xtrace_sdk.inference.embedding

Classes

Embedding

This class provides an interface to generate embeddings using different providers.

Module Contents

class xtrace_sdk.inference.embedding.Embedding(provider, model_name, dim)

This class provides an interface to generate embeddings using different providers. Supported providers include “ollama”, “openai”, and “sentence_transformer”. It also includes methods to convert float embeddings to binary format.

Parameters:

provider (str)
model_name (str)
dim (int)

dim

provider

url

model_name

__hash__()

Return type:: int

__eq__(other)

Parameters:: other (Any)
Return type:: bool

embed(text)

Generates an embedding for the given text using the specified provider.

Parameters:: text (str) – The input text to be embedded.
Returns:: A numpy array representing the embedding of the input text.
Return type:: np.ndarray
Raises:: ValueError – If the embedding dimension does not match the expected dimension.

static float_2_bin(float_array)

Convert a list of floats to a list of binary integers, naive implementation, preserves dimension

Parameters:: float_array (np.ndarray or list[float]) – A numpy array or list of floats to be converted.
Returns:: A numpy array of binary integers (0s and 1s).
Return type:: np.ndarray

sim_hash(float_array)

Parameters:: float_array (numpy.ndarray | list[float])
Return type:: None

bin_embed(text)

Generates a binary embedding for the given text. :param text: The input text to be embedded. :type text: str :return: A numpy array representing the binary embedding of the input text. :rtype: np.ndarray

Parameters:: text (str)
Return type:: numpy.ndarray