langchain.document_loaders.embaas.EmbaasBlobLoader

class langchain.document_loaders.embaas.EmbaasBlobLoader(*, embaas_api_key: Optional[str] = None, api_url: str = 'https://api.embaas.io/v1/document/extract-text/bytes/', params: EmbaasDocumentExtractionParameters = {})

Bases: BaseEmbaasLoader, BaseBlobParser

Embaas’s document byte loader.

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

Example

# Default parsing
from langchain.document_loaders.embaas import EmbaasBlobLoader
loader = EmbaasBlobLoader()
blob = Blob.from_path(path="example.mp3")
documents = loader.parse(blob=blob)

# Custom api parameters (create embeddings automatically)
from langchain.document_loaders.embaas import EmbaasBlobLoader
loader = EmbaasBlobLoader(
    params={
        "should_embed": True,
        "model": "e5-large-v2",
        "chunk_size": 256,
        "chunk_splitter": "CharacterTextSplitter"
    }
)
blob = Blob.from_path(path="example.pdf")
documents = loader.parse(blob=blob)

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 api_url: str = 'https://api.embaas.io/v1/document/extract-text/bytes/'

The URL of the embaas document extraction API.

param embaas_api_key: Optional[str] = None

The API key for the embaas document extraction API.

param params: langchain.document_loaders.embaas.EmbaasDocumentExtractionParameters = {}

Additional parameters to pass to the embaas document extraction API.

lazy_parse(blob: Blob) → Iterator[Document]

Parses the blob lazily.

Parameters

blob – The blob to parse.

validator validate_environment  »  all fields

Validate that api key and python package exists in environment.

Examples using EmbaasBlobLoader

• Embaas