
              "name": "self"
            },
            {
              "name": "topics",
              "type_hint": "List[Dict[str, Any]]"
            }
          ],
          "return_type": "List[Dict[str, Any]]",
          "docstring": "验证和标准化主题数据",
          "is_async": false,
          "decorators": [],
          "code": "    def _validate_topics(self, topics: List[Dict[str, Any]]) -> List[Dict[str, Any]]:\n        \"\"\"验证和标准化主题数据\"\"\"\n        validated_topics = []\n        \n        for i, topic in enumerate(topics):\n            if not isinstance(topic, dict):\n                logger.warning(f\"主题 {i+1} 不是字典格式，跳过\")\n                continue\n            \n            # 确保必需字段存在\n            validated_topic = {\n                'id': topic.get('id', f\"topic_{i+1}\"),\n                'title': topic.get('title', topic.get('主题', f\"主题{i+1}\")),\n                'content': topic.get('content', topic.get('描述', topic.get('内容', ''))),\n                'target': topic.get('target', topic.get('目标人群', '通用')),\n                'keywords': topic.get('keywords', topic.get('关键词', [])),\n                'tags': topic.get('tags', topic.get('标签', [])),\n                'metadata': topic.get('metadata', {})\n            }\n            \n            # 确保keywords和tags是列表\n            if isinstance(validated_topic['keywords'], str):\n                validated_topic['keywords'] = [kw.strip() for kw in validated_topic['keywords'].split(',')]\n            if isinstance(validated_topic['tags'], str):\n                validated_topic['tags'] = [tag.strip() for tag in validated_topic['tags'].split(',')]\n            \n            # 只保留有标题的主题\n            if validated_topic['title']:\n                validated_topics.append(validated_topic)\n            else:\n                logger.warning(f\"主题 {i+1} 缺少标题，跳过\")\n        \n        return validated_topics",
          "code_hash": "3dfeb3356b59c3101937584477962a06"
        },
        {
          "name": "parse_single_topic",
          "line_start": 195,
          "line_end": 206,
          "args": [
            {
              "name": "self"
            },
            {
              "name": "content",
              "type_hint": "str"
            }
          ],
          "return_type": "Optional[Dict[str, Any]]",
          "docstring": "解析单个主题\n\nArgs:\n    content: 主题内容\n\nReturns:\n    解析后的主题字典",
          "is_async": false,
          "decorators": [],
          "code": "    def parse_single_topic(self, content: str) -> Optional[Dict[str, Any]]:\n        \"\"\"\n        解析单个主题\n\n        Args:\n            content: 主题内容\n\n        Returns:\n            解析后的主题字典\n        \"\"\"\n        topics = self.parse(content)\n        return topics[0] if topics else None ",
          "code_hash": "4b6e0b313fdf155b6f375314ae7da82b"
        }
      ],
      "docstring": "主题解析器\n负责从AI生成的文本中解析出结构化的主题数据",
      "decorators": [],
      "code": "class TopicParser:\n    \"\"\"\n    主题解析器\n    负责从AI生成的文本中解析出结构化的主题数据\n    \"\"\"\n\n    def __init__(self):\n        \"\"\"初始化解析器\"\"\"\n        self.json_pattern = re.compile(r'```json\\s*(.*?)\\s*```', re.DOTALL)\n        self.fallback_patterns = [\n            re.compile(r'\\{.*\\}', re.DOTALL),  # 匹配JSON对象\n            re.compile(r'\\[.*\\]', re.DOTALL),  # 匹配JSON数组\n        ]\n\n    def parse(self, raw_content: str) -> List[Dict[str, Any]]:\n        \"\"\"\n        解析主题内容\n\n        Args:\n            raw_content: AI生成的原始内容\n\n        Returns:\n            解析后的主题列表\n        \"\"\"\n        if not raw_content or not raw_content.strip():\n            logger.warning(\"输入内容为空\")\n            return []\n\n        # 尝试多种解析方法\n        topics = (\n            self._parse_json_block(raw_content) or\n            self._parse_direct_json(raw_content) or\n            self._parse_structured_text(raw_content) or\n            []\n        )\n\n        if topics:\n            logger.info(f\"成功解析出 {len(topics)} 个主题\")\n            return self._validate_topics(topics)\n        else:\n            logger.error(\"未能解析出任何有效主题\")\n            return []\n\n    def _parse_json_block(self, content: str) -> Optional[List[Dict[str, Any]]]:\n        \"\"\"解析```json```代码块中的JSON\"\"\"\n        try:\n            matches = self.json_pattern.findall(content)\n            if matches:\n                json_str = matches[0].strip()\n                data = json.loads(json_str)\n                \n                if isinstance(data, list):\n                    return data\n                elif isinstance(data, dict):\n                    # 如果是字典，尝试提取topics字段\n                    if 'topics' in data:\n                        return data['topics']\n                    else:\n                        return [data]\n            return None\n        except (json.JSONDecodeError, Exception) as e:\n            logger.debug(f\"JSON代码块解析失败: {e}\")\n            return None\n\n    def _parse_direct_json(self, content: str) -> Optional[List[Dict[str, Any]]]:\n        \"\"\"直接解析JSON内容\"\"\"\n        try:\n            # 尝试直接解析整个内容\n            data = json.loads(content.strip())\n            \n            if isinstance(data, list):\n                return data\n            elif isinstance(data, dict):\n                if 'topics' in data:\n                    return data['topics']\n                else:\n                    return [data]\n            return None\n        except (json.JSONDecodeError, Exception):\n            # 尝试使用fallback patterns\n            for pattern in self.fallback_patterns:\n                matches = pattern.findall(content)\n                for match in matches:\n                    try:\n                        data = json.loads(match)\n                        if isinstance(data, list) and len(data) > 0:\n                            return data\n                        elif isinstance(data, dict):\n                            return [data]\n                    except json.JSONDecodeError:\n                        continue\n            return None\n\n    def _parse_structured_text(self, content: str) -> Optional[List[Dict[str, Any]]]:\n        \"\"\"解析结构化文本格式\"\"\"\n        try:\n            topics = []\n            lines = content.split('\\n')\n            current_topic = {}\n            \n            for line in lines:\n                line = line.strip()\n                if not line:\n                    continue\n                \n                # 检测主题开始（数字编号）\n                if re.match(r'^\\d+[\\.\\)]\\s*', line):\n                    if current_topic:\n                        topics.append(current_topic)\n                    current_topic = {}\n                    title = re.sub(r'^\\d+[\\.\\)]\\s*', '', line)\n                    current_topic['title'] = title\n                \n                # 检测字段\n                elif ':' in line and current_topic:\n                    key, value = line.split(':', 1)\n                    key = key.strip().lower()\n                    value = value.strip()\n                    \n                    # 映射中文字段到英文\n                    field_mapping = {\n                        '标题': 'title',\n                        '主题': 'title', \n                        '目标': 'target',\n                        '目标人群': 'target',\n                        '内容': 'content',\n                        '描述': 'content',\n                        '关键词': 'keywords',\n                        '标签': 'tags'\n                    }\n                    \n                    mapped_key = field_mapping.get(key, key)\n                    current_topic[mapped_key] = value\n            \n            # 添加最后一个主题\n            if current_topic:\n                topics.append(current_topic)\n            \n            return topics if topics else None\n            \n        except Exception as e:\n            logger.debug(f\"结构化文本解析失败: {e}\")\n            return None\n\n    def _validate_topics(self, topics: List[Dict[str, Any]]) -> List[Dict[str, Any]]:\n        \"\"\"验证和标准化主题数据\"\"\"\n        validated_topics = []\n        \n        for i, topic in enumerate(topics):\n            if not isinstance(topic, dict):\n                logger.warning(f\"主题 {i+1} 不是字典格式，跳过\")\n                continue\n            \n            # 确保必需字段存在\n            validated_topic = {\n                'id': topic.get('id', f\"topic_{i+1}\"),\n                'title': topic.get('title', topic.get('主题', f\"主题{i+1}\")),\n                'content': topic.get('content', topic.get('描述', topic.get('内容', ''))),\n                'target': topic.get('target', topic.get('目标人群', '通用')),\n                'keywords': topic.get('keywords', topic.get('关键词', [])),\n                'tags': topic.get('tags', topic.get('标签', [])),\n                'metadata': topic.get('metadata', {})\n            }\n            \n            # 确保keywords和tags是列表\n            if isinstance(validated_topic['keywords'], str):\n                validated_topic['keywords'] = [kw.strip() for kw in validated_topic['keywords'].split(',')]\n            if isinstance(validated_topic['tags'], str):\n                validated_topic['tags'] = [tag.strip() for tag in validated_topic['tags'].split(',')]\n            \n            # 只保留有标题的主题\n            if validated_topic['title']:\n                validated_topics.append(validated_topic)\n            else:\n                logger.warning(f\"主题 {i+1} 缺少标题，跳过\")\n        \n        return validated_topics\n\n    def parse_single_topic(self, content: str) -> Optional[Dict[str, Any]]:\n        \"\"\"\n        解析单个主题\n\n        Args:\n            content: 主题内容\n\n        Returns:\n            解析后的主题字典\n        \"\"\"\n        topics = self.parse(content)\n        return topics[0] if topics else None ",
      "code_hash": "e18d720056356adcfd93c009f5594b79"
    }
  ],
  "imports": [
    {
      "type": "import",
      "modules": [
        "json"
      ],
      "aliases": []
    },
    {
      "type": "import",
      "modules": [
        "re"
      ],
      "aliases": []
    },
    {
      "type": "import",
      "modules": [
        "logging"
      ],
      "aliases": []
    },
    {
      "type": "from_import",
      "module": "typing",
      "names": [
        "List",
        "Dict",
        "Any",
        "Optional"
      ],
      "aliases": [],
      "level": 0
    }
  ],
  "constants": [],
  "docstring": "Topic Parser\n主题解析器 - 从原项目迁移，解析AI生成的主题内容",
  "content_hash": "d74c0a64f33726e70ed1151d33e7d937"
}