mengbo Docling CLI
Convert documents to structured formats with intelligent parsing, OCR, and AI enhancement.
Installation
uv tool install docling[asr,vlm]
Directory Setup
Create working directories in your project root:
mkdir -p import export
import/- Source files to convertexport/- Converted output files
Note: You can specify any output directory with --output, but examples below use export/ for consistency.
Quick Start
Check complete options before using:
docling --help
Basic conversion (most parameters have sensible defaults):
# Convert PDF to Markdown
docling --output export/ import/document.pdf
# Convert to JSON
docling --to json --output export/ import/document.pdf
# Batch convert entire directory
docling --output export/ import/
Default behavior:
- Input format: auto-detects (PDF, DOCX, PPTX, images, etc.)
- Output format: Markdown
- Output directory: current directory
- OCR: enabled
- Table extraction: enabled
- Image export: embedded
Image Export Mode
Choose image export mode based on your needs:
| Mode | Description | When to use |
|---|---|---|
placeholder |
Only mark image positions | When user doesn't need images |
embedded |
Base64-encoded images (default) | When user needs images but wants single-file output |
referenced |
Export as PNG files, reference in document | When user needs separate image files |
docling --to json --image-export-mode referenced --output export/ import/document.pdf
Platform Optimization
macOS / Apple Silicon
Recommend using VLM pipeline for better performance, especially for scanned PDFs or documents with images:
docling --pipeline vlm --output export/ import/document.pdf
VLM pipeline with default model works well for documents with Chinese image content.
Audio Transcription
Convert audio files to text using ASR models:
# Use default whisper_tiny model
docling --pipeline asr --output export/ import/audio.mp3
# For better accuracy with Chinese
docling --pipeline asr --asr-model whisper_large --output export/ import/audio.mp3