langchain_community.embeddings.mlflow
.MlflowEmbeddingsΒΆ
- class langchain_community.embeddings.mlflow.MlflowEmbeddings[source]ΒΆ
Bases:
Embeddings
,BaseModel
Embedding LLMs in MLflow.
To use, you should have the mlflow[genai] python package installed. For more information, see https://mlflow.org/docs/latest/llms/deployments/server.html.
Example
from langchain_community.embeddings import MlflowEmbeddings embeddings = MlflowEmbeddings( target_uri="http://localhost:5000", endpoint="embeddings", )
- param documents_params: Dict[str, str] = {}ΒΆ
- param endpoint: str [Required]ΒΆ
The endpoint to use.
- param query_params: Dict[str, str] = {}ΒΆ
The parameters to use for documents.
- param target_uri: str [Required]ΒΆ
The target URI to use.
- async aembed_documents(texts: List[str]) List[List[float]] ΒΆ
Asynchronous Embed search docs.
- Parameters
texts (List[str]) β
- Return type
List[List[float]]
- async aembed_query(text: str) List[float] ΒΆ
Asynchronous Embed query text.
- Parameters
text (str) β
- Return type
List[float]
- classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) Model ΒΆ
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 = βallowβ was set since it adds all passed values
- Parameters
_fields_set (Optional[SetStr]) β
values (Any) β
- Return type
Model
- copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) Model ΒΆ
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) β fields to include in new model
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) β fields to exclude from new model, as with values this takes precedence over include
update (Optional[DictStrAny]) β 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 (bool) β set to True to make a deep copy of the model
self (Model) β
- Returns
new model instance
- Return type
Model
- 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 ΒΆ
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) β
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) β
by_alias (bool) β
skip_defaults (Optional[bool]) β
exclude_unset (bool) β
exclude_defaults (bool) β
exclude_none (bool) β
- Return type
DictStrAny
- embed(texts: List[str], params: Dict[str, str]) List[List[float]] [source]ΒΆ
- Parameters
texts (List[str]) β
params (Dict[str, str]) β
- Return type
List[List[float]]
- embed_documents(texts: List[str]) List[List[float]] [source]ΒΆ
Embed search docs.
- Parameters
texts (List[str]) β
- Return type
List[List[float]]
- embed_query(text: str) List[float] [source]ΒΆ
Embed query text.
- Parameters
text (str) β
- Return type
List[float]
- classmethod from_orm(obj: Any) Model ΒΆ
- Parameters
obj (Any) β
- Return type
Model
- 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 ΒΆ
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().
- Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) β
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) β
by_alias (bool) β
skip_defaults (Optional[bool]) β
exclude_unset (bool) β
exclude_defaults (bool) β
exclude_none (bool) β
encoder (Optional[Callable[[Any], Any]]) β
models_as_dict (bool) β
dumps_kwargs (Any) β
- Return type
unicode
- classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) Model ΒΆ
- Parameters
path (Union[str, Path]) β
content_type (unicode) β
encoding (unicode) β
proto (Protocol) β
allow_pickle (bool) β
- Return type
Model
- classmethod parse_obj(obj: Any) Model ΒΆ
- Parameters
obj (Any) β
- Return type
Model
- classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) Model ΒΆ
- Parameters
b (Union[str, bytes]) β
content_type (unicode) β
encoding (unicode) β
proto (Protocol) β
allow_pickle (bool) β
- Return type
Model
- classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') DictStrAny ΒΆ
- Parameters
by_alias (bool) β
ref_template (unicode) β
- Return type
DictStrAny
- classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) unicode ΒΆ
- Parameters
by_alias (bool) β
ref_template (unicode) β
dumps_kwargs (Any) β
- Return type
unicode
- classmethod update_forward_refs(**localns: Any) None ΒΆ
Try to update ForwardRefs on fields based on this Model, globalns and localns.
- Parameters
localns (Any) β
- Return type
None
- classmethod validate(value: Any) Model ΒΆ
- Parameters
value (Any) β
- Return type
Model