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License: GNU General Public License v3.0
All Python dependencies should be listed in a requirements.txt
file (see pip documentation).
The file can then be used to simplify the Dockerfile
and setting up a development environment.
with the new docker file there are some permission denied issues when saving the results (the docker volume folder needs to be writable by the user inside the docker container. I'm not sure how to handle this the correct way. I changed the access of the volume folder to 777...
when starting the pipeline it should be possible to skip steps (if there are already prerequisite steps available and one would only like to e.g. reprocess the graph creation step).
The reason why the image is comparably small now, is probably because only the spacy
models for preprocessing are downloaded and not the models for the sentence-transformer
, i.e. the embedding step. That might be reasonable because one wouldn't need the english model for if one only wants to process german data.
The only drawback seems to be that a respective model needs to be downloaded during runtime and this could potentially throw a wrench into the pipeline process. It might be best if we include a model check step before any of the requested pipeline steps is started and if a model is missing, it will be downloaded. This would mean that we could remove the download step for the spacy
models from the docker file as well.
all recent improvements/changes were made with the /pipeline
endpoint in mind. Make sure that all singular endpoints (e.g. /preprocessing
) also use those features
When I want to remove files from a volume that were created from within the docker container, it is refused: we need an endpoint that allows for deletion of project-folders
add a field to the document_server_config
that governs which field in ES is the document id if no id
field is given
right now the configuration for the negspacy
component is hardcoded. but this should be done in preprocessing_config.
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