UpstageEmbeddings#

class langchain_upstage.embeddings.UpstageEmbeddings[source]#

Bases: BaseModel, Embeddings

UpstageEmbeddings embedding model.

To use, set the environment variable UPSTAGE_API_KEY with your API key or pass it as a named parameter to the constructor.

Example

from langchain_upstage import UpstageEmbeddings

model = UpstageEmbeddings(model='solar-embedding-1-large')

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 allowed_special: Literal['all'] | Set[str] = {}#: Not yet supported.

param chunk_size: int = 1000#

Maximum number of texts to embed in each batch.

Not yet supported.

param dimensions: int | None = None#

The number of dimensions the resulting output embeddings should have.

Not yet supported.

param disallowed_special: Literal['all'] | Set[str] | Sequence[str] = 'all'#: Not yet supported.

param embedding_ctx_length: int = 4096#

The maximum number of tokens to embed at once.

Not yet supported.

param http_async_client: Any | None = None#: Optional httpx.AsyncClient. Only used for async invocations. Must specify http_client as well if you’d like a custom client for sync invocations.

param http_client: Any | None = None#: Optional httpx.Client. Only used for sync invocations. Must specify http_async_client as well if you’d like a custom client for async invocations.

param max_retries: int = 2#: Maximum number of retries to make when generating.

param model: str [Required]#: Embeddings model name to use. Do not add suffixes like -query and -passage. Instead, use ‘solar-embedding-1-large’ for example.

param model_kwargs: Dict[str, Any] [Optional]#: Holds any model parameters valid for create call not explicitly specified.

param request_timeout: float | Tuple[float, float] | Any | None = None (alias 'timeout')#: Timeout for requests to Upstage embedding API. Can be float, httpx.Timeout or None.

param show_progress_bar: bool = False#

Whether to show a progress bar when embedding.

Not yet supported.

param skip_empty: bool = False#

Whether to skip empty strings when embedding or raise an error. Defaults to not skipping.

Not yet supported.

param upstage_api_base: str | None [Optional] (alias 'base_url')#: Endpoint URL to use.

param upstage_api_key: SecretStr [Optional] (alias 'api_key')#: Automatically inferred from env are UPSTAGE_API_KEY if not provided.

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

Embed a list of document texts using passage model asynchronously.

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

Asynchronous Embed query text using query model.

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

Embed a list of document texts using passage model.

embed_query(text: str) → List[float][source]#

Embed query text using query model.