DeterministicFakeEmbedding

class langchain_community.embeddings.fake.DeterministicFakeEmbedding

Bases: Embeddings, BaseModel

Fake embedding model that always returns the same embedding vector for the same text.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

param size: int [Required]

The size of the embedding vector.

async aembed_documents(texts: list[str]) → list[list[float]]

Asynchronous Embed search docs.

Parameters:

texts (list[str]) – List of text to embed.

Returns:

List of embeddings.

Return type:

list[list[float]]

async aembed_query(text: str) → list[float]

Asynchronous Embed query text.

Parameters:

text (str) – Text to embed.

Returns:

Embedding.

Return type:

list[float]

embed_documents(texts: List[str]) → List[List[float]]

Embed search docs.

Parameters:

texts (List[str]) – List of text to embed.

Returns:

List of embeddings.

Return type:

List[List[float]]

embed_query(text: str) → List[float]

Embed query text.

Parameters:

text (str) – Text to embed.

Returns:

Embedding.

Return type:

List[float]

Examples using DeterministicFakeEmbedding

• ElasticsearchRetriever