feat(parsing): 使用 docling 处理 docx/xlsx/pptx #439
This commit is contained in:
Wenjie Zhang
parent
e7c078310e
commit
22921fdec7
@ -37,7 +37,6 @@ dependencies = [
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"pyjwt>=2.8.0",
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"pymilvus>=2.5.8",
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"pymupdf>=1.25.5",
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"python-docx>=1.2.0",
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"python-dotenv>=1.1.0",
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"python-jose[cryptography]>=3.4.0",
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"python-multipart>=0.0.20",
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@ -64,7 +63,7 @@ dependencies = [
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"chardet>=5.0.0",
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"deepagents>=0.2.5",
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"json-repair>=0.54.0",
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"openpyxl>=3.1.5",
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"docling>=2.68.0",
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]
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[tool.ruff]
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line-length = 120 # 代码最大行宽
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@ -1,11 +1,13 @@
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import asyncio
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import base64
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import os
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import re
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import xml.etree.ElementTree as ET
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import zipfile
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from pathlib import Path
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import aiofiles
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from docling.document_converter import DocumentConverter
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from docling.datamodel.base_models import InputFormat
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from langchain_community.document_loaders import (
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CSVLoader,
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JSONLoader,
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@ -32,6 +34,7 @@ SUPPORTED_FILE_EXTENSIONS: tuple[str, ...] = (
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".xls",
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".xlsx",
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".pdf",
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".pptx",
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".jpg",
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".jpeg",
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".png",
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@ -47,150 +50,117 @@ def is_supported_file_extension(file_name: str | os.PathLike[str]) -> bool:
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return Path(file_name).suffix.lower() in SUPPORTED_FILE_EXTENSIONS
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def _make_unique_columns(columns: list) -> list:
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# Docling 文档转换器（单例模式）
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_docling_converter: DocumentConverter | None = None
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def _get_docling_converter() -> DocumentConverter:
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"""获取 Docling 文档转换器单例"""
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global _docling_converter
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if _docling_converter is None:
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_docling_converter = DocumentConverter(
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format_options={
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InputFormat.DOCX: None,
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InputFormat.XLSX: None,
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InputFormat.PPTX: None,
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}
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)
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return _docling_converter
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def _upload_image_to_minio(image_data: bytes, filename: str, db_id: str) -> str:
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"""上传图片到 MinIO，返回 URL"""
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minio_client = get_minio_client()
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minio_client.ensure_bucket_exists("kb-images")
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file_id = hashstr(filename, length=16)
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object_name = f"{db_id}/{file_id}/images/{Path(filename).name}"
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suffix = Path(filename).suffix.lower()
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content_type_map = {
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".jpg": "image/jpeg",
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".jpeg": "image/jpeg",
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".png": "image/png",
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".gif": "image/gif",
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".webp": "image/webp",
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".bmp": "image/bmp",
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".tif": "image/tiff",
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".tiff": "image/tiff",
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}
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content_type = content_type_map.get(suffix, "image/jpeg")
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result = minio_client.upload_file(
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bucket_name="kb-images",
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object_name=object_name,
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data=image_data,
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content_type=content_type,
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)
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return result.url
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def _parse_data_uri(data_uri: str) -> tuple[bytes, str]:
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"""解析 data URI，返回 (image_data, mime_type)"""
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header, base64_data = data_uri.split(",", 1)
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mime_type = header.split(":")[1].split(";")[0]
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image_data = base64.b64decode(base64_data)
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return image_data, mime_type
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def _convert_with_docling(file_path: Path, params: dict | None = None) -> str:
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"""
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处理重复的列名,给重复的列添加数字后缀
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使用 Docling 将 docx/xlsx/pptx 转换为 Markdown
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Args:
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columns: 原始列名列表
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file_path: 文件路径
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params: 参数，包含 db_id 用于图片上传
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Returns:
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处理后的唯一列名列表
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Example:
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['A', 'B', 'A', 'C', 'B'] -> ['A', 'B', 'A_2', 'C', 'B_2']
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Markdown 字符串
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"""
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if not columns:
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return columns
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seen = {}
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unique_columns = []
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for col in columns:
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# 处理 None 或空值
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if col is None or (isinstance(col, str) and not col.strip()):
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col = "Unnamed"
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# 转换为字符串
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col_str = str(col)
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# 如果这个列名已经出现过
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if col_str in seen:
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seen[col_str] += 1
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# 添加后缀
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unique_col = f"{col_str}_{seen[col_str]}"
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unique_columns.append(unique_col)
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else:
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# 第一次出现
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seen[col_str] = 1
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unique_columns.append(col_str)
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return unique_columns
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def _extract_word_text(file_path: Path) -> str:
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"""
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Parse Word documents (.doc/.docx) into plain text.
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Try python-docx first for docx files and fall back to the unstructured
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loader so legacy .doc files are still parsed when possible.
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"""
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try:
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from docx import Document # type: ignore
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doc = Document(file_path)
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text = "\n".join(paragraph.text for paragraph in doc.paragraphs).strip()
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if text:
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return text
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except Exception as docx_error: # noqa: BLE001
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logger.warning(f"python-docx failed to parse {file_path.name}: {docx_error}")
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try:
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loader = UnstructuredWordDocumentLoader(str(file_path))
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docs = loader.load()
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return "\n".join(doc.page_content for doc in docs).strip()
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except Exception as unstructured_error: # noqa: BLE001
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logger.error(f"Unstructured failed to parse {file_path.name}: {unstructured_error}")
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raise ValueError(f"无法解析 Word 文档: {file_path.name}") from unstructured_error
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def _extract_docx_markdown_with_images(file_path: Path, params: dict | None = None) -> str:
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params = params or {}
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db_id = params.get("db_id") or "word-docs"
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minio_client = get_minio_client()
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bucket_name = "kb-images"
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minio_client.ensure_bucket_exists(bucket_name)
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file_id = hashstr(file_path.name, length=16)
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db_id = params.get("db_id") or "docling-docs"
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with zipfile.ZipFile(file_path, "r") as zf:
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rels_path = "word/_rels/document.xml.rels"
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rid_to_target: dict[str, str] = {}
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try:
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rels_xml = zf.read(rels_path).decode("utf-8")
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rels_root = ET.fromstring(rels_xml)
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for rel in list(rels_root):
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rid = rel.attrib.get("Id")
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target = rel.attrib.get("Target")
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rtype = rel.attrib.get("Type")
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if rid and target and rtype and rtype.endswith("/image"):
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rid_to_target[rid] = target
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except Exception:
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rid_to_target = {}
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converter = _get_docling_converter()
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result = converter.convert(file_path)
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doc_xml = zf.read("word/document.xml").decode("utf-8")
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ns = {
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"w": "http://schemas.openxmlformats.org/wordprocessingml/2006/main",
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"a": "http://schemas.openxmlformats.org/drawingml/2006/main",
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"r": "http://schemas.openxmlformats.org/officeDocument/2006/relationships",
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}
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root = ET.fromstring(doc_xml)
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md_lines: list[str] = []
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if result.status.name != "SUCCESS":
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raise RuntimeError(f"Docling 转换失败: {result.status}")
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for p in root.findall(".//w:p", ns):
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texts = [t.text or "" for t in p.findall(".//w:t", ns)]
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para_text = "".join(texts).strip()
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image_urls: list[tuple[str, str]] = []
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doc = result.document
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for blip in p.findall(".//a:blip", ns):
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rid = blip.attrib.get(f"{{{ns['r']}}}embed")
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if not rid:
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continue
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target = rid_to_target.get(rid)
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if not target:
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continue
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media_path = target if target.startswith("word/") else f"word/{target}"
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try:
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data = zf.read(media_path)
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object_name = f"{db_id}/{file_id}/images/{Path(target).name}"
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suffix = Path(target).suffix.lower()
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content_type = {
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".jpg": "image/jpeg",
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".jpeg": "image/jpeg",
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".png": "image/png",
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".gif": "image/gif",
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".webp": "image/webp",
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".bmp": "image/bmp",
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".tif": "image/tiff",
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".tiff": "image/tiff",
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}.get(suffix, "image/jpeg")
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result = minio_client.upload_file(
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bucket_name=bucket_name,
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object_name=object_name,
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data=data,
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content_type=content_type,
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)
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image_urls.append((Path(target).name, result.url))
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except Exception as e:
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logger.error(f"上传图片失败 {Path(target).name}: {e}")
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continue
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# 提取图片并上传到 MinIO
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if hasattr(doc, "pictures") and doc.pictures:
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image_refs: list[tuple[str, bytes]] = []
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line = para_text
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for name, url in image_urls:
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line = f"{line}\n"
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if line:
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md_lines.append(line)
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for pic in doc.pictures:
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if hasattr(pic, "image") and hasattr(pic.image, "uri"):
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uri = str(pic.image.uri)
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if uri.startswith("data:"):
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image_data, mime_type = _parse_data_uri(uri)
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filename = f"image_{len(image_refs)}.{mime_type.split('/')[-1]}"
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image_refs.append((filename, image_data))
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return "\n\n".join(md_lines)
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# 上传图片并收集 URL
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image_urls: list[str] = []
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for filename, image_data in image_refs:
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try:
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url = _upload_image_to_minio(image_data, filename, db_id)
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image_urls.append(f"")
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except Exception as e:
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logger.error(f"上传图片失败 {filename}: {e}")
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image_urls.append(f"[图片: {filename}]")
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# 导出 Markdown
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markdown = doc.export_to_markdown()
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# 替换 <!-- image --> 占位符为图片 URL
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# Docling 使用 <!-- image --> 作为占位符
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for url in reversed(image_urls):
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markdown = re.sub(r"<!--\s*image\s*-->", url, markdown, count=1)
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return markdown
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# 无图片时直接导出
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return doc.export_to_markdown()
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def chunk_with_parser(file_path, params=None):
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@ -470,13 +440,17 @@ async def process_file_to_markdown(file_path: str, params: dict | None = None) -
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content = f.read()
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result = f"{content}"
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elif file_ext == ".docx":
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text = _extract_docx_markdown_with_images(file_path_obj, params=params)
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result = "" + text
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elif file_ext in [".docx", ".pptx"]:
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# 使用 Docling 处理 docx 和 pptx
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result = _convert_with_docling(file_path_obj, params=params)
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elif file_ext == ".doc":
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text = _extract_word_text(file_path_obj)
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result = f"{text}"
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# 旧版 .doc 文件仍使用原有解析方式
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from langchain_community.document_loaders import UnstructuredWordDocumentLoader
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loader = UnstructuredWordDocumentLoader(str(file_path_obj))
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docs = loader.load()
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result = "\n".join(doc.page_content for doc in docs).strip()
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elif file_ext in [".jpg", ".jpeg", ".png", ".bmp", ".tiff", ".tif"]:
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# 使用 OCR 处理图片
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@ -509,71 +483,8 @@ async def process_file_to_markdown(file_path: str, params: dict | None = None) -
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result = markdown_content.strip()
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elif file_ext in [".xls", ".xlsx"]:
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# 处理 Excel 文件
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import pandas as pd
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from openpyxl import load_workbook
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markdown_content = ""
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# 使用 openpyxl 加载工作簿以正确处理合并单元格
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wb = load_workbook(file_path_obj, data_only=True)
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for sheet_name in wb.sheetnames:
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ws = wb[sheet_name]
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# 先取消所有合并单元格，并填充值
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merged_ranges = list(ws.merged_cells.ranges)
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for merged_range in merged_ranges:
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# 获取合并区域左上角单元格的值
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min_row, min_col, max_row, max_col = (
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merged_range.min_row,
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merged_range.min_col,
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merged_range.max_row,
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merged_range.max_col,
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)
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# 获取左上角单元格的值
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top_left_value = ws.cell(row=min_row, column=min_col).value
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# 取消合并
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ws.unmerge_cells(start_row=min_row, start_column=min_col, end_row=max_row, end_column=max_col)
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# 在所有原合并单元格区域填充值
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for row in range(min_row, max_row + 1):
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for col in range(min_col, max_col + 1):
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ws.cell(row=row, column=col).value = top_left_value
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# 转换为DataFrame
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data = []
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for row in ws.iter_rows(values_only=True):
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data.append(row)
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# 第一行作为列名
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columns = data[0] if data else []
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df_data = data[1:] if len(data) > 1 else []
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# 处理重复的列名,给重复的列添加后缀
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columns = _make_unique_columns(columns)
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df = pd.DataFrame(df_data, columns=columns)
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markdown_content += f"## {sheet_name}\n\n"
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# 在最左列添加标题字段
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table_title = f"{file_path_obj.stem} - {sheet_name}" # 使用"文件名 - Sheet名"作为标题
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df.insert(0, "表格标题", table_title)
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# 将每10行数据与表头组合成独立的表格
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chunk_size = 10
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for i in range(0, len(df), chunk_size):
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# 获取当前10行数据(或剩余不足10行的数据)
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chunk_df = df.iloc[i : i + chunk_size]
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markdown_content += f"### 数据行 {i + 1}-{min(i + chunk_size, len(df))}\n\n"
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markdown_table = chunk_df.to_markdown(index=False)
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markdown_content += f"{markdown_table}\n\n"
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result = markdown_content.strip()
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# 使用 Docling 处理 Excel 文件
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result = _convert_with_docling(file_path_obj, params=params)
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elif file_ext == ".json":
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# 处理 JSON 文件
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BIN
test/data/测试文档.docx
Normal file
BIN
test/data/测试文档.docx
Normal file
Binary file not shown.
BIN
test/data/测试演示.pptx
Normal file
BIN
test/data/测试演示.pptx
Normal file
Binary file not shown.
BIN
test/data/测试表格.xlsx
Normal file
BIN
test/data/测试表格.xlsx
Normal file
Binary file not shown.
497
uv.lock
497
uv.lock
@ -1235,6 +1235,132 @@ wheels = [
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{ url = "https://files.pythonhosted.org/packages/7e/ac/6e16e92f412d94494f6fed95cfdf3ff135cf09af09e4d4f10846e9d87f75/doclayout_yolo-0.0.4-py3-none-any.whl", hash = "sha256:934451385a6e50d71fbbda12e5866eb4003d87186364d0151d8e8ec898a21723", size = 711270, upload-time = "2025-06-10T09:06:30.063Z" },
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]
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[[package]]
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name = "docling"
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version = "2.68.0"
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source = { registry = "https://pypi.org/simple" }
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dependencies = [
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{ name = "accelerate" },
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{ name = "beautifulsoup4" },
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{ name = "certifi" },
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{ name = "docling-core", extra = ["chunking"] },
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{ name = "docling-ibm-models" },
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{ name = "docling-parse" },
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{ name = "filetype" },
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{ name = "huggingface-hub" },
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{ name = "lxml" },
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{ name = "marko" },
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{ name = "ocrmac", marker = "sys_platform == 'darwin'" },
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{ name = "openpyxl" },
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{ name = "pandas" },
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{ name = "pillow" },
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{ name = "pluggy" },
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{ name = "polyfactory" },
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{ name = "pydantic" },
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{ name = "pydantic-settings" },
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{ name = "pylatexenc" },
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{ name = "pypdfium2" },
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{ name = "python-docx" },
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||||
{ name = "python-pptx" },
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|
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version = "0.25.0"
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]
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||||
|
||||
[[package]]
|
||||
name = "tree-sitter-typescript"
|
||||
version = "0.23.2"
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||||
source = { registry = "https://pypi.org/simple" }
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sdist = { url = "https://files.pythonhosted.org/packages/1e/fc/bb52958f7e399250aee093751e9373a6311cadbe76b6e0d109b853757f35/tree_sitter_typescript-0.23.2.tar.gz", hash = "sha256:7b167b5827c882261cb7a50dfa0fb567975f9b315e87ed87ad0a0a3aedb3834d", size = 773053, upload-time = "2024-11-11T02:36:11.396Z" }
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wheels = [
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{ url = "https://files.pythonhosted.org/packages/7f/cb/f57b149d7beed1a85b8266d0c60ebe4c46e79c9ba56bc17b898e17daf88e/tree_sitter_typescript-0.23.2-cp39-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:8d4f0f9bcb61ad7b7509d49a1565ff2cc363863644a234e1e0fe10960e55aea0", size = 340245, upload-time = "2024-11-11T02:36:06.473Z" },
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{ url = "https://files.pythonhosted.org/packages/9f/e4/81f9a935789233cf412a0ed5fe04c883841d2c8fb0b7e075958a35c65032/tree_sitter_typescript-0.23.2-cp39-abi3-win_arm64.whl", hash = "sha256:05db58f70b95ef0ea126db5560f3775692f609589ed6f8dd0af84b7f19f1cbb7", size = 274052, upload-time = "2024-11-11T02:36:09.514Z" },
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]
|
||||
|
||||
[[package]]
|
||||
name = "triton"
|
||||
version = "3.5.1"
|
||||
@ -6613,7 +7100,7 @@ wheels = [
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||||
|
||||
[[package]]
|
||||
name = "typer"
|
||||
version = "0.21.0"
|
||||
version = "0.19.2"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "click" },
|
||||
@ -6621,9 +7108,9 @@ dependencies = [
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{ name = "shellingham" },
|
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{ name = "typing-extensions" },
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]
|
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sdist = { url = "https://files.pythonhosted.org/packages/85/30/ff9ede605e3bd086b4dd842499814e128500621f7951ca1e5ce84bbf61b1/typer-0.21.0.tar.gz", hash = "sha256:c87c0d2b6eee3b49c5c64649ec92425492c14488096dfbc8a0c2799b2f6f9c53", size = 106781, upload-time = "2025-12-25T09:54:53.651Z" }
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sdist = { url = "https://files.pythonhosted.org/packages/21/ca/950278884e2ca20547ff3eb109478c6baf6b8cf219318e6bc4f666fad8e8/typer-0.19.2.tar.gz", hash = "sha256:9ad824308ded0ad06cc716434705f691d4ee0bfd0fb081839d2e426860e7fdca", size = 104755, upload-time = "2025-09-23T09:47:48.256Z" }
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wheels = [
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{ url = "https://files.pythonhosted.org/packages/e1/e4/5ebc1899d31d2b1601b32d21cfb4bba022ae6fce323d365f0448031b1660/typer-0.21.0-py3-none-any.whl", hash = "sha256:c79c01ca6b30af9fd48284058a7056ba0d3bf5cf10d0ff3d0c5b11b68c258ac6", size = 47109, upload-time = "2025-12-25T09:54:51.918Z" },
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{ url = "https://files.pythonhosted.org/packages/00/22/35617eee79080a5d071d0f14ad698d325ee6b3bf824fc0467c03b30e7fa8/typer-0.19.2-py3-none-any.whl", hash = "sha256:755e7e19670ffad8283db353267cb81ef252f595aa6834a0d1ca9312d9326cb9", size = 46748, upload-time = "2025-09-23T09:47:46.777Z" },
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]
|
||||
|
||||
[[package]]
|
||||
@ -7347,6 +7834,7 @@ dependencies = [
|
||||
{ name = "colorlog" },
|
||||
{ name = "dashscope" },
|
||||
{ name = "deepagents" },
|
||||
{ name = "docling" },
|
||||
{ name = "docx2txt" },
|
||||
{ name = "fastapi" },
|
||||
{ name = "httpx" },
|
||||
@ -7422,6 +7910,7 @@ requires-dist = [
|
||||
{ name = "colorlog", specifier = ">=6.9.0" },
|
||||
{ name = "dashscope", specifier = ">=1.23.2" },
|
||||
{ name = "deepagents", specifier = ">=0.2.5" },
|
||||
{ name = "docling", specifier = ">=2.68.0" },
|
||||
{ name = "docx2txt", specifier = ">=0.9" },
|
||||
{ name = "fastapi", specifier = ">=0.121" },
|
||||
{ name = "httpx", specifier = ">=0.27.0" },
|
||||
|
||||
@ -1,5 +1,5 @@
|
||||
// 文件相关工具函数
|
||||
import { FileTextFilled, FileMarkdownFilled, FilePdfFilled, FileWordFilled, FileExcelFilled, FileImageFilled, FileUnknownFilled } from '@ant-design/icons-vue';
|
||||
import { FileTextFilled, FileMarkdownFilled, FilePdfFilled, FileWordFilled, FileExcelFilled, FileImageFilled, FileUnknownFilled, FilePptFilled } from '@ant-design/icons-vue';
|
||||
import { formatRelative, parseToShanghai } from '@/utils/time';
|
||||
|
||||
// 根据文件扩展名获取文件图标
|
||||
@ -30,6 +30,10 @@ export const getFileIcon = (filename) => {
|
||||
'xlsx': FileExcelFilled,
|
||||
'csv': FileExcelFilled,
|
||||
|
||||
// PPT文档
|
||||
'ppt': FilePptFilled,
|
||||
'pptx': FilePptFilled,
|
||||
|
||||
// 图片文件
|
||||
'jpg': FileImageFilled,
|
||||
'jpeg': FileImageFilled,
|
||||
@ -75,6 +79,10 @@ export const getFileIconColor = (filename) => {
|
||||
'xlsx': '#52c41a',
|
||||
'csv': '#52c41a',
|
||||
|
||||
// PPT文档 - 橙色
|
||||
'ppt': '#f6720d',
|
||||
'pptx': '#f6720d',
|
||||
|
||||
// 图片文件 - 紫色
|
||||
'jpg': '#722ed1',
|
||||
'jpeg': '#722ed1',
|
||||
|
||||
Loading…
Reference in New Issue
Block a user