As a pipeline node

"""
Use a Transformation as a Pipeline node.

`pipeline.add(...).transformation(transformation=<id>, **inputs)` references a
stored transformation. Each keyword maps to one of the transformation's
declared input names; the value is an upstream node output (or a literal).
"""

from vectorshift import Transformation
from vectorshift.pipeline import Pipeline

# A transformation with one string input named `text`.
shout = Transformation.new(
    name="shout",
    function_name="shout",
    inputs={"text": "string"},
    outputs={"result": "string"},
    function="def shout(text):\n    return {'result': text.upper()}",
)

# Build the graph: input -> transformation -> output.
pipeline = Pipeline.new(name="shout_pipeline")

input_node = pipeline.add(name="input_node", id="input_node").input(input_type="string")

transform_node = pipeline.add(name="shout", id="shout").transformation(
    transformation=shout.id,   # reference by id
    text=input_node.text,      # wire the `text` input to the input node
)

output_node = pipeline.add(name="output_node", id="output_node").output(
    output_type="string", value=transform_node.output
)

pipeline.save(deploy=True)
print(f"Saved pipeline {pipeline.id} with a transformation node -> {shout.id}")

# Run it end to end.
result = pipeline.run(inputs={"input_node": "hello"})
print(result)

Saved pipeline ... with a transformation node -> ...
{'outputs': {'output_node': 'HELLO'}, 'status': 'success', 'run_id': '...'}