vectorisers.ollama.OllamaVectoriser

vectorisers.ollama.OllamaVectoriser(model_name)

A wrapper class allowing a locally-running ollama server to generate text embeddings.

The OllamaVectoriser interacts with a locally-running Ollama server, which must be set up by the user separately. In general, Ollama can run the same encoder-based models as the HuggingFaceVectoriser. A future goal is to extend the OllamaVectoriser to interface with an external Ollama server, allowing separation of embedding generation from the user’s local environment.

Attributes

Name	Type	Description
model_name	str	The name of the local model to use.

Methods

Name	Description
transform	Transforms input text(s) into embeddings using the Huggingface model.

transform

vectorisers.ollama.OllamaVectoriser.transform(texts)

Transforms input text(s) into embeddings using the Huggingface model.

Parameters

Name	Type	Description	Default
texts	(str, list[str])	The input text(s) to embed. Can be a single string or a list of strings.	required

Returns

Name	Type	Description
	np.ndarray	numpy.ndarray: A 2D array of embeddings, where each row corresponds to an input text.

Raises

Name	Type	Description
	ExternalServiceError	If the Ollama service fails to generate embeddings.
	VectorisationError	If embedding extraction from the Ollama response fails.