id stringlengths 14 16 | text stringlengths 13 2.7k | source stringlengths 57 178 |
|---|---|---|
b33b070f8c5c-16 | "narrative_input": "what\'s the pet count for cindy and marcia?",\n "llm_error_msg": "",\n "expression": "SELECT name, value FROM df WHERE name IN (\'cindy\', \'marcia\')"\n }}\n\n\n\n\nnarrative_input: what\'s the total pet count for cindy and marcia?\n\n\n\n# JSON:\n\n {{\n "narrative_input... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.QueryChain.html |
b33b070f8c5c-17 | "narrative_input": "what\'s the total pet count for TED and cindy?",\n "llm_error_msg": "",\n "expression": "SELECT SUM(value) FROM df WHERE name IN (\'TED\', \'cindy\')"\n }}\n\n\n\n\nnarrative_input: what\'s the best for TED and cindy?\n\n\n\n\n# JSON:\n\n {{\n "narrative_input": "what\'s t... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.QueryChain.html |
b33b070f8c5c-18 | meta private: | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.QueryChain.html |
87cc00bc14bd-0 | langchain_experimental.cpal.base.CPALChain¶
class langchain_experimental.cpal.base.CPALChain[source]¶
Bases: _BaseStoryElementChain
Causal program-aided language (CPAL) chain implementation.
Security note: The building blocks of this class include the implementationof an AI technique that generates SQL code. If those S... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CPALChain.html |
87cc00bc14bd-1 | and at the end of every chain. At the start, memory loads variables and passes
them along in the chain. At the end, it saves any returned variables.
There are many different types of memory - please see memory docs
for the full catalog.
param metadata: Optional[Dict[str, Any]] = None¶
Optional metadata associated with ... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CPALChain.html |
87cc00bc14bd-2 | 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, only new keys generated by this chain will be
returned. If False, both input keys and new keys generated by thi... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CPALChain.html |
87cc00bc14bd-3 | e.g., if the underlying runnable uses an API which supports a batch mode.
async acall(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, ... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CPALChain.html |
87cc00bc14bd-4 | Default implementation of ainvoke, calls invoke from a thread.
The default implementation allows usage of async code even if
the runnable did not implement a native async version of invoke.
Subclasses should override this method if they can run asynchronously.
apply(input_list: List[Dict[str, Any]], callbacks: Optional... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CPALChain.html |
87cc00bc14bd-5 | # -> "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?"
context = "Weather report for Boise, Idaho on 07/03/23..."
await chain.arun(question=question, context=context)
# -> "The temperature in... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CPALChain.html |
87cc00bc14bd-6 | Default implementation of atransform, which buffers input and calls astream.
Subclasses should override this method if they can start producing output while
input is still being generated.
batch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CPALChain.html |
87cc00bc14bd-7 | 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... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CPALChain.html |
87cc00bc14bd-8 | instantiation depends on component chains
Security note: The building blocks of this class include the implementationof an AI technique that generates SQL code. If those SQL commands
are executed, it’s critical to ensure they use credentials that
are narrowly-scoped to only include the permissions this chain needs.
Fai... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CPALChain.html |
87cc00bc14bd-9 | Parameters
config – A config to use when generating the schema.
Returns
A pydantic model that can be used to validate output.
invoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None, **kwargs: Any) → Dict[str, Any]¶
Transform a single input into an output. Override to implement.
Parameters
input – The inp... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CPALChain.html |
87cc00bc14bd-10 | 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, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod parse_obj(obj: Any) → Model¶
cl... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CPALChain.html |
87cc00bc14bd-11 | 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... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CPALChain.html |
87cc00bc14bd-12 | 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... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CPALChain.html |
87cc00bc14bd-13 | Add fallbacks to a runnable, returning a new Runnable.
Parameters
fallbacks – A sequence of runnables to try if the original runnable fails.
exceptions_to_handle – A tuple of exception types to handle.
Returns
A new Runnable that will try the original runnable, and then each
fallback in order, upon failures.
with_liste... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CPALChain.html |
87cc00bc14bd-14 | Bind input and output types to a Runnable, returning a new Runnable.
property InputType: Type[langchain.schema.runnable.utils.Input]¶
The type of input this runnable accepts specified as a type annotation.
property OutputType: Type[langchain.schema.runnable.utils.Output]¶
The type of output this runnable produces speci... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CPALChain.html |
ce49027f9a43-0 | langchain_experimental.cpal.models.SystemSettingModel¶
class langchain_experimental.cpal.models.SystemSettingModel[source]¶
Bases: BaseModel
Initial global conditions for the system.
{“parameter”: “interest_rate”, “value”: .05}
Create a new model by parsing and validating input data from keyword arguments.
Raises Valid... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.models.SystemSettingModel.html |
ce49027f9a43-1 | 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, ex... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.models.SystemSettingModel.html |
ce49027f9a43-2 | 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... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.models.SystemSettingModel.html |
f61d2c30697d-0 | langchain_experimental.cpal.base.CausalChain¶
class langchain_experimental.cpal.base.CausalChain[source]¶
Bases: _BaseStoryElementChain
Translate the causal narrative into a stack of operations.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cann... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CausalChain.html |
f61d2c30697d-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 verbose: bool [Optional]¶
Whether or not run in verbose mode. In verbose mode, some intermediate logs
will be printed to the console. Defaults to the global verbose valu... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CausalChain.html |
f61d2c30697d-2 | 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, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwar... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CausalChain.html |
f61d2c30697d-3 | 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 ... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CausalChain.html |
f61d2c30697d-4 | 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... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CausalChain.html |
f61d2c30697d-5 | Stream all output from a runnable, as reported to the callback system.
This includes all inner runs of LLMs, Retrievers, Tools, etc.
Output is streamed as Log objects, which include a list of
jsonpatch ops that describe how the state of the run has changed in each
step, and the final state of the run.
The jsonpatch ops... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CausalChain.html |
f61d2c30697d-6 | Returns
A pydantic model that can be used to validate config.
configurable_alternatives(which: ConfigurableField, default_key: str = 'default', **kwargs: Union[Runnable[Input, Output], Callable[[], Runnable[Input, Output]]]) → RunnableSerializable[Input, Output]¶
configurable_fields(**kwargs: Union[ConfigurableField, C... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CausalChain.html |
f61d2c30697d-7 | method.
Returns
A dictionary representation of the chain.
Example
chain.dict(exclude_unset=True)
# -> {"_type": "foo", "verbose": False, ...}
classmethod from_orm(obj: Any) → Model¶
classmethod from_univariate_prompt(llm: BaseLanguageModel, **kwargs: Any) → Any¶
get_input_schema(config: Optional[RunnableConfig] = None)... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CausalChain.html |
f61d2c30697d-8 | Transform a single input into an output. Override to implement.
Parameters
input – The input to the runnable.
config – A config to use when invoking the runnable.
The config supports standard keys like ‘tags’, ‘metadata’ for tracing
purposes, ‘max_concurrency’ for controlling how much work to do
in parallel, and other ... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CausalChain.html |
f61d2c30697d-9 | 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 parser() → PydanticOutputParser¶
Parse LLM output into a pydantic object.
prep_inputs(inputs: Union[D... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CausalChain.html |
f61d2c30697d-10 | 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... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CausalChain.html |
f61d2c30697d-11 | stream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → Iterator[Output]¶
Default implementation of stream, which calls invoke.
Subclasses should override this method if they support streaming output.
to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶
to_json_not_implem... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CausalChain.html |
f61d2c30697d-12 | Bind lifecycle listeners to a Runnable, returning a new Runnable.
on_start: Called before the runnable starts running, with the Run object.
on_end: Called after the runnable finishes running, with the Run object.
on_error: Called if the runnable throws an error, with the Run object.
The Run object contains information ... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CausalChain.html |
f61d2c30697d-13 | property input_schema: Type[pydantic.main.BaseModel]¶
The type of input this runnable accepts specified as a pydantic model.
property lc_attributes: Dict¶
List of attribute names that should be included in the serialized kwargs.
These attributes must be accepted by the constructor.
property lc_secrets: Dict[str, str]¶
... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CausalChain.html |
f61d2c30697d-14 | template: ClassVar[str] = 'Transform the math story plot into a JSON object. Don\'t guess at any of the parts.\n\n{format_instructions}\n\n\n\nStory: Boris has seven times the number of pets as Marcia. Jan has three times the number of pets as Marcia. Marcia has two more pets than Cindy.\n\n\n\n# JSON:\n\n\n\n{{\n "... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CausalChain.html |
f61d2c30697d-15 | JSON:\n\n\n\n{{\n "attribute": "money",\n "entities": [\n {{\n "name": "boris",\n "value": 0,\n "depends_on": [],\n "code": "pass"\n }},\n {{\n "name": "marcia",\n "value": 0,\n "depends_on": ["boris"],\n ... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CausalChain.html |
f61d2c30697d-16 | meta private: | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.base.CausalChain.html |
f9245fbe795a-0 | langchain_experimental.cpal.models.EntityModel¶
class langchain_experimental.cpal.models.EntityModel[source]¶
Bases: BaseModel
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 code: str [Required]¶
enti... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.models.EntityModel.html |
f9245fbe795a-1 | 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, ex... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.models.EntityModel.html |
f9245fbe795a-2 | 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... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.models.EntityModel.html |
b4766b86e928-0 | langchain_experimental.cpal.models.StoryModel¶
class langchain_experimental.cpal.models.StoryModel[source]¶
Bases: BaseModel
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 causal_operations: Any = Non... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.models.StoryModel.html |
b4766b86e928-1 | 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, ex... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.models.StoryModel.html |
b4766b86e928-2 | print_debug_report() → None[source]¶
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)... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.models.StoryModel.html |
c2d6e8af0282-0 | langchain_experimental.cpal.models.EntitySettingModel¶
class langchain_experimental.cpal.models.EntitySettingModel[source]¶
Bases: BaseModel
Initial conditions for an entity
{“name”: “bud”, “attribute”: “pet_count”, “value”: 12}
Create a new model by parsing and validating input data from keyword arguments.
Raises Vali... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.models.EntitySettingModel.html |
c2d6e8af0282-1 | 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, ex... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.models.EntitySettingModel.html |
c2d6e8af0282-2 | 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... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.models.EntitySettingModel.html |
74dadf5e1737-0 | langchain_experimental.cpal.models.QueryModel¶
class langchain_experimental.cpal.models.QueryModel[source]¶
Bases: BaseModel
translate a question about the story outcome into a programmatic expression
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input dat... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.models.QueryModel.html |
74dadf5e1737-1 | 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, ex... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.models.QueryModel.html |
74dadf5e1737-2 | 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... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.models.QueryModel.html |
3a9b40e255b2-0 | langchain_experimental.cpal.models.NarrativeModel¶
class langchain_experimental.cpal.models.NarrativeModel[source]¶
Bases: BaseModel
Represent the narrative input as three story elements.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be p... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.models.NarrativeModel.html |
3a9b40e255b2-1 | 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, ex... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.models.NarrativeModel.html |
3a9b40e255b2-2 | 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... | lang/api.python.langchain.com/en/latest/cpal/langchain_experimental.cpal.models.NarrativeModel.html |
bb875a277a69-0 | langchain.retrievers.bm25.default_preprocessing_func¶
langchain.retrievers.bm25.default_preprocessing_func(text: str) → List[str][source]¶ | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.bm25.default_preprocessing_func.html |
0f3353b05b13-0 | langchain.retrievers.self_query.opensearch.OpenSearchTranslator¶
class langchain.retrievers.self_query.opensearch.OpenSearchTranslator[source]¶
Translate OpenSearch internal query domain-specific
language elements to valid filters.
Attributes
allowed_comparators
Subset of allowed logical comparators.
allowed_operators
... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.self_query.opensearch.OpenSearchTranslator.html |
157e7d49e696-0 | langchain_experimental.retrievers.vector_sql_database.VectorSQLDatabaseChainRetriever¶
class langchain_experimental.retrievers.vector_sql_database.VectorSQLDatabaseChainRetriever[source]¶
Bases: BaseRetriever
Retriever that uses SQLDatabase as Retriever
Create a new model by parsing and validating input data from keywo... | lang/api.python.langchain.com/en/latest/retrievers/langchain_experimental.retrievers.vector_sql_database.VectorSQLDatabaseChainRetriever.html |
157e7d49e696-1 | e.g., if the underlying runnable uses an API which supports a batch mode.
async aget_relevant_documents(query: str, *, callbacks: Callbacks = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, run_name: Optional[str] = None, **kwargs: Any) → List[Document]¶
Asynchronously get documents r... | lang/api.python.langchain.com/en/latest/retrievers/langchain_experimental.retrievers.vector_sql_database.VectorSQLDatabaseChainRetriever.html |
157e7d49e696-2 | Subclasses should override this method if they support streaming output.
async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, diff: bool = True, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names:... | lang/api.python.langchain.com/en/latest/retrievers/langchain_experimental.retrievers.vector_sql_database.VectorSQLDatabaseChainRetriever.html |
157e7d49e696-3 | e.g., if the underlying runnable uses an API which supports a batch mode.
bind(**kwargs: Any) → Runnable[Input, Output]¶
Bind arguments to a Runnable, returning a new Runnable.
config_schema(*, include: Optional[Sequence[str]] = None) → Type[BaseModel]¶
The type of config this runnable accepts specified as a pydantic m... | lang/api.python.langchain.com/en/latest/retrievers/langchain_experimental.retrievers.vector_sql_database.VectorSQLDatabaseChainRetriever.html |
157e7d49e696-4 | 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(*, i... | lang/api.python.langchain.com/en/latest/retrievers/langchain_experimental.retrievers.vector_sql_database.VectorSQLDatabaseChainRetriever.html |
157e7d49e696-5 | Get a pydantic model that can be used to validate output to the runnable.
Runnables that leverage the configurable_fields and configurable_alternatives
methods will have a dynamic output schema that depends on which
configuration the runnable is invoked with.
This method allows to get an output schema for a specific co... | lang/api.python.langchain.com/en/latest/retrievers/langchain_experimental.retrievers.vector_sql_database.VectorSQLDatabaseChainRetriever.html |
157e7d49e696-6 | Returns
The output of the runnable.
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, exclu... | lang/api.python.langchain.com/en/latest/retrievers/langchain_experimental.retrievers.vector_sql_database.VectorSQLDatabaseChainRetriever.html |
157e7d49e696-7 | classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
stream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → Iterator[Output]¶
Default implementation of stream, which calls invoke.
Subclasses should override t... | lang/api.python.langchain.com/en/latest/retrievers/langchain_experimental.retrievers.vector_sql_database.VectorSQLDatabaseChainRetriever.html |
157e7d49e696-8 | fallback in order, upon failures.
with_listeners(*, on_start: Optional[Listener] = None, on_end: Optional[Listener] = None, on_error: Optional[Listener] = None) → Runnable[Input, Output]¶
Bind lifecycle listeners to a Runnable, returning a new Runnable.
on_start: Called before the runnable starts running, with the Run ... | lang/api.python.langchain.com/en/latest/retrievers/langchain_experimental.retrievers.vector_sql_database.VectorSQLDatabaseChainRetriever.html |
157e7d49e696-9 | The type of output this runnable produces specified as a type annotation.
property config_specs: List[langchain.schema.runnable.utils.ConfigurableFieldSpec]¶
List configurable fields for this runnable.
property input_schema: Type[pydantic.main.BaseModel]¶
The type of input this runnable accepts specified as a pydantic ... | lang/api.python.langchain.com/en/latest/retrievers/langchain_experimental.retrievers.vector_sql_database.VectorSQLDatabaseChainRetriever.html |
be934a66cb35-0 | langchain.retrievers.kendra.DocumentAttributeValue¶
class langchain.retrievers.kendra.DocumentAttributeValue[source]¶
Bases: BaseModel
Value of a document attribute.
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 ... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.kendra.DocumentAttributeValue.html |
be934a66cb35-1 | 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, ex... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.kendra.DocumentAttributeValue.html |
be934a66cb35-2 | 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... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.kendra.DocumentAttributeValue.html |
fc11f34c36dd-0 | langchain.retrievers.pubmed.PubMedRetriever¶
class langchain.retrievers.pubmed.PubMedRetriever[source]¶
Bases: BaseRetriever, PubMedAPIWrapper
PubMed API retriever.
It wraps load() to get_relevant_documents().
It uses all PubMedAPIWrapper arguments without any change.
Create a new model by parsing and validating input ... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.pubmed.PubMedRetriever.html |
fc11f34c36dd-1 | use case.
param top_k_results: int = 3¶
async abatch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Optional[Any]) → List[Output]¶
Default implementation runs ainvoke in parallel using asyncio.gather.
The default implementation of... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.pubmed.PubMedRetriever.html |
fc11f34c36dd-2 | Subclasses should override this method if they can run asynchronously.
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.
a... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.pubmed.PubMedRetriever.html |
fc11f34c36dd-3 | Default implementation runs invoke in parallel using a thread pool executor.
The default implementation of batch works well for IO bound runnables.
Subclasses should override this method if they can batch more efficiently;
e.g., if the underlying runnable uses an API which supports a batch mode.
bind(**kwargs: Any) → R... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.pubmed.PubMedRetriever.html |
fc11f34c36dd-4 | 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 creat... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.pubmed.PubMedRetriever.html |
fc11f34c36dd-5 | namespace is [“langchain”, “llms”, “openai”]
get_output_schema(config: Optional[RunnableConfig] = None) → Type[BaseModel]¶
Get a pydantic model that can be used to validate output to the runnable.
Runnables that leverage the configurable_fields and configurable_alternatives
methods will have a dynamic output schema tha... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.pubmed.PubMedRetriever.html |
fc11f34c36dd-6 | purposes, ‘max_concurrency’ for controlling how much work to do
in parallel, and other keys. Please refer to the RunnableConfig
for more details.
Returns
The output of the runnable.
classmethod is_lc_serializable() → bool¶
Is this class serializable?
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]]... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.pubmed.PubMedRetriever.html |
fc11f34c36dd-7 | by calling invoke() with each input.
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 = No... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.pubmed.PubMedRetriever.html |
fc11f34c36dd-8 | 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... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.pubmed.PubMedRetriever.html |
fc11f34c36dd-9 | added to the run.
with_retry(*, retry_if_exception_type: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,), wait_exponential_jitter: bool = True, stop_after_attempt: int = 3) → Runnable[Input, Output]¶
Create a new Runnable that retries the original runnable on exceptions.
Parameters
retry_if_exc... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.pubmed.PubMedRetriever.html |
fc11f34c36dd-10 | property output_schema: Type[pydantic.main.BaseModel]¶
The type of output this runnable produces specified as a pydantic model.
Examples using PubMedRetriever¶
PubMed | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.pubmed.PubMedRetriever.html |
cfa74f0ff6c6-0 | langchain.retrievers.cohere_rag_retriever.CohereRagRetriever¶
class langchain.retrievers.cohere_rag_retriever.CohereRagRetriever[source]¶
Bases: BaseRetriever
Cohere Chat API with RAG.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be pars... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.cohere_rag_retriever.CohereRagRetriever.html |
cfa74f0ff6c6-1 | The default implementation of batch works well for IO bound runnables.
Subclasses should override this method if they can batch more efficiently;
e.g., if the underlying runnable uses an API which supports a batch mode.
async aget_relevant_documents(query: str, *, callbacks: Callbacks = None, tags: Optional[List[str]] ... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.cohere_rag_retriever.CohereRagRetriever.html |
cfa74f0ff6c6-2 | Subclasses should override this method if they support streaming output.
async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, diff: bool = True, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names:... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.cohere_rag_retriever.CohereRagRetriever.html |
cfa74f0ff6c6-3 | e.g., if the underlying runnable uses an API which supports a batch mode.
bind(**kwargs: Any) → Runnable[Input, Output]¶
Bind arguments to a Runnable, returning a new Runnable.
config_schema(*, include: Optional[Sequence[str]] = None) → Type[BaseModel]¶
The type of config this runnable accepts specified as a pydantic m... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.cohere_rag_retriever.CohereRagRetriever.html |
cfa74f0ff6c6-4 | 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(*, i... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.cohere_rag_retriever.CohereRagRetriever.html |
cfa74f0ff6c6-5 | Get a pydantic model that can be used to validate output to the runnable.
Runnables that leverage the configurable_fields and configurable_alternatives
methods will have a dynamic output schema that depends on which
configuration the runnable is invoked with.
This method allows to get an output schema for a specific co... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.cohere_rag_retriever.CohereRagRetriever.html |
cfa74f0ff6c6-6 | Returns
The output of the runnable.
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, exclu... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.cohere_rag_retriever.CohereRagRetriever.html |
cfa74f0ff6c6-7 | classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
stream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → Iterator[Output]¶
Default implementation of stream, which calls invoke.
Subclasses should override t... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.cohere_rag_retriever.CohereRagRetriever.html |
cfa74f0ff6c6-8 | fallback in order, upon failures.
with_listeners(*, on_start: Optional[Listener] = None, on_end: Optional[Listener] = None, on_error: Optional[Listener] = None) → Runnable[Input, Output]¶
Bind lifecycle listeners to a Runnable, returning a new Runnable.
on_start: Called before the runnable starts running, with the Run ... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.cohere_rag_retriever.CohereRagRetriever.html |
cfa74f0ff6c6-9 | The type of output this runnable produces specified as a type annotation.
property config_specs: List[langchain.schema.runnable.utils.ConfigurableFieldSpec]¶
List configurable fields for this runnable.
property input_schema: Type[pydantic.main.BaseModel]¶
The type of input this runnable accepts specified as a pydantic ... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.cohere_rag_retriever.CohereRagRetriever.html |
516aecd193b5-0 | langchain.retrievers.kendra.QueryResult¶
class langchain.retrievers.kendra.QueryResult[source]¶
Bases: BaseModel
Amazon Kendra Query API search result.
It is composed of:
Relevant suggested answers: either a text excerpt or table excerpt.
Matching FAQs or questions-answer from your FAQ file.
Documents including an exce... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.kendra.QueryResult.html |
516aecd193b5-1 | 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, ex... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.kendra.QueryResult.html |
516aecd193b5-2 | 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... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.kendra.QueryResult.html |
df58c57253c8-0 | langchain.retrievers.google_vertex_ai_search.GoogleCloudEnterpriseSearchRetriever¶
class langchain.retrievers.google_vertex_ai_search.GoogleCloudEnterpriseSearchRetriever[source]¶
Bases: GoogleVertexAISearchRetriever
Google Vertex Search API retriever alias for backwards compatibility.
DEPRECATED: Use GoogleVertexAISea... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.google_vertex_ai_search.GoogleCloudEnterpriseSearchRetriever.html |
df58c57253c8-1 | Constraints
minimum = 1
maximum = 1
param metadata: Optional[Dict[str, Any]] = None¶
Optional metadata associated with the retriever. Defaults to None
This metadata will be associated with each call to this retriever,
and passed as arguments to the handlers defined in callbacks.
You can use these to eg identify a speci... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.google_vertex_ai_search.GoogleCloudEnterpriseSearchRetriever.html |
df58c57253c8-2 | and passed as arguments to the handlers defined in callbacks.
You can use these to eg identify a specific instance of a retriever with its
use case.
async abatch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Optional[Any]) → List... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.google_vertex_ai_search.GoogleCloudEnterpriseSearchRetriever.html |
df58c57253c8-3 | the runnable did not implement a native async version of invoke.
Subclasses should override this method if they can run asynchronously.
async astream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶
Default implementation of astream, which calls ainvoke.
Subclasse... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.google_vertex_ai_search.GoogleCloudEnterpriseSearchRetriever.html |
df58c57253c8-4 | Default implementation runs invoke in parallel using a thread pool executor.
The default implementation of batch works well for IO bound runnables.
Subclasses should override this method if they can batch more efficiently;
e.g., if the underlying runnable uses an API which supports a batch mode.
bind(**kwargs: Any) → R... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.google_vertex_ai_search.GoogleCloudEnterpriseSearchRetriever.html |
df58c57253c8-5 | 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 creat... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.google_vertex_ai_search.GoogleCloudEnterpriseSearchRetriever.html |
df58c57253c8-6 | namespace is [“langchain”, “llms”, “openai”]
get_output_schema(config: Optional[RunnableConfig] = None) → Type[BaseModel]¶
Get a pydantic model that can be used to validate output to the runnable.
Runnables that leverage the configurable_fields and configurable_alternatives
methods will have a dynamic output schema tha... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.google_vertex_ai_search.GoogleCloudEnterpriseSearchRetriever.html |
df58c57253c8-7 | purposes, ‘max_concurrency’ for controlling how much work to do
in parallel, and other keys. Please refer to the RunnableConfig
for more details.
Returns
The output of the runnable.
classmethod is_lc_serializable() → bool¶
Is this class serializable?
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]]... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.google_vertex_ai_search.GoogleCloudEnterpriseSearchRetriever.html |
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