Docling Client

Lightweight client SDK for converting documents via a remote Docling Serve endpoint

docling-client is a meta-package that installs docling-slim[service-client], giving you DoclingServiceClient — a drop-in replacement for the local DocumentConverter that offloads conversion to a Docling Serve instance over HTTP.

For the full documentation, see the Docling docs.

Why a remote client?

You want to…	Use
Convert documents in a Python application, without running models locally	`docling-client` → point at a Docling Serve endpoint
Run Docling directly in-process in a Python application	`docling`
Full control over which extras are installed	`docling-slim[service-client]`

Switching from local to remote conversion typically requires changing only the client class and the endpoint URL — the conversion API (sources, options, output formats) stays the same.

Getting started

1. Install

bash

pip install docling-client

2. Point at a Docling Serve endpoint

You need a running Docling Serve instance — self-hosted or a managed service.

Set your connection details in the environment (or a .env file):

DOCLING_SERVICE_URL=https://your-docling-service.example.com
DOCLING_SERVICE_API_KEY=your-api-key   # omit if the service is unauthenticated

3. Convert a document

python

import os
from docling.service_client import DoclingServiceClient

with DoclingServiceClient(
    url=os.environ["DOCLING_SERVICE_URL"],
    api_key=os.environ.get("DOCLING_SERVICE_API_KEY", ""),
) as client:
    result = client.convert(source="https://arxiv.org/pdf/2501.17887")
    print(result.document.export_to_markdown())

Convert many documents concurrently:

python

sources = [
    "https://arxiv.org/pdf/2501.17887",
    "path/to/report.pdf",
    "path/to/slides.pptx",
]

with DoclingServiceClient(url=os.environ["DOCLING_SERVICE_URL"]) as client:
    for result in client.convert_all(source=sources, max_concurrency=4):
        print(result.input.file.name, result.status)
        print(result.document.export_to_markdown()[:200])

Switching from local to remote

If you already use the local DocumentConverter, the client API mirrors it closely. Only the import and instantiation change:

python

# Before — local, runs models on this machine
from docling.document_converter import DocumentConverter
converter = DocumentConverter()
result = converter.convert("report.pdf")

# After — remote, offloads conversion to Docling Serve
from docling.service_client import DoclingServiceClient
converter = DoclingServiceClient(url="https://...", api_key="...")
result = converter.convert(source="report.pdf")

Both result.document.export_to_markdown() and other output methods work the same way.

Managed services

Running Docling Serve yourself means operating infrastructure. Managed services remove that overhead.

Docling for IBM watsonx

A fully managed, hosted instance of Docling Serve — no servers, GPUs, scaling, or operational monitoring required. It exposes the same REST API, so your client code stays portable: swap the base URL, supply your API key, and go.

Product page
Free trial — no credit card needed

More examples

Runnable examples are in docs/examples/service_client/ in the repository:

Script	What it shows
`convert.py`	`convert()` and `convert_all()` — the high-level API
`tasks.py`	Job lifecycle: `submit()`, `watch()`, `result()`, result targets
`batch.py`	`submit_batch()` for plugin sources and artifact targets
`chunk.py`	`chunk()` — split a document into retrieval-ready pieces

Documentation

License

MIT License — see LICENSE