feat: 实现智能指令的格式转换和文档编辑功能

主要更新:
- 新增 transform 意图:支持 Word/Excel/Markdown 格式互转
- 新增 edit 意图:使用 LLM 润色编辑文档内容
- 智能指令接口增加异步执行模式(async_execute 参数)
- 修复 Word 模板导出文档损坏问题(改用临时文件方式)
- 优化 intent_parser 增加 transform/edit 关键词识别

新增文件:
- app/api/endpoints/instruction.py: 智能指令 API 端点
- app/services/multi_doc_reasoning_service.py: 多文档推理服务

其他优化:
- RAG 服务混合搜索(BM25 + 向量)融合
- 模板填充服务表头匹配增强
- Word AI 解析服务返回结构完善
- 前端 InstructionChat 组件对接真实 API
This commit is contained in:
dj
2026-04-14 20:39:37 +08:00
parent 51350e3002
commit ecad9ccd82
12 changed files with 2943 additions and 196 deletions

View File

@@ -2,17 +2,51 @@
意图解析器模块
解析用户自然语言指令,识别意图和参数
注意: 此模块为可选功能,当前尚未实现。
"""
from abc import ABC, abstractmethod
from typing import Any, Dict, Tuple
import re
import logging
from typing import Any, Dict, List, Optional, Tuple
logger = logging.getLogger(__name__)
class IntentParser(ABC):
"""意图解析器抽象基类"""
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", ""],
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}", 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]] = []
@abstractmethod
async def parse(self, text: str) -> Tuple[str, Dict[str, Any]]:
"""
解析自然语言指令
@@ -23,12 +57,186 @@ class IntentParser(ABC):
Returns:
(意图类型, 参数字典)
"""
pass
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 = []
class DefaultIntentParser(IntentParser):
"""默认意图解析器"""
async def parse(self, text: str) -> Tuple[str, Dict[str, Any]]:
"""暂未实现"""
raise NotImplementedError("意图解析功能暂未实现")
# 全局单例
intent_parser = IntentParser()