id stringlengths 14 15 | text stringlengths 44 2.47k | source stringlengths 61 181 |
|---|---|---|
6b75ba941317-46 | func = getattr(self, "func", None) or getattr(self, "afunc")
try:
sig = inspect.signature(func)
return (
sig.return_annotation
if sig.return_annotation != inspect.Signature.empty
else Any
)
except ValueError:
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-47 | input: Input,
run_manager: AsyncCallbackManagerForChainRun,
config: RunnableConfig,
) -> Output:
output = await acall_func_with_variable_args(
self.afunc, input, run_manager, config
)
# If the output is a runnable, invoke it
if isinstance(output, Runnable)... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-48 | "Use `ainvoke` instead."
)
[docs] async def ainvoke(
self,
input: Input,
config: Optional[RunnableConfig] = None,
**kwargs: Optional[Any],
) -> Output:
if hasattr(self, "afunc"):
return await self._acall_with_config(
self._ainvoke,
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-49 | return create_model(
"RunnableEachOutput",
__root__=(
List[self.bound.output_schema], # type: ignore[name-defined]
None,
),
)
[docs] @classmethod
def is_lc_serializable(cls) -> bool:
return True
[docs] @classmethod
def ge... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-50 | return await self._acall_with_config(self._ainvoke, input, config)
[docs]class RunnableBinding(Serializable, Runnable[Input, Output]):
"""
A runnable that delegates calls to another runnable with a set of kwargs.
"""
bound: Runnable[Input, Output]
kwargs: Mapping[str, Any]
config: Mapping[str, A... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-51 | # because both dicts are same type
copy[key] = config[key] or copy.get(key) # type: ignore
return copy
[docs] def bind(self, **kwargs: Any) -> Runnable[Input, Output]:
return self.__class__(
bound=self.bound, config=self.config, kwargs={**self.kwargs, **kwargs}
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-52 | self._merge_config(config),
**{**self.kwargs, **kwargs},
)
[docs] def batch(
self,
inputs: List[Input],
config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None,
*,
return_exceptions: bool = False,
**kwargs: Optional[Any],
) -> List[... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-53 | [docs] def stream(
self,
input: Input,
config: Optional[RunnableConfig] = None,
**kwargs: Optional[Any],
) -> Iterator[Output]:
yield from self.bound.stream(
input,
self._merge_config(config),
**{**self.kwargs, **kwargs},
)
[docs... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-54 | Callable[[Input], Output],
Callable[[Input], Awaitable[Output]],
Callable[[Iterator[Input]], Iterator[Output]],
Callable[[AsyncIterator[Input]], AsyncIterator[Output]],
Mapping[str, Any],
]
[docs]def coerce_to_runnable(thing: RunnableLike) -> Runnable[Input, Output]:
if isinstance(thing, Runnable):
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
8cd4c6f6b273-0 | Source code for langchain.schema.runnable.config
from __future__ import annotations
from concurrent.futures import Executor, ThreadPoolExecutor
from contextlib import contextmanager
from typing import (
TYPE_CHECKING,
Any,
Awaitable,
Callable,
Dict,
Generator,
List,
Optional,
Union,
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/config.html |
8cd4c6f6b273-1 | """
locals: Dict[str, Any]
"""
Variables scoped to this call and any sub-calls. Usually used with
GetLocalVar() and PutLocalVar(). Care should be taken when placing mutable
objects in locals, as they will be shared between parallel sub-calls.
"""
max_concurrency: Optional[int]
"""
Ma... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/config.html |
8cd4c6f6b273-2 | f"config must be a list of the same length as inputs, "
f"but got {len(config)} configs for {length} inputs"
)
return (
list(map(ensure_config, config))
if isinstance(config, list)
else [patch_config(config, copy_locals=True) for _ in range(length)]
)
[docs]def patch_... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/config.html |
8cd4c6f6b273-3 | ],
input: Input,
run_manager: CallbackManagerForChainRun,
config: RunnableConfig,
**kwargs: Any,
) -> Output:
"""Call function that may optionally accept a run_manager and/or config."""
if accepts_config(func):
kwargs["config"] = patch_config(config, callbacks=run_manager.get_child())
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/config.html |
8cd4c6f6b273-4 | [docs]def get_async_callback_manager_for_config(
config: RunnableConfig,
) -> AsyncCallbackManager:
from langchain.callbacks.manager import AsyncCallbackManager
return AsyncCallbackManager.configure(
inheritable_callbacks=config.get("callbacks"),
inheritable_tags=config.get("tags"),
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/config.html |
43d39f2fe33a-0 | langchain.evaluation.comparison.eval_chain.PairwiseStringEvalChain¶
class langchain.evaluation.comparison.eval_chain.PairwiseStringEvalChain[source]¶
Bases: PairwiseStringEvaluator, LLMEvalChain, LLMChain
A chain for comparing two outputs, such as the outputsof two models, prompts, or outputs of a single model on simil... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.comparison.eval_chain.PairwiseStringEvalChain.html |
43d39f2fe33a-1 | Callback handlers are called throughout the lifecycle of a call to a chain,
starting with on_chain_start, ending with on_chain_end or on_chain_error.
Each custom chain can optionally call additional callback methods, see Callback docs
for full details.
param llm: BaseLanguageModel [Required]¶
Language model to call.
pa... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.comparison.eval_chain.PairwiseStringEvalChain.html |
43d39f2fe33a-2 | You can use these to eg identify a specific instance of a chain with its use case.
param verbose: bool [Optional]¶
Whether or not run in verbose mode. In verbose mode, some intermediate logs
will be printed to the console. Defaults to langchain.verbose value.
__call__(inputs: Union[Dict[str, Any], Any], return_only_out... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.comparison.eval_chain.PairwiseStringEvalChain.html |
43d39f2fe33a-3 | Returns
A dict of named outputs. Should contain all outputs specified inChain.output_keys.
async aapply(input_list: List[Dict[str, Any]], callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None) → List[Dict[str, str]]¶
Utilize the LLM generate method for speed gains.
async aapply_and_parse(inp... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.comparison.eval_chain.PairwiseStringEvalChain.html |
43d39f2fe33a-4 | chain will be returned. Defaults to False.
callbacks – Callbacks to use for this chain run. These will be called in
addition to callbacks passed to the chain during construction, but only
these runtime callbacks will propagate to calls to other objects.
tags – List of string tags to pass to all callbacks. These will be... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.comparison.eval_chain.PairwiseStringEvalChain.html |
43d39f2fe33a-5 | Subclasses should override this method if they can run asynchronously.
apply(input_list: List[Dict[str, Any]], callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None) → List[Dict[str, str]]¶
Utilize the LLM generate method for speed gains.
apply_and_parse(input_list: List[Dict[str, Any]], cal... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.comparison.eval_chain.PairwiseStringEvalChain.html |
43d39f2fe33a-6 | The main difference between this method and Chain.__call__ is that this
method expects inputs to be passed directly in as positional arguments or
keyword arguments, whereas Chain.__call__ expects a single input dictionary
with all the inputs
Parameters
*args – If the chain expects a single input, it can be passed in as... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.comparison.eval_chain.PairwiseStringEvalChain.html |
43d39f2fe33a-7 | Subclasses should override this method if they support streaming output.
async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names: Optional[Sequence[... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.comparison.eval_chain.PairwiseStringEvalChain.html |
43d39f2fe33a-8 | 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, exclu... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.comparison.eval_chain.PairwiseStringEvalChain.html |
43d39f2fe33a-9 | Parameters
prediction (str) – The output string from the first model.
prediction_b (str) – The output string from the second model.
reference (Optional[str], optional) – The expected output / reference string.
input (Optional[str], optional) – The input string.
**kwargs – Additional keyword arguments, such as callbacks... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.comparison.eval_chain.PairwiseStringEvalChain.html |
43d39f2fe33a-10 | namespace is [“langchain”, “llms”, “openai”]
invoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None, **kwargs: Any) → Dict[str, Any]¶
classmethod is_lc_serializable() → bool¶
Is this class serializable?
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.comparison.eval_chain.PairwiseStringEvalChain.html |
43d39f2fe33a-11 | predict(callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, **kwargs: Any) → str¶
Format prompt with kwargs and pass to LLM.
Parameters
callbacks – Callbacks to pass to LLMChain
**kwargs – Keys to pass to prompt template.
Returns
Completion from LLM.
Example
completion = llm.predict(adjec... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.comparison.eval_chain.PairwiseStringEvalChain.html |
43d39f2fe33a-12 | Prepare prompts from inputs.
run(*args: Any, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → Any¶
Convenience method for executing chain.
The main difference between this method and Chain.__c... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.comparison.eval_chain.PairwiseStringEvalChain.html |
43d39f2fe33a-13 | save(file_path: Union[Path, str]) → None¶
Save the chain.
Expects Chain._chain_type property to be implemented and for memory to benull.
Parameters
file_path – Path to file to save the chain to.
Example
chain.save(file_path="path/chain.yaml")
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definiti... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.comparison.eval_chain.PairwiseStringEvalChain.html |
43d39f2fe33a-14 | Bind config to a Runnable, returning a new Runnable.
with_fallbacks(fallbacks: ~typing.Sequence[~langchain.schema.runnable.base.Runnable[~langchain.schema.runnable.utils.Input, ~langchain.schema.runnable.utils.Output]], *, exceptions_to_handle: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,)) →... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.comparison.eval_chain.PairwiseStringEvalChain.html |
3f84c2857fb4-0 | langchain.evaluation.criteria.eval_chain.Criteria¶
class langchain.evaluation.criteria.eval_chain.Criteria(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)[source]¶
A Criteria to evaluate.
CONCISENESS = 'conciseness'¶
RELEVANCE = 'relevance'¶
CORRECTNESS = 'correctness'¶
COHERENCE = ... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.criteria.eval_chain.Criteria.html |
b72433272d77-0 | langchain.evaluation.string_distance.base.StringDistance¶
class langchain.evaluation.string_distance.base.StringDistance(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)[source]¶
Distance metric to use.
DAMERAU_LEVENSHTEIN¶
The Damerau-Levenshtein distance.
LEVENSHTEIN¶
The Levenshte... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.string_distance.base.StringDistance.html |
36f2497ea19b-0 | langchain.evaluation.string_distance.base.PairwiseStringDistanceEvalChain¶
class langchain.evaluation.string_distance.base.PairwiseStringDistanceEvalChain[source]¶
Bases: PairwiseStringEvaluator, _RapidFuzzChainMixin
Compute string edit distances between two predictions.
param callback_manager: Optional[BaseCallbackMan... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.string_distance.base.PairwiseStringDistanceEvalChain.html |
36f2497ea19b-1 | Optional list of tags associated with the chain. Defaults to None.
These tags will be associated with each call to this chain,
and passed as arguments to the handlers defined in callbacks.
You can use these to eg identify a specific instance of a chain with its use case.
param verbose: bool [Optional]¶
Whether or not r... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.string_distance.base.PairwiseStringDistanceEvalChain.html |
36f2497ea19b-2 | metadata – Optional metadata associated with the chain. Defaults to None
include_run_info – Whether to include run info in the response. Defaults
to False.
Returns
A dict of named outputs. Should contain all outputs specified inChain.output_keys.
async abatch(inputs: List[Input], config: Optional[Union[RunnableConfig, ... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.string_distance.base.PairwiseStringDistanceEvalChain.html |
36f2497ea19b-3 | addition to tags passed to the chain during construction, but only
these runtime tags will propagate to calls to other objects.
metadata – Optional metadata associated with the chain. Defaults to None
include_run_info – Whether to include run info in the response. Defaults
to False.
Returns
A dict of named outputs. Sho... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.string_distance.base.PairwiseStringDistanceEvalChain.html |
36f2497ea19b-4 | Convenience method for executing chain.
The main difference between this method and Chain.__call__ is that this
method expects inputs to be passed directly in as positional arguments or
keyword arguments, whereas Chain.__call__ expects a single input dictionary
with all the inputs
Parameters
*args – If the chain expect... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.string_distance.base.PairwiseStringDistanceEvalChain.html |
36f2497ea19b-5 | Subclasses should override this method if they support streaming output.
async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names: Optional[Sequence[... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.string_distance.base.PairwiseStringDistanceEvalChain.html |
36f2497ea19b-6 | Compute the distance between two strings.
Parameters
a (str) – The first string.
b (str) – The second string.
Returns
The distance between the two strings.
Return type
float
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from t... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.string_distance.base.PairwiseStringDistanceEvalChain.html |
36f2497ea19b-7 | # -> {"_type": "foo", "verbose": False, ...}
evaluate_string_pairs(*, prediction: str, prediction_b: str, reference: Optional[str] = None, input: Optional[str] = None, **kwargs: Any) → dict¶
Evaluate the output string pairs.
Parameters
prediction (str) – The output string from the first model.
prediction_b (str) – The ... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.string_distance.base.PairwiseStringDistanceEvalChain.html |
36f2497ea19b-8 | 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 lc_id() → List[str]¶
A unique identifier for this class for serialization purposes.
The unique identifier is a ... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.string_distance.base.PairwiseStringDistanceEvalChain.html |
36f2497ea19b-9 | memory.
outputs – Dictionary of initial chain outputs.
return_only_outputs – Whether to only return the chain outputs. If False,
inputs are also added to the final outputs.
Returns
A dict of the final chain outputs.
run(*args: Any, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, tags:... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.string_distance.base.PairwiseStringDistanceEvalChain.html |
36f2497ea19b-10 | context = "Weather report for Boise, Idaho on 07/03/23..."
chain.run(question=question, context=context)
# -> "The temperature in Boise is..."
save(file_path: Union[Path, str]) → None¶
Save the chain.
Expects Chain._chain_type property to be implemented and for memory to benull.
Parameters
file_path – Path to file to s... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.string_distance.base.PairwiseStringDistanceEvalChain.html |
36f2497ea19b-11 | Bind config to a Runnable, returning a new Runnable.
with_fallbacks(fallbacks: ~typing.Sequence[~langchain.schema.runnable.base.Runnable[~langchain.schema.runnable.utils.Input, ~langchain.schema.runnable.utils.Output]], *, exceptions_to_handle: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,)) →... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.string_distance.base.PairwiseStringDistanceEvalChain.html |
36f2497ea19b-12 | property requires_input: bool¶
Whether this evaluator requires an input string.
property requires_reference: bool¶
Whether this evaluator requires a reference label. | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.string_distance.base.PairwiseStringDistanceEvalChain.html |
856f7814567c-0 | langchain.evaluation.embedding_distance.base.EmbeddingDistanceEvalChain¶
class langchain.evaluation.embedding_distance.base.EmbeddingDistanceEvalChain[source]¶
Bases: _EmbeddingDistanceChainMixin, StringEvaluator
Use embedding distances to score semantic difference between
a prediction and reference.
Examples
>>> chain... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.embedding_distance.base.EmbeddingDistanceEvalChain.html |
856f7814567c-1 | and passed as arguments to the handlers defined in callbacks.
You can use these to eg identify a specific instance of a chain with its use case.
param tags: Optional[List[str]] = None¶
Optional list of tags associated with the chain. Defaults to None.
These tags will be associated with each call to this chain,
and pass... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.embedding_distance.base.EmbeddingDistanceEvalChain.html |
856f7814567c-2 | tags – List of string tags to pass to all callbacks. These will be passed in
addition to tags passed to the chain during construction, but only
these runtime tags will propagate to calls to other objects.
metadata – Optional metadata associated with the chain. Defaults to None
include_run_info – Whether to include run ... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.embedding_distance.base.EmbeddingDistanceEvalChain.html |
856f7814567c-3 | addition to callbacks passed to the chain during construction, but only
these runtime callbacks will propagate to calls to other objects.
tags – List of string tags to pass to all callbacks. These will be passed in
addition to tags passed to the chain during construction, but only
these runtime tags will propagate to c... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.embedding_distance.base.EmbeddingDistanceEvalChain.html |
856f7814567c-4 | Call the chain on all inputs in the list.
async arun(*args: Any, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → Any¶
Convenience method for executing chain.
The main difference between this ... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.embedding_distance.base.EmbeddingDistanceEvalChain.html |
856f7814567c-5 | # -> "The temperature in Boise is..."
async astream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶
Default implementation of astream, which calls ainvoke.
Subclasses should override this method if they support streaming output.
async astream_log(input: Any, conf... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.embedding_distance.base.EmbeddingDistanceEvalChain.html |
856f7814567c-6 | Subclasses should override this method if they can batch more efficiently.
bind(**kwargs: Any) → Runnable[Input, Output]¶
Bind arguments to a Runnable, returning a new Runnable.
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ fr... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.embedding_distance.base.EmbeddingDistanceEvalChain.html |
856f7814567c-7 | Evaluate Chain or LLM output, based on optional input and label.
Parameters
prediction (str) – The LLM or chain prediction to evaluate.
reference (Optional[str], optional) – The reference label to evaluate against.
input (Optional[str], optional) – The input to consider during evaluation.
**kwargs – Additional keyword ... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.embedding_distance.base.EmbeddingDistanceEvalChain.html |
856f7814567c-8 | The unique identifier is a list of strings that describes the path
to the object.
map() → Runnable[List[Input], List[Output]]¶
Return a new Runnable that maps a list of inputs to a list of outputs,
by calling invoke() with each input.
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encod... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.embedding_distance.base.EmbeddingDistanceEvalChain.html |
856f7814567c-9 | Returns
A dict of the final chain outputs.
run(*args: Any, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → Any¶
Convenience method for executing chain.
The main difference between this method... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.embedding_distance.base.EmbeddingDistanceEvalChain.html |
856f7814567c-10 | save(file_path: Union[Path, str]) → None¶
Save the chain.
Expects Chain._chain_type property to be implemented and for memory to benull.
Parameters
file_path – Path to file to save the chain to.
Example
chain.save(file_path="path/chain.yaml")
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definiti... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.embedding_distance.base.EmbeddingDistanceEvalChain.html |
856f7814567c-11 | Bind config to a Runnable, returning a new Runnable.
with_fallbacks(fallbacks: ~typing.Sequence[~langchain.schema.runnable.base.Runnable[~langchain.schema.runnable.utils.Input, ~langchain.schema.runnable.utils.Output]], *, exceptions_to_handle: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,)) →... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.embedding_distance.base.EmbeddingDistanceEvalChain.html |
856f7814567c-12 | property requires_reference: bool¶
Return whether the chain requires a reference.
Returns
True if a reference is required, False otherwise.
Return type
bool | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.embedding_distance.base.EmbeddingDistanceEvalChain.html |
fa62308b94a6-0 | langchain.evaluation.loading.load_evaluators¶
langchain.evaluation.loading.load_evaluators(evaluators: Sequence[EvaluatorType], *, llm: Optional[BaseLanguageModel] = None, config: Optional[dict] = None, **kwargs: Any) → List[Union[Chain, StringEvaluator]][source]¶
Load evaluators specified by a list of evaluator types.... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.loading.load_evaluators.html |
f5c2844567c9-0 | langchain.evaluation.agents.trajectory_eval_chain.TrajectoryEvalChain¶
class langchain.evaluation.agents.trajectory_eval_chain.TrajectoryEvalChain[source]¶
Bases: AgentTrajectoryEvaluator, LLMEvalChain
A chain for evaluating ReAct style agents.
This chain is used to evaluate ReAct style agents by reasoning about
the se... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.agents.trajectory_eval_chain.TrajectoryEvalChain.html |
f5c2844567c9-1 | Deprecated, use callbacks instead.
param callbacks: Callbacks = None¶
Optional list of callback handlers (or callback manager). Defaults to None.
Callback handlers are called throughout the lifecycle of a call to a chain,
starting with on_chain_start, ending with on_chain_end or on_chain_error.
Each custom chain can op... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.agents.trajectory_eval_chain.TrajectoryEvalChain.html |
f5c2844567c9-2 | param verbose: bool [Optional]¶
Whether or not run in verbose mode. In verbose mode, some intermediate logs
will be printed to the console. Defaults to langchain.verbose value.
__call__(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallba... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.agents.trajectory_eval_chain.TrajectoryEvalChain.html |
f5c2844567c9-3 | Returns
A dict of named outputs. Should contain all outputs specified inChain.output_keys.
async abatch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Optional[Any]) → List[Output]¶
Default implementation of abatch, which calls ai... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.agents.trajectory_eval_chain.TrajectoryEvalChain.html |
f5c2844567c9-4 | include_run_info – Whether to include run info in the response. Defaults
to False.
Returns
A dict of named outputs. Should contain all outputs specified inChain.output_keys.
async aevaluate_agent_trajectory(*, prediction: str, agent_trajectory: Sequence[Tuple[AgentAction, str]], input: str, reference: Optional[str] = N... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.agents.trajectory_eval_chain.TrajectoryEvalChain.html |
f5c2844567c9-5 | with all the inputs
Parameters
*args – If the chain expects a single input, it can be passed in as the
sole positional argument.
callbacks – Callbacks to use for this chain run. These will be called in
addition to callbacks passed to the chain during construction, but only
these runtime callbacks will propagate to call... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.agents.trajectory_eval_chain.TrajectoryEvalChain.html |
f5c2844567c9-6 | Subclasses should override this method if they support streaming output.
async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names: Optional[Sequence[... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.agents.trajectory_eval_chain.TrajectoryEvalChain.html |
f5c2844567c9-7 | 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, exclu... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.agents.trajectory_eval_chain.TrajectoryEvalChain.html |
f5c2844567c9-8 | input (str) – The input to the agent.
reference (Optional[str]) – The reference answer.
Returns
The evaluation result.
Return type
dict
classmethod from_llm(llm: BaseLanguageModel, agent_tools: Optional[Sequence[BaseTool]] = None, output_parser: Optional[TrajectoryOutputParser] = None, **kwargs: Any) → TrajectoryEvalCh... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.agents.trajectory_eval_chain.TrajectoryEvalChain.html |
f5c2844567c9-9 | classmethod is_lc_serializable() → bool¶
Is this class serializable?
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_defa... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.agents.trajectory_eval_chain.TrajectoryEvalChain.html |
f5c2844567c9-10 | Validate and prep inputs.
prep_outputs(inputs: Dict[str, str], outputs: Dict[str, str], return_only_outputs: bool = False) → Dict[str, str]¶
Validate and prepare chain outputs, and save info about this run to memory.
Parameters
inputs – Dictionary of chain inputs, including any inputs added by chain
memory.
outputs – D... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.agents.trajectory_eval_chain.TrajectoryEvalChain.html |
f5c2844567c9-11 | Example
# Suppose we have a single-input chain that takes a 'question' string:
chain.run("What's the temperature in Boise, Idaho?")
# -> "The temperature in Boise is..."
# Suppose we have a multi-input chain that takes a 'question' string
# and 'context' string:
question = "What's the temperature in Boise, Idaho?"
cont... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.agents.trajectory_eval_chain.TrajectoryEvalChain.html |
f5c2844567c9-12 | 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¶
with_config(config: Optional[RunnableConfig] = None, **kwargs: Any) → Runnable[Input, Output]¶
Bind config to a Runnable, returning a new Runna... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.agents.trajectory_eval_chain.TrajectoryEvalChain.html |
f5c2844567c9-13 | Returns
The output keys.
Return type
List[str]
property output_schema: Type[pydantic.main.BaseModel]¶
property requires_input: bool¶
Whether this evaluator requires an input string.
property requires_reference: bool¶
Whether this evaluator requires a reference label. | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.agents.trajectory_eval_chain.TrajectoryEvalChain.html |
ed7d3083924d-0 | langchain.evaluation.embedding_distance.base.PairwiseEmbeddingDistanceEvalChain¶
class langchain.evaluation.embedding_distance.base.PairwiseEmbeddingDistanceEvalChain[source]¶
Bases: _EmbeddingDistanceChainMixin, PairwiseStringEvaluator
Use embedding distances to score semantic difference between two predictions.
Examp... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.embedding_distance.base.PairwiseEmbeddingDistanceEvalChain.html |
ed7d3083924d-1 | and passed as arguments to the handlers defined in callbacks.
You can use these to eg identify a specific instance of a chain with its use case.
param tags: Optional[List[str]] = None¶
Optional list of tags associated with the chain. Defaults to None.
These tags will be associated with each call to this chain,
and pass... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.embedding_distance.base.PairwiseEmbeddingDistanceEvalChain.html |
ed7d3083924d-2 | tags – List of string tags to pass to all callbacks. These will be passed in
addition to tags passed to the chain during construction, but only
these runtime tags will propagate to calls to other objects.
metadata – Optional metadata associated with the chain. Defaults to None
include_run_info – Whether to include run ... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.embedding_distance.base.PairwiseEmbeddingDistanceEvalChain.html |
ed7d3083924d-3 | addition to callbacks passed to the chain during construction, but only
these runtime callbacks will propagate to calls to other objects.
tags – List of string tags to pass to all callbacks. These will be passed in
addition to tags passed to the chain during construction, but only
these runtime tags will propagate to c... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.embedding_distance.base.PairwiseEmbeddingDistanceEvalChain.html |
ed7d3083924d-4 | Call the chain on all inputs in the list.
async arun(*args: Any, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → Any¶
Convenience method for executing chain.
The main difference between this ... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.embedding_distance.base.PairwiseEmbeddingDistanceEvalChain.html |
ed7d3083924d-5 | # -> "The temperature in Boise is..."
async astream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶
Default implementation of astream, which calls ainvoke.
Subclasses should override this method if they support streaming output.
async astream_log(input: Any, conf... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.embedding_distance.base.PairwiseEmbeddingDistanceEvalChain.html |
ed7d3083924d-6 | Subclasses should override this method if they can batch more efficiently.
bind(**kwargs: Any) → Runnable[Input, Output]¶
Bind arguments to a Runnable, returning a new Runnable.
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ fr... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.embedding_distance.base.PairwiseEmbeddingDistanceEvalChain.html |
ed7d3083924d-7 | # -> {"_type": "foo", "verbose": False, ...}
evaluate_string_pairs(*, prediction: str, prediction_b: str, reference: Optional[str] = None, input: Optional[str] = None, **kwargs: Any) → dict¶
Evaluate the output string pairs.
Parameters
prediction (str) – The output string from the first model.
prediction_b (str) – The ... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.embedding_distance.base.PairwiseEmbeddingDistanceEvalChain.html |
ed7d3083924d-8 | 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 lc_id() → List[str]¶
A unique identifier for this class for serialization purposes.
The unique identifier is a ... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.embedding_distance.base.PairwiseEmbeddingDistanceEvalChain.html |
ed7d3083924d-9 | memory.
outputs – Dictionary of initial chain outputs.
return_only_outputs – Whether to only return the chain outputs. If False,
inputs are also added to the final outputs.
Returns
A dict of the final chain outputs.
run(*args: Any, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, tags:... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.embedding_distance.base.PairwiseEmbeddingDistanceEvalChain.html |
ed7d3083924d-10 | context = "Weather report for Boise, Idaho on 07/03/23..."
chain.run(question=question, context=context)
# -> "The temperature in Boise is..."
save(file_path: Union[Path, str]) → None¶
Save the chain.
Expects Chain._chain_type property to be implemented and for memory to benull.
Parameters
file_path – Path to file to s... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.embedding_distance.base.PairwiseEmbeddingDistanceEvalChain.html |
ed7d3083924d-11 | Bind config to a Runnable, returning a new Runnable.
with_fallbacks(fallbacks: ~typing.Sequence[~langchain.schema.runnable.base.Runnable[~langchain.schema.runnable.utils.Input, ~langchain.schema.runnable.utils.Output]], *, exceptions_to_handle: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,)) →... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.embedding_distance.base.PairwiseEmbeddingDistanceEvalChain.html |
719006b6abdd-0 | langchain.evaluation.agents.trajectory_eval_chain.TrajectoryOutputParser¶
class langchain.evaluation.agents.trajectory_eval_chain.TrajectoryOutputParser[source]¶
Bases: BaseOutputParser
Trajectory output parser.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if th... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.agents.trajectory_eval_chain.TrajectoryOutputParser.html |
719006b6abdd-1 | Default implementation of astream, which calls ainvoke.
Subclasses should override this method if they support streaming output.
async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.agents.trajectory_eval_chain.TrajectoryOutputParser.html |
719006b6abdd-2 | Bind arguments to a Runnable, returning a new Runnable.
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... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.agents.trajectory_eval_chain.TrajectoryOutputParser.html |
719006b6abdd-3 | classmethod is_lc_serializable() → bool¶
Is this class serializable?
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_defa... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.agents.trajectory_eval_chain.TrajectoryOutputParser.html |
719006b6abdd-4 | 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¶
parse_result(result: List[Generation], *, partial: bool = False) → T¶
Parse a list of candidate model Generations... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.agents.trajectory_eval_chain.TrajectoryOutputParser.html |
719006b6abdd-5 | to_json_not_implemented() → SerializedNotImplemented¶
transform(input: Iterator[Input], config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → Iterator[Output]¶
Default implementation of transform, which buffers input and then calls stream.
Subclasses should override this method if they can start producing... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.agents.trajectory_eval_chain.TrajectoryOutputParser.html |
719006b6abdd-6 | For example,{“openai_api_key”: “OPENAI_API_KEY”}
property output_schema: Type[pydantic.main.BaseModel]¶ | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.agents.trajectory_eval_chain.TrajectoryOutputParser.html |
a43807e0b3e8-0 | langchain.evaluation.criteria.eval_chain.LabeledCriteriaEvalChain¶
class langchain.evaluation.criteria.eval_chain.LabeledCriteriaEvalChain[source]¶
Bases: CriteriaEvalChain
Criteria evaluation chain that requires references.
param callback_manager: Optional[BaseCallbackManager] = None¶
Deprecated, use callbacks instead... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.criteria.eval_chain.LabeledCriteriaEvalChain.html |
a43807e0b3e8-1 | Prompt object to use.
param return_final_only: bool = True¶
Whether to return only the final parsed result. Defaults to True.
If false, will return a bunch of extra information about the generation.
param tags: Optional[List[str]] = None¶
Optional list of tags associated with the chain. Defaults to None.
These tags wil... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.criteria.eval_chain.LabeledCriteriaEvalChain.html |
a43807e0b3e8-2 | these runtime callbacks will propagate to calls to other objects.
tags – List of string tags to pass to all callbacks. These will be passed in
addition to tags passed to the chain during construction, but only
these runtime tags will propagate to calls to other objects.
metadata – Optional metadata associated with the ... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.criteria.eval_chain.LabeledCriteriaEvalChain.html |
a43807e0b3e8-3 | Asynchronously execute the chain.
Parameters
inputs – Dictionary of inputs, or single input if chain expects
only one param. Should contain all inputs specified in
Chain.input_keys except for inputs that will be set by the chain’s
memory.
return_only_outputs – Whether to return only outputs in the
response. If True, on... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.criteria.eval_chain.LabeledCriteriaEvalChain.html |
a43807e0b3e8-4 | Returns
The evaluation results containing the score or value.
Return type
dict
async agenerate(input_list: List[Dict[str, Any]], run_manager: Optional[AsyncCallbackManagerForChainRun] = None) → LLMResult¶
Generate LLM result from inputs.
async ainvoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None, **kw... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.criteria.eval_chain.LabeledCriteriaEvalChain.html |
a43807e0b3e8-5 | Call apredict and then parse the results.
async aprep_prompts(input_list: List[Dict[str, Any]], run_manager: Optional[AsyncCallbackManagerForChainRun] = None) → Tuple[List[PromptValue], Optional[List[str]]]¶
Prepare prompts from inputs.
async arun(*args: Any, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCal... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.criteria.eval_chain.LabeledCriteriaEvalChain.html |
a43807e0b3e8-6 | question = "What's the temperature in Boise, Idaho?"
context = "Weather report for Boise, Idaho on 07/03/23..."
await chain.arun(question=question, context=context)
# -> "The temperature in Boise is..."
async astream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.criteria.eval_chain.LabeledCriteriaEvalChain.html |
a43807e0b3e8-7 | input is still being generated.
batch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Optional[Any]) → List[Output]¶
Default implementation of batch, which calls invoke N times.
Subclasses should override this method if they can ba... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.criteria.eval_chain.LabeledCriteriaEvalChain.html |
a43807e0b3e8-8 | dict(**kwargs: Any) → Dict¶
Dictionary representation of chain.
Expects Chain._chain_type property to be implemented and for memory to benull.
Parameters
**kwargs – Keyword arguments passed to default pydantic.BaseModel.dict
method.
Returns
A dictionary representation of the chain.
Example
chain.dict(exclude_unset=True... | https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.criteria.eval_chain.LabeledCriteriaEvalChain.html |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.