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Update the default buildpacks to use paketo and add a tip for tilt #119

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Update the default buildpacks to use paketo and add a tip for tilt #119

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73bc0c4
Update the default buildpacks to use paketo and add a tip for tilt
sambhav Feb 24, 2022
698d3f8
Use paketo full builder
sambhav Feb 26, 2022
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4 changes: 3 additions & 1 deletion docs/modelserving/v1beta1/custom/custom_model/README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -43,7 +43,7 @@ to run the image build on the cloud and continuously build/deploy new versions f

### Use pack to build and push the custom model server image
```bash
pack build --builder=heroku/buildpacks:20 ${DOCKER_USER}/custom-model:v1
pack build --builder paketobuildpacks/builder:full ${DOCKER_USER}/custom-model:v1
docker push ${DOCKER_USER}/custom-model:v1
```

Expand Down Expand Up @@ -93,6 +93,8 @@ curl localhost:8080/v1/models/custom-model:predict -d @./input.json

{"predictions": [[14.861763000488281, 13.94291877746582, 13.924378395080566, 12.182709693908691, 12.00634765625]]}
```
!!! tip
You can also use [`tilt`](https://tilt.dev/) along with `pack` and [`paketo`](https://paketo.io/) Buildpacks allowing you make code changes and have them reflected live in your custom inference service. For more details see - [Paketo Python Buildpacks - Enable Process Reloading](https://paketo.io/docs/howto/python/#enable-process-reloading)
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This looks cool, you can create the Tiltfile like following for continuous dev development, we might want to add a bit more instruction for how to do this.

load('ext://pack', 'pack')
k8s_kind('InferenceService', api_version='serving.kserve.io/v1beta1', image_json_path='{.spec.predictor.containers[*].image}')

allow_k8s_contexts('docker-desktop')

pack(
  'yuzisun/tilt-demo-2022',
  ignore=[
    'Tiltfile',
    'service.yaml',
    '.*',
  ],
  live_update = [
    sync('.', '/workspace'),
  ],
  deps=["."],
)
k8s_yaml('service.yaml')
k8s_resource('tilt-demo', extra_pod_selectors={'serving.kserve.io/inferenceservice':'tilt-demo'})

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The tiltfile I am using looks a bit like -

# -*- mode: Python -*-

version_settings(constraint='>=0.22.1')
load('ext://pack', 'pack')
docker_compose('docker-compose.yml')

pack('myapp',
  builder="paketobuildpacks/builder:full",
  live_update=[
    sync('.', '/workspace'),
  ]
)


## Deploy the Custom Predictor on KServe
### Create the InferenceService
Expand Down