""" 意图解析器模块 解析用户自然语言指令，识别意图和参数 """ import re import logging from typing import Any, Dict, List, Optional, Tuple logger = logging.getLogger(__name__) class IntentParser: """意图解析器""" # 意图类型定义 INTENT_EXTRACT = "extract" # 信息提取 INTENT_FILL_TABLE = "fill_table" # 填表 INTENT_SUMMARIZE = "summarize" # 摘要总结 INTENT_QUESTION = "question" # 问答 INTENT_SEARCH = "search" # 搜索 INTENT_COMPARE = "compare" # 对比分析 INTENT_TRANSFORM = "transform" # 格式转换 INTENT_EDIT = "edit" # 编辑文档 INTENT_UNKNOWN = "unknown" # 未知 # 意图关键词映射 INTENT_KEYWORDS = { INTENT_EXTRACT: ["提取", "抽取", "获取", "找出", "查找", "识别", "找到"], INTENT_FILL_TABLE: ["填表", "填写", "填充", "录入", "导入到表格", "填写到"], INTENT_SUMMARIZE: ["总结", "摘要", "概括", "概述", "归纳", "提炼"], INTENT_QUESTION: ["问答", "回答", "解释", "什么是", "为什么", "如何", "怎样", "多少", "几个"], INTENT_SEARCH: ["搜索", "查找", "检索", "查询", "找"], INTENT_COMPARE: ["对比", "比较", "差异", "区别", "不同"], INTENT_TRANSFORM: ["转换", "转化", "变成", "转为", "导出"], INTENT_EDIT: ["修改", "编辑", "调整", "改写", "润色", "优化"], } # 实体模式定义 ENTITY_PATTERNS = { "number": [r"\d+", r"[一二三四五六七八九十百千万]+"], "date": [r"\d{4}年", r"\d{1,2}月", r"\d{1,2}日"], "percentage": [r"\d+(\.\d+)?%", r"\d+(\.\d+)?‰"], "currency": [r"\d+(\.\d+)?万元", r"\d+(\.\d+)?亿元", r"\d+(\.\d+)?元"], } def __init__(self): self.intent_history: List[Dict[str, Any]] = [] async def parse(self, text: str) -> Tuple[str, Dict[str, Any]]: """ 解析自然语言指令 Args: text: 用户输入的自然语言 Returns: (意图类型, 参数字典) """ text = text.strip() if not text: return self.INTENT_UNKNOWN, {} # 记录历史 self.intent_history.append({"text": text, "intent": None}) # 识别意图 intent = self._recognize_intent(text) # 提取参数 params = self._extract_params(text, intent) # 更新历史 if self.intent_history: self.intent_history[-1]["intent"] = intent logger.info(f"意图解析: text={text[:50]}..., intent={intent}, params={params}") return intent, params def _recognize_intent(self, text: str) -> str: """识别意图类型""" intent_scores: Dict[str, float] = {} for intent, keywords in self.INTENT_KEYWORDS.items(): score = 0 for keyword in keywords: if keyword in text: score += 1 if score > 0: intent_scores[intent] = score if not intent_scores: return self.INTENT_UNKNOWN # 返回得分最高的意图 return max(intent_scores, key=intent_scores.get) def _extract_params(self, text: str, intent: str) -> Dict[str, Any]: """提取参数""" params: Dict[str, Any] = { "entities": self._extract_entities(text), "document_refs": self._extract_document_refs(text), "field_refs": self._extract_field_refs(text), "template_refs": self._extract_template_refs(text), } # 根据意图类型提取特定参数 if intent == self.INTENT_QUESTION: params["question"] = text params["focus"] = self._extract_question_focus(text) elif intent == self.INTENT_FILL_TABLE: params["template"] = self._extract_template_info(text) elif intent == self.INTENT_EXTRACT: params["target_fields"] = self._extract_target_fields(text) return params def _extract_entities(self, text: str) -> Dict[str, List[str]]: """提取实体""" entities: Dict[str, List[str]] = {} for entity_type, patterns in self.ENTITY_PATTERNS.items(): matches = [] for pattern in patterns: found = re.findall(pattern, text) matches.extend(found) if matches: entities[entity_type] = list(set(matches)) return entities def _extract_document_refs(self, text: str) -> List[str]: """提取文档引用""" # 匹配 "文档1"、"doc1"、"第一个文档" 等 refs = [] # 数字索引: 文档1, doc1, 第1个文档 num_patterns = [ r"[文档doc]+(\d+)", r"第(\d+)个文档", r"第(\d+)份", ] for pattern in num_patterns: matches = re.findall(pattern, text.lower()) refs.extend([f"doc_{m}" for m in matches]) # "所有文档"、"全部文档" if any(kw in text for kw in ["所有", "全部", "整个"]): refs.append("all_docs") return refs def _extract_field_refs(self, text: str) -> List[str]: """提取字段引用""" fields = [] # 匹配引号内的字段名 quoted = re.findall(r"['\"『「]([^'\"』」]+)['\"』」]", text) fields.extend(quoted) # 匹配 "xxx字段"、"xxx列" 等 field_patterns = [ r"([^\s]+)字段", r"([^\s]+)列", r"([^\s]+)数据", ] for pattern in field_patterns: matches = re.findall(pattern, text) fields.extend(matches) return list(set(fields)) def _extract_template_refs(self, text: str) -> List[str]: """提取模板引用""" templates = [] # 匹配 "表格模板"、"Excel模板"、"表1" 等 template_patterns = [ r"([^\s]+模板)", r"表(\d+)", r"([^\s]+表格)", ] for pattern in template_patterns: matches = re.findall(pattern, text) templates.extend(matches) return list(set(templates)) def _extract_question_focus(self, text: str) -> Optional[str]: """提取问题焦点""" # "什么是XXX"、"XXX是什么" match = re.search(r"[什么是]([^?]+)", text) if match: return match.group(1).strip() # "XXX有多少" match = re.search(r"([^?]+)有多少", text) if match: return match.group(1).strip() return None def _extract_template_info(self, text: str) -> Optional[Dict[str, str]]: """提取模板信息""" template_info: Dict[str, str] = {} # 提取模板类型 if "excel" in text.lower() or "xlsx" in text.lower() or "电子表格" in text: template_info["type"] = "xlsx" elif "word" in text.lower() or "docx" in text.lower() or "文档" in text: template_info["type"] = "docx" return template_info if template_info else None def _extract_target_fields(self, text: str) -> List[str]: """提取目标字段""" fields = [] # 匹配 "提取XXX和YYY"、"抽取XXX、YYY" patterns = [ r"提取([^(and|,|，)+]+?)(?:和|与|、|,|plus)", r"抽取([^(and|,|，)+]+?)(?:和|与|、|,|plus)", ] for pattern in patterns: matches = re.findall(pattern, text) fields.extend([m.strip() for m in matches if m.strip()]) return list(set(fields)) def get_intent_history(self) -> List[Dict[str, Any]]: """获取意图历史""" return self.intent_history def clear_history(self): """清空历史""" self.intent_history = [] # 全局单例 intent_parser = IntentParser()