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* Add poetry install shell cmd to the readme Signed-off-by: Brent Salisbury <bsalisbu@redhat.com> * Add GPU support instructions - Validated on an EC2 GPU instance to work. - Closes #8 Signed-off-by: Brent Salisbury <bsalisbu@redhat.com> * Update README.md Signed-off-by: Anil Vishnoi <vishnoianil@gmail.com> --------- Signed-off-by: Brent Salisbury <bsalisbu@redhat.com> Signed-off-by: Anil Vishnoi <vishnoianil@gmail.com> Co-authored-by: Anil Vishnoi <vishnoianil@gmail.com>
Docling Serve
Running Docling as an API service.
Note
This is an unstable draft implementation which will quickly evolve.
Development
Install the dependencies
# Install poetry if not already available
curl -sSL https://install.python-poetry.org | python3 -
# Install dependencies
poetry install
# Run the server
poetry run uvicorn docling_serve.app:app --reload
Example payload (http source):
curl -X 'POST' \
'http://127.0.0.1:8000/convert' \
-H 'accept: application/json' \
-H 'Content-Type: application/json' \
-d '{
"http_source": {
"url": "https://arxiv.org/pdf/2206.01062"
}
}'
Cuda GPU Support
For GPU support try the following:
# Create a virtual env
python3 -m venv venv
# Activate the venv
source venv/bin/active
# Install torch with the special index
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu124
# Install the package
pip install -e .
# Run the server
poetry run uvicorn docling_serve.app:app --reload
Languages
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Makefile
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