---
title: Quick start
description: Install the Pictograph SDK, get an API key, and run your first end-to-end pipeline in five minutes.
section: Get Started
order: 1
---
## Install

```bash
pip install pictograph
```

For the CLI + Rich-formatted output:

```bash
pip install 'pictograph[cli]'
```

For the agent toolkit (Claude Agent SDK + openai-agents):

```bash
pip install 'pictograph[agents]'
```

## Get an API key

1. Sign in at [app.pictograph.io](https://app.pictograph.io).
2. Navigate to **Settings → API Keys**.
3. Click **Create API Key**, give it a role (`viewer` / `member` / `admin` / `owner`).
4. Copy the key (`pk_live_…`) — it is only shown once.

```bash
export PICTOGRAPH_API_KEY=pk_live_…
```

Or use the CLI's interactive setup:

```bash
pictograph login
```

This writes `~/.pictograph/config.toml`.

## First call

```python
from pictograph import Client

client = Client()  # reads PICTOGRAPH_API_KEY
datasets = client.datasets.list(limit=10)
print(datasets)
```

## End-to-end: upload, annotate, train

The headline workflow — one function call:

```python
from pictograph import Client
from pictograph.workflows import full_pipeline

client = Client()
report = full_pipeline(
    client,
    dataset_name="road-signs",
    folder="./road_signs",
    classes=[("stop_sign", "bbox"), ("yield", "bbox")],
    pipeline="yolox",
)

if report.success:
    print(f"Trained model: {report.model.id}")
else:
    print(report.credit_skip_reason or "see sub-reports")
```

Each phase short-circuits on failure and the `PipelineReport` carries every sub-report. See [`full_pipeline`](/docs/workflows/full-pipeline.md) for every parameter.

## CLI equivalent

```bash
pictograph login                                # one-time
pictograph datasets list
pictograph train start road-signs --pipeline yolox --gpu a10g
pictograph models download <model-id> -o ./yolox.onnx
```

## Next

- [Workflows](/docs/workflows.md) — the four batteries-included helpers
- [Agents](/docs/agents.md) — wire Pictograph into Claude or OpenAI
- [Annotation format](/docs/annotation-format.md) — the canonical JSON schema
- [Credits](/docs/api-reference/credits.md) — budget gating and cost estimation