Kris
b3bdb4fa2f
1. 新增内置TTS工具，支持OpenAI兼容语音合成服务 2. 新增ASR音频解析和视频解析处理器 3. 扩展文件解析支持范围，添加音视频格式支持 4. 新增ffmpeg音视频处理基础工具库 5. 补充相关单元测试用例
510 lines
18 KiB
Python
510 lines
18 KiB
Python
"""Unified parser module for markdown conversion."""
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from __future__ import annotations
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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 tempfile
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import time
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from dataclasses import dataclass, field
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from pathlib import Path
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from typing import Any
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import aiofiles
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from docling.datamodel.base_models import InputFormat
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from docling.document_converter import DocumentConverter
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from langchain_community.document_loaders import PyPDFLoader
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from markdownify import markdownify as md_convert
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from yuxi.knowledge.parser.zip_utils import process_zip_file as _process_zip_file
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from yuxi.storage.minio import get_minio_client
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from yuxi.utils import logger
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SUPPORTED_FILE_EXTENSIONS: tuple[str, ...] = (
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".txt",
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".md",
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".docx",
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".html",
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".htm",
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".json",
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".csv",
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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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".bmp",
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".tiff",
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".tif",
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".zip",
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# 音频
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".mp3",
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".wav",
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".m4a",
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".flac",
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".ogg",
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".wma",
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# 视频
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".mp4",
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".avi",
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".mov",
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".mkv",
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".webm",
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".flv",
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)
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AUDIO_EXTENSIONS = {".mp3", ".wav", ".m4a", ".flac", ".ogg", ".wma"}
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VIDEO_EXTENSIONS = {".mp4", ".avi", ".mov", ".mkv", ".webm", ".flv"}
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def is_supported_file_extension(file_name: str | os.PathLike[str]) -> bool:
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"""Check whether the given file path has a supported extension."""
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return Path(file_name).suffix.lower() in SUPPORTED_FILE_EXTENSIONS
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@dataclass(slots=True)
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class MarkdownParseResult:
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"""统一的 Markdown 解析结果。"""
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markdown: str
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file_ext: str | None = None
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artifacts: dict[str, Any] = field(default_factory=dict)
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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 _resolve_image_storage_params(params: dict | None) -> tuple[str, str]:
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params = params or {}
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image_bucket = params.get("image_bucket") or "public"
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image_prefix = params.get("image_prefix")
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if image_prefix:
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normalized_prefix = str(image_prefix).strip("/")
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if normalized_prefix:
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return image_bucket, normalized_prefix
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return image_bucket, "unknown/kb-images"
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def _resolve_ocr_engine_params(params: dict | None) -> tuple[str, dict[str, Any]]:
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params = params or {}
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engine = str(params.get("ocr_engine") or "disable")
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engine_config = params.get("ocr_engine_config")
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processor_params = dict(params)
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if isinstance(engine_config, dict):
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processor_params.update(engine_config)
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return engine, processor_params
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def _upload_image_to_minio(image_data: bytes, filename: str, bucket_name: str, object_prefix: 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(bucket_name)
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normalized_prefix = object_prefix.strip("/") or "unknown/kb-images"
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timestamp = int(time.time() * 1000000)
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object_name = f"{normalized_prefix}/{timestamp}_{Path(filename).name}"
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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=image_data,
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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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"""使用 Docling 将 docx/xlsx/pptx 转换为 Markdown。"""
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params = params or {}
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image_bucket, image_prefix = _resolve_image_storage_params(params)
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converter = _get_docling_converter()
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result = converter.convert(file_path)
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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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doc = result.document
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if hasattr(doc, "pictures") and doc.pictures:
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replacements: list[str] = []
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for pic in doc.pictures:
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uri = str(pic.image.uri) if hasattr(pic, "image") and hasattr(pic.image, "uri") else ""
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if uri.startswith("data:"):
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filename = "image"
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try:
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image_data, mime_type = _parse_data_uri(uri)
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filename = f"image_{int(time.time() * 1000000)}.{mime_type.split('/')[-1]}"
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url = _upload_image_to_minio(image_data, filename, image_bucket, image_prefix)
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replacements.append(f"")
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except Exception as e: # noqa: BLE001
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logger.error(f"上传图片失败 {filename}: {e}")
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replacements.append(f"[图片: {filename}]")
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else:
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replacements.append("")
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markdown = doc.export_to_markdown()
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for replacement in replacements:
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markdown = re.sub(r"<!--\s*image\s*-->", replacement, markdown, count=1)
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return markdown
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return doc.export_to_markdown()
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def _convert_docx_with_python_docx(file_path: Path) -> str:
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"""使用 python-docx 解析 DOCX（Docling 失败时兜底）。"""
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from docx import Document
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document = Document(str(file_path))
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blocks: list[str] = []
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for para in document.paragraphs:
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text = para.text.strip()
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if text:
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blocks.append(text)
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for table in document.tables:
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rows: list[list[str]] = []
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for row in table.rows:
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cells = [cell.text.strip().replace("\n", " ") for cell in row.cells]
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if any(cells):
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rows.append(cells)
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if not rows:
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continue
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header = rows[0]
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blocks.append(f"| {' | '.join(header)} |")
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blocks.append(f"| {' | '.join(['---'] * len(header))} |")
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for row in rows[1:]:
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normalized_row = row + [""] * (len(header) - len(row))
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blocks.append(f"| {' | '.join(normalized_row[: len(header)])} |")
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blocks.append("")
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return "\n\n".join(blocks).strip()
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def pdfreader(file_path, params=None):
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"""读取 PDF 文件并返回 text 文本。"""
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if isinstance(file_path, str):
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file_path = Path(file_path)
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assert file_path.exists(), "File not found"
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assert file_path.suffix.lower() == ".pdf", "File format not supported"
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loader = PyPDFLoader(str(file_path))
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docs = loader.load()
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text = "\n\n".join([d.page_content for d in docs])
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return text
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def parse_pdf(file, params=None):
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"""解析 PDF 文件，支持多种 OCR 方式。"""
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from yuxi.knowledge.parser.base import DocumentProcessorException
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from yuxi.knowledge.parser.factory import DocumentProcessorFactory
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opt_ocr, processor_params = _resolve_ocr_engine_params(params)
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if opt_ocr == "disable":
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return pdfreader(file, params=processor_params)
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image_bucket, image_prefix = _resolve_image_storage_params(processor_params)
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processor_params.setdefault("image_bucket", image_bucket)
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processor_params.setdefault("image_prefix", image_prefix)
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try:
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return DocumentProcessorFactory.process_file(opt_ocr, file, processor_params)
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except DocumentProcessorException as e:
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logger.error(f"文档处理失败: {e.service_name} - {str(e)}")
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raise
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except Exception as e: # noqa: BLE001
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logger.error(f"PDF 解析失败: {str(e)}")
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raise DocumentProcessorException(f"PDF解析失败: {str(e)}", opt_ocr, "parsing_failed")
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def parse_image(file, params=None):
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"""解析图像文件，支持多种 OCR 方式。"""
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from yuxi.knowledge.parser.base import DocumentProcessorException
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from yuxi.knowledge.parser.factory import DocumentProcessorFactory
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opt_ocr, processor_params = _resolve_ocr_engine_params(params)
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if opt_ocr == "disable":
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raise ValueError(
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"图像文件必须启用OCR才能提取文本内容。"
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"请选择OCR方式 (rapid_ocr/mineru_ocr/mineru_official/pp_structure_v3_ocr/deepseek_ocr) 或移除该文件。"
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)
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image_bucket, image_prefix = _resolve_image_storage_params(processor_params)
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processor_params.setdefault("image_bucket", image_bucket)
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processor_params.setdefault("image_prefix", image_prefix)
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try:
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return DocumentProcessorFactory.process_file(opt_ocr, file, processor_params)
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except DocumentProcessorException as e:
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logger.error(f"图像处理失败: {e.service_name} - {str(e)}")
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raise
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except Exception as e: # noqa: BLE001
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logger.error(f"图像解析失败: {str(e)}")
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raise DocumentProcessorException(f"图像解析失败: {str(e)}", opt_ocr, "parsing_failed")
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async def parse_pdf_async(file, params=None):
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return await asyncio.to_thread(parse_pdf, file, params=params)
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async def parse_image_async(file, params=None):
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return await asyncio.to_thread(parse_image, file, params=params)
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def parse_audio(file, params=None):
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"""解析音频文件，使用 ASR 转写为文本。"""
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from yuxi.knowledge.parser.base import DocumentProcessorException
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from yuxi.knowledge.parser.factory import DocumentProcessorFactory
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try:
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return DocumentProcessorFactory.process_file("asr", file, params)
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except DocumentProcessorException as e:
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logger.error(f"音频处理失败: {e.service_name} - {str(e)}")
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raise
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except Exception as e: # noqa: BLE001
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logger.error(f"音频解析失败: {str(e)}")
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raise DocumentProcessorException(f"音频解析失败: {str(e)}", "asr", "parsing_failed")
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def parse_video(file, params=None):
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"""解析视频文件，提取音频 ASR + 关键帧 OCR。"""
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from yuxi.knowledge.parser.base import DocumentProcessorException
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from yuxi.knowledge.parser.factory import DocumentProcessorFactory
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try:
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return DocumentProcessorFactory.process_file("video", file, params)
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except DocumentProcessorException as e:
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logger.error(f"视频处理失败: {e.service_name} - {str(e)}")
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raise
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except Exception as e: # noqa: BLE001
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logger.error(f"视频解析失败: {str(e)}")
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raise DocumentProcessorException(f"视频解析失败: {str(e)}", "video", "parsing_failed")
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async def parse_audio_async(file, params=None):
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return await asyncio.to_thread(parse_audio, file, params=params)
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async def parse_video_async(file, params=None):
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return await asyncio.to_thread(parse_video, file, params=params)
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async def _process_file_to_markdown_core(
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file_path: str, params: dict | None = None
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) -> tuple[str, str | None, dict[str, Any]]:
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"""将不同类型的文件转换为 markdown，支持本地文件和 MinIO 文件。"""
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from yuxi.knowledge.utils.kb_utils import is_minio_url, parse_minio_url
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from yuxi.storage.minio.client import get_minio_client
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if is_minio_url(file_path):
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logger.debug(f"Downloading file from MinIO: {file_path}")
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if "?" in file_path:
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file_path_clean = file_path.split("?")[0]
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else:
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file_path_clean = file_path
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original_filename = file_path_clean.split("/")[-1]
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with tempfile.NamedTemporaryFile(delete=False, suffix=Path(original_filename).suffix) as temp_file:
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temp_path = temp_file.name
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try:
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bucket_name, object_name = parse_minio_url(file_path)
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minio_client = get_minio_client()
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file_content = await minio_client.adownload_file(bucket_name, object_name)
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async with aiofiles.open(temp_path, "wb") as f:
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await f.write(file_content)
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logger.debug(f"File downloaded to temp path: {temp_path}")
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actual_file_path = temp_path
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except Exception as e: # noqa: BLE001
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if os.path.exists(temp_path):
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os.unlink(temp_path)
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logger.error(f"Failed to download file from MinIO: {e}")
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raise ValueError(f"无法从MinIO下载文件: {e}")
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else:
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actual_file_path = file_path
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file_ext: str | None = None
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artifacts: dict[str, Any] = {}
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try:
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file_path_obj = Path(actual_file_path)
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file_ext = file_path_obj.suffix.lower()
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if file_ext == ".pdf":
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text = await parse_pdf_async(str(file_path_obj), params=params)
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result = f"{text}"
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elif file_ext in [".txt", ".md"]:
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with open(file_path_obj, encoding="utf-8") as f:
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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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try:
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result = _convert_with_docling(file_path_obj, params=params)
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except Exception as e: # noqa: BLE001
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logger.warning(f"Docling 解析 DOCX 失败，回退到 python-docx: {file_path_obj.name}, {e}")
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result = _convert_docx_with_python_docx(file_path_obj)
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elif file_ext == ".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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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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text = await parse_image_async(str(file_path_obj), params=params)
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result = f"{text}"
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elif file_ext in AUDIO_EXTENSIONS:
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text = await parse_audio_async(str(file_path_obj), params=params)
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result = f"{text}"
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elif file_ext in VIDEO_EXTENSIONS:
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text = await parse_video_async(str(file_path_obj), params=params)
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result = f"{text}"
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elif file_ext in [".html", ".htm"]:
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with open(file_path_obj, encoding="utf-8") as f:
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content = f.read()
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text = md_convert(content, heading_style="ATX")
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result = f"{text}"
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elif file_ext == ".csv":
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import pandas as pd
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df = pd.read_csv(file_path_obj)
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markdown_content = ""
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for _, row in df.iterrows():
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row_df = pd.DataFrame([row], columns=df.columns)
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markdown_table = row_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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elif file_ext in [".xls", ".xlsx"]:
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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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import json
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async with aiofiles.open(file_path_obj, encoding="utf-8") as f:
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content = await f.read()
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data = json.loads(content)
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json_str = json.dumps(data, ensure_ascii=False, indent=2)
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result = f"```json\n{json_str}\n```"
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elif file_ext == ".zip":
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image_bucket, image_prefix = _resolve_image_storage_params(params)
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zip_result = await _process_zip_file(
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str(file_path_obj),
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image_bucket=image_bucket,
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image_prefix=image_prefix,
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)
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artifacts = {
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"zip_images_info": zip_result["images_info"],
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"zip_content_hash": zip_result["content_hash"],
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"zip_image_bucket": image_bucket,
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"zip_image_prefix": image_prefix,
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}
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result = zip_result["markdown_content"]
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else:
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raise ValueError(f"Unsupported file type: {file_ext}")
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except Exception:
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if is_minio_url(file_path) and os.path.exists(actual_file_path):
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try:
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os.unlink(actual_file_path)
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logger.debug(f"Cleaned up temp file: {actual_file_path}")
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except Exception as cleanup_e: # noqa: BLE001
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logger.warning(f"Failed to clean up temp file {actual_file_path}: {cleanup_e}")
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raise
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finally:
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if is_minio_url(file_path) and os.path.exists(actual_file_path):
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try:
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os.unlink(actual_file_path)
|
||
logger.debug(f"Cleaned up temp file: {actual_file_path}")
|
||
except Exception as e: # noqa: BLE001
|
||
logger.warning(f"Failed to clean up temp file {actual_file_path}: {e}")
|
||
|
||
return result, file_ext, artifacts
|
||
|
||
|
||
async def parse_source_to_markdown(source: str, params: dict | None = None) -> MarkdownParseResult:
|
||
"""统一入口: 将文件解析为 Markdown（URL 解析已废弃）。"""
|
||
markdown, file_ext, artifacts = await _process_file_to_markdown_core(source, params=params)
|
||
return MarkdownParseResult(
|
||
markdown=markdown,
|
||
file_ext=file_ext,
|
||
artifacts=artifacts,
|
||
)
|
||
|
||
|
||
class Parser:
|
||
"""Lightweight facade for converting file sources to markdown."""
|
||
|
||
@staticmethod
|
||
async def aparse(source: str, params: dict | None = None) -> str:
|
||
"""Asynchronously parse source content and return markdown text."""
|
||
parsed = await parse_source_to_markdown(source=source, params=params)
|
||
return parsed.markdown
|
||
|
||
@classmethod
|
||
def parse(cls, source: str, params: dict | None = None) -> str:
|
||
"""Synchronously parse source content and return markdown text."""
|
||
try:
|
||
asyncio.get_running_loop()
|
||
except RuntimeError:
|
||
return asyncio.run(cls.aparse(source=source, params=params))
|
||
|
||
raise RuntimeError("当前处于异步上下文，请使用 `await Parser.aparse(...)`")
|