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[UI] Supports storage: "inline" for all types of visualizations #3177

Merged
merged 2 commits into from
Feb 27, 2020
Merged

[UI] Supports storage: "inline" for all types of visualizations #3177

merged 2 commits into from
Feb 27, 2020

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Bobgy
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@Bobgy Bobgy commented Feb 27, 2020 •
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/area frontend
/kind feature

Resolves #3133
Related to #3162

Metadata format is consistent with existing inline markdown:

metadata = {
        'outputs': [{
            'storage': 'inline',
            'source': '# Inline Markdown\n[A link](https://www.kubeflow.org/)',
            'type': 'markdown',
        }, {
            'storage': 'inline',
            'source': '<body>Hello, World!</body>',
            'type': 'web-app',
        }]
    }

Tried with the following pipeline.

import kfp
import kfp.components as comp

from typing import NamedTuple


#Define a Python function
def hello_world(name) -> NamedTuple('HelloWorldOutput', [(
        'echo', 'string'), ('mlpipeline_ui_metadata', 'UI_metadata')]):

    import json
    hello_world = """
    <html>
        <body>
            Hello_World
        </body>
    </html>
    """
    metadata = {
        'outputs': [{
            'storage': 'inline',
            'source': '# Inline Markdown\n[A link](https://www.kubeflow.org/)',
            'type': 'markdown',
        }, {
            'storage': 'inline',
            'source': hello_world,
            'type': 'web-app',
        }]
    }
    from collections import namedtuple
    output = namedtuple('HelloWorldOutput', ['echo', 'mlpipeline_ui_metadata'])
    return output(name + ': Hello, Wolrd!', json.dumps(metadata))


hello_world_op = comp.func_to_container_op(hello_world)

import kfp.dsl as dsl


@dsl.pipeline(
    name='Calculation pipeline',
    description='A toy pipeline that performs arithmetic calculations.')
def calc_pipeline(name='Placeholder'):
    #Passing pipeline parameter and a constant value as operation arguments
    add_task = hello_world_op(name)  #Returns a dsl.ContainerOp class instance.


#Specify pipeline argument values
arguments = {'name': 'Bob'}

#Submit a pipeline run
import kfp
client = kfp.Client(
    host='<FILL YOUR HOST HERE>')
client.list_pipelines()
result = client.create_run_from_pipeline_func(calc_pipeline,
                                              arguments=arguments)

print(result)

This change is Reviewable

@Bobgy Bobgy self-assigned this Feb 27, 2020
@Bobgy
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Bobgy commented Feb 27, 2020

/approve

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[APPROVALNOTIFIER] This PR is APPROVED

This pull-request has been approved by: Bobgy

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@rmgogogo
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/lgtm

Awesome!!!

I didn't know we have so fancy feature.

@k8s-ci-robot k8s-ci-robot merged commit 852114e into kubeflow:master Feb 27, 2020
@Bobgy Bobgy deleted the fe_support_inline_html branch February 27, 2020 03:39
This was referenced Feb 28, 2020
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Jeffwan pushed a commit to Jeffwan/pipelines that referenced this pull request Dec 9, 2020
@Bobgy @Jeffwan
[UI] Supports storage: "inline" for all types of visualizations (kube…
e974ac5 
…flow#3177)

* [UI] Supports inline html visualization

* [UI] Support storage: "inline" for all types of visualization
magdalenakuhn17 pushed a commit to magdalenakuhn17/pipelines that referenced this pull request Oct 22, 2023
@sivanantha321
Fix runtime not found for triton due to wrong default protocolVersion (…
b91e2b1 
…kubeflow#3177)

Signed-off-by: Sivanantham Chinnaiyan <sivanantham.chinnaiyan@ideas2it.com>
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@IronPan IronPan Awaiting requested review from IronPan

@neuromage neuromage Awaiting requested review from neuromage

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@rmgogogo rmgogogo

@Bobgy Bobgy

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Support inline sources in all visualizations
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@Bobgy @k8s-ci-robot @rmgogogo