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Preliminary work for nlp model runtime integration
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033872718e
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@ -25,8 +25,6 @@ def contributions():
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spacy_nlp_user_models = [
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spacy_nlp_user_models = [
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x for x in current_user.spacy_nlp_pipeline_models
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x for x in current_user.spacy_nlp_pipeline_models
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]
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]
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spacy_models = SpaCyNLPPipelineModel.query.all()
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print(spacy_models)
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return render_template(
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return render_template(
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'contributions/contribution_overview.html.j2',
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'contributions/contribution_overview.html.j2',
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tesseract_ocr_user_models=tesseract_ocr_user_models,
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tesseract_ocr_user_models=tesseract_ocr_user_models,
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@ -3,7 +3,8 @@ from app.models import (
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Job,
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Job,
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JobResult,
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JobResult,
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JobStatus,
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JobStatus,
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TesseractOCRPipelineModel
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TesseractOCRPipelineModel,
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SpaCyNLPPipelineModel
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)
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)
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from datetime import datetime
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from datetime import datetime
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from flask import current_app
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from flask import current_app
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@ -103,6 +104,16 @@ def _create_job_service(job):
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models_mount_target = f'/usr/local/share/tessdata/{model.filename}'
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models_mount_target = f'/usr/local/share/tessdata/{model.filename}'
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models_mount = f'{models_mount_source}:{models_mount_target}:ro'
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models_mount = f'{models_mount_source}:{models_mount_target}:ro'
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mounts.append(models_mount)
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mounts.append(models_mount)
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elif job.service == 'spacy-nlp-pipeline':
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model_id = hashids.decode(job.service_args['model'])
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model = SpaCyNLPPipelineModel.query.get(model_id)
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if model is None:
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job.status = JobStatus.FAILED
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return
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models_mount_source = model.path
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models_mount_target = f'/usr/local/share/spacy/models/{model.filename}'
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models_mount = f'{models_mount_source}:{models_mount_target}:ro'
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mounts.append(models_mount)
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''' ### Output mount ### '''
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''' ### Output mount ### '''
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output_mount_source = os.path.join(job.path, 'results')
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output_mount_source = os.path.join(job.path, 'results')
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output_mount_target = '/output'
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output_mount_target = '/output'
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