embedding.EmbeddingOpenAI

Creates an embedding function provider backed by OpenAI’s embedding models

Usage

Source

embedding.EmbeddingOpenAI()

Implements the EmbeddingProvider interface.

Parameters

model: str = "text-embedding-3-small"

The OpenAI embedding model to use. Default is “text-embedding-3-small”

base_url: str = "https://api.openai.com/v1"

The base URL for the OpenAI API. Default is “https://api.openai.com/v1”.

api_key: Optional[str] = None

The API key for authenticating with OpenAI. If None, it will use the OPENAI_API_KEY environment variable if set.

batch_size: int = 20

The number of texts to process in each batch when calling the API.

Examples

from raghilda.embedding import EmbeddingOpenAI

provider = EmbeddingOpenAI(model="text-embedding-3-small")
embeddings = provider.embed(["hello world", "testing embeddings"])
print(len(embeddings))
print(len(embeddings[0]))  # Dimension of the embedding
print(embeddings[0][:10])  # The embedding vector