--- title: ZeroEntropy description: Learn how to use the ZeroEntropy community provider. --- # ZeroEntropy Provider [zeroentropy-ai/zeroentropy-ai-provider](https://github.com/zeroentropy-ai/zeroentropy-ai-provider) is a community provider that uses [ZeroEntropy](https://zeroentropy.dev) to provide text embedding and reranking support for the AI SDK. ## Setup The ZeroEntropy provider is available in the `zeroentropy-ai-provider` module. You can install it with: ## Provider Instance You can import the default provider instance `zeroentropy` from `zeroentropy-ai-provider`: ```ts import { zeroentropy } from 'zeroentropy-ai-provider'; ``` If you need a customized setup, you can import `createZeroEntropy` from `zeroentropy-ai-provider` and create a provider instance with your settings: ```ts import { createZeroEntropy } from 'zeroentropy-ai-provider'; const zeroentropy = createZeroEntropy({ apiKey: process.env.ZEROENTROPY_API_KEY ?? '', }); ``` You can use the following optional settings to customize the ZeroEntropy provider instance: - **baseURL** _string_ The base URL of the ZeroEntropy API. The default prefix is `https://api.zeroentropy.dev/v1`. - **apiKey** _string_ API key that is being sent using the `Authorization` header. It defaults to the `ZEROENTROPY_API_KEY` environment variable. Obtain your API key from the [ZeroEntropy Dashboard](https://dashboard.zeroentropy.dev). - **headers** _Record<string,string>_ Custom headers to include in the requests. - **fetch** _(input: RequestInfo, init?: RequestInit) => Promise<Response>_ Custom [fetch](https://developer.mozilla.org/en-US/docs/Web/API/fetch) implementation. Defaults to the global `fetch` function. You can use it as a middleware to intercept requests, or to provide a custom fetch implementation for e.g. testing. ## Text Embedding Models You can create models that call the [ZeroEntropy embeddings API](https://docs.zeroentropy.dev) using the `.textEmbeddingModel()` factory method. ```ts import { zeroentropy } from 'zeroentropy-ai-provider'; const embeddingModel = zeroentropy.textEmbeddingModel('zembed-1'); ``` You can use ZeroEntropy embedding models to generate embeddings with the `embed` or `embedMany` function: ```ts import { zeroentropy } from 'zeroentropy-ai-provider'; import { embed, embedMany } from 'ai'; // Single embedding const { embedding } = await embed({ model: zeroentropy.textEmbeddingModel('zembed-1'), value: 'sunny day at the beach', }); // Batch embeddings const { embeddings } = await embedMany({ model: zeroentropy.textEmbeddingModel('zembed-1'), values: ['first document', 'second document'], }); ``` ZeroEntropy embedding models support additional provider options that can be passed via `providerOptions.zeroentropy`: ```ts import { zeroentropy } from 'zeroentropy-ai-provider'; import { embed } from 'ai'; const { embedding } = await embed({ model: zeroentropy.textEmbeddingModel('zembed-1'), value: 'sunny day at the beach', providerOptions: { zeroentropy: { inputType: 'document', dimensions: 1280, }, }, }); ``` The following provider options are available: - **inputType** _'query' | 'document'_ Whether the input is a search query or a document to index. Use `'query'` for retrieval queries and `'document'` for content being indexed. Defaults to `'document'`. - **dimensions** _2560 | 1280 | 640 | 320 | 160 | 80 | 40_ Output vector dimensions. Defaults to `2560`. Supports Matryoshka representations for flexible dimensionality reduction. - **latency** _'fast' | 'slow'_ `'fast'` for sub-second latency; `'slow'` for higher throughput limits. ### Model Capabilities | Model | Default Dimensions | Context Length | Description | | ---------- | ------------------ | -------------- | ------------------------------------------------------------ | | `zembed-1` | 2560 | 8192 | Multilingual embedding model, supports Matryoshka dimensions | ## Reranking Models You can create models that call the [ZeroEntropy reranking API](https://docs.zeroentropy.dev) using the `.rerankingModel()` factory method. ```ts import { zeroentropy } from 'zeroentropy-ai-provider'; import { rerank } from 'ai'; const result = await rerank({ model: zeroentropy.rerankingModel('zerank-2'), query: 'talk about rain', documents: ['sunny day at the beach', 'rainy day in the city'], topN: 2, }); ``` ZeroEntropy reranking models support additional provider options that can be passed via `providerOptions.zeroentropy`: ```ts import { zeroentropy } from 'zeroentropy-ai-provider'; import { rerank } from 'ai'; const result = await rerank({ model: zeroentropy.rerankingModel('zerank-2'), query: 'talk about rain', documents: ['sunny day at the beach', 'rainy day in the city'], topN: 2, providerOptions: { zeroentropy: { latency: 'fast', }, }, }); ``` The following provider option is available: - **latency** _'fast' | 'slow'_ `'fast'` for sub-second latency; `'slow'` for higher throughput limits. ### Model Capabilities | Model | Description | | ---------------- | ------------------------------------------------------ | | `zerank-2` | Flagship state-of-the-art cross-encoder reranker | | `zerank-2-nano` | Compact `zerank-2` variant for lower-latency use cases | | `zerank-1` | Previous generation reranker | | `zerank-1-small` | Lightweight reranker for lower-latency use cases | Please see the [ZeroEntropy docs](https://docs.zeroentropy.dev) for the full list of available models and options.