> ## Documentation Index
> Fetch the complete documentation index at: https://llm-tools.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# 🎬 TwelveLabs Video

To add any video to your app, use the `TwelveLabsVideoLoader`. It analyses the video with the [TwelveLabs](https://twelvelabs.io) Pegasus video understanding model — which watches the visuals, motion and audio — and loads the resulting description into your RAG application. This lets you run RAG over video content directly from a public URL, without a separate transcription step.

* Sign up for an account with TwelveLabs and grab an API key. There's a generous free tier at [twelvelabs.io](https://twelvelabs.io).

* Set the key in the environment variable `TWELVELABS_API_KEY` (or pass it directly to the loader).

```bash theme={null}
TWELVELABS_API_KEY="<YOUR_KEY>"
```

## Install TwelveLabs addon

```bash theme={null}
npm install @llm-tools/embedjs-twelvelabs
```

## Usage

```ts theme={null}
import { RAGApplicationBuilder } from '@llm-tools/embedjs';
import { OpenAiEmbeddings } from '@llm-tools/embedjs-openai';
import { HNSWDb } from '@llm-tools/embedjs-hnswlib';
import { TwelveLabsVideoLoader } from '@llm-tools/embedjs-twelvelabs';

const app = await new RAGApplicationBuilder()
.setModel(SIMPLE_MODELS.OPENAI_GPT4_O)
.setEmbeddingModel(new OpenAiEmbeddings())
.setVectorDatabase(new HNSWDb())
.build();

app.addLoader(new TwelveLabsVideoLoader({ url: 'https://example.com/video.mp4' }))
```

You can customise the analysis with an optional `prompt`, `model` (`pegasus1.2` or `pegasus1.5`) and `maxTokens`:

```ts theme={null}
app.addLoader(new TwelveLabsVideoLoader({
    url: 'https://example.com/video.mp4',
    prompt: 'Summarize the key moments in this video.',
    model: 'pegasus1.2',
    maxTokens: 2048,
}))
```