> ## Documentation Index
> Fetch the complete documentation index at: https://docs.woodwide.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Console

> Use the Wood Wide web console to upload data, train models, and manage account settings.

The [Wood Wide console](https://console.woodwide.ai) is the web UI for the same workflow as the API — upload a dataset, train a model, run inference. Use it to explore data, manage API keys, and configure platform settings without writing code.

<CardGroup cols={2}>
  <Card title="Open console" icon="window" href="https://console.woodwide.ai">
    Sign in and start from your workspace.
  </Card>

  <Card title="API keys" icon="key" href="https://console.woodwide.ai/settings?tab=api-keys">
    Create keys for the API, SDK, CLI, and agent tools.
  </Card>
</CardGroup>

***

## When to use the console

Use the console when you want a UI for setup and exploration — uploading files, inspecting datasets, training a first model, or credentialing a warehouse connection.

For production integrations, automation, or custom backends, use the [API quickstart](/api-reference/getting-started), [Python SDK](/sdk-quickstart), or [CLI](/cli) instead. You can mix both: explore in the console, then call the same datasets and models from code.

***

## Common tasks

<Steps>
  <Step title="Create an API key">
    Open **Settings** → **API keys** and create a key. Use it for HTTP requests, the Python SDK, CLI, [MCP](/mcp-connector), and [SKILL.md](/skill-md). See the [API quickstart](/api-reference/getting-started#1-get-your-api-key) for header and env var setup.
  </Step>

  <Step title="Upload a dataset">
    Upload CSV or Parquet from the console, or import from a warehouse or bucket via [Connections](/connection).
  </Step>

  <Step title="Train and infer">
    Train a model on the dataset, then run inference from the console. The same dataset and model IDs work in API, SDK, and CLI calls.
  </Step>
</Steps>

***

## Related docs

* [Connections](/connection) — import from BigQuery, Snowflake, S3, and other sources
* [API quickstart](/api-reference/getting-started) — same workflow with curl, JavaScript, or Python
* [CLI](/cli) — script datasets, training, and inference with `wwai`