VectorShift SDK
The Python SDK for building, saving, and running AI pipelines and agents on the VectorShift platform.
Prerequisites: Python 3.10+ and a VectorShift account.
Quickstart
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(name="query").input(input_type="string")
llm = p.add(name="llm").llm(provider="openai", model="gpt-5.4", prompt=query.text)
p.add(name="answer").output(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.
Build with ChatGPT or Claude
Paste this at the start of a ChatGPT or Claude chat, then describe what you want. It points the model at the SDK docs so it builds the right VectorShift object — pipeline, agent, knowledge base, or table — correctly.
You are building with the VectorShift Python SDK. Before writing code, read
https://docs.vectorshift.ai/llms.txt and the SDK reference pages it links.
Follow the documented patterns exactly: use the builder API, correct node and
field names, and the right object type for my request (pipeline, agent,
knowledge base, or table). Install with `pip install vectorshift` and
authenticate via the VECTORSHIFT_API_KEY environment variable. Then build,
save, and run what I describe, returning one complete runnable script.
My request:
Documentation
Full documentation — streaming, background runs, agents, knowledge bases, and the complete API reference — lives at docs.vectorshift.ai/sdk.
2 maintainers
Metadata
2 maintainers
Release files for vectorshift 0.1.15
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| vectorshift-0.1.15.tar.gz | 2.4 MB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| vectorshift-0.1.15-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 5.4 MB
Release files / vectorshift-0.1.15.tar.gz
| Download URL | vectorshift-0.1.15.tar.gz |
|---|---|
| Size | 2.4 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Release files / vectorshift-0.1.15-py3-none-any.whl
| Download URL | vectorshift-0.1.15-py3-none-any.whl |
|---|---|
| Size | 2.9 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Security for vectorshift 0.1.15
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