OllamaDocumentEmbedder

Computes the embeddings of a list of Documents and stores the obtained vectors in the embedding field of each

Basic Information

• Type: haystack_integrations.components.embedders.ollama.document_embedder.OllamaDocumentEmbedder

Inputs

Parameter	Type	Default	Description
documents	List[Document]		Documents to be converted to an embedding.
generation_kwargs	Optional[Dict[str, Any]]	None	Optional arguments to pass to the Ollama generation endpoint, such as temperature, top_p, etc. See the Ollama docs.

Outputs

Parameter	Type	Default	Description
documents	List[Document]		A dictionary with the following keys: - documents: Documents with embedding information attached - meta: The metadata collected during the embedding process
meta	Dict[str, Any]		A dictionary with the following keys: - documents: Documents with embedding information attached - meta: The metadata collected during the embedding process

Overview

Work in Progress

Bear with us while we're working on adding pipeline examples and most common components connections.

Computes the embeddings of a list of Documents and stores the obtained vectors in the embedding field of each Document. It uses embedding models compatible with the Ollama Library.

Usage example:

from haystack import Document
from haystack_integrations.components.embedders.ollama import OllamaDocumentEmbedder

doc = Document(content="What do llamas say once you have thanked them? No probllama!")
document_embedder = OllamaDocumentEmbedder()

result = document_embedder.run([doc])
print(result['documents'][0].embedding)

Usage Example

components:
  OllamaDocumentEmbedder:
    type: ollama.src.haystack_integrations.components.embedders.ollama.document_embedder.OllamaDocumentEmbedder
    init_parameters:

Parameters

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 model to use. The model should be available in the running Ollama instance.
url	str	http://localhost:11434	The URL of a running Ollama instance.
generation_kwargs	Optional[Dict[str, Any]]	None	Optional arguments to pass to the Ollama generation endpoint, such as temperature, top_p, and others. See the available arguments in Ollama docs.
timeout	int	120	The number of seconds before throwing a timeout error from the Ollama API.
prefix	str		A string to add at the beginning of each text.
suffix	str		A string to add at the end of each text.
progress_bar	bool	True	If True, shows a progress bar when running.
meta_fields_to_embed	Optional[List[str]]	None	List of metadata fields to embed along with the document text.
embedding_separator	str	\n	Separator used to concatenate the metadata fields to the document text.
batch_size	int	32	Number of documents to process at once.

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
documents	List[Document]		Documents to be converted to an embedding.
generation_kwargs	Optional[Dict[str, Any]]	None	Optional arguments to pass to the Ollama generation endpoint, such as temperature, top_p, etc. See the Ollama docs.