langchain_community.document_loaders.blob_loaders.schema.Blob

class langchain_community.document_loaders.blob_loaders.schema.Blob[source]

Bases: BaseModel

Blob represents raw data by either reference or value.

Provides an interface to materialize the blob in different representations, and help to decouple the development of data loaders from the downstream parsing of the raw data.

Inspired by: https://developer.mozilla.org/en-US/docs/Web/API/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 data: Optional[Union[bytes, str]] = None

Raw data associated with the blob.

param encoding: str = 'utf-8'

Encoding to use if decoding the bytes into a string.

Use utf-8 as default encoding, if decoding to string.

param metadata: Dict[str, Any] [Optional]

Metadata about the blob (e.g., source)

param mimetype: Optional[str] = None

MimeType not to be confused with a file extension.

param path: Optional[Union[str, PurePath]] = None

Location where the original content was found.

as_bytes() bytes[source]

Read data as bytes.

as_bytes_io() Generator[Union[BytesIO, BufferedReader], None, None][source]

Read data as a byte stream.

as_string() str[source]

Read data as a string.

classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model

Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values

copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters
  • include – fields to include in new model

  • exclude – fields to exclude from new model, as with values this takes precedence over include

  • update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data

  • deep – set to True to make a deep copy of the model

Returns

new model instance

dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

classmethod from_data(data: Union[str, bytes], *, encoding: str = 'utf-8', mime_type: Optional[str] = None, path: Optional[str] = None, metadata: Optional[dict] = None) Blob[source]

Initialize the blob from in-memory data.

Parameters
  • data – the in-memory data associated with the blob

  • encoding – Encoding to use if decoding the bytes into a string

  • mime_type – if provided, will be set as the mime-type of the data

  • path – if provided, will be set as the source from which the data came

  • metadata – Metadata to associate with the blob

Returns

Blob instance

classmethod from_orm(obj: Any) Model
classmethod from_path(path: Union[str, PurePath], *, encoding: str = 'utf-8', mime_type: Optional[str] = None, guess_type: bool = True, metadata: Optional[dict] = None) Blob[source]

Load the blob from a path like object.

Parameters
  • path – path like object to file to be read

  • encoding – Encoding to use if decoding the bytes into a string

  • mime_type – if provided, will be set as the mime-type of the data

  • guess_type – If True, the mimetype will be guessed from the file extension, if a mime-type was not provided

  • metadata – Metadata to associate with the blob

Returns

Blob instance

json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) Model
classmethod parse_obj(obj: Any) Model
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) Model
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') DictStrAny
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) unicode
classmethod update_forward_refs(**localns: Any) None

Try to update ForwardRefs on fields based on this Model, globalns and localns.

classmethod validate(value: Any) Model
property source: Optional[str]

The source location of the blob as string if known otherwise none.

If a path is associated with the blob, it will default to the path location.

Unless explicitly set via a metadata field called “source”, in which case that value will be used instead.

Examples using Blob