> ## 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.
# Quickstart
> From zero to a running pipeline in 60 seconds.
**Prerequisites:** Python 3.10+ and a VectorShift account. If you haven't installed yet, see [Installation](/sdk/installation).
## Run your first pipeline
Pick where you're writing code — the pipeline you build is identical in each, and shows up in the [platform editor](https://app.vectorshift.ai) either way.
```bash theme={"languages":{}}
pip install vectorshift
```
Generate one at [Account → API Keys](https://app.vectorshift.ai/account/api-keys), then export it:
```bash theme={"languages":{}}
export VECTORSHIFT_API_KEY="vs-..."
```
Paste this into a file (`hello.py`) and run it.
```python theme={"languages":{}}
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-5.1", 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"])
```
```bash theme={"languages":{}}
python hello.py
```
Open the [platform](https://app.vectorshift.ai) — your new pipeline is editable in the visual editor, identical to one built there.
In a new [Colab notebook](https://colab.research.google.com), run this in the first cell:
```python theme={"languages":{}}
!pip install vectorshift
```
Generate one at [Account → API Keys](https://app.vectorshift.ai/account/api-keys). Use `getpass` so the key isn't saved in the notebook:
```python theme={"languages":{}}
import os
from getpass import getpass
os.environ["VECTORSHIFT_API_KEY"] = getpass("VectorShift API key: ")
```
Prefer Colab's **🔑 Secrets** panel? Store it as `VECTORSHIFT_API_KEY`, then `os.environ["VECTORSHIFT_API_KEY"] = userdata.get("VECTORSHIFT_API_KEY")` after `from google.colab import userdata`.
Paste this into the next cell and run it.
```python theme={"languages":{}}
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-5.1", 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"])
```
Open the [platform](https://app.vectorshift.ai) — your new pipeline is editable in the visual editor, identical to one built there.
Start a new **Python** Repl at [replit.com](https://replit.com).
Add `vectorshift` from the **Packages** pane, or just import it — Replit installs it on first run. You can also run it in the Shell:
```bash theme={"languages":{}}
pip install vectorshift
```
Open **Tools → Secrets**, add a secret named `VECTORSHIFT_API_KEY` with your key from [Account → API Keys](https://app.vectorshift.ai/account/api-keys). Replit injects secrets as environment variables, so the SDK picks it up automatically.
Paste this into `main.py` and click **Run**.
```python theme={"languages":{}}
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-5.1", 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"])
```
**For the best developer experience, enable the [mypy plugin](/sdk/installation#type-checking-with-mypy).** 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
Swap `run` for `stream` and yield tokens as they arrive.
`start()` returns immediately; poll or stream for results.
Add tools and multi-turn conversation.
## What's next
Pipeline vs Agent vs Session vs Knowledge Base.
Every public method.
## Building with AI
Want ChatGPT or Claude to build a pipeline, agent, knowledge base, or table for you? Paste this prompt first, then describe what you want — it points the model at the SDK docs and `llms.txt` so it follows the documented patterns.
```text theme={"languages":{}}
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:
```