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KabongosalomonKabongosalomon
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Merge pull request #87 from espoirMur/feat/integrate-m2m-models
Feat/integrate m2m models
2 parents 1c7ad22 + 2f1053a commit 4f501f9

30 files changed

+2905
-13
lines changed

‎.gitignore

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@@ -102,4 +102,11 @@ src/server/core/models/joeynmt
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.env.prod
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*.sqlite
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*.sqlite
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### ignore model export
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onnx/
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*.onnx
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model_store/
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logs/

‎.python-version

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3.10.7

‎docker-compose.yml

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@@ -10,6 +10,7 @@ services:
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command: python manage.py run -h 0.0.0.0
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volumes:
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- './src/server:/usr/src/app'
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- './models/joeynmt:/usr/src/app/models/joeynmt'
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ports:
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- 5000:5000
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@@ -45,4 +46,4 @@ services:
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# we configured a volume. This config will bind
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# postgres_data to the "/var/lib/postgresql/data/" directory in the container.
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volumes:
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postgres_data:
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postgres_data:

‎kubernetes/ingress-def.yml

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apiVersion: networking.k8s.io/v1
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kind: Ingress
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metadata:
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name: seldon-ingress
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namespace: seldon
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spec:
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rules:
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- host: seldon-ingress.com
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http:
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paths:
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- path: "/"
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pathType: Prefix
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backend:
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service:
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name: iris-model-sklearn-iris-predictor
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port:
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number: 8000

‎kubernetes/sample-server.yaml

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apiVersion: machinelearning.seldon.io/v1
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kind: SeldonDeployment
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metadata:
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name: iris-model
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namespace: seldon
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spec:
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name: iris
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annotations:
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prometheus.io/scrape: "false"
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predictors:
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- componentSpecs:
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- spec:
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containers:
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- env:
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- name: SELDON_LOG_LEVEL
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value: DEBUG
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- name: SELDON_DEBUG
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value: 'True'
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- name: FLASK_DEBUG
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value: 'True'
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image: seldonio/sklearn-iris:0.3
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imagePullPolicy: IfNotPresent
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name: sklearn-iris-classifier
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graph:
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endpoint:
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type: REST
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name: sklearn-iris-classifier
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type: MODEL
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name: sklearn-iris-predictor
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replicas: 1

‎onnx-export.ipynb

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Large diffs are not rendered by default.

‎requirements-python3.10.txt

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aiohttp==3.8.4
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aiosignal==1.3.1
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appnope==0.1.3
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asttokens==2.2.1
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async-timeout==4.0.2
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attrs==22.2.0
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backcall==0.2.0
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captum==0.6.0
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certifi==2022.12.7
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cffi==1.15.1
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charset-normalizer==3.0.1
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click==8.0.4
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coloredlogs==15.0.1
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comm==0.1.2
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contourpy==1.0.7
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cryptography==3.4.8
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cycler==0.11.0
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datasets==2.10.0
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debugpy==1.6.6
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decorator==5.1.1
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dill==0.3.6
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enum-compat==0.0.3
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executing==1.2.0
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filelock==3.9.0
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Flask==2.2.3
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Flask-Cors==3.0.10
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Flask-OpenTracing==1.1.0
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flatbuffers==1.12
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fonttools==4.38.0
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frozenlist==1.3.3
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fsspec==2023.1.0
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grpcio==1.51.3
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grpcio-opentracing==1.1.4
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grpcio-reflection==1.34.1
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gunicorn==20.1.0
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huggingface-hub==0.12.1
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humanfriendly==10.0
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idna==3.4
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ipykernel==6.21.2
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ipython==8.10.0
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itsdangerous==2.1.2
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jaeger-client==4.4.0
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jedi==0.18.2
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Jinja2==3.1.2
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jsonschema==3.2.0
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jupyter_client==8.0.3
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jupyter_core==5.2.0
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kiwisolver==1.4.4
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MarkupSafe==2.1.2
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matplotlib==3.7.0
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matplotlib-inline==0.1.6
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mpmath==1.2.1
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multidict==6.0.4
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multiprocess==0.70.14
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nest-asyncio==1.5.6
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numpy==1.23.5
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onnx==1.13.1
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onnxruntime==1.13.1
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onnxruntime-tools==1.7.0
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opentracing==2.4.0
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optimum==1.6.4
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ort-nightly==1.11.0.dev20220320001
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packaging==23.0
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pandas==1.5.3
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parso==0.8.3
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pexpect==4.8.0
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pickleshare==0.7.5
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Pillow==9.4.0
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platformdirs==3.0.0
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prometheus-client==0.8.0
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prompt-toolkit==3.0.37
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protobuf==3.20.3
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psutil==5.9.4
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ptyprocess==0.7.0
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pure-eval==0.2.2
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py-cpuinfo==9.0.0
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py3nvml==0.2.7
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pyarrow==11.0.0
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pycodestyle==2.10.0
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pycparser==2.21
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Pygments==2.14.0
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pyparsing==3.0.9
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pyrsistent==0.19.3
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python-dateutil==2.8.2
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pytz==2022.7.1
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PyYAML==5.4.1
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pyzmq==25.0.0
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regex==2022.10.31
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requests==2.28.2
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responses==0.18.0
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seldon-core==1.15.0
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sentencepiece==0.1.97
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six==1.16.0
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stack-data==0.6.2
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sympy==1.11.1
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threadloop==1.0.2
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thrift==0.16.0
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tokenizers==0.13.2
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torch==1.13.1
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torch-model-archiver==0.7.1
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torch-workflow-archiver==0.2.7
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torchserve==0.7.1
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tornado==6.2
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tqdm==4.64.1
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traitlets==5.9.0
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transformers==4.26.1
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typing_extensions==4.5.0
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urllib3==1.26.14
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wcwidth==0.2.6
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Werkzeug==2.2.3
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xmltodict==0.13.0
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xxhash==3.2.0
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yarl==1.8.2

‎src/client/src/components/translateCard.js

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@@ -77,7 +77,7 @@ export default function TranslateCard() {
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})
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.then(res => res.json())
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.then(data => {
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// console.log({ data })
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console.log({ data })
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// do something here
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setTranslation(data.output)
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})
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</div>
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</Container>
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)
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}
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}

‎src/client/webpack.config.js

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proxy: {
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'/': {
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// target: 'http://[::1]:5000',
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target: 'http://localhost:5000',
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// todo: make the ip a configuration environment variable
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target: 'http://45.147.99.147:5000',
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// target: 'http://127.0.0.1:5000',
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bypass: function (req, res, proxyOptions) {
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if (req.headers.accept.indexOf('html') !== -1) {

‎src/m_to_m_models/Dockerfile

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FROM python:3.10 as base
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LABEL maintainer="Espoir Murhabazi<espoir.mur [] gmail>"
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# Never prompt the user for choices on installation/configuration of packages
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ENV DEBIAN_FRONTEND noninteractive
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ENV PYTHONUNBUFFERED=1 \
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PORT=9000 \
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PYTHONDONTWRITEBYTECODE=1 \
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PIP_NO_CACHE_DIR=off \
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PIP_DISABLE_PIP_VERSION_CHECK=on \
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PIP_DEFAULT_TIMEOUT=100
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FROM base AS python-deps
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RUN apt-get update \
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&& apt-get install --no-install-recommends -y \
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curl \
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build-essential\
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software-properties-common
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RUN python -m venv /opt/venv
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# Make sure we use the virtualenv:
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ENV PATH="/opt/venv/bin:$PATH"
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# Install pip
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COPY requirements.txt ./
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RUN pip install --upgrade pip
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RUN pip install -r requirements.txt
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FROM base AS runtime
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# copy nltk data
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COPY --from=python-deps /opt/venv /opt/venv
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RUN useradd --create-home masakhane
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RUN usermod -aG sudo masakhane
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RUN mkdir /home/masakhane/translation_app/
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ENV WORKING_DIR=/home/masakhane/translation_app/
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ENV PATH="${WORKING_DIR}:$PATH"
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ENV PATH="/opt/venv/bin:$PATH"
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ENV PYTHONPATH="/opt/venv/bin:$PYTHONPATH"
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ENV PYTHONPATH="${PYTHONPATH}:${WORKING_DIR}"
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ENV MODEL_NAME model_handlers.OptimizedM100Model
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ENV SERVICE_TYPE MODEL
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COPY model_handlers.py ${WORKING_DIR}
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WORKDIR ${WORKING_DIR}
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RUN chown -R masakhane:masakhane ${WORKING_DIR}
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RUN chmod -R 777 ${WORKING_DIR}
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USER masakhane
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EXPOSE 9000 5000
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CMD exec seldon-core-microservice $MODEL_NAME --service-type $SERVICE_TYPE

‎src/m_to_m_models/app.py

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from flask import Flask, jsonify, request
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from flask_cors import CORS
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import logging
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logger = logging.getLogger(__name__)
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def create_app(model_handler):
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app = Flask(__name__, static_url_path="")
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CORS(app)
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@app.route("/predict", methods=["GET", "POST"])
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def predict():
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request_data = request.get_json()
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logger.debug("REST Request: %s", request)
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response = model_handler.predict_raw(request_data)
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json_response = jsonify(response)
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if (
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isinstance(response, dict)
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and "status" in response
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and "code" in response["status"]
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):
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json_response.status_code = response["status"]["code"]
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logger.debug("REST Response: %s", response)
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return json_response
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return app

‎src/m_to_m_models/kubernetes/deployment.yaml

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apiVersion: machinelearning.seldon.io/v1
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kind: SeldonDeployment
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metadata:
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name: translation-deployment
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namespace: masakhane
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spec:
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name: translation-worker
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predictors:
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- componentSpecs:
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- spec:
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containers:
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- image: masakhane/translation:alpha
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name: translation-container
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imagePullPolicy: IfNotPresent
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env:
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- name: TRANSFORMERS_CACHE
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value: "/models_datastore/.cache"
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- name: GUNICORN_WORKERS
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value: '1'
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- name: GRPC_WORKERS
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value: '0'
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- name: SELDON_LOG_LEVEL
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value: DEBUG
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- name: SELDON_DEBUG
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value: 'True'
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- name: FLASK_DEBUG
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value: 'True'
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volumeMounts:
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- mountPath: "/models_datastore/" # mount the cache volume here
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name: translation-volume-storage
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resources:
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requests:
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memory: 8Gi
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cpu: 3
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limits:
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memory: 9Gi
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cpu: 4
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terminationGracePeriodSeconds: 1
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volumes:
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- name: translation-volume-storage
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persistentVolumeClaim:
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claimName: masakhane-model-cache-volume-claim
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graph:
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envSecretRefName: masakhane-container-secret
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children: []
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endpoint:
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type: REST
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name: translation-container
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type: MODEL
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parameters:
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- name: model_path
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type: STRING
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value: "/models_datastore/" # this should come form volume.
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- name: src_lang
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type: STRING
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value: "en"
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- name: tgt_lang
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type: STRING
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value: "sw"
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labels:
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version: v1
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name: translation-predictor
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replicas: 1

‎src/m_to_m_models/kubernetes/secret.yaml

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apiVersion: v1
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kind: Secret
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metadata:
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name: masakhane-container-secret
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namespace: masakhane
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type: Opaque
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stringData:
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RCLONE_CONFIG_S3_TYPE: s3
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RCLONE_CONFIG_S3_PROVIDER: minio
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RCLONE_CONFIG_S3_ENV_AUTH: "false"
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RCLONE_CONFIG_S3_ACCESS_KEY_ID: minioadmin
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RCLONE_CONFIG_S3_SECRET_ACCESS_KEY: minioadmin
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RCLONE_CONFIG_S3_ENDPOINT: http://minio.minio-system.svc.cluster.local:9000

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