OllamaTextEmbedder

Embed strings using embedding models served with Ollama. Use this component in query pipelines to transform user queries into vectors for embedding-based retrieval.

Key Features

• Works with any embedding model available through Ollama.
• Outputs a float vector embedding suitable for use with embedding retrievers.
• The embedding model must match the one used by OllamaDocumentEmbedder in the indexing pipeline.

Embedding Models in Query Pipelines and Indexes

The embedding model you use to embed documents in your indexing pipeline must be the same as the embedding model you use to embed the query in your query pipeline.

This means the embedders for your indexing and query pipelines must match. For example, if you use CohereDocumentEmbedder to embed your documents, you should use CohereTextEmbedder with the same model to embed your queries.

Configuration

1. Drag the OllamaTextEmbedder component onto the canvas from the Component Library.
2. Click on the component to open the configuration panel.
3. On the General tab:
   1. Set the model to the same embedding model used in your indexing pipeline (for example, nomic-embed-text).
   2. Set the url to your Ollama server address. The default is http://localhost:11434.
4. Go to the Advanced tab to configure timeout, keep_alive, and dimensions.

Connections

OllamaTextEmbedder receives the user query as a text string, typically from the Input component. It outputs a float vector through its embedding output, which you connect to an embedding retriever such as OpenSearchEmbeddingRetriever.

Source Code

To check this component's source code, open text_embedder.py in the Haystack Core Integrations repository.

Usage Examples

Basic Configuration

  OllamaTextEmbedder:
    type: haystack_integrations.components.embedders.ollama.text_embedder.OllamaTextEmbedder
    init_parameters:
      model: nomic-embed-text
      url: http://localhost:11434
      timeout: 120

Using the Component in a Pipeline

# haystack-pipeline
components:
  OllamaTextEmbedder:
    type: haystack_integrations.components.embedders.ollama.text_embedder.OllamaTextEmbedder
    init_parameters:
      model: nomic-embed-text
      url: http://localhost:11434
      timeout: 120

  OpenSearchEmbeddingRetriever:
    type: haystack_integrations.components.retrievers.opensearch.embedding_retriever.OpenSearchEmbeddingRetriever
    init_parameters:
      filters:
      top_k: 10
      filter_policy: replace
      custom_query:
      raise_on_failure: true
      document_store:
        type: haystack_integrations.document_stores.opensearch.document_store.OpenSearchDocumentStore
        init_parameters:
          hosts:
          index: my-index
          embedding_dim: 768

connections:
- sender: OllamaTextEmbedder.embedding
  receiver: OpenSearchEmbeddingRetriever.query_embedding

max_runs_per_component: 100

metadata: {}

inputs:
  query:
  - OllamaTextEmbedder.text

Parameters

Inputs

Parameter	Type	Description
text	str	The text to embed.

Outputs

Parameter	Type	Description
embedding	List[float]	The embedding of the text.
meta	Dict[str, Any]	Metadata about the request.

Init Parameters

These are the parameters you can configure in Pipeline Builder:

Parameter	Type	Default	Description
model	str	nomic-embed-text	The name of the Ollama embedding model to use.
url	str	http://localhost:11434	The URL of the Ollama API server.
generation_kwargs	Optional[Dict[str, Any]]	None	Additional parameters for the embedding request.
timeout	int	120	Request timeout in seconds.
keep_alive	Optional[Union[float, str]]	None	Controls how long the model stays loaded in memory.
dimensions	Optional[int]	None	The number of dimensions in the output embedding, if supported by the model.

Run Method Parameters

These are the parameters you can configure for the component's run() method. This means you can pass these parameters at query time through the API, in Playground, or when running a job. For details, see Modify Pipeline Parameters at Query Time.

Parameter	Type	Default	Description
text	str		The text to embed.
generation_kwargs	Optional[Dict[str, Any]]	None	Generation parameters to override init-time values.

Related Information

• Pipeline Components