Documentation Index
Fetch the complete documentation index at: https://docs.vectorshift.ai/llms.txt
Use this file to discover all available pages before exploring further.
import asyncio
from vectorshift.pipeline import Pipeline
PIPELINE_NAME = "bg_run_async_example"
async def main():
try:
pipeline = await Pipeline.afetch(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 = await Pipeline.anew(name=PIPELINE_NAME)
print(f"Pipeline created: id={pipeline.id}, branch_id={pipeline.branch_id}")
inp = pipeline.add(name="input_0", id="input_0").input(input_type="string")
llm = pipeline.add(name="llm", id="llm").llm(
provider="openai", model="gpt-4o", prompt=inp.text
)
pipeline.add(name="output_0", id="output_0").output(
output_type="string", value=llm.response
)
await pipeline.asave(deploy=True)
# Start in background
handler = await pipeline.astart(
inputs={"input_0": "Tell me a fun fact about oceans."}
)
print(f"Task ID: {handler.task_id}")
# Check status
status = await handler.arun_status()
print(f"Status: {status['status']}")
# Wait for completion
result = await handler.aresult(poll_interval=2.0, timeout=60.0)
print(f"Result: {result}")
asyncio.run(main())
Source:
examples/pipelines/background_run_async.py in the SDK repo.