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Merge pull request #34 from CogStack/production
release: Prepare release 0.2.0 chore: post release tidy up
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.github/workflows/release.yaml

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@@ -42,6 +42,7 @@ jobs:
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- name: Install dependencies
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run: |
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uv sync --extra dev --extra docs --extra llm
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uv run python -m ensurepip
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- name: Run unit tests
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run: |
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uv run pytest -v tests/app --cov --cov-report=html:coverage_reports #--random-order

README.md

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@@ -34,7 +34,7 @@ cms train --help
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## Download models:
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CMS runs the NLP model packaged in a ZIP file or a Gzipped tarball. To download pretrained GA models, please follow the [instructions](https://github.com/CogStack/MedCAT#available-models). Contact [Cogstack]([email protected])
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CMS runs the NLP model packaged in a ZIP file or a Gzipped tarball. To download pretrained GA models, please follow the [instructions](https://medcat.readthedocs.io/en/latest/main.html#models). Contact [Cogstack]([email protected])
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if you are interested in trying out Alpha release such as the de-identification model. To serve or train existing HuggingFace NER models, you can
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package the model, either downloaded from the Hugging Face Hub or cached locally, as a ZIP or Gzipped tarball by running:
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```commandline

docker-compose-mlflow.yml

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condition: "service_healthy"
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mlflow-ui:
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image: cogstacksystems/cogstack-mlflow-ui:0.1.1
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image: cogstacksystems/cogstack-mlflow-ui:0.2.0
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restart: always
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networks:
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- cogstack-model-serve_cms

docker-compose.yml

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services:
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medcat-snomed:
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image: cogstacksystems/cogstack-modelserve:0.1.1
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image: cogstacksystems/cogstack-modelserve:0.2.0
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labels:
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- org.cogstack.model-serve=medcat_snomed
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- org.cogstack.model-name=SNOMED MedCAT model
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- http_proxy=$HTTP_PROXY
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- https_proxy=$HTTPS_PROXY
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- no_proxy=mlflow-ui,minio,graylog,auth-db,localhost
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- COLUMNS=200
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expose:
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- 8000
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ports:
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start_period: 60s
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medcat-icd10:
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image: cogstacksystems/cogstack-modelserve:0.1.1
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image: cogstacksystems/cogstack-modelserve:0.2.0
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labels:
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- org.cogstack.model-serve=medcat_icd10
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- org.cogstack.model-name=ICD-10 MedCAT model
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- http_proxy=$HTTP_PROXY
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- https_proxy=$HTTPS_PROXY
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- no_proxy=mlflow-ui,minio,graylog,auth-db,localhost
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- COLUMNS=200
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expose:
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- 8000
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ports:
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start_period: 60s
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medcat-opcs4:
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image: cogstacksystems/cogstack-modelserve:0.1.1
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image: cogstacksystems/cogstack-modelserve:0.2.0
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labels:
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- org.cogstack.model-serve=medcat_opcs4
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- org.cogstack.model-name=OPCS-4 MedCAT model
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- http_proxy=$HTTP_PROXY
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- https_proxy=$HTTPS_PROXY
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- no_proxy=mlflow-ui,minio,graylog,auth-db,localhost
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- COLUMNS=200
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expose:
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- 8000
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ports:
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start_period: 60s
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medcat-deid:
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image: cogstacksystems/cogstack-modelserve:0.1.1
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image: cogstacksystems/cogstack-modelserve:0.2.0
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labels:
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- org.cogstack.model-serve=medcat_deid
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- org.cogstack.model-name=De-Identification MedCAT model
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- http_proxy=$HTTP_PROXY
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- https_proxy=$HTTPS_PROXY
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- no_proxy=mlflow-ui,minio,graylog,auth-db,localhost
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- COLUMNS=200
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expose:
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- 8000
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ports:
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start_period: 60s
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medcat-umls:
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image: cogstacksystems/cogstack-modelserve:0.1.1
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image: cogstacksystems/cogstack-modelserve:0.2.0
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labels:
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- org.cogstack.model-serve=medcat_umls
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- org.cogstack.model-name=UMLS MedCAT model
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- http_proxy=$HTTP_PROXY
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- https_proxy=$HTTPS_PROXY
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- no_proxy=mlflow-ui,minio,graylog,auth-db,localhost
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- COLUMNS=200
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expose:
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- 8000
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ports:
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start_period: 60s
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huggingface-ner:
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image: cogstacksystems/cogstack-modelserve:0.1.1
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image: cogstacksystems/cogstack-modelserve:0.2.0
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labels:
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- org.cogstack.model-serve=huggingface_ner
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- org.cogstack.model-name=HuggingFace NER model
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- http_proxy=$HTTP_PROXY
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- https_proxy=$HTTPS_PROXY
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- no_proxy=mlflow-ui,minio,graylog,auth-db,localhost
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- COLUMNS=200
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expose:
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ports:
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start_period: 60s
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huggingface-llm:
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image: cogstacksystems/cogstack-modelserve:0.1.0
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image: cogstacksystems/cogstack-modelserve:0.2.0
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labels:
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- org.cogstack.model-serve=huggingface_llm
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- org.cogstack.model-name=HuggingFace LLM model
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- ./docker/huggingface-llm/.env:/app/envs/.env:ro
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environment:
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- BASE_MODEL_FULL_PATH=$MODEL_PACKAGE_FULL_PATH
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- CMS_MODEL_TYPE=huggingface_ner
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- CMS_MODEL_NAME=HuggingFace NER model
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- CMS_MODEL_TYPE=huggingface_llm
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- CMS_MODEL_NAME=HuggingFace LLM model
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- CMS_STREAMABLE=${CMS_STREAMABLE:-false}
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- AWS_ACCESS_KEY_ID=$AWS_ACCESS_KEY_ID
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- AWS_SECRET_ACCESS_KEY=$AWS_SECRET_ACCESS_KEY
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- http_proxy=$HTTP_PROXY
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- https_proxy=$HTTPS_PROXY
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- no_proxy=mlflow-ui,minio,graylog,auth-db,localhost
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- COLUMNS=200
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expose:
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- 8000
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ports:

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