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

# W&B Weave

> Track, test, and improve language model apps with W&B Weave

W\&B Weave is an observability and evaluation platform that helps you track, evaluate, and improve your LLM application. With Weave, you can:

* [Observe and debug](/weave/quickstart) your LLM application
* [Evaluate](/weave/tutorial-eval) your application’s responses using LLM judges and custom scorers

## Get started

The following docs guide you through the basics of how to use Weave's suite of tools.

<CardGroup cols={3}>
  <Card title="Quickstart: Track LLM inputs & outputs" icon="chart-line" href="/weave/quickstart">
    Start by tracing a basic call to an LLM and reviewing the data in your W\&B account.
  </Card>

  <Card title="Get started evaluating your app" icon="clipboard-check" href="/weave/tutorial-eval">
    Learn how to build an evaluation pipeline using Weave scorers to test and track your application's performance.
  </Card>

  <Card title="Evaluate a RAG application" icon="search" href="/weave/tutorial-rag">
    Build and evaluate RAG applications using Weave with LLM judges to measure retrieval quality.
  </Card>
</CardGroup>

## Install Weave

W\&B Weave provides Python and TypeScript libraries. To install the Weave library, run the following command:

<Tabs>
  <Tab title="Python">
    ```bash theme={null}
    pip install weave
    ```
  </Tab>

  <Tab title="TypeScript">
    ```bash theme={null}
    pnpm install weave
    ```
  </Tab>
</Tabs>

To start using the Weave library, create a [Weights & Biases (W\&B) account](https://wandb.ai) and an [API key at User Settings](https://wandb.ai/settings). The API key allows you to authenticate to your W\&B account and start sending data to it.