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69 lines
18 KiB
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69 lines
18 KiB
Plaintext
---
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title: "Embedders"
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id: embedders
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slug: "/embedders"
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description: "Embedders in Haystack transform texts or documents into vector representations using pre-trained models. You can then use the embedding for tasks like question answering, information retrieval, and more."
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---
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# Embedders
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Embedders in Haystack transform texts or documents into vector representations using pre-trained models. You can then use the embedding for tasks like question answering, information retrieval, and more.
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:::info
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For general guidance on how to choose an Embedder that would be right for you, read our [Choosing the Right Embedder](embedders/choosing-the-right-embedder.mdx) page.
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:::
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These are the Embedders available in Haystack:
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| Embedder | Description |
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| --- | --- |
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| [AmazonBedrockTextEmbedder](embedders/amazonbedrocktextembedder.mdx) | Computes embeddings for text (such as a query) using models through Amazon Bedrock API. |
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| [AmazonBedrockDocumentEmbedder](embedders/amazonbedrockdocumentembedder.mdx) | Computes embeddings for documents using models through Amazon Bedrock API. |
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| [AmazonBedrockDocumentImageEmbedder](embedders/amazonbedrockdocumentimageembedder.mdx) | Computes image embeddings for a document. |
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| [AzureOpenAITextEmbedder](embedders/azureopenaitextembedder.mdx) | Computes embeddings for text (such as a query) using OpenAI models deployed through Azure. |
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| [AzureOpenAIDocumentEmbedder](embedders/azureopenaidocumentembedder.mdx) | Computes embeddings for documents using OpenAI models deployed through Azure. |
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| [CohereTextEmbedder](embedders/coheretextembedder.mdx) | Embeds a simple string (such as a query) with a Cohere model. Requires an API key from Cohere |
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| [CohereDocumentEmbedder](embedders/coheredocumentembedder.mdx) | Embeds a list of documents with a Cohere model. Requires an API key from Cohere. |
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| [CohereDocumentImageEmbedder](embedders/coheredocumentimageembedder.mdx) | Computes the image embeddings of a list of documents and stores the obtained vectors in the embedding field of each document. |
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| [FastembedTextEmbedder](embedders/fastembedtextembedder.mdx) | Computes the embeddings of a string using embedding models supported by Fastembed. |
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| [FastembedDocumentEmbedder](embedders/fastembeddocumentembedder.mdx) | Computes the embeddings of a list of documents using the models supported by Fastembed. |
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| [FastembedSparseTextEmbedder](embedders/fastembedsparsetextembedder.mdx) | Embeds a simple string (such as a query) into a sparse vector using the models supported by Fastembed. |
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| [FastembedSparseDocumentEmbedder](embedders/fastembedsparsedocumentembedder.mdx) | Enriches a list of documents with their sparse embeddings using the models supported by Fastembed. |
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| [GoogleGenAITextEmbedder](embedders/googlegenaitextembedder.mdx) | Embeds a simple string (such as a query) with a Google AI model. Requires an API key from Google. |
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| [GoogleGenAIDocumentEmbedder](embedders/googlegenaidocumentembedder.mdx) | Embeds a list of documents with a Google AI model. Requires an API key from Google. |
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| [GoogleGenAIMultimodalDocumentEmbedder](embedders/googlegenaimultimodaldocumentembedder.mdx) | Embeds a list of non-textual documents with a Google AI model. Requires an API key from Google. |
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| [HuggingFaceAPIDocumentEmbedder](embedders/huggingfaceapidocumentembedder.mdx) | Computes document embeddings using various Hugging Face APIs. |
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| [HuggingFaceAPITextEmbedder](embedders/huggingfaceapitextembedder.mdx) | Embeds strings using various Hugging Face APIs. |
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| [JinaTextEmbedder](embedders/jinatextembedder.mdx) | Embeds a simple string (such as a query) with a Jina AI Embeddings model. Requires an API key from Jina AI. |
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| [JinaDocumentEmbedder](embedders/jinadocumentembedder.mdx) | Embeds a list of documents with a Jina AI Embeddings model. Requires an API key from Jina AI. |
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| [JinaDocumentImageEmbedder](embedders/jinadocumentimageembedder.mdx) | Computes the image embeddings of a list of documents and stores the obtained vectors in the embedding field of each document. |
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| [MistralTextEmbedder](embedders/mistraltextembedder.mdx) | Transforms a string into a vector using the Mistral API and models. |
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| [MistralDocumentEmbedder](embedders/mistraldocumentembedder.mdx) | Computes the embeddings of a list of documents using the Mistral API and models. |
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| [MockTextEmbedder](embedders/mocktextembedder.mdx) | Returns deterministic embeddings for a string without calling any API — a zero-cost stand-in for real Text Embedders in tests and prototypes. |
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| [MockDocumentEmbedder](embedders/mockdocumentembedder.mdx) | Returns deterministic embeddings for a list of documents without calling any API — a zero-cost stand-in for real Document Embedders in tests and prototypes. |
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| [NvidiaTextEmbedder](embedders/nvidiatextembedder.mdx) | Embeds a simple string (such as a query) into a vector. |
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| [NvidiaDocumentEmbedder](embedders/nvidiadocumentembedder.mdx) | Enriches the metadata of documents with an embedding of their content. |
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| [OllamaTextEmbedder](embedders/ollamatextembedder.mdx) | Computes the embeddings of a string using embedding models compatible with the Ollama Library. |
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| [OllamaDocumentEmbedder](embedders/ollamadocumentembedder.mdx) | Computes the embeddings of a list of documents using embedding models compatible with the Ollama Library. |
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| [OpenAIDocumentEmbedder](embedders/openaidocumentembedder.mdx) | Embeds a list of documents with an OpenAI embedding model. Requires an API key from an active OpenAI account. |
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| [OpenAITextEmbedder](embedders/openaitextembedder.mdx) | Embeds a simple string (such as a query) with an OpenAI embedding model. Requires an API key from an active OpenAI account. |
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| [OptimumTextEmbedder](embedders/optimumtextembedder.mdx) | Embeds text using models loaded with the Hugging Face Optimum library. |
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| [OptimumDocumentEmbedder](embedders/optimumdocumentembedder.mdx) | Computes documents’ embeddings using models loaded with the Hugging Face Optimum library. |
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| [PerplexityDocumentEmbedder](embedders/perplexitydocumentembedder.mdx) | Computes embeddings for a list of documents using Perplexity embedding models. Requires an API key from Perplexity. |
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| [PerplexityTextEmbedder](embedders/perplexitytextembedder.mdx) | Embeds a simple string (such as a query) using a Perplexity embedding model. Requires an API key from Perplexity. |
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| [SentenceTransformersTextEmbedder](embedders/sentencetransformerstextembedder.mdx) | Embeds a simple string (such as a query) using a Sentence Transformer model. |
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| [SentenceTransformersDocumentEmbedder](embedders/sentencetransformersdocumentembedder.mdx) | Embeds a list of documents with a Sentence Transformer model. |
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| [SentenceTransformersDocumentImageEmbedder](embedders/sentencetransformersdocumentimageembedder.mdx) | Computes the image embeddings of a list of documents and stores the obtained vectors in the embedding field of each document. |
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| [SentenceTransformersSparseTextEmbedder](embedders/sentencetransformerssparsetextembedder.mdx) | Embeds a simple string (such as a query) into a sparse vector using Sentence Transformers models. |
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| [SentenceTransformersSparseDocumentEmbedder](embedders/sentencetransformerssparsedocumentembedder.mdx) | Enriches a list of documents with their sparse embeddings using Sentence Transformers models. |
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| [STACKITTextEmbedder](embedders/stackittextembedder.mdx) | Enables text embedding using the STACKIT API. |
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| [STACKITDocumentEmbedder](embedders/stackitdocumentembedder.mdx) | Enables document embedding using the STACKIT API. |
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| [TwelveLabsTextEmbedder](embedders/twelvelabstextembedder.mdx) | Embeds a simple string (such as a query) with the TwelveLabs Marengo multimodal model. Requires an API key from TwelveLabs. |
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| [TwelveLabsDocumentEmbedder](embedders/twelvelabsdocumentembedder.mdx) | Embeds a list of documents with the TwelveLabs Marengo multimodal model. Requires an API key from TwelveLabs. |
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| [VertexAITextEmbedder](embedders/vertexaitextembedder.mdx) | Computes embeddings for text (such as a query) using models through VertexAI Embeddings API. **_This integration will be deprecated soon. We recommend using [GoogleGenAITextEmbedder](embedders/googlegenaitextembedder.mdx) integration instead._** |
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| [VertexAIDocumentEmbedder](embedders/vertexaidocumentembedder.mdx) | Computes embeddings for documents using models through VertexAI Embeddings API. **_This integration will be deprecated soon. We recommend using [GoogleGenAIDocumentEmbedder](embedders/googlegenaidocumentembedder.mdx) integration instead._** |
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| [VLLMTextEmbedder](embedders/vllmtextembedder.mdx) | Computes the embeddings of a string using models served with vLLM. |
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| [VLLMDocumentEmbedder](embedders/vllmdocumentembedder.mdx) | Computes the embeddings of a list of documents using models served with vLLM. |
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| [WatsonxTextEmbedder](embedders/watsonxtextembedder.mdx) | Computes embeddings for text (such as a query) using IBM Watsonx models. |
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| [WatsonxDocumentEmbedder](embedders/watsonxdocumentembedder.mdx) | Computes embeddings for documents using IBM Watsonx models. |
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