docling

# Docling Docling converts documents — PDF, DOCX, PPTX, XLSX, HTML, Markdown, AsciiDoc, CSV, images, audio, and XML — into a single unified representation, the **`DoclingDocument`**, which you can export as **Markdown** (human-readable) or **JSON** (structured, lossless). Reach for Docling whenever you need to understand the content of a file you cannot read directly, especially PDFs (including scanned ones, via OCR or a vision-language model). ## The fastest thing that works: the CLI If you just need to read a document's content, run the CLI. It is installed with the `docling` package and accepts a local path **or** a URL: ```bash docling report.pdf --to md --output /tmp/ # → /tmp/report.md docling https://example.com/paper.pdf --to json --output /tmp/ ``` Output files are named after the input (`report.pdf` → `report.md`). Default output directory is the current directory. This handles the majority of "what's in this file" requests. See **[references/cli.md](references/cli.md)** for pipelines (standard vs VLM vs native), OCR engines, tables, scanned PDFs, passwords, and every flag. ## Choosing how to use Docling | You need to… | Use | Reference | |---|---|---| | Read / convert a file once, from the shell | **CLI** (`docling …`) | [references/cli.md](references/cli.md) | | Convert programmatically, tune the pipeline, batch, ASR, export images/tables | **Python SDK** (`DocumentConverter` + `PipelineOptions`) | [references/python-sdk.md](references/python-sdk.md) | | Pull specific typed fields out of a document (not the whole doc) | **DocumentExtractor** (structured extraction, beta) | [references/extraction.md](references/extraction.md) | | Chunk documents for retrieval / feed a RAG index | **Chunking + framework loaders** | [references/rag.md](references/rag.md) | | Offload conversion to a remote service — low latency, scalable, no local ML deps or GPU | **Service Client** (self-hosted or managed docling-serve) | [references/service-client.md](references/service-client.md) | | Install only the dependencies you actually use | **docling-slim** extras | [references/slim-packaging.md](references/slim-packaging.md) | Rules of thumb: - **Local, one-off, no code** → CLI. - **Custom pipeline, chunking, structure analysis, embedding in an app** → Python SDK. - **Many documents, low-latency, no GPU/ML install to manage, scale on demand** → Service Client against a `docling-serve` endpoint (self-hosted or the managed **Docling for IBM watsonx** service). - **Minimize install size / avoid pulling torch and OCR engines you don't need** → docling-slim with targeted extras. ## Running without installing (uvx) You can run the CLI without a persistent install: ```bash uvx --from docling docling report.pdf --to md --output /tmp/ ``` ## Output conventions - Always report the conversion status and (for PDFs) the page count. - If the user does not specify a format, ask whether they want **Markdown** (readable) or **JSON / DoclingDocument** (structured, lossless). - For tables, prefer `export_to_markdown()` / `export_to_dataframe()` on the table item (Python) — see [references/python-sdk.md](references/python-sdk.md). - If a converted PDF comes back near-empty, repeated, or full of `�`, the source is likely scanned or complex layout — retry with OCR or `--pipeline vlm` (see [references/cli.md](references/cli.md)).