from vectorshift.pipeline import Pipeline
# Fetch the pipeline if it already exists, otherwise create it
PIPELINE_NAME = "llm-pipeline"
try:
pipeline = Pipeline.fetch(name=PIPELINE_NAME)
print(f"Pipeline fetched: id={pipeline.id}, branch_id={pipeline.branch_id}")
except Exception as e:
print(f"Error fetching pipeline: {e}")
pipeline = Pipeline.new(name=PIPELINE_NAME)
print(f"Pipeline created: id={pipeline.id}, branch_id={pipeline.branch_id}")
input_node = pipeline.add(name="input_node").input(input_type="string")
llm = pipeline.add(name="llm_node").llm(
provider="openai",
model="gpt-4o-mini",
system="You are a helpful assistant. Reply in one short sentence.",
prompt=input_node.text,
)
pipeline.add(name="output_node").output(output_type="string", value=llm.response)
pipeline.save(deploy=True)
result = pipeline.run(inputs={"input_node": "Say hello in French."})
print(result)
Source:
examples/pipelines/llm_pipeline.py in the SDK repo.