From bf730377ebe6bb82b477335dcdc0ab827c9079d6 Mon Sep 17 00:00:00 2001 From: junlan <15167915727@163.com> Date: Tue, 3 Feb 2026 22:48:22 +0800 Subject: [PATCH] project init. --- .gitignore | 10 + README.md | 102 ++++++ config.yaml | 83 +++++ input/test.docx | Bin 0 -> 62487 bytes json_to_excel.py | 202 +++++++++++ main.py | 251 +++++++++++++ output/output_llm.json | 682 +++++++++++++++++++++++++++++++++++ requirements.txt | 6 + src/__init__.py | 20 + src/document_parser.py | 597 ++++++++++++++++++++++++++++++ src/json_generator.py | 214 +++++++++++ src/llm_interface.py | 197 ++++++++++ src/requirement_extractor.py | 643 +++++++++++++++++++++++++++++++++ src/utils.py | 134 +++++++ 14 files changed, 3141 insertions(+) create mode 100644 .gitignore create mode 100644 README.md create mode 100644 config.yaml create mode 100644 input/test.docx create mode 100644 json_to_excel.py create mode 100644 main.py create mode 100644 output/output_llm.json create mode 100644 requirements.txt create mode 100644 src/__init__.py create mode 100644 src/document_parser.py create mode 100644 src/json_generator.py create mode 100644 src/llm_interface.py create mode 100644 src/requirement_extractor.py create mode 100644 src/utils.py diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..ff5aae0 --- /dev/null +++ b/.gitignore @@ -0,0 +1,10 @@ +.vscode/ +__pycache__/ +*.pyc +*.pyo +*.pyd +.env +.venv +venv/ +*.log +.DS_Store \ No newline at end of file diff --git a/README.md b/README.md new file mode 100644 index 0000000..10b5e0b --- /dev/null +++ b/README.md @@ -0,0 +1,102 @@ +# SRS需求文档解析工具 + +一个智能的SRS（软件需求规格说明书）文档解析工具，支持PDF和Docx格式，能够自动提取需求并生成结构化JSON输出。 + +## 特性 + +- **LLM增强**：集成阿里云千问大模型，智能识别和提取需求 +- **多格式支持**：支持PDF和Docx格式的SRS文档 +- **非严格GJB结构**：支持不完全遵循GJB 438B标准的文档结构 +- **智能过滤**：自动过滤系统描述、重复需求等非需求内容 +- **结构化输出**：按章节层次组织的JSON格式输出 +- **灵活模式**：支持纯规则提取和LLM增强两种模式 +- **表格需求识别**：支持从表格中提取功能/接口/其他需求 + +## 快速开始 + +### 安装依赖 + +```bash +pip install -r requirements.txt + +# 如果使用LLM功能，还需安装： +pip install dashscope +``` + +### 配置API密钥（LLM模式） + +```bash +# 方式1：环境变量（推荐） +# Linux/Mac +export DASHSCOPE_API_KEY="your-api-key" + +# Windows PowerShell +$env:DASHSCOPE_API_KEY="your-api-key" + +# 方式2：在config.yaml中配置 +# llm: +# api_key: "your-api-key" +``` + +### 运行 + +```bash +# LLM增强模式 +python main.py -i DC-SRS.pdf -o output.json + +# 纯规则模式（不使用LLM） +python main.py -i DC-SRS.pdf -o output.json --no-llm +``` + + + +## 需求类型说明 + +工具统计**三类**需求类型： + +| 类型 | 描述 | +|------|------| +| **功能需求** | 系统应该提供的功能和行为 | +| **接口需求** | 系统的输入/输出接口规范、通信协议等 | +| **其他需求** | 性能、安全、可靠性等非功能性需求 | + +### 接口需求扩展字段 + +接口需求除了基本的"需求编号"和"需求描述"外，还包含以下字段： + +| 字段 | 说明 | +|------|------| +| **接口名称** | 接口的名称 +| **接口类型** | 接口的类型（如：CAN总线接口、以太网接口、串口等） | +| **来源** | 数据或信号的来源/发送方 | +| **目的地** | 数据或信号的目的地/接收方 | + +### 需求描述规则 + +- **功能需求**：保持原文描述，不改写润色 +- **接口需求**：允许改写润色，确保描述清晰完整 +- **其他需求**：保持原文描述，不改写润色 + +## 目录结构 + +``` +SRS_reqs_qwen/ +├── main.py # 主程序入口 +├── config.yaml # 配置文件 +├── requirements.txt # 依赖 +├── src/ +│ ├── document_parser.py # 文档解析器 +│ ├── requirement_extractor.py # 需求提取器 +│ ├── json_generator.py # JSON生成器 +│ ├── llm_interface.py # LLM接口 +│ └── utils.py # 工具函数 +├── docs/ +│ ├── README.md # 项目说明 +│ ├── ARCHITECTURE.md # 架构文档 +│ └── USAGE.md # 使用指南 +└── tests/ # 测试文件 +``` + diff --git a/config.yaml b/config.yaml new file mode 100644 index 0000000..7644bab --- /dev/null +++ b/config.yaml @@ -0,0 +1,83 @@ +# 配置文件 - SRS 需求文档解析工具 (LLM增强版) +# Configuration file for SRS Requirement Document Parser (LLM Enhanced Version) + +# LLM配置 - 阿里云千问 +llm: + # 是否启用LLM（设为false则使用纯规则提取） + enabled: true + # LLM提供商：qwen（阿里云千问） + provider: "qwen" + # 模型名称 + model: "qwen3-max" + # API密钥（建议使用环境变量 DASHSCOPE_API_KEY） + api_key: "sk-7097f7842f724f0c9e70c4bf3b16dacb" + # 可选参数 + temperature: 0.3 + max_tokens: 1024 + +# 文档解析配置 +document: + supported_formats: + - ".pdf" + - ".docx" + # 标题识别的样式列表 + heading_styles: + - "Heading 1" + - "Heading 2" + - "Heading 3" + - "Heading 4" + - "Heading 5" + # 需要过滤的非需求章节（GJB438B标准） + non_requirement_sections: + - "标识" + - "系统概述" + - "文档概述" + - "引用文档" + - "合格性规定" + - "需求可追踪性" + - "注释" + - "附录" + +# 需求提取配置 +extraction: + # 需求类型关键字（用于自动判断需求类型） + requirement_types: + 功能需求: + prefix: "FR" + keywords: ["功能", "feature", "requirement", "CSCI组成", "控制", "处理", "监测", "显示"] + priority: 1 + 接口需求: + prefix: "IR" + keywords: ["接口", "interface", "api", "外部接口", "内部接口", "CAN", "以太网", "通信"] + priority: 2 + 性能需求: + prefix: "PR" + keywords: ["性能", "performance", "速度", "响应时间", "吞吐量"] + priority: 3 + 安全需求: + prefix: "SR" + keywords: ["安全", "security", "安全性", "报警"] + priority: 4 + 可靠性需求: + prefix: "RR" + keywords: ["可靠", "reliability", "容错", "恢复", "冗余"] + priority: 5 + 其他需求: + prefix: "OR" + keywords: ["约束", "资源", "适应性", "保密", "环境", "计算机", "质量", "设计", "人员", "培训", "保障", "验收", "交付"] + priority: 6 + +# 输出配置 +output: + format: "json" + indent: 2 + # 是否美化输出（格式化） + pretty_print: true + # 是否包含元数据 + include_metadata: true + +# 日志配置 +logging: + level: "INFO" # DEBUG, INFO, 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zxi87S%Mw%hkmawrcwfbQmmsU^A;GU^{FUXQhWD0d3oID_Wz=;~(fjZ=9*PZa@m_8J z`da@jJ$MLySRB6vBhLN-KPZ(yWO!KJy=4fW`@?Xr*832Dzkqd%hJe@s&qV*Dob?cX zzqW7}9 None: + self.children.append(child) + child.parent = self + + def add_content(self, text: str) -> None: + if self.content: + self.content += "\n" + text + else: + self.content = text + + def add_table(self, table_data: List[List[str]]) -> None: + self.tables.append(table_data) + + def generate_auto_number(self, parent_number: str = "", sibling_index: int = 1) -> None: + """ + 自动生成章节编号（当章节没有编号时） + + Args: + parent_number: 父章节编号 + sibling_index: 在同级章节中的序号（从1开始） + """ + if not self.number: + if parent_number: + self.number = f"{parent_number}.{sibling_index}" + else: + self.number = str(sibling_index) + + def __repr__(self) -> str: + return f"Section(level={self.level}, number='{self.number}', title='{self.title}')" + + +class DocumentParser(ABC): + """文档解析器基类""" + + def __init__(self, file_path: str): + self.file_path = file_path + self.sections: List[Section] = [] + self.document_title = "" + self.raw_text = "" + self.llm = None + self._uid_counter = 0 + + def set_llm(self, llm) -> None: + """设置LLM实例""" + self.llm = llm + + @abstractmethod + def parse(self) -> List[Section]: + pass + + def get_document_title(self) -> str: + return self.document_title + + def _next_uid(self) -> str: + self._uid_counter += 1 + return f"sec-{self._uid_counter}" + + def _auto_number_sections(self, sections: List[Section], parent_number: str = "") -> None: + """ + 为没有编号的章节自动生成编号 + + 规则：使用Word样式确定级别，跳过前置章节（目录、概述等）， + 从第一个正文章节（如"外部接口"）开始编号为1 + + Args: + sections: 章节列表 + parent_number: 父章节编号 + """ + # 仅在顶级章节重编号 + if not parent_number: + # 前置章节关键词（需要跳过的） + skip_keywords = ['目录', '封面', '扉页', '未命名', '年', '月'] + # 正文章节关键词（遇到这些说明正文开始） + content_keywords = ['外部接口', '接口', '软件需求', '需求', '功能', '性能', '设计', '概述', '标识', '引言'] + + start_index = 0 + for idx, section in enumerate(sections): + # 优先检查是否是正文章节 + is_content = any(kw in section.title for kw in content_keywords) + if is_content and section.level == 1: + start_index = idx + break + + # 重新编号所有章节 + counter = 1 + for i, section in enumerate(sections): + if i < start_index: + # 前置章节不编号 + section.number = "" + else: + # 正文章节：顶级章节从1开始编号 + if section.level == 1: + section.number = str(counter) + counter += 1 + + # 递归处理子章节 + if section.children: + self._auto_number_sections(section.children, section.number) + else: + # 子章节编号 + for i, section in enumerate(sections, 1): + if not section.number or self._is_chinese_number(section.number): + section.generate_auto_number(parent_number, i) + if section.children: + self._auto_number_sections(section.children, section.number) + + def _is_chinese_number(self, text: str) -> bool: + """检查是否是中文数字编号""" + chinese_numbers = '一二三四五六七八九十百千万' + return text and all(c in chinese_numbers for c in text) + + +class DocxParser(DocumentParser): + """DOCX格式文档解析器""" + + def __init__(self, file_path: str): + if not HAS_DOCX: + raise ImportError("python-docx库未安装，请运行: pip install python-docx") + super().__init__(file_path) + self.document = None + + def parse(self) -> List[Section]: + try: + self.document = Document(self.file_path) + self.document_title = self.document.core_properties.title or "SRS Document" + + section_stack = {} + + for block in self._iter_block_items(self.document): + from docx.text.paragraph import Paragraph + from docx.table import Table + if isinstance(block, Paragraph): + text = block.text.strip() + if not text: + continue + + heading_info = self._parse_heading(block, text) + if heading_info: + number, title, level = heading_info + section = Section(level=level, title=title, number=number, uid=self._next_uid()) + + if level == 1 or not section_stack: + self.sections.append(section) + section_stack = {1: section} + else: + parent_level = level - 1 + while parent_level >= 1 and parent_level not in section_stack: + parent_level -= 1 + + if parent_level >= 1 and parent_level in section_stack: + section_stack[parent_level].add_child(section) + elif self.sections: + self.sections[-1].add_child(section) + + section_stack[level] = section + for l in list(section_stack.keys()): + if l > level: + del section_stack[l] + else: + # 添加内容到当前章节 + if section_stack: + max_level = max(section_stack.keys()) + section_stack[max_level].add_content(text) + else: + # 没有标题时，创建默认章节 + default_section = Section(level=1, title="未命名章节", number="", uid=self._next_uid()) + default_section.add_content(text) + self.sections.append(default_section) + section_stack = {1: default_section} + elif isinstance(block, Table): + # 表格处理 + table_data = self._extract_table_data(block) + if table_data: + if section_stack: + max_level = max(section_stack.keys()) + section_stack[max_level].add_table(table_data) + else: + default_section = Section(level=1, title="未命名章节", number="", uid=self._next_uid()) + default_section.add_table(table_data) + self.sections.append(default_section) + section_stack = {1: default_section} + + # 为没有编号的章节自动生成编号 + self._auto_number_sections(self.sections) + + logger.info(f"完成Docx解析，提取{len(self.sections)}个顶级章节") + return self.sections + + except Exception as e: + logger.error(f"解析Docx文档失败: {e}") + raise + + def _is_valid_heading(self, text: str) -> bool: + """检查是否是有效的标题""" + if len(text) > 120 or '...' in text: + return False + # 标题应包含中文或字母 + if not re.search(r'[\u4e00-\u9fa5A-Za-z]', text): + return False + # 过滤目录项（标题后跟页码，如"概述 2"或"概述 . . . . 2"） + if re.search(r'\s{2,}\d+$', text): # 多个空格后跟数字结尾 + return False + if re.search(r'[\.。\s]+\d+$', text): # 点号或空格后跟数字结尾 + return False + return True + + def _parse_heading(self, paragraph, text: str) -> Optional[Tuple[str, str, int]]: + """解析标题，返回(编号, 标题, 级别)""" + style_name = paragraph.style.name if paragraph.style else "" + is_heading_style = style_name.lower().startswith('heading') if style_name else False + + # 数字编号标题 + match = re.match(r'^(\d+(?:\.\d+)*)\s*[\.、]?\s*(.+)$', text) + if match and self._is_valid_heading(match.group(2)): + number = match.group(1) + title = match.group(2).strip() + level = len(number.split('.')) + return number, title, level + + # 中文编号标题 + match = re.match(r'^([一二三四五六七八九十]+)[、\.]+\s*(.+)$', text) + if match and self._is_valid_heading(match.group(2)): + number = match.group(1) + title = match.group(2).strip() + level = 1 + return number, title, level + + # 样式标题 + if is_heading_style and self._is_valid_heading(text): + level = 1 + level_match = re.search(r'(\d+)', style_name) + if level_match: + level = int(level_match.group(1)) + return "", text, level + + return None + + def _iter_block_items(self, parent): + """按文档顺序迭代段落和表格""" + from docx.text.paragraph import Paragraph + from docx.table import Table + from docx.oxml.text.paragraph import CT_P + from docx.oxml.table import CT_Tbl + + for child in parent.element.body.iterchildren(): + if isinstance(child, CT_P): + yield Paragraph(child, parent) + elif isinstance(child, CT_Tbl): + yield Table(child, parent) + + def _extract_table_data(self, table) -> List[List[str]]: + """提取表格数据""" + table_data = [] + for row in table.rows: + row_data = [] + for cell in row.cells: + text = cell.text.replace('\n', ' ').strip() + text = re.sub(r'\s+', ' ', text) + row_data.append(text) + if any(cell for cell in row_data): + table_data.append(row_data) + return table_data + + +class PDFParser(DocumentParser): + """PDF格式文档解析器 - LLM增强版""" + + # GJB438B标准SRS文档的有效章节标题关键词 + VALID_TITLE_KEYWORDS = [ + '范围', '标识', '概述', '引用', '文档', + '需求', '功能', '接口', '性能', '安全', '保密', + '环境', '资源', '质量', '设计', '约束', + '人员', '培训', '保障', '验收', '交付', '包装', + '优先', '关键', '合格', '追踪', '注释', + 'CSCI', '计算机', '软件', '硬件', '通信', '通讯', + '数据', '适应', '可靠', '内部', '外部', + '描述', '要求', '规定', '说明', '定义', + '电场', '防护', '装置', '控制', '监控', '显控' + ] + + # 明显无效的章节标题模式（噪声） + INVALID_TITLE_PATTERNS = [ + '本文档可作为', '参比电位', '补偿电流', '以太网', + '电源', '软件接', '功能\\', '性能 \\', '输入/输出 \\', + '数据处理要求 \\', '固件 \\', '质量控制要求', + '信安科技', '浙江', '公司' + ] + + def __init__(self, file_path: str): + if not HAS_PDF: + raise ImportError("PyPDF2库未安装，请运行: pip install PyPDF2") + super().__init__(file_path) + self.document_title = "SRS Document" + + def parse(self) -> List[Section]: + """解析PDF文档""" + try: + # 1. 提取所有文本 + self.raw_text = self._extract_all_text() + + # 2. 清洗文本 + cleaned_text = self._clean_text(self.raw_text) + + # 3. 识别章节结构 + self.sections = self._parse_sections(cleaned_text) + + # 4. 使用LLM验证和清理章节（如果可用） + if self.llm: + self.sections = self._llm_validate_sections(self.sections) + + # 5. 为没有编号的章节自动生成编号 + self._auto_number_sections(self.sections) + + logger.info(f"完成PDF解析，提取{len(self.sections)}个顶级章节") + return self.sections + + except Exception as e: + logger.error(f"解析PDF文档失败: {e}") + raise + + def _extract_all_text(self) -> str: + """从PDF提取所有文本""" + all_text = [] + with open(self.file_path, 'rb') as f: + pdf_reader = PyPDF2.PdfReader(f) + for page in pdf_reader.pages: + text = page.extract_text() + if text: + all_text.append(text) + return '\n'.join(all_text) + + def _clean_text(self, text: str) -> str: + """清洗PDF提取的文本""" + lines = text.split('\n') + cleaned_lines = [] + + for line in lines: + line = line.strip() + if not line: + continue + # 跳过页码（通常是1-3位数字单独一行） + if re.match(r'^\d{1,3}$', line): + continue + # 跳过目录行 + if line.count('.') > 10 and '...' in line: + continue + + cleaned_lines.append(line) + + return '\n'.join(cleaned_lines) + + def _parse_sections(self, text: str) -> List[Section]: + """解析章节结构""" + sections = [] + section_stack = {} + lines = text.split('\n') + current_section = None + content_buffer = [] + found_sections = set() + + for line in lines: + line = line.strip() + if not line: + continue + + # 尝试匹配章节标题 + section_info = self._match_section_header(line, found_sections) + + if section_info: + number, title = section_info + level = len(number.split('.')) + + # 保存之前章节的内容 + if current_section and content_buffer: + current_section.add_content('\n'.join(content_buffer)) + content_buffer = [] + + # 创建新章节 + section = Section(level=level, title=title, number=number, uid=self._next_uid()) + found_sections.add(number) + + # 建立层次结构 + if level == 1: + sections.append(section) + section_stack = {1: section} + else: + parent_level = level - 1 + while parent_level >= 1 and parent_level not in section_stack: + parent_level -= 1 + + if parent_level >= 1 and parent_level in section_stack: + section_stack[parent_level].add_child(section) + elif sections: + sections[-1].add_child(section) + else: + sections.append(section) + section_stack = {1: section} + + section_stack[level] = section + for l in list(section_stack.keys()): + if l > level: + del section_stack[l] + + current_section = section + else: + # 收集内容 + if line and not self._is_noise(line): + content_buffer.append(line) + + # 保存最后一个章节的内容 + if current_section and content_buffer: + current_section.add_content('\n'.join(content_buffer)) + + return sections + + def _match_section_header(self, line: str, found_sections: set) -> Optional[Tuple[str, str]]: + """ + 匹配章节标题 + + Returns: + (章节编号, 章节标题) 或 None + """ + # 模式: "3.1功能需求" 或 "3.1 功能需求" + match = re.match(r'^(\d+(?:\.\d+)*)\s*(.+)$', line) + if not match: + return None + + number = match.group(1) + title = match.group(2).strip() + + # 排除目录行 + if '...' in title or title.count('.') > 5: + return None + + # 验证章节编号 + parts = number.split('.') + first_part = int(parts[0]) + + # 放宽一级章节编号范围（非严格GJB结构） + if first_part < 1 or first_part > 30: + return None + + # 检查子部分是否合理 + for part in parts[1:]: + if int(part) > 20: + return None + + # 避免重复 + if number in found_sections: + return None + + # 标题长度检查 + if len(title) > 60 or len(title) < 2: + return None + + # 标题必须包含中文 + if not re.search(r'[\u4e00-\u9fa5]', title): + return None + + # 放宽标题关键词要求（非严格GJB结构） + if not re.search(r'[\u4e00-\u9fa5A-Za-z]', title): + return None + + # 检查是否包含无效模式 + for invalid_pattern in self.INVALID_TITLE_PATTERNS: + if invalid_pattern in title: + return None + + # 标题不能以数字开头 + if title[0].isdigit(): + return None + + # 数字比例检查 + digit_ratio = sum(c.isdigit() for c in title) / max(len(title), 1) + if digit_ratio > 0.3: + return None + + # 检查标题是否包含反斜杠（通常是表格噪声） + if '\\' in title and '需求' not in title: + return None + + return (number, title) + + def _is_noise(self, line: str) -> bool: + """检查是否是噪声行""" + # 纯数字行 + if re.match(r'^[\d\s,.]+$', line): + return True + # 非常短的行 + if len(line) < 3: + return True + # 罗马数字 + if re.match(r'^[ivxIVX]+$', line): + return True + return False + + def _llm_validate_sections(self, sections: List[Section]) -> List[Section]: + """使用LLM验证章节是否有效""" + if not self.llm: + return sections + + validated_sections = [] + + for section in sections: + # 验证顶级章节 + if self._is_valid_section_with_llm(section): + # 递归验证子章节 + section.children = self._validate_children(section.children) + validated_sections.append(section) + + return validated_sections + + def _validate_children(self, children: List[Section]) -> List[Section]: + """递归验证子章节""" + validated = [] + for child in children: + if self._is_valid_section_with_llm(child): + child.children = self._validate_children(child.children) + validated.append(child) + return validated + + def _is_valid_section_with_llm(self, section: Section) -> bool: + """使用LLM判断章节是否有效""" + # 先用规则快速过滤明显无效的章节 + invalid_titles = [ + '本文档可作为', '故障', '实时', '输入/输出', + '固件', '功能\\', '\\4.', '\\3.' + ] + for invalid in invalid_titles: + if invalid in section.title: + logger.debug(f"过滤无效章节: {section.number} {section.title}") + return False + + # 对于需求相关章节（第3章），额外验证 + if section.number and section.number.startswith('3'): + # 检查标题是否看起来像是有效的需求章节标题 + # 有效的标题应该是完整的中文短语 + if '\\' in section.title or '/' in section.title: + if not any(kw in section.title for kw in ['输入', '输出', '接口']): + return False + + return True + + +def create_parser(file_path: str) -> DocumentParser: + """ + 工厂函数：根据文件扩展名创建相应的解析器 + """ + ext = Path(file_path).suffix.lower() + + if ext == '.docx': + return DocxParser(file_path) + elif ext == '.pdf': + return PDFParser(file_path) + else: + raise ValueError(f"不支持的文件格式: {ext}") diff --git a/src/json_generator.py b/src/json_generator.py new file mode 100644 index 0000000..0eca52c --- /dev/null +++ b/src/json_generator.py @@ -0,0 +1,214 @@ +# -*- coding: utf-8 -*- +""" +JSON生成器模块 - LLM增强版 +将提取的需求和章节结构转换为结构化JSON输出 +""" + +import json +import logging +from datetime import datetime +from typing import List, Dict, Any, Optional +from .document_parser import Section +from .requirement_extractor import Requirement + +logger = logging.getLogger(__name__) + + +class JSONGenerator: + """JSON输出生成器""" + + # 需求类型中文映射 + TYPE_CHINESE = { + 'functional': '功能需求', + 'interface': '接口需求', + 'performance': '其他需求', + 'security': '其他需求', + 'reliability': '其他需求', + 'other': '其他需求' + } + + # 非需求章节（不输出到JSON） + NON_REQUIREMENT_SECTIONS = [ + '标识', '系统概述', '文档概述', '引用文档', + '合格性规定', '需求可追踪性', '注释', '附录', + '范围', '概述' + ] + + def __init__(self, config: Dict = None): + self.config = config or {} + + def generate(self, sections: List[Section], requirements: List[Requirement], + document_title: str = "SRS Document") -> Dict[str, Any]: + """ + 生成JSON输出 + + Args: + sections: 章节列表 + requirements: 需求列表 + document_title: 文档标题 + + Returns: + 结构化JSON字典 + """ + # 按章节组织需求 + reqs_by_section = self._group_requirements_by_section(requirements) + + # 统计需求类型 + type_stats = self._calculate_type_statistics(requirements) + + # 构建输出结构 + output = { + "文档元数据": { + "标题": document_title, + "生成时间": datetime.now().isoformat(), + "总需求数": len(requirements), + "需求类型统计": type_stats + }, + "需求内容": self._build_requirement_content(sections, reqs_by_section) + } + + logger.info(f"生成JSON输出，共{len(requirements)}个需求") + return output + + def _group_requirements_by_section(self, requirements: List[Requirement]) -> Dict[str, List[Requirement]]: + """按章节编号分组需求""" + grouped = {} + for req in requirements: + section_key = req.section_uid or req.section_number or 'unknown' + if section_key not in grouped: + grouped[section_key] = [] + grouped[section_key].append(req) + return grouped + + def _calculate_type_statistics(self, requirements: List[Requirement]) -> Dict[str, int]: + """计算需求类型统计""" + stats = {} + for req in requirements: + type_chinese = self.TYPE_CHINESE.get(req.type, '其他需求') + if type_chinese not in stats: + stats[type_chinese] = 0 + stats[type_chinese] += 1 + return stats + + def _should_include_section(self, section: Section) -> bool: + """判断章节是否应该包含在输出中""" + # 排除非需求章节 + for keyword in self.NON_REQUIREMENT_SECTIONS: + if keyword in section.title: + return False + + return True + + def _build_requirement_content(self, sections: List[Section], + reqs_by_section: Dict[str, List[Requirement]]) -> Dict[str, Any]: + """构建需求内容的层次结构""" + content = {} + + for section in sections: + # 只处理需求相关章节 + if not self._should_include_section(section): + # 但仍需检查子章节 + for child in section.children: + child_content = self._build_section_content_recursive(child, reqs_by_section) + if child_content: + key = f"{child.number} {child.title}" if child.number else child.title + content[key] = child_content + continue + + section_content = self._build_section_content_recursive(section, reqs_by_section) + if section_content: + key = f"{section.number} {section.title}" if section.number else section.title + content[key] = section_content + + return content + + def _build_section_content_recursive(self, section: Section, + reqs_by_section: Dict[str, List[Requirement]]) -> Optional[Dict[str, Any]]: + """递归构建章节内容""" + # 检查是否应该包含此章节 + if not self._should_include_section(section): + return None + + # 章节基本信息 + result = { + "章节信息": { + "章节编号": section.number or "", + "章节标题": section.title, + "章节级别": section.level + } + } + + # 检查是否有子章节 + has_valid_children = False + subsections = {} + + for child in section.children: + child_content = self._build_section_content_recursive(child, reqs_by_section) + if child_content: + has_valid_children = True + key = f"{child.number} {child.title}" if child.number else child.title + subsections[key] = child_content + + # 添加当前章节需求 + reqs = reqs_by_section.get(section.uid or section.number or 'unknown', []) + if reqs: + result["需求列表"] = [] + for req in reqs: + # 需求类型放在最前面 + type_chinese = self.TYPE_CHINESE.get(req.type, '功能需求') + req_dict = { + "需求类型": type_chinese, + "需求编号": req.id, + "需求描述": req.description + } + # 接口需求增加额外字段 + if req.type == 'interface': + req_dict["接口名称"] = req.interface_name + req_dict["接口类型"] = req.interface_type + req_dict["来源"] = req.source + req_dict["目的地"] = req.destination + result["需求列表"].append(req_dict) + + # 如果有子章节，添加子章节 + if has_valid_children: + result["子章节"] = subsections + + # 如果章节既没有需求也没有子章节，返回None + if "需求列表" not in result and "子章节" not in result: + return None + + return result + + def save_to_file(self, output: Dict[str, Any], file_path: str) -> None: + """ + 将输出保存到文件 + + Args: + output: 输出字典 + file_path: 输出文件路径 + """ + try: + with open(file_path, 'w', encoding='utf-8') as f: + json.dump(output, f, ensure_ascii=False, indent=2) + logger.info(f"成功保存JSON到: {file_path}") + except Exception as e: + logger.error(f"保存JSON文件失败: {e}") + raise + + def generate_and_save(self, sections: List[Section], requirements: List[Requirement], + document_title: str, file_path: str) -> Dict[str, Any]: + """ + 生成并保存JSON + + Args: + sections: 章节列表 + requirements: 需求列表 + document_title: 文档标题 + file_path: 输出文件路径 + + Returns: + 生成的输出字典 + """ + output = self.generate(sections, requirements, document_title) + self.save_to_file(output, file_path) + return output diff --git a/src/llm_interface.py b/src/llm_interface.py new file mode 100644 index 0000000..b2db801 --- /dev/null +++ b/src/llm_interface.py @@ -0,0 +1,197 @@ +# src/llm_interface.py +""" +LLM接口模块 - 支持多个LLM提供商 +""" + +import logging +import json +from abc import ABC, abstractmethod +from typing import Dict, List, Optional, Any + +from .utils import get_env_or_config + +logger = logging.getLogger(__name__) + + +class LLMInterface(ABC): + """LLM接口基类""" + + def __init__(self, api_key: str = None, model: str = None, **kwargs): + """ + 初始化LLM接口 + + Args: + api_key: API密钥 + model: 模型名称 + **kwargs: 其他参数（如temperature, max_tokens等） + """ + self.api_key = api_key + self.model = model + self.extra_params = kwargs + + @abstractmethod + def call(self, prompt: str) -> str: + """ + 调用LLM API + + Args: + prompt: 提示词 + + Returns: + LLM的响应文本 + """ + pass + + @abstractmethod + def call_json(self, prompt: str) -> Dict[str, Any]: + """ + 调用LLM API并获取JSON格式的响应 + + Args: + prompt: 提示词 + + Returns: + 解析后的JSON字典 + """ + pass + + def validate_config(self) -> bool: + """验证配置是否完整""" + return bool(self.api_key and self.model) + + +class QwenLLM(LLMInterface): + """阿里云千问LLM实现""" + + def __init__(self, api_key: str = None, model: str = "qwen-plus", + api_endpoint: str = None, **kwargs): + """ + 初始化千问LLM + + Args: + api_key: 阿里云API密钥 + model: 模型名称（如qwen-plus, qwen-turbo） + api_endpoint: API端点地址 + **kwargs: 其他参数 + """ + super().__init__(api_key, model, **kwargs) + self.api_endpoint = api_endpoint or "https://dashscope.aliyuncs.com/compatible-mode/v1" + self._check_dashscope_import() + + def _check_dashscope_import(self) -> None: + """检查dashscope库是否已安装""" + try: + import dashscope + self.dashscope = dashscope + except ImportError: + logger.error("dashscope库未安装，请运行: pip install dashscope") + raise + + def call(self, prompt: str) -> str: + """ + 调用千问LLM + + Args: + prompt: 提示词 + + Returns: + LLM的响应文本 + """ + if not self.validate_config(): + raise ValueError("LLM配置不完整（api_key或model未设置）") + + try: + from dashscope import Generation + + # 设置API密钥 + self.dashscope.api_key = self.api_key + + # 构建请求参数 - dashscope 1.7.0 格式 + response = Generation.call( + model=self.model, + messages=[ + {'role': 'user', 'content': prompt} + ], + result_format='message' # 使用message格式 + ) + + # 调试输出 + logger.debug(f"API响应类型: {type(response)}") + logger.debug(f"API响应内容: {response}") + + # 处理响应 + if isinstance(response, dict): + # dict格式响应 + status_code = response.get('status_code', 200) + if status_code == 200: + output = response.get('output', {}) + if 'choices' in output: + return output['choices'][0]['message']['content'] + elif 'text' in output: + return output['text'] + else: + # 尝试直接获取text + return output.get('text', str(output)) + else: + error_msg = response.get('message', response.get('code', 'Unknown error')) + logger.error(f"千问API返回错误: {error_msg}") + raise Exception(f"API调用失败: {error_msg}") + else: + # 对象格式响应 + if hasattr(response, 'status_code') and response.status_code == 200: + output = response.output + if hasattr(output, 'choices'): + return output.choices[0].message.content + elif hasattr(output, 'text'): + return output.text + else: + return str(output) + elif hasattr(response, 'status_code'): + error_msg = getattr(response, 'message', str(response)) + raise Exception(f"API调用失败: {error_msg}") + else: + return str(response) + + except Exception as e: + logger.error(f"调用千问LLM失败: {e}") + raise + + def call_json(self, prompt: str) -> Dict[str, Any]: + """ + 调用千问LLM并获取JSON格式响应 + + Args: + prompt: 提示词 + + Returns: + 解析后的JSON字典 + """ + # 添加JSON格式要求到提示词 + json_prompt = prompt + "\n\n请确保响应是有效的JSON格式。" + + response = self.call(json_prompt) + + try: + # 尝试解析JSON + # 首先尝试直接解析 + return json.loads(response) + except json.JSONDecodeError: + # 尝试提取JSON代码块 + try: + import re + # 查找JSON代码块 + json_match = re.search(r'```json\s*(.*?)\s*```', response, re.DOTALL) + if json_match: + return json.loads(json_match.group(1)) + + # 尝试查找任何JSON对象 + json_match = re.search(r'\{.*\}', response, re.DOTALL) + if json_match: + return json.loads(json_match.group(0)) + + except Exception as e: + logger.warning(f"无法从响应中提取JSON: {e}") + + # 如果都失败，返回错误信息 + logger.error(f"无法解析LLM响应为JSON: {response}") + return {"error": "Failed to parse response as JSON", "raw_response": response} diff --git a/src/requirement_extractor.py b/src/requirement_extractor.py new file mode 100644 index 0000000..6a9a1a0 --- /dev/null +++ b/src/requirement_extractor.py @@ -0,0 +1,643 @@ +# -*- coding: utf-8 -*- +""" +需求提取器模块 - LLM增强版 +使用阿里云千问大模型智能提取和分类需求 +""" + +import re +import json +import logging +from typing import List, Dict, Optional, Tuple, Any +from .document_parser import Section + +logger = logging.getLogger(__name__) + + +class Requirement: + """表示一个需求项""" + + def __init__(self, req_id: str, description: str, req_type: str = "functional", + section_number: str = "", section_title: str = "", + interface_name: str = "", interface_type: str = "", + section_uid: str = "", + source: str = "", destination: str = ""): + self.id = req_id + self.description = description + self.type = req_type + self.section_number = section_number + self.section_title = section_title + self.section_uid = section_uid + # 接口需求特有字段 + self.interface_name = interface_name + self.interface_type = interface_type + self.source = source + self.destination = destination + + def to_dict(self) -> Dict: + result = { + "需求编号": self.id, + "需求描述": self.description + } + # 接口需求增加额外字段 + if self.type == 'interface': + result["接口名称"] = self.interface_name + result["接口类型"] = self.interface_type + result["来源"] = self.source + result["目的地"] = self.destination + return result + + def __repr__(self) -> str: + return f"Requirement(id='{self.id}', type='{self.type}')" + + +class RequirementExtractor: + """需求提取器 - LLM增强版""" + + # 需求类型前缀映射 + TYPE_PREFIX = { + 'functional': 'FR', + 'interface': 'IR', + 'performance': 'PR', + 'security': 'SR', + 'reliability': 'RR', + 'other': 'OR' + } + + # 中文类型到英文的映射 + TYPE_MAPPING = { + '功能需求': 'functional', + '接口需求': 'interface', + '其他需求': 'other' + } + + # 非需求章节（应该跳过的） + NON_REQUIREMENT_SECTIONS = [ + '标识', '系统概述', '文档概述', '引用文档', + '合格性规定', '需求可追踪性', '注释', '附录', + '范围', '概述' + ] + + def __init__(self, config: Dict = None, llm=None): + self.config = config or {} + self.llm = llm + self.requirements: List[Requirement] = [] + self._req_counters: Dict[str, Dict[str, int]] = {} # {section_number: {type: count}} + + def extract_from_sections(self, sections: List[Section]) -> List[Requirement]: + """ + 从章节列表中提取需求 + + Args: + sections: 解析后的章节列表 + + Returns: + 需求列表 + """ + self.requirements = [] + self._req_counters = {} + + for section in sections: + self._process_section(section) + + logger.info(f"共提取 {len(self.requirements)} 个需求项") + return self.requirements + + def _process_section(self, section: Section, depth: int = 0) -> None: + """递归处理章节，提取需求""" + # 检查是否应该跳过此章节 + if self._should_skip_section(section): + logger.debug(f"跳过非需求章节: {section.number} {section.title}") + for child in section.children: + self._process_section(child, depth + 1) + return + + # 先提取当前章节需求（包含表格） + reqs = self._extract_requirements_from_section(section) + self.requirements.extend(reqs) + + # 再递归处理子章节 + for child in section.children: + self._process_section(child, depth + 1) + + def _should_skip_section(self, section: Section) -> bool: + """判断是否应该跳过此章节""" + # 检查标题是否包含非需求关键词 + for keyword in self.NON_REQUIREMENT_SECTIONS: + if keyword in section.title: + return True + + # 检查是否是系统描述章节（如3.1.1通常是系统描述） + if self._is_system_description(section): + return True + + return False + + def _is_system_description(self, section: Section) -> bool: + """判断是否是系统描述章节（应该跳过）""" + # 检查标题 + desc_keywords = ['系统描述', '功能描述', '概述', '示意图', '组成'] + for kw in desc_keywords: + if kw in section.title: + return True + + # 使用LLM判断 + if self.llm and section.content: + try: + result = self._llm_check_system_description(section) + return result + except Exception as e: + logger.warning(f"LLM判断失败，使用规则判断: {e}") + + return False + + def _llm_check_system_description(self, section: Section) -> bool: + """使用LLM判断是否是系统描述""" + prompt = f"""请判断以下章节是否是对系统的整体描述（而不是具体的功能需求）。 + +章节编号：{section.number} +章节标题：{section.title} +章节内容（前500字符）： +{section.content[:500] if section.content else '无'} + +请只回答"是"或"否"： +- "是"：这是系统整体描述、功能模块组成介绍、系统架构说明等概述性内容 +- "否"：这是具体的功能需求、接口需求、性能要求等可提取的需求内容 + +回答（只需要回答"是"或"否"）：""" + + response = self.llm.call(prompt).strip() + return '是' in response + + def _extract_requirements_from_section(self, section: Section) -> List[Requirement]: + """从单个章节提取需求""" + requirements = [] + + # 获取需求类型 + req_type = self._identify_requirement_type(section.title, section.content) + + if self.llm: + # 使用LLM提取需求 + reqs = self._llm_extract_requirements(section, req_type) + requirements.extend(reqs) + else: + # 使用规则提取 + reqs = self._rule_extract_requirements(section, req_type) + requirements.extend(reqs) + + return requirements + + def _llm_extract_requirements(self, section: Section, req_type: str) -> List[Requirement]: + """使用LLM提取需求""" + requirements = [] + + content_text = section.content or "" + table_text = self._format_tables_for_prompt(section.tables) + if len(content_text.strip()) < 8 and not table_text: + return requirements + + # 根据需求类型构建不同的提示词 + if req_type == 'interface': + # 接口需求：允许改写润色，并提取接口详细信息 + prompt = f"""请从以下SRS文档章节中提取具体的接口需求，并对需求描述进行改写润色。同时智能识别每个接口的详细信息。 + +章节编号：{section.number} +章节标题：{section.title} +章节内容： +{content_text} + +章节内表格（若有）： +{table_text if table_text else '无'} + +提取要求： +1. 只提取具体的、可验证的接口需求 +2. 不要提取系统描述、背景说明等非需求内容 +3. 去除原文中的换行符、表格格式噪声 +4. 对提取的需求描述进行改写润色，使其更加清晰完整 +5. 每条需求应该是完整的句子，描述清楚接口规范 +6. 如果有多条需求，请分别列出 +7. 对于每条接口需求，请智能识别以下信息： + - interface_name: 接口名称 + - interface_type: 接口类型 （如：CAN接口、以太网接口、串口等） + - source: 来源/发送方（数据或信号从哪里来） + - destination: 目的地/接收方（数据或信号发送到哪里） +8. 如果某个字段无法从文本中识别，请填写"未知" +9. 若原文给出需求编号，请优先使用原文编号（req_id） + +请以JSON格式输出，格式如下： +{{ + "requirements": [ + {{ + "req_id": "需求编号（如有）", + "description": "接口需求描述", + "interface_name": "接口名称", + "interface_type": "接口类型", + "source": "来源", + "destination": "目的地" + }} + ] +}} + +如果该章节没有可提取的需求，返回空数组： +{{"requirements": []}} + +JSON输出：""" + else: + # 功能需求、其他需求：保留原文描述，不改写润色 + prompt = f"""请从以下SRS文档章节中提取具体的软件需求。保持原文描述，不要改写或润色。 + +章节编号：{section.number} +章节标题：{section.title} +章节内容： +{content_text} + +章节内表格（若有）： +{table_text if table_text else '无'} + +提取要求： +1. 同时提取正文与表格中的具体、可验证的软件需求 +2. 不要提取系统描述、背景说明等非需求内容 +3. 保持原文描述，不要对需求进行改写、润色或重新组织 +4. 去除原文中的多余换行符和表格格式符号，但保留语句内容 +5. 每条需求应该是完整的句子 +6. 如果有多条需求，请分别列出 +7. 如果一段需求描述内有多条需求，请尽量拆分成独立的需求项 +8. 过滤重复或过于相似的需求，只保留独特的需求 +9. 若原文给出需求编号，请优先使用原文编号（req_id） + +请以JSON格式输出，格式如下： +{{ + "requirements": [ + {{"req_id": "需求编号（如有）", "description": "需求描述1"}}, + {{"req_id": "需求编号（如有）", "description": "需求描述2"}} + ] +}} + +如果该章节没有可提取的需求，返回空数组： +{{"requirements": []}} + +JSON输出：""" + + try: + response = self.llm.call(prompt) + data = self._parse_llm_json_response(response) + + if data and 'requirements' in data: + # 查找父需求编号（第一个合法完整编号的需求） + parent_req_id = "" + complete_id_pattern = r'^[A-Za-z0-9]{2,10}[-_].+$' + for req_data in data['requirements']: + temp_id = self._normalize_req_id(req_data.get('req_id', '') or req_data.get('id', '')) + if not temp_id: + temp_desc = req_data.get('description', '').strip() + temp_id, _ = self._extract_requirement_id_from_text(temp_desc) + # 验证是否为合法的完整编号格式 + if temp_id and re.match(complete_id_pattern, temp_id): + parent_req_id = temp_id.replace('_', '-') + break + + for i, req_data in enumerate(data['requirements'], 1): + desc = req_data.get('description', '').strip() + if desc and len(desc) > 5: + # 清理描述中的多余换行符和表格符号 + desc = self._clean_description(desc) + + # 需求ID优先使用文档给出的编号 + doc_req_id = self._normalize_req_id(req_data.get('req_id', '') or req_data.get('id', '')) + if not doc_req_id: + doc_req_id, desc = self._extract_requirement_id_from_text(desc) + + # 生成最终的需求ID（三级优先级） + req_id = self._generate_requirement_id(req_type, section.number, i, doc_req_id, parent_req_id) + + # 接口需求提取额外字段 + interface_name = "" + interface_type = "" + source = "" + destination = "" + if req_type == 'interface': + interface_name = req_data.get('interface_name', '未知').strip() + interface_type = req_data.get('interface_type', '未知').strip() + source = req_data.get('source', '未知').strip() + destination = req_data.get('destination', '未知').strip() + + req = Requirement( + req_id=req_id, + description=desc, + req_type=req_type, + section_number=section.number, + section_title=section.title, + section_uid=section.uid, + interface_name=interface_name, + interface_type=interface_type, + source=source, + destination=destination + ) + requirements.append(req) + except Exception as e: + logger.warning(f"LLM提取需求失败: {e}，使用规则提取") + return self._rule_extract_requirements(section, req_type) + + return requirements + + def _rule_extract_requirements(self, section: Section, req_type: str) -> List[Requirement]: + """使用规则提取需求（备用方法）""" + requirements = [] + content = section.content + + # 正文需求 + descriptions = [] + if content and len(content.strip()) >= 8: + descriptions = self._extract_list_items(content) + + if not descriptions: + # 如果没有列表项，将整个内容作为一个需求 + desc = self._clean_description(content) + if len(desc) > 5: + descriptions = [f"{section.title}：{desc}"] + + # 表格需求 + table_requirements = self._extract_requirements_from_tables_rule(section.tables) + + # 查找父需求编号（第一个合法完整编号） + parent_req_id = "" + complete_id_pattern = r'^[A-Za-z0-9]{2,10}[-_].+$' + for desc in descriptions: + temp_id, _ = self._extract_requirement_id_from_text(desc) + # 验证是否为合法的完整编号格式 + if temp_id and re.match(complete_id_pattern, temp_id): + parent_req_id = temp_id.replace('_', '-') + break + if not parent_req_id: + for temp_id, _ in table_requirements: + # 验证是否为合法的完整编号格式 + if temp_id and re.match(complete_id_pattern, temp_id): + parent_req_id = temp_id.replace('_', '-') + break + + index = 1 + for desc in descriptions: + desc = self._clean_description(desc) + if len(desc) > 5: + doc_req_id, cleaned_desc = self._extract_requirement_id_from_text(desc) + # 生成最终的需求ID（三级优先级） + req_id = self._generate_requirement_id(req_type, section.number, index, doc_req_id, parent_req_id) + req = Requirement( + req_id=req_id, + description=cleaned_desc, + req_type=req_type, + section_number=section.number, + section_title=section.title, + section_uid=section.uid + ) + requirements.append(req) + index += 1 + + for doc_req_id, desc in table_requirements: + # 生成最终的需求ID（三级优先级） + req_id = self._generate_requirement_id(req_type, section.number, index, doc_req_id, parent_req_id) + req = Requirement( + req_id=req_id, + description=desc, + req_type=req_type, + section_number=section.number, + section_title=section.title, + section_uid=section.uid + ) + requirements.append(req) + index += 1 + + return requirements + + def _extract_list_items(self, content: str) -> List[str]: + """提取列表项""" + items = [] + + # 模式1: a) b) c) 或 1) 2) 3) + patterns = [ + r'([a-z][\)）])\s*(.+?)(?=[a-z][\)）]|$)', + r'(\d+[\)）])\s*(.+?)(?=\d+[\)）]|$)', + r'([①②③④⑤⑥⑦⑧⑨⑩])\s*(.+?)(?=[①②③④⑤⑥⑦⑧⑨⑩]|$)' + ] + + for pattern in patterns: + matches = re.findall(pattern, content, re.DOTALL) + if matches: + for marker, text in matches: + text = text.strip() + if text and len(text) > 5: + items.append(text) + break + + return items + + def _identify_requirement_type(self, title: str, content: str) -> str: + """ + 通过标题和内容识别需求类型 + + 根据章节标题和内容判断需求类型： + - 标题或内容中包含"接口"相关词汇 -> 接口需求 + - 其他情况 -> 功能需求（默认） + + 注意：不能仅靠标题判断是否为功能需求，若无法识别具体类型，默认为功能需求 + """ + title_lower = title.lower() + content_lower = (content or "").lower()[:500] # 只检查前500字符 + combined_text = title_lower + " " + content_lower + + # 优先识别接口需求，根据具体文件情况修改关键词 + interface_keywords = ['接口', 'interface', 'api', '串口', '通信协议', '数据交换'] + for keyword in interface_keywords: + if keyword in combined_text: + return 'interface' + + # 默认为功能需求（不能仅靠标题判断，无法识别时默认为功能需求） + return 'functional' + + def _generate_requirement_id(self, req_type: str, section_number: str, index: int, + doc_req_id: str = "", parent_req_id: str = "") -> str: + """ + 生成需求ID（三级优先级） + + 优先级规则： + 1. 如果doc_req_id是合法的完整编号（以2-10个字母或数字开头，后跟分隔符），直接使用 + 例如: NY01-01、FR-3.1.2-1、AIRSAT07-GD03-04 + 2. 如果doc_req_id是代号/序号，且有parent_req_id，则组合 + 格式: {parent_req_id}-{doc_req_id}，例如: NY01-01-K101 + 3. 否则自动生成 + 格式: {PREFIX}-{section_number}-{index}，例如: IR-4.1.1-1（保留章节号中的点号） + + Args: + req_type: 需求类型 + section_number: 章节编号 + index: 序号 + doc_req_id: 文档中提取的编号/代号 + parent_req_id: 父需求编号（用于子需求） + """ + # 优先级1：合法的完整编号（以2-10个字母或数字开头，后跟分隔符） + if doc_req_id: + # 检查是否为合法的完整编号格式：2-10个字母或数字开头 + 分隔符 + 其他字符 + # 例如: NY01-01、FR-3.1.2-1、AIRSAT07-GD03-04 + complete_id_pattern = r'^[A-Za-z0-9]{2,10}[-_].+$' + if re.match(complete_id_pattern, doc_req_id): + return doc_req_id.replace('_', '-') + + # 优先级2：代号/序号 + 父需求编号 + if doc_req_id and parent_req_id: + return f"{parent_req_id}-{doc_req_id}" + + # 优先级3：自动生成（保留章节号中的点号） + prefix = self.TYPE_PREFIX.get(req_type, 'FR') # 默认FR（功能需求） + section_part = section_number if section_number else "NA" + return f"{prefix}-{section_part}-{index}" + + def _normalize_req_id(self, req_id: str) -> str: + """规范化需求编号""" + if not req_id: + return "" + req_id = str(req_id).strip() + return req_id + + def _clean_description(self, text: str) -> str: + """清理需求描述""" + # 替换换行符为空格 + text = re.sub(r'\n+', ' ', text) + # 替换多个空格为单个空格 + text = re.sub(r'\s+', ' ', text) + # 去除表格噪声 + text = re.sub(r'[\|│┃]+', ' ', text) + # 去除首尾空白 + text = text.strip() + # 限制长度 + if len(text) > 1000: + text = text[:1000] + '...' + return text + + def _format_tables_for_prompt(self, tables: List[List[List[str]]]) -> str: + """格式化表格内容用于LLM提示词""" + if not tables: + return "" + lines = [] + for idx, table in enumerate(tables, 1): + lines.append(f"表格{idx}:") + for row in table: + row_text = " | ".join(self._clean_description(cell) for cell in row if cell) + if row_text: + lines.append(row_text) + return "\n".join(lines) + + def _extract_requirement_id_from_text(self, text: str) -> Tuple[Optional[str], str]: + """ + 从文本中提取需求编号 + + 支持的格式： + 1. 完整编号：NY01-01、FR-3.1.2-1 + 2. 代号/序号：K101、D61、a)、1) + """ + if not text: + return None, text + + # 模式1：完整需求编号（如 NY01-01、FR-3.1.2-1） + pattern1 = r'^\s*([A-Za-z]{2,6}[-_]\d+(?:[-.\d]+)*)\s*[:：\)\]】]?\s*(.+)$' + match = re.match(pattern1, text) + if match: + return match.group(1).strip(), match.group(2).strip() + + # 模式2：代号（如 K101、D61） + pattern2 = r'^\s*([A-Za-z]\d+)\s*[:：\)\]】]?\s*(.+)$' + match = re.match(pattern2, text) + if match: + return match.group(1).strip(), match.group(2).strip() + + # 模式3：序号（如 a)、1)） + pattern3 = r'^\s*([a-z0-9]{1,2}[\)）])\s*(.+)$' + match = re.match(pattern3, text) + if match: + code = match.group(1).strip().rstrip(')）') + return code, match.group(2).strip() + + return None, text + + def _extract_requirements_from_tables_rule(self, tables: List[List[List[str]]]) -> List[Tuple[Optional[str], str]]: + """从表格中提取需求（规则方式）""" + results = [] + if not tables: + return results + + id_keywords = ['需求编号', '编号', '序号', 'id', 'ID'] + desc_keywords = ['需求', '描述', '内容', '说明', '要求'] + + for table in tables: + if not table: + continue + header = table[0] if table else [] + header_lower = [h.lower() for h in header] + id_idx = None + desc_idx = None + for i, h in enumerate(header_lower): + if any(k.lower() in h for k in id_keywords): + id_idx = i + if any(k.lower() in h for k in desc_keywords): + desc_idx = i + + start_row = 1 if (id_idx is not None or desc_idx is not None) else 0 + for row in table[start_row:]: + if not row: + continue + row = [self._clean_description(cell) for cell in row] + if not any(row): + continue + + req_id = None + desc = "" + if id_idx is not None and id_idx < len(row): + req_id = self._normalize_req_id(row[id_idx]) + if desc_idx is not None and desc_idx < len(row): + desc = row[desc_idx] + if not desc: + # 如果无明确描述列，拼接整行作为描述 + desc = " | ".join([cell for cell in row if cell]) + + # 若描述里包含编号，尝试再次提取 + if not req_id: + req_id, desc = self._extract_requirement_id_from_text(desc) + + if desc and len(desc) > 5: + results.append((req_id, desc)) + + return results + + def _parse_llm_json_response(self, response: str) -> Optional[Dict]: + """解析LLM的JSON响应""" + try: + return json.loads(response) + except json.JSONDecodeError: + # 尝试提取JSON代码块 + try: + json_match = re.search(r'```(?:json)?\s*(.*?)\s*```', response, re.DOTALL) + if json_match: + return json.loads(json_match.group(1)) + + # 尝试查找JSON对象 + json_match = re.search(r'\{.*\}', response, re.DOTALL) + if json_match: + return json.loads(json_match.group(0)) + except Exception: + pass + + logger.warning(f"无法解析LLM响应为JSON: {response[:200]}") + return None + + def get_statistics(self) -> Dict: + """获取需求统计信息""" + stats = { + 'total': len(self.requirements), + 'by_type': {} + } + + for req in self.requirements: + req_type = req.type + if req_type not in stats['by_type']: + stats['by_type'][req_type] = 0 + stats['by_type'][req_type] += 1 + + return stats diff --git a/src/utils.py b/src/utils.py new file mode 100644 index 0000000..53e5a65 --- /dev/null +++ b/src/utils.py @@ -0,0 +1,134 @@ +# src/utils.py +""" +工具函数模块 - 提供各种辅助功能 +""" + +import os +import logging +from pathlib import Path +from typing import Dict, Any, List, Optional +import yaml + +logger = logging.getLogger(__name__) + + +def load_config(config_path: str = None) -> Dict[str, Any]: + """ + 加载配置文件 + + Args: + config_path: 配置文件路径，如果为None则使用默认路径 + + Returns: + 配置字典 + """ + if config_path is None: + config_path = os.path.join(os.path.dirname(__file__), '..', 'config.yaml') + + if not os.path.exists(config_path): + logger.warning(f"配置文件不存在: {config_path}") + return {} + + try: + with open(config_path, 'r', encoding='utf-8') as f: + config = yaml.safe_load(f) + logger.info(f"成功加载配置文件: {config_path}") + return config or {} + except Exception as e: + logger.error(f"加载配置文件失败: {e}") + return {} + + +def setup_logging(config: Dict[str, Any]) -> None: + """ + 配置日志系统 + + Args: + config: 配置字典 + """ + logging_config = config.get('logging', {}) + level = logging_config.get('level', 'INFO') + log_format = logging_config.get('format', '%(asctime)s - %(name)s - %(levelname)s - %(message)s') + log_file = logging_config.get('file', None) + + # 创建logger + logging.basicConfig( + level=getattr(logging, level), + format=log_format, + handlers=[ + logging.StreamHandler(), + logging.FileHandler(log_file) if log_file else logging.NullHandler() + ] + ) + + +def validate_file_path(file_path: str, allowed_extensions: List[str] = None) -> bool: + """ + 验证文件路径的合法性 + + Args: + file_path: 文件路径 + allowed_extensions: 允许的文件扩展名列表（如['.pdf', '.docx']） + + Returns: + 文件是否合法 + """ + if not os.path.exists(file_path): + logger.error(f"文件不存在: {file_path}") + return False + + if not os.path.isfile(file_path): + logger.error(f"路径不是文件: {file_path}") + return False + + if allowed_extensions: + ext = Path(file_path).suffix.lower() + if ext not in allowed_extensions: + logger.error(f"不支持的文件格式: {ext}") + return False + + return True + + +def ensure_directory_exists(directory: str) -> bool: + """ + 确保目录存在，如果不存在则创建 + + Args: + directory: 目录路径 + + Returns: + 目录是否存在或创建成功 + """ + try: + Path(directory).mkdir(parents=True, exist_ok=True) + return True + except Exception as e: + logger.error(f"创建目录失败: {e}") + return False + + +def get_env_or_config(env_var: str, config_dict: Dict[str, Any], + default: Any = None) -> Any: + """ + 优先从环境变量读取，其次从配置字典读取 + + Args: + env_var: 环境变量名 + config_dict: 配置字典 + default: 默认值 + + Returns: + 获取到的值 + """ + # 尝试从环境变量读取 + env_value = os.environ.get(env_var) + if env_value: + return env_value + + # 尝试从配置字典读取 + config_value = config_dict.get(env_var) + if config_value and not config_value.startswith('${'): + return config_value + + return default