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Signed-off-by: Panos Vagenas <35837085+vagenas@users.noreply.github.com>
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Panos Vagenas 2024-07-25 22:58:05 +02:00
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@ -30,19 +30,35 @@ To use Docling, simply install `docling` from your package manager, e.g. pip:
pip install docling
```
> [!NOTE]
> [!NOTE]
> Works on macOS and Linux environments. Windows platforms are currently not tested.
### Development setup
To develop for Docling, you need Python 3.10 / 3.11 / 3.12 and Poetry. You can then install from your local clone's root dir:
```bash
poetry install
poetry install --all-extras
```
## Usage
For basic usage, see the [convert.py](https://github.com/DS4SD/docling/blob/main/examples/convert.py) example module. Run with:
### Convert a single document
To convert invidual PDF documents, use `convert_single()`, for example:
```python
from docling.document_converter import DocumentConverter
source = "https://arxiv.org/pdf/2206.01062" # PDF path or URL
converter = DocumentConverter()
doc = converter.convert_single(source)
print(doc.export_to_markdown()) # output: "## DocLayNet: A Large Human-Annotated Dataset for Document-Layout Analysis [...]"
```
### Convert a batch of documents
For an example of converting multiple documents, see [convert.py](https://github.com/DS4SD/docling/blob/main/examples/convert.py).
From a local repo clone, you can run it with:
```
python examples/convert.py
@ -58,7 +74,7 @@ You can control if table structure recognition or OCR should be performed by arg
doc_converter = DocumentConverter(
artifacts_path=artifacts_path,
pipeline_options=PipelineOptions(
do_table_structure=False, # controls if table structure is recovered
do_table_structure=False, # controls if table structure is recovered
do_ocr=True, # controls if OCR is applied (ignores programmatic content)
),
)
@ -90,7 +106,7 @@ conv_input = DocumentConversionInput.from_paths(
)
```
### Convert from binary PDF streams
### Convert from binary PDF streams
You can convert PDFs from a binary stream instead of from the filesystem as follows:
```python