AutoEmbeddings is a class that automatically selects the appropriate embeddings handler for you, based on the model name you provide.

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Installation

Embeddings require the appropriate library to be installed. See the Installation Guide for more information.

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Usage

Load the embeddings handler for the model you want to use. 
from chonkie import AutoEmbeddings

# Get the embeddings handler for SentenceTransformer
embeddings = AutoEmbeddings.get_embeddings("all-MiniLM-L6-v2")

# Get the embeddings handler for OpenAI
embeddings = AutoEmbeddings.get_embeddings("text-embedding-3-large")

# Get the embeddings handler for Model2Vec
embeddings = AutoEmbeddings.get_embeddings("minishlab/potion-base-8M")
After loading the embeddings handler, you can use it in the same way you would use any other embeddings handler. 
from chonkie import SemanticChunker
chunker = SemanticChunker(embeddings=embeddings, similarity_threshold=0.7)

# Chunk the text
chunks = chunker(text)
SemanticChunkers interally call upon the AutoEmbeddings class to get the embeddings handler. So you can directly pass in a string to the embeddings parameter as well, as long as it matches one of the models supported by AutoEmbeddings, and its dependencies are installed.

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Method: get_embeddings

The get_embeddings method is a factory method that returns an instance of the appropriate embeddings handler.
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model_name
str
The name of the embeddings model to use.