panda
2befd44430
Key resolutions: - agent/nodes.py: Merged session_id exclusion fix with new persistable fields (ocr_extraction_result, annotation_result, layout_schema, ocr_elements) - app.py: Adopted st-multimodal-chatinput for unified paste/drop/upload, removed custom JS paste bridge - backend/file_parser.py: Kept local XLSX parser, added remote XLS/DOC parsers - CLAUDE.md + CODE_GUIDE.md: Merged documentation from both branches Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
302 lines
9.8 KiB
Python
302 lines
9.8 KiB
Python
"""文件解析器：将上传文件转为文本，供 LLM 处理。
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支持:
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- 图片 (.png/.jpg/.jpeg/.bmp) → OCR 提取文本
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- PDF (.pdf) → 文本提取
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- Word (.docx) → 文本提取
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- 纯文本 (.txt/.csv/.json/.xml) → 直接读取
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策略选择:
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- 原生多模态: 模型支持图片时直接传文件（当前 MiniMax 不支持，自动退回文本转换）
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- 文本转换: 所有文件转为 UTF-8 文本后注入 prompt
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"""
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import os
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import io
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from pathlib import Path
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from typing import Optional
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import PIL.Image
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MODELS_WITH_VISION = {
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"gpt-4o", "gpt-4-turbo", "gpt-4-vision-preview",
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"claude-3", "claude-3.5", "claude-4",
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"gemini-1.5", "gemini-2",
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}
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def can_use_vision(model: str = "") -> bool:
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"""检查当前模型是否支持原生多模态（图片直接上传）。"""
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if not model:
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model = os.getenv("LLM_MODEL", "")
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return any(v in model.lower() for v in MODELS_WITH_VISION)
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def parse_file(file_path: str, file_type: str = "") -> dict:
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"""解析任意文件为文本。
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返回: {"text": str, "file_type": str, "method": str, "error": Optional[str]}
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"""
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path = Path(file_path)
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if not path.exists():
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return {"text": "", "file_type": file_type, "method": "none", "error": "文件不存在"}
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suffix = file_type or path.suffix.lower()
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parsers = {
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".png": _parse_image,
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".jpg": _parse_image,
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".jpeg": _parse_image,
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".bmp": _parse_image,
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".webp": _parse_image,
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".pdf": _parse_pdf,
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".docx": _parse_docx,
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".xlsx": _parse_xlsx,
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".xls": _parse_xls,
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".doc": _parse_doc,
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}
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parser = parsers.get(suffix)
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if parser:
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return parser(path)
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else:
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return _parse_text(path)
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# ---------------------------------------------------------------------------
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# 各类型解析器
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# ---------------------------------------------------------------------------
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def _parse_image(path: Path) -> dict:
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"""OCR 提取图片中的文字。优先 EasyOCR，回退 PaddleOCR。"""
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try:
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img = PIL.Image.open(path)
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info = f"[图片: {img.size[0]}x{img.size[1]}, {img.mode}]"
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except Exception:
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info = "[图片: 无法读取元数据]"
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# 优先 PaddleOCR（精确识别）
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try:
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from paddleocr import PaddleOCR
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ocr = PaddleOCR(lang="ch")
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result = ocr.ocr(str(path))
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lines = []
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if result and result[0]:
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for line in result[0]:
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text = line[1][0] if len(line) > 1 else ""
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if text.strip():
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lines.append(text.strip())
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if lines:
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return {
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"text": f"{info}\n识别文本:\n" + "\n".join(lines),
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"file_type": "image",
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"method": "paddleocr",
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"error": None,
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}
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except ImportError:
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pass
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except Exception:
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pass
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# 回退 EasyOCR
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try:
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import easyocr
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import numpy as np
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reader = easyocr.Reader(["ch_sim", "en"], gpu=False, verbose=False)
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result = reader.readtext(np.array(img))
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lines = [text.strip() for (_, text, _) in result if text.strip()]
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if lines:
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return {
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"text": f"{info}\n识别文本:\n" + "\n".join(lines),
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"file_type": "image",
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"method": "easyocr",
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"error": None,
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}
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except ImportError:
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pass
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except Exception:
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pass
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# OCR 不可用 → 返回图片元信息 + 安装提示
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return {
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"text": f"{info}\n(如需 OCR 文字识别，请安装: pip install easyocr)",
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"file_type": "image",
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"method": "metadata_only",
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"error": "OCR 引擎未安装，已返回图片元信息",
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}
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def _parse_pdf(path: Path) -> dict:
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"""提取 PDF 中的文本。"""
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try:
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import pdfplumber
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with pdfplumber.open(path) as pdf:
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pages = []
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for page in pdf.pages:
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text = page.extract_text()
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if text:
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pages.append(text)
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full = "\n\n".join(pages)
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return {
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"text": full,
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"file_type": "pdf",
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"method": "pdfplumber",
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"error": None,
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}
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except ImportError:
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pass
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except Exception as e:
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pass
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# Fallback: 尝试 PyMuPDF
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try:
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import fitz
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doc = fitz.open(path)
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pages = []
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for page in doc:
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pages.append(page.get_text())
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doc.close()
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return {
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"text": "\n\n".join(pages),
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"file_type": "pdf",
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"method": "pymupdf",
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"error": None,
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}
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except ImportError:
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pass
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except Exception:
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pass
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return {"text": "", "file_type": "pdf", "method": "none",
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"error": "PDF 解析需要安装 pdfplumber 或 PyMuPDF"}
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def _parse_docx(path: Path) -> dict:
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"""提取 Word 文档中的文本。"""
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try:
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from docx import Document
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doc = Document(path)
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paragraphs = [p.text for p in doc.paragraphs if p.text.strip()]
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# 同时提取表格内容
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for table in doc.tables:
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for row in table.rows:
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cells = [cell.text for cell in row.cells if cell.text.strip()]
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if cells:
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paragraphs.append(" | ".join(cells))
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return {
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"text": "\n\n".join(paragraphs),
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"file_type": "docx",
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"method": "python-docx",
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"error": None,
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}
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except ImportError:
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pass
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except Exception as e:
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pass
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return {"text": "", "file_type": "docx", "method": "none",
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"error": "DOCX 解析需要安装 python-docx"}
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def _parse_xlsx(path: Path) -> dict:
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"""提取 Excel .xlsx 文件中的文本。"""
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try:
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from openpyxl import load_workbook
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wb = load_workbook(path, read_only=True, data_only=True)
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parts = []
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for name in wb.sheetnames:
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ws = wb[name]
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rows = []
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for row in ws.iter_rows(values_only=True):
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cells = [str(c) if c is not None else "" for c in row]
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if any(c for c in cells):
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rows.append("\t".join(cells))
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if rows:
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parts.append(f"[Sheet: {name}]\n" + "\n".join(rows))
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wb.close()
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text = "\n\n".join(parts)
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return {"text": text, "file_type": "xlsx", "method": "openpyxl", "error": None}
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except ImportError:
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pass
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except Exception as e:
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return {"text": "", "file_type": "xlsx", "method": "none",
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"error": f"XLSX 解析失败: {e}"}
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return {"text": "", "file_type": "xlsx", "method": "none",
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"error": "XLSX 解析需要安装 openpyxl"}
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def _parse_xls(path: Path) -> dict:
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"""提取旧版 Excel .xls 文件中的文本。"""
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try:
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import xlrd
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wb = xlrd.open_workbook(path)
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parts = []
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for name in wb.sheet_names():
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ws = wb.sheet_by_name(name)
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rows = []
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for rx in range(ws.nrows):
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cells = [str(ws.cell_value(rx, cx)) if ws.cell_value(rx, cx) != "" else ""
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for cx in range(ws.ncols)]
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if any(c for c in cells):
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rows.append("\t".join(cells))
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if rows:
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parts.append(f"[Sheet: {name}]\n" + "\n".join(rows))
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text = "\n\n".join(parts)
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return {"text": text, "file_type": "xls", "method": "xlrd", "error": None}
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except ImportError:
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pass
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except Exception as e:
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return {"text": "", "file_type": "xls", "method": "none",
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"error": f"XLS 解析失败: {e}"}
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return {"text": "", "file_type": "xls", "method": "none",
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"error": "XLS 解析需要安装 xlrd"}
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def _parse_doc(path: Path) -> dict:
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"""提取旧版 Word .doc 文件中的文本（尽力而为，二进制格式）。"""
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try:
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import olefile
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ole = olefile.OleFileIO(path)
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if not ole.exists("WordDocument"):
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ole.close()
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return {"text": "", "file_type": "doc", "method": "none",
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"error": "不是有效的 .doc 文件"}
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raw = ole.openstream("WordDocument").read()
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ole.close()
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# 提取可打印 UTF-16LE 字符段
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text = ""
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try:
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decoded = raw.decode("utf-16-le", errors="ignore")
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text = "".join(c for c in decoded if c.isprintable() or c in "\n\r\t")
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except Exception:
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pass
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if not text.strip():
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return {"text": "", "file_type": "doc", "method": "olefile",
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"error": "无法提取文本（.doc 为二进制格式，建议转换为 .docx）"}
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return {"text": text.strip(), "file_type": "doc", "method": "olefile", "error": None}
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except ImportError:
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pass
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except Exception as e:
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return {"text": "", "file_type": "doc", "method": "none",
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"error": f"DOC 解析失败: {e}"}
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return {"text": "", "file_type": "doc", "method": "none",
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"error": "DOC 解析需要安装 olefile"}
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def _parse_text(path: Path) -> dict:
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"""读取纯文本文件。"""
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try:
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text = path.read_text(encoding="utf-8")
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return {"text": text, "file_type": path.suffix, "method": "direct", "error": None}
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except UnicodeDecodeError:
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try:
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text = path.read_text(encoding="gbk")
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return {"text": text, "file_type": path.suffix, "method": "direct_gbk", "error": None}
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except Exception:
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return {"text": "", "file_type": path.suffix, "method": "none",
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"error": "无法解码文件"}
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except Exception:
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return {"text": "", "file_type": path.suffix, "method": "none",
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"error": "读取失败"}
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