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trulens.providers.langchain.endpoint

trulens.providers.langchain.endpoint

Classes

LangchainEndpoint

Bases: Endpoint

LangChain endpoint.

Attributes
tru_class_info instance-attribute
tru_class_info: Class

Class information of this pydantic object for use in deserialization.

Using this odd key to not pollute attribute names in whatever class we mix this into. Should be the same as CLASS_INFO.

instrumented_methods class-attribute
instrumented_methods: Dict[
    Any, List[Tuple[Callable, Callable, Type[Endpoint]]]
] = defaultdict(list)

Mapping of classes/module-methods that have been instrumented for cost tracking along with the wrapper methods and the class that instrumented them.

Key is the class or module owning the instrumented method. Tuple value has:

  • original function,

  • wrapped version,

  • endpoint that did the wrapping.

name instance-attribute
name: str

API/endpoint name.

rpm class-attribute instance-attribute

Requests per minute.

retries class-attribute instance-attribute
retries: int = 3

Retries (if performing requests using this class).

post_headers class-attribute instance-attribute
post_headers: Dict[str, str] = Field(
    default_factory=dict, exclude=True
)

Optional post headers for post requests if done by this class.

pace class-attribute instance-attribute
pace: Pace = Field(
    default_factory=lambda: Pace(
        marks_per_second=DEFAULT_RPM / 60.0,
        seconds_per_period=60.0,
    ),
    exclude=True,
)

Pacing instance to maintain a desired rpm.

global_callback class-attribute instance-attribute
global_callback: EndpointCallback = Field(exclude=True)

Track costs not run inside "track_cost" here.

Also note that Endpoints are singletons (one for each unique name argument) hence this global callback will track all requests for the named api even if you try to create multiple endpoints (with the same name).

callback_class class-attribute instance-attribute
callback_class: Type[EndpointCallback] = Field(exclude=True)

Callback class to use for usage tracking.

callback_name class-attribute instance-attribute
callback_name: str = Field(exclude=True)

Name of variable that stores the callback noted above.

Classes
EndpointSetup dataclass

Class for storing supported endpoint information.

See track_all_costs for usage.

Functions
get_instances classmethod
get_instances() -> Generator[InstanceRefMixin]

Get all instances of the class.

delete_instances classmethod
delete_instances()

Delete all instances of the class.

__rich_repr__
__rich_repr__() -> Result

Requirement for pretty printing using the rich package.

load staticmethod
load(obj, *args, **kwargs)

Deserialize/load this object using the class information in tru_class_info to lookup the actual class that will do the deserialization.

model_validate classmethod
model_validate(*args, **kwargs) -> Any

Deserialized a jsonized version of the app into the instance of the class it was serialized from.

Note

This process uses extra information stored in the jsonized object and handled by WithClassInfo.

pace_me
pace_me() -> float

Block until we can make a request to this endpoint to keep pace with maximum rpm. Returns time in seconds since last call to this method returned.

run_in_pace
run_in_pace(
    func: Callable[[A], B], *args, **kwargs
) -> B

Run the given func on the given args and kwargs at pace with the endpoint-specified rpm. Failures will be retried self.retries times.

run_me
run_me(thunk: Thunk[T]) -> T

DEPRECATED: Run the given thunk, returning itse output, on pace with the api. Retries request multiple times if self.retries > 0.

DEPRECATED: Use run_in_pace instead.

print_instrumented classmethod
print_instrumented()

Print out all of the methods that have been instrumented for cost tracking. This is organized by the classes/modules containing them.

track_all_costs staticmethod
track_all_costs(
    __func: CallableMaybeAwaitable[A, T],
    *args,
    with_openai: bool = True,
    with_hugs: bool = True,
    with_litellm: bool = True,
    with_bedrock: bool = True,
    with_cortex: bool = True,
    with_dummy: bool = True,
    **kwargs
) -> Tuple[T, Sequence[EndpointCallback]]

Track costs of all of the apis we can currently track, over the execution of thunk.

track_all_costs_tally staticmethod
track_all_costs_tally(
    __func: CallableMaybeAwaitable[A, T],
    *args,
    with_openai: bool = True,
    with_hugs: bool = True,
    with_litellm: bool = True,
    with_bedrock: bool = True,
    with_cortex: bool = True,
    with_dummy: bool = True,
    **kwargs
) -> Tuple[T, Thunk[Cost]]

Track costs of all of the apis we can currently track, over the execution of thunk.

RETURNS DESCRIPTION
T

Result of evaluating the thunk.

TYPE: T

Thunk[Cost]

Thunk[Cost]: A thunk that returns the total cost of all callbacks that tracked costs. This is a thunk as the costs might change after this method returns in case of Awaitable results.

track_cost
track_cost(
    __func: CallableMaybeAwaitable[..., T], *args, **kwargs
) -> Tuple[T, EndpointCallback]

Tally only the usage performed within the execution of the given thunk.

Returns the thunk's result alongside the EndpointCallback object that includes the usage information.

wrap_function
wrap_function(func)

Create a wrapper of the given function to perform cost tracking.