gen_ai_hub.proxy.langchain.base
index
/home/jenkins/agent/workspace/ation_generative-ai-hub-sdk_main/gen_ai_hub/proxy/langchain/base.py

 
Classes
       
pydantic.v1.main.BaseModel(pydantic.v1.utils.Representation)
BaseAuth

 
class BaseAuth(pydantic.v1.main.BaseModel)
    BaseAuth(*, proxy_client: Optional[Any] = None, deployment_id: Optional[str] = None, config_name: Optional[str] = None, config_id: Optional[str] = None, proxy_model_name: Optional[str] = None) -> None
 

 
 
Method resolution order:
BaseAuth
pydantic.v1.main.BaseModel
pydantic.v1.utils.Representation
builtins.object

Static methods defined here:
__json_encoder__ = pydantic_encoder(obj: Any) -> Any

Data and other attributes defined here:
__abstractmethods__ = frozenset()
__annotations__ = {'config_id': typing.Optional[str], 'config_name': typing.Optional[str], 'deployment_id': typing.Optional[str], 'proxy_client': typing.Optional[typing.Any], 'proxy_model_name': typing.Optional[str]}
__class_vars__ = set()
__config__ = <class 'pydantic.v1.config.Config'>
__custom_root_type__ = False
__exclude_fields__ = None
__fields__ = {'config_id': ModelField(name='config_id', type=Optional[str], required=False, default=None), 'config_name': ModelField(name='config_name', type=Optional[str], required=False, default=None), 'deployment_id': ModelField(name='deployment_id', type=Optional[str], required=False, default=None), 'proxy_client': ModelField(name='proxy_client', type=Optional[Any], required=False, default=None), 'proxy_model_name': ModelField(name='proxy_model_name', type=Optional[str], required=False, default=None)}
__hash__ = None
__include_fields__ = None
__post_root_validators__ = []
__pre_root_validators__ = []
__private_attributes__ = {}
__schema_cache__ = {}
__signature__ = <Signature (*, proxy_client: Optional[Any] = Non... proxy_model_name: Optional[str] = None) -> None>
__validators__ = {}

Methods inherited from pydantic.v1.main.BaseModel:
__eq__(self, other: Any) -> bool
Return self==value.
__getstate__(self) -> 'DictAny'
__init__(__pydantic_self__, **data: Any) -> None
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.
__iter__(self) -> 'TupleGenerator'
so `dict(model)` works
__repr_args__(self) -> 'ReprArgs'
Returns the attributes to show in __str__, __repr__, and __pretty__ this is generally overridden.
 
Can either return:
* name - value pairs, e.g.: `[('foo_name', 'foo'), ('bar_name', ['b', 'a', 'r'])]`
* or, just values, e.g.: `[(None, 'foo'), (None, ['b', 'a', 'r'])]`
__setattr__(self, name, value)
Implement setattr(self, name, value).
__setstate__(self, state: 'DictAny') -> None
copy(self: 'Model', *, include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None, exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None, update: Optional[ForwardRef('DictStrAny')] = None, deep: bool = False) -> 'Model'
Duplicate a model, optionally choose which fields to include, exclude and change.
 
:param include: fields to include in new model
:param exclude: fields to exclude from new model, as with values this takes precedence over include
:param 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
:param deep: set to `True` to make a deep copy of the model
:return: new model instance
dict(self, *, include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None, exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = 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.
json(self, *, include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None, exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = 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) -> str
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()`.

Class methods inherited from pydantic.v1.main.BaseModel:
__get_validators__() -> 'CallableGenerator' from pydantic.v1.main.ModelMetaclass
__try_update_forward_refs__(**localns: Any) -> None from pydantic.v1.main.ModelMetaclass
Same as update_forward_refs but will not raise exception
when forward references are not defined.
construct(_fields_set: Optional[ForwardRef('SetStr')] = None, **values: Any) -> 'Model' from pydantic.v1.main.ModelMetaclass
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
from_orm(obj: Any) -> 'Model' from pydantic.v1.main.ModelMetaclass
parse_file(path: Union[str, pathlib.Path], *, content_type: str = None, encoding: str = 'utf8', proto: pydantic.v1.parse.Protocol = None, allow_pickle: bool = False) -> 'Model' from pydantic.v1.main.ModelMetaclass
parse_obj(obj: Any) -> 'Model' from pydantic.v1.main.ModelMetaclass
parse_raw(b: Union[str, bytes], *, content_type: str = None, encoding: str = 'utf8', proto: pydantic.v1.parse.Protocol = None, allow_pickle: bool = False) -> 'Model' from pydantic.v1.main.ModelMetaclass
schema(by_alias: bool = True, ref_template: str = '#/definitions/{model}') -> 'DictStrAny' from pydantic.v1.main.ModelMetaclass
schema_json(*, by_alias: bool = True, ref_template: str = '#/definitions/{model}', **dumps_kwargs: Any) -> str from pydantic.v1.main.ModelMetaclass
update_forward_refs(**localns: Any) -> None from pydantic.v1.main.ModelMetaclass
Try to update ForwardRefs on fields based on this Model, globalns and localns.
validate(value: Any) -> 'Model' from pydantic.v1.main.ModelMetaclass

Data descriptors inherited from pydantic.v1.main.BaseModel:
__dict__
dictionary for instance variables (if defined)
__fields_set__

Data and other attributes inherited from pydantic.v1.main.BaseModel:
Config = <class 'pydantic.v1.config.BaseConfig'>

Methods inherited from pydantic.v1.utils.Representation:
__pretty__(self, fmt: Callable[[Any], Any], **kwargs: Any) -> Generator[Any, NoneType, NoneType]
Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects
__repr__(self) -> str
Return repr(self).
__repr_name__(self) -> str
Name of the instance's class, used in __repr__.
__repr_str__(self, join_str: str) -> str
__rich_repr__(self) -> 'RichReprResult'
Get fields for Rich library
__str__(self) -> str
Return str(self).

 
Data
        Any = typing.Any
Optional = typing.Optional