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 convert
• export/ - 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