Skip to main content

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.

Prerequisites: Python 3.10+ and a VectorShift account. If you haven’t installed yet, see Installation.

​
Run your first pipeline

1

Install the SDK

pip install vectorshift
2

Set your API key

Generate one at Account → API Keys, then export it:
export VECTORSHIFT_API_KEY="vs-..."
3

Build, save, and run

Paste this into a file (hello.py) and run it.
from vectorshift import Pipeline

p = Pipeline.new(name="Hello pipeline")
query = p.add.input(name="query", input_type="string")
llm = p.add.llm(provider="openai", model="gpt-4o", prompt=query.text)
p.add.output(name="answer", value=llm.response)

p.save()
result = p.run({"query": "What is VectorShift in one sentence?"})
print(result["outputs"]["answer"])

python hello.py
4

See it in the editor

Open the platform — your new pipeline is editable in the visual editor, identical to one built there.
For the best developer experience, enable the mypy plugin. It catches wrong field names on node builders, mismatched types between wired nodes, and agent tools missing required inputs — at edit time, before you save. Drop a mypy.ini with plugins = vectorshift.mypy_plugin and most editors (VS Code, Cursor, PyCharm, Zed) light up SDK-aware errors inline as you type.

​
Now try

Stream tokens

Swap run for stream and yield tokens as they arrive.

Run in the background

start() returns immediately; poll or stream for results.

Turn it into an agent

Add tools and multi-turn conversation.

​
What’s next

Concepts

Pipeline vs Agent vs Session vs Knowledge Base.

Pipeline reference

Every public method.