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What this builds. A main pipeline that wraps a previously-saved sub-pipeline as a PipelineNode, forwarding input_0 through and reading the sub-pipeline’s output_0 back out. You’ll end up with. A saved main-pipeline-9 pipeline whose run delegates to the sub-pipeline and returns whatever it produces. 
#
import vectorshift

from vectorshift import Pipeline
from vectorshift.pipeline import InputNode, OutputNode, PipelineNode

vectorshift.api_key = 'your api key here'


sub_pipeline = Pipeline.fetch(name="your sub pipeline")

print(sub_pipeline)

# output = sub_pipeline.run({"input_0": "What is the capital of France?"})

# print(output)


input_node = InputNode(input_type="string", node_name="input_0")

pipeline_node = PipelineNode(
    pipeline_id=sub_pipeline.id, node_name="sub_pipeline", input_0=input_node.text
)

output_node = OutputNode(node_name="output_0", value=pipeline_node.output_0)

PIPELINE_NAME = "main-pipeline-9"
try:
    main_pipeline = Pipeline.fetch(name=PIPELINE_NAME)
    print(
        f"Pipeline fetched: id={main_pipeline.id}, branch_id={main_pipeline.branch_id}"
    )
except Exception as e:
    print(f"Error fetching pipeline: {e}")
    main_pipeline = Pipeline.new(
        name=PIPELINE_NAME, nodes=[input_node, pipeline_node, output_node]
    )
    print(
        f"Pipeline created: id={main_pipeline.id}, branch_id={main_pipeline.branch_id}"
    )


main_output = main_pipeline.run(inputs={"input_0": "What is the capital of France?"})

print(main_output)

​
Expected output

<Pipeline ...>
Pipeline created: id=..., branch_id=...
{'outputs': {'output_0': '...'}, 'status': 'success', 'run_id': '...'}
PipelineNode exposes the sub-pipeline’s outputs as attributes (pipeline_node.output_0), so wiring is just like any other node.

​
See also

Sub-pipelines (list mode)

Run the sub-pipeline once per element in a list.

AI routing node

Route to different sub-pipelines based on intent.

Pipeline reference

Full method surface.