VoyageAI ↗

    import chromadb.utils.embedding_functions as embedding_functions
    voyageai_ef  = embedding_functions.VoyageAIEmbeddingFunction(api_key="YOUR_API_KEY",  model_name="voyage-3-large")
    voyageai_ef(input=["document1","document2"])
    ```
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  <span class="tab-start" data-tab-title="TypeScript"></span>
```typescript
    // npm install @chroma-core/voyageai

    import { VoyageAIEmbeddingFunction } from "@chroma-core/voyageai";

    const embedder = new VoyageAIEmbeddingFunction({
        apiKey: "apiKey",
        modelName: "model_name",
    });

    // use directly
    const embeddings = embedder.generate(["document1", "document2"]);

    // pass documents to query for .add and .query
    const collection = await client.createCollection({
        name: "name",
        embeddingFunction: embedder,
    });
    const collectionGet = await client.getCollection({
        name: "name",
        embeddingFunction: embedder,
    });
    ```
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<span class="tab-group-end"></span>

### Multilingual model example


  ```python
  voyageai_ef  = embedding_functions.VoyageAIEmbeddingFunction(
      api_key="YOUR_API_KEY",
      model_name="voyage-3-large"
  )

  multilingual_texts  = [
      'Hello from VoyageAI!', 'مرحباً من VoyageAI!!',
      'Hallo von VoyageAI!', 'Bonjour de VoyageAI!',
      '¡Hola desde VoyageAI!', 'Olá do VoyageAI!',
      'Ciao da VoyageAI!', '您好，来自 VoyageAI！',
      'कोहिअर से VoyageAI!'
  ]

  voyageai_ef(input=multilingual_texts)

import { VoyageAIEmbeddingFunction } from "chromadb";

const embedder = new VoyageAIEmbeddingFunction("apiKey", "voyage-3-large");

multilingual_texts = [
    "Hello from VoyageAI!",
    "مرحباً من VoyageAI!!",
    "Hallo von VoyageAI!",
    "Bonjour de VoyageAI!",
    "¡Hola desde VoyageAI!",
    "Olá do VoyageAI!",
    "Ciao da VoyageAI!",
    "您好，来自 VoyageAI！",
    "कोहिअर से VoyageAI!",
];

const embeddings = embedder.generate(multilingual_texts);