langchain_community.embeddings.infinity.InfinityEmbeddings

class langchain_community.embeddings.infinity.InfinityEmbeddings

Bases: BaseModel, Embeddings

Self-hosted embedding models for infinity package.

See https://github.com/michaelfeil/infinity This also works for text-embeddings-inference and other self-hosted openai-compatible servers.

Infinity is a package to interact with Embedding Models on https://github.com/michaelfeil/infinity

Example

from langchain_community.embeddings import InfinityEmbeddings
InfinityEmbeddings(
    model="BAAI/bge-small",
    infinity_api_url="http://localhost:7997",
)

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

Raises ValidationError if the input data cannot be parsed to form a valid model.

param client: Any = None

Infinity client.

param infinity_api_url: str = 'http://localhost:7997'

Endpoint URL to use.

param model: str [Required]

Underlying Infinity model id.

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

Async call out to Infinity’s embedding endpoint.

Parameters

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

Returns

List of embeddings, one for each text.

Return type

List[List[float]]

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

Async call out to Infinity’s embedding endpoint.

Parameters

text (str) – The text to embed.

Returns

Embeddings for the text.

Return type

List[float]

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

Call out to Infinity’s embedding endpoint.

Parameters

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

Returns

List of embeddings, one for each text.

Return type

List[List[float]]

embed_query(text: str) → List[float]

Call out to Infinity’s embedding endpoint.

Parameters

text (str) – The text to embed.

Returns

Embeddings for the text.

Return type

List[float]

Examples using InfinityEmbeddings

• Infinity