Core technology realization programme
| Document type | underlying technology | processing flow |
|---|---|---|
| pdf-lib + text reorganization | Parsing document structure → extracting text elements → applying Markdown markup | |
| imagery | Tesseract OCR | Image Preprocessing → Text Recognition → Format Correction |
| sound frequency | Web Speech API | Audio Segmentation → Speech to Text → Punctuation Recovery |
| web page | Cheerio + Readability | Download HTML → Extract main content → Clear ads |
Featured Technical Details
- Forms processing: Auto-detect alignment to generate Markdown table syntax.
- code block identification: Intelligent determination of programming language type
- Catalog Generation: Create nested lists based on title hierarchy
Precision Optimization Mechanism
The quality of the conversion is ensured in the following ways:
- Multi-round calibration: dictionary comparison of OCR results
- Layout analysis: preserving paragraph relationships in the original document
- Postprocessor: automatically fixes common markup errors
Performance indicators
In a standard test environment: A4 document conversion takes an average of 500ms, image OCR processing about 2s/page, audio transcription speed depends on the duration.
This answer comes from the articleMarkdownify MCP Server: Converts various content to Markdown format based on the MCP protocol.The
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