855 lines
30 KiB
Diff
855 lines
30 KiB
Diff
diff --git a/backend/app/api/endpoints/templates.py b/backend/app/api/endpoints/templates.py
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index 572d56e..706f281 100644
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--- a/backend/app/api/endpoints/templates.py
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+++ b/backend/app/api/endpoints/templates.py
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@@ -13,7 +13,7 @@ import pandas as pd
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from pydantic import BaseModel
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from app.services.template_fill_service import template_fill_service, TemplateField
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-from app.services.excel_storage_service import excel_storage_service
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+from app.services.file_service import file_service
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logger = logging.getLogger(__name__)
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@@ -28,13 +28,15 @@ class TemplateFieldRequest(BaseModel):
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name: str
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field_type: str = "text"
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required: bool = True
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+ hint: str = ""
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class FillRequest(BaseModel):
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"""填写请求"""
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template_id: str
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template_fields: List[TemplateFieldRequest]
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- source_doc_ids: Optional[List[str]] = None
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+ source_doc_ids: Optional[List[str]] = None # MongoDB 文档 ID 列表
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+ source_file_paths: Optional[List[str]] = None # 源文档文件路径列表
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user_hint: Optional[str] = None
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@@ -71,7 +73,6 @@ async def upload_template(
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try:
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# 保存文件
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- from app.services.file_service import file_service
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content = await file.read()
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saved_path = file_service.save_uploaded_file(
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content,
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@@ -87,7 +88,7 @@ async def upload_template(
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return {
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"success": True,
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- "template_id": saved_path, # 使用文件路径作为ID
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+ "template_id": saved_path,
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"filename": file.filename,
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"file_type": file_ext,
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"fields": [
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@@ -95,7 +96,8 @@ async def upload_template(
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"cell": f.cell,
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"name": f.name,
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"field_type": f.field_type,
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- "required": f.required
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+ "required": f.required,
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+ "hint": f.hint
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}
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for f in template_fields
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],
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@@ -135,7 +137,8 @@ async def extract_template_fields(
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"cell": f.cell,
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"name": f.name,
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"field_type": f.field_type,
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- "required": f.required
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+ "required": f.required,
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+ "hint": f.hint
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}
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for f in fields
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]
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@@ -153,7 +156,7 @@ async def fill_template(
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"""
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执行表格填写
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- 根据提供的字段定义，从已上传的文档中检索信息并填写
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+ 根据提供的字段定义，从源文档中检索信息并填写
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Args:
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request: 填写请求
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@@ -168,7 +171,8 @@ async def fill_template(
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cell=f.cell,
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name=f.name,
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field_type=f.field_type,
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- required=f.required
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+ required=f.required,
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+ hint=f.hint
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)
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for f in request.template_fields
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]
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@@ -177,6 +181,7 @@ async def fill_template(
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result = await template_fill_service.fill_template(
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template_fields=fields,
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source_doc_ids=request.source_doc_ids,
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+ source_file_paths=request.source_file_paths,
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user_hint=request.user_hint
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)
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@@ -194,6 +199,8 @@ async def export_filled_template(
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"""
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导出填写后的表格
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+ 支持 Excel (.xlsx) 和 Word (.docx) 格式
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+
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Args:
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request: 导出请求
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@@ -201,25 +208,124 @@ async def export_filled_template(
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文件流
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"""
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try:
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- # 创建 DataFrame
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- df = pd.DataFrame([request.filled_data])
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+ if request.format == "xlsx":
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+ return await _export_to_excel(request.filled_data, request.template_id)
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+ elif request.format == "docx":
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+ return await _export_to_word(request.filled_data, request.template_id)
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+ else:
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+ raise HTTPException(
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+ status_code=400,
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+ detail=f"不支持的导出格式: {request.format}，仅支持 xlsx/docx"
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+ )
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- # 导出为 Excel
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- output = io.BytesIO()
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- with pd.ExcelWriter(output, engine='openpyxl') as writer:
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- df.to_excel(writer, index=False, sheet_name='填写结果')
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+ except HTTPException:
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+ raise
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+ except Exception as e:
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+ logger.error(f"导出失败: {str(e)}")
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+ raise HTTPException(status_code=500, detail=f"导出失败: {str(e)}")
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- output.seek(0)
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- # 生成文件名
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- filename = f"filled_template.{request.format}"
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+async def _export_to_excel(filled_data: dict, template_id: str) -> StreamingResponse:
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+ """导出为 Excel 格式"""
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+ # 将字典转换为单行 DataFrame
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+ df = pd.DataFrame([filled_data])
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- return StreamingResponse(
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- io.BytesIO(output.getvalue()),
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- media_type="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
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- headers={"Content-Disposition": f"attachment; filename={filename}"}
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- )
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+ output = io.BytesIO()
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+ with pd.ExcelWriter(output, engine='openpyxl') as writer:
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+ df.to_excel(writer, index=False, sheet_name='填写结果')
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- except Exception as e:
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- logger.error(f"导出失败: {str(e)}")
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- raise HTTPException(status_code=500, detail=f"导出失败: {str(e)}")
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+ output.seek(0)
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+
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+ filename = f"filled_template.xlsx"
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+
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+ return StreamingResponse(
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+ io.BytesIO(output.getvalue()),
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+ media_type="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
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+ headers={"Content-Disposition": f"attachment; filename={filename}"}
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+ )
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+
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+
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+async def _export_to_word(filled_data: dict, template_id: str) -> StreamingResponse:
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+ """导出为 Word 格式"""
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+ from docx import Document
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+ from docx.shared import Pt, RGBColor
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+ from docx.enum.text import WD_ALIGN_PARAGRAPH
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+
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+ doc = Document()
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+
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+ # 添加标题
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+ title = doc.add_heading('填写结果', level=1)
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+ title.alignment = WD_ALIGN_PARAGRAPH.CENTER
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+
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+ # 添加填写时间和模板信息
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+ from datetime import datetime
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+ info_para = doc.add_paragraph()
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+ info_para.add_run(f"模板ID: {template_id}\n").bold = True
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+ info_para.add_run(f"导出时间: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
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+
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+ doc.add_paragraph() # 空行
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+
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+ # 添加字段表格
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+ table = doc.add_table(rows=1, cols=3)
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+ table.style = 'Light Grid Accent 1'
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+
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+ # 表头
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+ header_cells = table.rows[0].cells
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+ header_cells[0].text = '字段名'
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+ header_cells[1].text = '填写值'
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+ header_cells[2].text = '状态'
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+
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+ for field_name, field_value in filled_data.items():
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+ row_cells = table.add_row().cells
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+ row_cells[0].text = field_name
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+ row_cells[1].text = str(field_value) if field_value else ''
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+ row_cells[2].text = '已填写' if field_value else '为空'
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+
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+ # 保存到 BytesIO
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+ output = io.BytesIO()
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+ doc.save(output)
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+ output.seek(0)
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+
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+ filename = f"filled_template.docx"
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+
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+ return StreamingResponse(
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+ io.BytesIO(output.getvalue()),
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+ media_type="application/vnd.openxmlformats-officedocument.wordprocessingml.document",
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+ headers={"Content-Disposition": f"attachment; filename={filename}"}
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+ )
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+
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+
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+@router.post("/export/excel")
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+async def export_to_excel(
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+ filled_data: dict,
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+ template_id: str = Query(..., description="模板ID")
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+):
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+ """
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+ 专门导出为 Excel 格式
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+
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+ Args:
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+ filled_data: 填写数据
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+ template_id: 模板ID
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+
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+ Returns:
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+ Excel 文件流
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+ """
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+ return await _export_to_excel(filled_data, template_id)
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+
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+
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+@router.post("/export/word")
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+async def export_to_word(
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+ filled_data: dict,
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+ template_id: str = Query(..., description="模板ID")
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+):
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+ """
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+ 专门导出为 Word 格式
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+
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+ Args:
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+ filled_data: 填写数据
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+ template_id: 模板ID
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+
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+ Returns:
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+ Word 文件流
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+ """
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+ return await _export_to_word(filled_data, template_id)
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diff --git a/backend/app/core/document_parser/docx_parser.py b/backend/app/core/document_parser/docx_parser.py
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index 75e79da..03c341d 100644
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--- a/backend/app/core/document_parser/docx_parser.py
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+++ b/backend/app/core/document_parser/docx_parser.py
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@@ -161,3 +161,133 @@ class DocxParser(BaseParser):
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fields[field_name] = match.group(1)
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return fields
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+
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+ def parse_tables_for_template(
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+ self,
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+ file_path: str
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+ ) -> Dict[str, Any]:
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+ """
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+ 解析 Word 文档中的表格，提取模板字段
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+
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+ 专门用于比赛场景：解析表格模板，识别需要填写的字段
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+
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+ Args:
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+ file_path: Word 文件路径
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+
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+ Returns:
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+ 包含表格字段信息的字典
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+ """
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+ from docx import Document
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+ from docx.table import Table
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+ from docx.oxml.ns import qn
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+
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+ doc = Document(file_path)
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+
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+ template_info = {
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+ "tables": [],
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+ "fields": [],
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+ "field_count": 0
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+ }
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+
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+ for table_idx, table in enumerate(doc.tables):
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+ table_info = {
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+ "table_index": table_idx,
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+ "rows": [],
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+ "headers": [],
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+ "data_rows": [],
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+ "field_hints": {} # 字段名称 -> 提示词/描述
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+ }
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+
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+ # 提取表头（第一行）
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+ if table.rows:
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+ header_cells = [cell.text.strip() for cell in table.rows[0].cells]
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+ table_info["headers"] = header_cells
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+
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+ # 提取数据行
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+ for row_idx, row in enumerate(table.rows[1:], 1):
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+ row_data = [cell.text.strip() for cell in row.cells]
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+ table_info["data_rows"].append(row_data)
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+ table_info["rows"].append({
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+ "row_index": row_idx,
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+ "cells": row_data
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+ })
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+
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+ # 尝试从第二列/第三列提取提示词
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+ # 比赛模板通常格式为：字段名 | 提示词 | 填写值
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+ if len(table.rows[0].cells) >= 2:
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+ for row_idx, row in enumerate(table.rows[1:], 1):
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+ cells = [cell.text.strip() for cell in row.cells]
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+ if len(cells) >= 2 and cells[0]:
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+ # 第一列是字段名
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+ field_name = cells[0]
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+ # 第二列可能是提示词或描述
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+ hint = cells[1] if len(cells) > 1 else ""
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+ table_info["field_hints"][field_name] = hint
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+
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+ template_info["fields"].append({
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+ "table_index": table_idx,
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+ "row_index": row_idx,
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+ "field_name": field_name,
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+ "hint": hint,
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+ "expected_value": cells[2] if len(cells) > 2 else ""
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+ })
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+
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+ template_info["tables"].append(table_info)
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+
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+ template_info["field_count"] = len(template_info["fields"])
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+ return template_info
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+
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+ def extract_template_fields_from_docx(
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+ self,
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+ file_path: str
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+ ) -> List[Dict[str, Any]]:
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+ """
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+ 从 Word 文档中提取模板字段定义
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+
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+ 适用于比赛评分表格：表格第一列是字段名，第二列是提示词/填写示例
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+
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+ Args:
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+ file_path: Word 文件路径
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+
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+ Returns:
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+ 字段定义列表
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+ """
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+ template_info = self.parse_tables_for_template(file_path)
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+
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+ fields = []
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+ for field in template_info["fields"]:
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+ fields.append({
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+ "cell": f"T{field['table_index']}R{field['row_index']}", # TableXRowY 格式
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+ "name": field["field_name"],
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+ "hint": field["hint"],
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+ "table_index": field["table_index"],
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+ "row_index": field["row_index"],
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+ "field_type": self._infer_field_type_from_hint(field["hint"]),
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+ "required": True
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+ })
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+
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+ return fields
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+
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+ def _infer_field_type_from_hint(self, hint: str) -> str:
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+ """
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+ 从提示词推断字段类型
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+
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+ Args:
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+ hint: 字段提示词
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+
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+ Returns:
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+ 字段类型 (text/number/date)
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+ """
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+ hint_lower = hint.lower()
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+
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+ # 日期关键词
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+ date_keywords = ["年", "月", "日", "日期", "时间", "出生"]
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+ if any(kw in hint for kw in date_keywords):
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+ return "date"
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+
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+ # 数字关键词
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+ number_keywords = ["数量", "金额", "人数", "面积", "增长", "比率", "%", "率"]
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+ if any(kw in hint_lower for kw in number_keywords):
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+ return "number"
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+
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+ return "text"
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diff --git a/backend/app/services/template_fill_service.py b/backend/app/services/template_fill_service.py
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index 2612354..94930fb 100644
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--- a/backend/app/services/template_fill_service.py
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+++ b/backend/app/services/template_fill_service.py
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@@ -4,13 +4,12 @@
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从非结构化文档中检索信息并填写到表格模板
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"""
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import logging
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-from dataclasses import dataclass
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+from dataclasses import dataclass, field
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from typing import Any, Dict, List, Optional
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from app.core.database import mongodb
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-from app.services.rag_service import rag_service
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from app.services.llm_service import llm_service
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-from app.services.excel_storage_service import excel_storage_service
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+from app.core.document_parser import ParserFactory
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logger = logging.getLogger(__name__)
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@@ -22,6 +21,17 @@ class TemplateField:
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name: str # 字段名称
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field_type: str = "text" # 字段类型: text/number/date
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required: bool = True
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+ hint: str = "" # 字段提示词
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+
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+
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+@dataclass
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+class SourceDocument:
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+ """源文档"""
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+ doc_id: str
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+ filename: str
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+ doc_type: str
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+ content: str = ""
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+ structured_data: Dict[str, Any] = field(default_factory=dict)
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@dataclass
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@@ -38,12 +48,12 @@ class TemplateFillService:
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def __init__(self):
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self.llm = llm_service
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- self.rag = rag_service
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async def fill_template(
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self,
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template_fields: List[TemplateField],
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source_doc_ids: Optional[List[str]] = None,
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+ source_file_paths: Optional[List[str]] = None,
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user_hint: Optional[str] = None
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) -> Dict[str, Any]:
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"""
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@@ -51,7 +61,8 @@ class TemplateFillService:
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|
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Args:
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template_fields: 模板字段列表
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- source_doc_ids: 源文档ID列表，不指定则从所有文档检索
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+ source_doc_ids: 源文档 MongoDB ID 列表
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+ source_file_paths: 源文档文件路径列表
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user_hint: 用户提示（如"请从合同文档中提取"）
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Returns:
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@@ -60,28 +71,23 @@ class TemplateFillService:
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filled_data = {}
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fill_details = []
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+ # 1. 加载源文档内容
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+ source_docs = await self._load_source_documents(source_doc_ids, source_file_paths)
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+
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+ if not source_docs:
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+ logger.warning("没有找到源文档，填表结果将全部为空")
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+
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+ # 2. 对每个字段进行提取
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for field in template_fields:
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try:
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- # 1. 从 RAG 检索相关上下文
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- rag_results = await self._retrieve_context(field.name, user_hint)
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-
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- if not rag_results:
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- # 如果没有检索到结果，尝试直接询问 LLM
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- result = FillResult(
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- field=field.name,
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- value="",
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- source="未找到相关数据",
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- confidence=0.0
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||
- )
|
||
- else:
|
||
- # 2. 构建 Prompt 让 LLM 提取信息
|
||
- result = await self._extract_field_value(
|
||
- field=field,
|
||
- rag_context=rag_results,
|
||
- user_hint=user_hint
|
||
- )
|
||
-
|
||
- # 3. 存储结果
|
||
+ # 从源文档中提取字段值
|
||
+ result = await self._extract_field_value(
|
||
+ field=field,
|
||
+ source_docs=source_docs,
|
||
+ user_hint=user_hint
|
||
+ )
|
||
+
|
||
+ # 存储结果
|
||
filled_data[field.name] = result.value
|
||
fill_details.append({
|
||
"field": field.name,
|
||
@@ -107,75 +113,113 @@ class TemplateFillService:
|
||
return {
|
||
"success": True,
|
||
"filled_data": filled_data,
|
||
- "fill_details": fill_details
|
||
+ "fill_details": fill_details,
|
||
+ "source_doc_count": len(source_docs)
|
||
}
|
||
|
||
- async def _retrieve_context(
|
||
+ async def _load_source_documents(
|
||
self,
|
||
- field_name: str,
|
||
- user_hint: Optional[str] = None
|
||
- ) -> List[Dict[str, Any]]:
|
||
+ source_doc_ids: Optional[List[str]] = None,
|
||
+ source_file_paths: Optional[List[str]] = None
|
||
+ ) -> List[SourceDocument]:
|
||
"""
|
||
- 从 RAG 检索相关上下文
|
||
+ 加载源文档内容
|
||
|
||
Args:
|
||
- field_name: 字段名称
|
||
- user_hint: 用户提示
|
||
+ source_doc_ids: MongoDB 文档 ID 列表
|
||
+ source_file_paths: 源文档文件路径列表
|
||
|
||
Returns:
|
||
- 检索结果列表
|
||
+ 源文档列表
|
||
"""
|
||
- # 构建查询文本
|
||
- query = field_name
|
||
- if user_hint:
|
||
- query = f"{user_hint} {field_name}"
|
||
-
|
||
- # 检索相关文档片段
|
||
- results = self.rag.retrieve(query=query, top_k=5)
|
||
-
|
||
- return results
|
||
+ source_docs = []
|
||
+
|
||
+ # 1. 从 MongoDB 加载文档
|
||
+ if source_doc_ids:
|
||
+ for doc_id in source_doc_ids:
|
||
+ try:
|
||
+ doc = await mongodb.get_document(doc_id)
|
||
+ if doc:
|
||
+ source_docs.append(SourceDocument(
|
||
+ doc_id=doc_id,
|
||
+ filename=doc.get("metadata", {}).get("original_filename", "unknown"),
|
||
+ doc_type=doc.get("doc_type", "unknown"),
|
||
+ content=doc.get("content", ""),
|
||
+ structured_data=doc.get("structured_data", {})
|
||
+ ))
|
||
+ logger.info(f"从MongoDB加载文档: {doc_id}")
|
||
+ except Exception as e:
|
||
+ logger.error(f"从MongoDB加载文档失败 {doc_id}: {str(e)}")
|
||
+
|
||
+ # 2. 从文件路径加载文档
|
||
+ if source_file_paths:
|
||
+ for file_path in source_file_paths:
|
||
+ try:
|
||
+ parser = ParserFactory.get_parser(file_path)
|
||
+ result = parser.parse(file_path)
|
||
+ if result.success:
|
||
+ source_docs.append(SourceDocument(
|
||
+ doc_id=file_path,
|
||
+ filename=result.metadata.get("filename", file_path.split("/")[-1]),
|
||
+ doc_type=result.metadata.get("extension", "unknown").replace(".", ""),
|
||
+ content=result.data.get("content", ""),
|
||
+ structured_data=result.data.get("structured_data", {})
|
||
+ ))
|
||
+ logger.info(f"从文件加载文档: {file_path}")
|
||
+ except Exception as e:
|
||
+ logger.error(f"从文件加载文档失败 {file_path}: {str(e)}")
|
||
+
|
||
+ return source_docs
|
||
|
||
async def _extract_field_value(
|
||
self,
|
||
field: TemplateField,
|
||
- rag_context: List[Dict[str, Any]],
|
||
+ source_docs: List[SourceDocument],
|
||
user_hint: Optional[str] = None
|
||
) -> FillResult:
|
||
"""
|
||
- 使用 LLM 从上下文中提取字段值
|
||
+ 使用 LLM 从源文档中提取字段值
|
||
|
||
Args:
|
||
field: 字段定义
|
||
- rag_context: RAG 检索到的上下文
|
||
+ source_docs: 源文档列表
|
||
user_hint: 用户提示
|
||
|
||
Returns:
|
||
提取结果
|
||
"""
|
||
+ if not source_docs:
|
||
+ return FillResult(
|
||
+ field=field.name,
|
||
+ value="",
|
||
+ source="无源文档",
|
||
+ confidence=0.0
|
||
+ )
|
||
+
|
||
# 构建上下文文本
|
||
- context_text = "\n\n".join([
|
||
- f"【文档 {i+1}】\n{doc['content']}"
|
||
- for i, doc in enumerate(rag_context)
|
||
- ])
|
||
+ context_text = self._build_context_text(source_docs, max_length=8000)
|
||
+
|
||
+ # 构建提示词
|
||
+ hint_text = field.hint if field.hint else f"请提取{field.name}的信息"
|
||
+ if user_hint:
|
||
+ hint_text = f"{user_hint}。{hint_text}"
|
||
|
||
- # 构建 Prompt
|
||
- prompt = f"""你是一个数据提取专家。请根据以下文档内容，提取指定字段的信息。
|
||
+ prompt = f"""你是一个专业的数据提取专家。请根据以下文档内容，提取指定字段的信息。
|
||
|
||
需要提取的字段：
|
||
- 字段名称：{field.name}
|
||
- 字段类型：{field.field_type}
|
||
+- 填写提示：{hint_text}
|
||
- 是否必填：{'是' if field.required else '否'}
|
||
|
||
-{'用户提示：' + user_hint if user_hint else ''}
|
||
-
|
||
参考文档内容：
|
||
{context_text}
|
||
|
||
请严格按照以下 JSON 格式输出，不要添加任何解释：
|
||
{{
|
||
"value": "提取到的值，如果没有找到则填写空字符串",
|
||
- "source": "数据来源的文档描述",
|
||
- "confidence": 0.0到1.0之间的置信度
|
||
+ "source": "数据来源的文档描述（如：来自xxx文档）",
|
||
+ "confidence": 0.0到1.0之间的置信度，表示对提取结果的信心程度"
|
||
}}
|
||
"""
|
||
|
||
@@ -226,6 +270,54 @@ class TemplateFillService:
|
||
confidence=0.0
|
||
)
|
||
|
||
+ def _build_context_text(self, source_docs: List[SourceDocument], max_length: int = 8000) -> str:
|
||
+ """
|
||
+ 构建上下文文本
|
||
+
|
||
+ Args:
|
||
+ source_docs: 源文档列表
|
||
+ max_length: 最大字符数
|
||
+
|
||
+ Returns:
|
||
+ 上下文文本
|
||
+ """
|
||
+ contexts = []
|
||
+ total_length = 0
|
||
+
|
||
+ for doc in source_docs:
|
||
+ # 优先使用结构化数据（表格），其次使用文本内容
|
||
+ doc_content = ""
|
||
+
|
||
+ if doc.structured_data and doc.structured_data.get("tables"):
|
||
+ # 如果有表格数据，优先使用
|
||
+ tables = doc.structured_data.get("tables", [])
|
||
+ for table in tables:
|
||
+ if isinstance(table, dict):
|
||
+ rows = table.get("rows", [])
|
||
+ if rows:
|
||
+ doc_content += f"\n【文档: {doc.filename} 表格数据】\n"
|
||
+ for row in rows[:20]: # 限制每表最多20行
|
||
+ if isinstance(row, list):
|
||
+ doc_content += " | ".join(str(cell) for cell in row) + "\n"
|
||
+ elif isinstance(row, dict):
|
||
+ doc_content += " | ".join(str(v) for v in row.values()) + "\n"
|
||
+ elif doc.content:
|
||
+ doc_content = doc.content[:5000] # 限制文本长度
|
||
+
|
||
+ if doc_content:
|
||
+ doc_context = f"【文档: {doc.filename} ({doc.doc_type})】\n{doc_content}"
|
||
+ if total_length + len(doc_context) <= max_length:
|
||
+ contexts.append(doc_context)
|
||
+ total_length += len(doc_context)
|
||
+ else:
|
||
+ # 如果超出长度，截断
|
||
+ remaining = max_length - total_length
|
||
+ if remaining > 100:
|
||
+ contexts.append(doc_context[:remaining])
|
||
+ break
|
||
+
|
||
+ return "\n\n".join(contexts) if contexts else "（源文档内容为空）"
|
||
+
|
||
async def get_template_fields_from_file(
|
||
self,
|
||
file_path: str,
|
||
@@ -236,7 +328,7 @@ class TemplateFillService:
|
||
|
||
Args:
|
||
file_path: 模板文件路径
|
||
- file_type: 文件类型
|
||
+ file_type: 文件类型 (xlsx/xls/docx)
|
||
|
||
Returns:
|
||
字段列表
|
||
@@ -245,43 +337,108 @@ class TemplateFillService:
|
||
|
||
try:
|
||
if file_type in ["xlsx", "xls"]:
|
||
- # 从 Excel 读取表头
|
||
- import pandas as pd
|
||
- df = pd.read_excel(file_path, nrows=5)
|
||
+ fields = await self._get_template_fields_from_excel(file_path)
|
||
+ elif file_type == "docx":
|
||
+ fields = await self._get_template_fields_from_docx(file_path)
|
||
|
||
- for idx, col in enumerate(df.columns):
|
||
- # 获取单元格位置 (A, B, C, ...)
|
||
- cell = self._column_to_cell(idx)
|
||
+ except Exception as e:
|
||
+ logger.error(f"提取模板字段失败: {str(e)}")
|
||
|
||
- fields.append(TemplateField(
|
||
- cell=cell,
|
||
- name=str(col),
|
||
- field_type=self._infer_field_type(df[col]),
|
||
- required=True
|
||
- ))
|
||
+ return fields
|
||
|
||
- elif file_type == "docx":
|
||
- # 从 Word 表格读取
|
||
- from docx import Document
|
||
- doc = Document(file_path)
|
||
-
|
||
- for table_idx, table in enumerate(doc.tables):
|
||
- for row_idx, row in enumerate(table.rows):
|
||
- for col_idx, cell in enumerate(row.cells):
|
||
- cell_text = cell.text.strip()
|
||
- if cell_text:
|
||
- fields.append(TemplateField(
|
||
- cell=self._column_to_cell(col_idx),
|
||
- name=cell_text,
|
||
- field_type="text",
|
||
- required=True
|
||
- ))
|
||
+ async def _get_template_fields_from_excel(self, file_path: str) -> List[TemplateField]:
|
||
+ """从 Excel 模板提取字段"""
|
||
+ fields = []
|
||
+
|
||
+ try:
|
||
+ import pandas as pd
|
||
+ df = pd.read_excel(file_path, nrows=5)
|
||
+
|
||
+ for idx, col in enumerate(df.columns):
|
||
+ cell = self._column_to_cell(idx)
|
||
+ col_str = str(col)
|
||
+
|
||
+ fields.append(TemplateField(
|
||
+ cell=cell,
|
||
+ name=col_str,
|
||
+ field_type=self._infer_field_type_from_value(df[col].iloc[0] if len(df) > 0 else ""),
|
||
+ required=True,
|
||
+ hint=""
|
||
+ ))
|
||
|
||
except Exception as e:
|
||
- logger.error(f"提取模板字段失败: {str(e)}")
|
||
+ logger.error(f"从Excel提取字段失败: {str(e)}")
|
||
|
||
return fields
|
||
|
||
+ async def _get_template_fields_from_docx(self, file_path: str) -> List[TemplateField]:
|
||
+ """从 Word 模板提取字段"""
|
||
+ fields = []
|
||
+
|
||
+ try:
|
||
+ from docx import Document
|
||
+
|
||
+ doc = Document(file_path)
|
||
+
|
||
+ for table_idx, table in enumerate(doc.tables):
|
||
+ for row_idx, row in enumerate(table.rows):
|
||
+ cells = [cell.text.strip() for cell in row.cells]
|
||
+
|
||
+ # 假设第一列是字段名
|
||
+ if cells and cells[0]:
|
||
+ field_name = cells[0]
|
||
+ hint = cells[1] if len(cells) > 1 else ""
|
||
+
|
||
+ # 跳过空行或标题行
|
||
+ if field_name and field_name not in ["", "字段名", "名称", "项目"]:
|
||
+ fields.append(TemplateField(
|
||
+ cell=f"T{table_idx}R{row_idx}",
|
||
+ name=field_name,
|
||
+ field_type=self._infer_field_type_from_hint(hint),
|
||
+ required=True,
|
||
+ hint=hint
|
||
+ ))
|
||
+
|
||
+ except Exception as e:
|
||
+ logger.error(f"从Word提取字段失败: {str(e)}")
|
||
+
|
||
+ return fields
|
||
+
|
||
+ def _infer_field_type_from_hint(self, hint: str) -> str:
|
||
+ """从提示词推断字段类型"""
|
||
+ hint_lower = hint.lower()
|
||
+
|
||
+ date_keywords = ["年", "月", "日", "日期", "时间", "出生"]
|
||
+ if any(kw in hint for kw in date_keywords):
|
||
+ return "date"
|
||
+
|
||
+ number_keywords = ["数量", "金额", "人数", "面积", "增长", "比率", "%", "率", "总计", "合计"]
|
||
+ if any(kw in hint_lower for kw in number_keywords):
|
||
+ return "number"
|
||
+
|
||
+ return "text"
|
||
+
|
||
+ def _infer_field_type_from_value(self, value: Any) -> str:
|
||
+ """从示例值推断字段类型"""
|
||
+ if value is None or value == "":
|
||
+ return "text"
|
||
+
|
||
+ value_str = str(value)
|
||
+
|
||
+ # 检查日期模式
|
||
+ import re
|
||
+ if re.search(r'\d{4}[年/-]\d{1,2}[月/-]\d{1,2}', value_str):
|
||
+ return "date"
|
||
+
|
||
+ # 检查数值
|
||
+ try:
|
||
+ float(value_str.replace(',', '').replace('%', ''))
|
||
+ return "number"
|
||
+ except ValueError:
|
||
+ pass
|
||
+
|
||
+ return "text"
|
||
+
|
||
def _column_to_cell(self, col_idx: int) -> str:
|
||
"""将列索引转换为单元格列名 (0 -> A, 1 -> B, ...)"""
|
||
result = ""
|
||
@@ -290,17 +447,6 @@ class TemplateFillService:
|
||
col_idx = col_idx // 26 - 1
|
||
return result
|
||
|
||
- def _infer_field_type(self, series) -> str:
|
||
- """推断字段类型"""
|
||
- import pandas as pd
|
||
-
|
||
- if pd.api.types.is_numeric_dtype(series):
|
||
- return "number"
|
||
- elif pd.api.types.is_datetime64_any_dtype(series):
|
||
- return "date"
|
||
- else:
|
||
- return "text"
|
||
-
|
||
|
||
# ==================== 全局单例 ====================
|
||
|