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Docling Graph Examples

Example scripts and Pydantic templates for docling-graph. Run scripts from the project root with uv run python docs/examples/scripts/....

Project Structure

Path Description
docs/examples/scripts/ Python example scripts (01–13)
docs/examples/templates/ Pydantic templates (e.g. billing_document.py, rheology_research.py)

Example Scripts (01–13)

Getting Started

  1. 01_quickstart_vlm_image.py — VLM extraction from an invoice image
  2. 02_quickstart_llm_pdf.py — LLM extraction from a multi-page PDF (e.g. rheology)
  3. 03_url_processing.py — Process documents from URLs (e.g. arXiv)

Core Features

  1. 04_input_formats.py — Text, Markdown, and DoclingDocument inputs
  2. 05_processing_modes.py — One-to-one vs many-to-one modes
  3. 06_export_formats.py — CSV, Cypher, and JSON exports
  4. 07_local_inference.py — Local inference with Ollama

Optimization & Providers

  1. 08_chunking_consolidation.py — Chunking and merge behavior
  2. 09_batch_processing.py — Batch processing with error handling
  3. 10_provider_configs.py — OpenAI, Mistral, Gemini, WatsonX
  4. 11_staged_extraction.py — Staged extraction (ID pass → fill pass → merge) for complex templates
  5. 12_custom_llm_client.py — Custom LLM client (bring your own URL) with full pipeline
  6. 13_delta_extraction.py — Delta extraction (chunk → batch → graph IR → merge → projection) for long documents
  7. 14_streaming_responses.py — Streaming LLM responses for real-time processing and progress feedback

For CLI usage, see CLI Reference and convert command.

Quick Start

# From project root: VLM from image
uv run python docs/examples/scripts/01_quickstart_vlm_image.py

# Or use the CLI
uv run docling-graph convert "https://upload.wikimedia.org/wikipedia/commons/9/9f/Swiss_QR-Bill_example.jpg" \
    --template "docs.examples.templates.billing_document.BillingDocument" \
    --backend "vlm"

Learning Path

  1. Run 01 for a minimal VLM run, then 02 for LLM extraction.
  2. Use 03–07 for input formats, processing modes, exports, and local inference.
  3. Use 08–10 for chunking, batch runs, and multiple providers.