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To add any video to your app, use the TwelveLabsVideoLoader. It analyses the video with the TwelveLabs 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.
  • Set the key in the environment variable TWELVELABS_API_KEY (or pass it directly to the loader). 
TWELVELABS_API_KEY="<YOUR_KEY>"

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Install TwelveLabs addon

npm install @llm-tools/embedjs-twelvelabs

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Usage

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