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Chroma Cloud Qwen

docs/mintlify/integrations/embedding-models/chroma-cloud-qwen.mdx

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Chroma provides a convenient wrapper around Chroma Cloud's Qwen embedding API. This embedding function runs remotely on Chroma Cloud's servers, and requires a Chroma API key. You can get an API key by signing up for an account at Chroma Cloud.

<Tabs> <Tab title="Python" icon="python">

This embedding function relies on the httpx python package, which you can install with pip install httpx.

python
from chromadb.utils.embedding_functions import ChromaCloudQwenEmbeddingFunction, ChromaCloudQwenEmbeddingModel
import os

os.environ["CHROMA_API_KEY"] = "YOUR_API_KEY"
qwen_ef = ChromaCloudQwenEmbeddingFunction(
    model=ChromaCloudQwenEmbeddingModel.QWEN3_EMBEDDING_0p6B,
    task="nl_to_code"
)

texts = ["Hello, world!", "How are you?"]
embeddings = qwen_ef(texts)

You must pass in a model argument and task argument. The task parameter specifies the task for which embeddings are being generated. You can optionally provide custom instructions for both documents and queries.

</Tab> <Tab title="TypeScript" icon="js">
typescript
// npm install @chroma-core/chroma-cloud-qwen

import { ChromaCloudQwenEmbeddingFunction, ChromaCloudQwenEmbeddingModel } from "@chroma-core/chroma-cloud-qwen";

const embedder = new ChromaCloudQwenEmbeddingFunction({
  apiKeyEnvVar: "CHROMA_API_KEY", // Or set CHROMA_API_KEY env var
  model: ChromaCloudQwenEmbeddingModel.QWEN3_EMBEDDING_0p6B,
  task: "nl_to_code",
});

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

// pass documents to query for .add and .query
const collection = await client.createCollection({
  name: "name",
  embeddingFunction: embedder,
});
</Tab> <Tab title="HTTP" icon="terminal"> To use the Chroma Cloud Embedding API directly, see the [Generate Sparse Embeddings API reference](/reference/embeddings-api/generate-sparse-embeddings) for detailed request and response formats. </Tab> </Tabs>