id stringlengths 14 16 | text stringlengths 13 2.7k | source stringlengths 57 178 |
|---|---|---|
df58c57253c8-8 | 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¶
stream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.google_vertex_ai_search.GoogleCloudEnterpriseSearchRetriever.html |
df58c57253c8-9 | Returns
A new Runnable that will try the original runnable, and then each
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 Ru... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.google_vertex_ai_search.GoogleCloudEnterpriseSearchRetriever.html |
df58c57253c8-10 | 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 specified as a type annotation.
property client_options: ClientOptions¶
property config_specs: List[langchain.schema.runnable.utils.Configu... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.google_vertex_ai_search.GoogleCloudEnterpriseSearchRetriever.html |
c89aa8c49845-0 | langchain.retrievers.self_query.deeplake.can_cast_to_float¶
langchain.retrievers.self_query.deeplake.can_cast_to_float(string: str) → bool[source]¶
Check if a string can be cast to a float. | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.self_query.deeplake.can_cast_to_float.html |
3d093b4c52b7-0 | langchain.retrievers.document_compressors.base.BaseDocumentCompressor¶
class langchain.retrievers.document_compressors.base.BaseDocumentCompressor[source]¶
Bases: BaseModel, ABC
Base class for document compressors.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.document_compressors.base.BaseDocumentCompressor.html |
3d093b4c52b7-1 | 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(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[boo... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.document_compressors.base.BaseDocumentCompressor.html |
3d093b4c52b7-2 | 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.document_compressors.base.BaseDocumentCompressor.html |
808c8b73bba3-0 | langchain.retrievers.knn.KNNRetriever¶
class langchain.retrievers.knn.KNNRetriever[source]¶
Bases: BaseRetriever
KNN retriever.
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 embeddings: Embeddings [R... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.knn.KNNRetriever.html |
808c8b73bba3-1 | 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]] = None, metadata: Optional[Dict[str, Any]] = None, run_name: Optional[s... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.knn.KNNRetriever.html |
808c8b73bba3-2 | 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.knn.KNNRetriever.html |
808c8b73bba3-3 | 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.knn.KNNRetriever.html |
808c8b73bba3-4 | 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.knn.KNNRetriever.html |
808c8b73bba3-5 | 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.knn.KNNRetriever.html |
808c8b73bba3-6 | 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.knn.KNNRetriever.html |
808c8b73bba3-7 | 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¶
stream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.knn.KNNRetriever.html |
808c8b73bba3-8 | Returns
A new Runnable that will try the original runnable, and then each
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 Ru... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.knn.KNNRetriever.html |
808c8b73bba3-9 | 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 specified as a type annotation.
property config_specs: List[langchain.schema.runnable.utils.ConfigurableFieldSpec]¶
List configurable field... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.knn.KNNRetriever.html |
0caecd6e573a-0 | langchain.retrievers.pinecone_hybrid_search.PineconeHybridSearchRetriever¶
class langchain.retrievers.pinecone_hybrid_search.PineconeHybridSearchRetriever[source]¶
Bases: BaseRetriever
Pinecone Hybrid Search retriever.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationErro... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.pinecone_hybrid_search.PineconeHybridSearchRetriever.html |
0caecd6e573a-1 | Default implementation runs ainvoke in parallel using asyncio.gather.
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.
add_texts(texts: List[str], id... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.pinecone_hybrid_search.PineconeHybridSearchRetriever.html |
0caecd6e573a-2 | 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, *, diff: bool = True, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, incl... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.pinecone_hybrid_search.PineconeHybridSearchRetriever.html |
0caecd6e573a-3 | 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) → Runnable[Input, Output]¶
Bind arguments to a Runnable, returning a new Runnable.
config_schema(*, include: Optional[Sequence[str]] = None) → Type[Bas... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.pinecone_hybrid_search.PineconeHybridSearchRetriever.html |
0caecd6e573a-4 | 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 creating
the new model: you should trust this data
deep – set to True to make a deep co... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.pinecone_hybrid_search.PineconeHybridSearchRetriever.html |
0caecd6e573a-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.pinecone_hybrid_search.PineconeHybridSearchRetriever.html |
0caecd6e573a-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.pinecone_hybrid_search.PineconeHybridSearchRetriever.html |
0caecd6e573a-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.pinecone_hybrid_search.PineconeHybridSearchRetriever.html |
0caecd6e573a-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.pinecone_hybrid_search.PineconeHybridSearchRetriever.html |
0caecd6e573a-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.pinecone_hybrid_search.PineconeHybridSearchRetriever.html |
f7b2acf72da7-0 | langchain.retrievers.zep.SearchScope¶
class langchain.retrievers.zep.SearchScope(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)[source]¶
Which documents to search. Messages or Summaries?
messages = 'messages'¶
Search chat history messages.
summary = 'summary'¶
Search chat history s... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.zep.SearchScope.html |
ceb6011fa561-0 | langchain.retrievers.chatgpt_plugin_retriever.ChatGPTPluginRetriever¶
class langchain.retrievers.chatgpt_plugin_retriever.ChatGPTPluginRetriever[source]¶
Bases: BaseRetriever
ChatGPT plugin retriever.
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/retrievers/langchain.retrievers.chatgpt_plugin_retriever.ChatGPTPluginRetriever.html |
ceb6011fa561-1 | Default implementation runs ainvoke in parallel using asyncio.gather.
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(... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.chatgpt_plugin_retriever.ChatGPTPluginRetriever.html |
ceb6011fa561-2 | 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.chatgpt_plugin_retriever.ChatGPTPluginRetriever.html |
ceb6011fa561-3 | 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.chatgpt_plugin_retriever.ChatGPTPluginRetriever.html |
ceb6011fa561-4 | 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.chatgpt_plugin_retriever.ChatGPTPluginRetriever.html |
ceb6011fa561-5 | 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.chatgpt_plugin_retriever.ChatGPTPluginRetriever.html |
ceb6011fa561-6 | 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.chatgpt_plugin_retriever.ChatGPTPluginRetriever.html |
ceb6011fa561-7 | 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.chatgpt_plugin_retriever.ChatGPTPluginRetriever.html |
ceb6011fa561-8 | 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.chatgpt_plugin_retriever.ChatGPTPluginRetriever.html |
ceb6011fa561-9 | 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.chatgpt_plugin_retriever.ChatGPTPluginRetriever.html |
299d245f2f89-0 | langchain.retrievers.web_research.SearchQueries¶
class langchain.retrievers.web_research.SearchQueries[source]¶
Bases: BaseModel
Search queries to research for the user’s goal.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to fo... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.web_research.SearchQueries.html |
299d245f2f89-1 | 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.web_research.SearchQueries.html |
299d245f2f89-2 | 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.web_research.SearchQueries.html |
a8a71522e89f-0 | langchain.retrievers.web_research.LineList¶
class langchain.retrievers.web_research.LineList[source]¶
Bases: BaseModel
List of questions.
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 lines: List[str... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.web_research.LineList.html |
a8a71522e89f-1 | Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
classmethod from_orm(obj: Any) → Model¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False,... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.web_research.LineList.html |
8063156a5b69-0 | langchain.retrievers.tavily_search_api.SearchDepth¶
class langchain.retrievers.tavily_search_api.SearchDepth(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)[source]¶
Search depth as enumerator.
BASIC = 'basic'¶
ADVANCED = 'advanced'¶ | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.tavily_search_api.SearchDepth.html |
65d9bc972579-0 | langchain.retrievers.web_research.QuestionListOutputParser¶
class langchain.retrievers.web_research.QuestionListOutputParser[source]¶
Bases: PydanticOutputParser
Output parser for a list of numbered questions.
param pydantic_object: Type[T] [Required]¶
The pydantic model to parse.
async abatch(inputs: List[Input], conf... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.web_research.QuestionListOutputParser.html |
65d9bc972579-1 | to be different candidate outputs for a single model input.
Returns
Structured output.
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 str... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.web_research.QuestionListOutputParser.html |
65d9bc972579-2 | 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.web_research.QuestionListOutputParser.html |
65d9bc972579-3 | 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.web_research.QuestionListOutputParser.html |
65d9bc972579-4 | 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 configuration.
Parameters
config – A config to use when generating the schema.
Returns
A pydantic model that can be used to validate output.
invoke(input:... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.web_research.QuestionListOutputParser.html |
65d9bc972579-5 | 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.
parse(text: str) → LineList[source]¶
Parse a single string model output into some str... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.web_research.QuestionListOutputParser.html |
65d9bc972579-6 | prompt – Input PromptValue.
Returns
Structured output
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¶
stream(input: Input, config: O... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.web_research.QuestionListOutputParser.html |
65d9bc972579-7 | 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_listeners(*, on_start: Optional[Listener] = None, on_end: Optional[Listener] = None, on_error: Optional[Listener] = None) → Runnable[Input, Output... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.web_research.QuestionListOutputParser.html |
65d9bc972579-8 | The type of input this runnable accepts specified as a type annotation.
property OutputType: Type[langchain.schema.output_parser.T]¶
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 ... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.web_research.QuestionListOutputParser.html |
5f7a2facb549-0 | langchain.retrievers.zep.ZepRetriever¶
class langchain.retrievers.zep.ZepRetriever[source]¶
Bases: BaseRetriever
Zep MemoryStore Retriever.
Search your user’s long-term chat history with Zep.
Zep offers both simple semantic search and Maximal Marginal Relevance (MMR)
reranking of search results.
Note: You will need to ... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.zep.ZepRetriever.html |
5f7a2facb549-1 | use case.
param mmr_lambda: Optional[float] = None¶
Lambda value for MMR search.
param search_scope: langchain.retrievers.zep.SearchScope = SearchScope.messages¶
Which documents to search. Messages or Summaries?
param search_type: langchain.retrievers.zep.SearchType = SearchType.similarity¶
Type of search to perform (s... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.zep.ZepRetriever.html |
5f7a2facb549-2 | Asynchronously get documents relevant to a query.
:param query: string to find relevant documents for
:param callbacks: Callback manager or list of callbacks
:param tags: Optional list of tags associated with the retriever. Defaults to None
These tags will be associated with each call to this retriever,
and passed as a... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.zep.ZepRetriever.html |
5f7a2facb549-3 | 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/retrievers/langchain.retrievers.zep.ZepRetriever.html |
5f7a2facb549-4 | 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/retrievers/langchain.retrievers.zep.ZepRetriever.html |
5f7a2facb549-5 | 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.zep.ZepRetriever.html |
5f7a2facb549-6 | This method allows to get an output schema for a specific configuration.
Parameters
config – A config to use when generating the schema.
Returns
A pydantic model that can be used to validate output.
get_relevant_documents(query: str, *, callbacks: Callbacks = None, tags: Optional[List[str]] = None, metadata: Optional[D... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.zep.ZepRetriever.html |
5f7a2facb549-7 | 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... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.zep.ZepRetriever.html |
5f7a2facb549-8 | 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.zep.ZepRetriever.html |
5f7a2facb549-9 | 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.zep.ZepRetriever.html |
5f7a2facb549-10 | 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.zep.ZepRetriever.html |
b60431e800fa-0 | langchain.retrievers.bm25.BM25Retriever¶
class langchain.retrievers.bm25.BM25Retriever[source]¶
Bases: BaseRetriever
BM25 retriever without Elasticsearch.
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.
para... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.bm25.BM25Retriever.html |
b60431e800fa-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.bm25.BM25Retriever.html |
b60431e800fa-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.bm25.BM25Retriever.html |
b60431e800fa-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.bm25.BM25Retriever.html |
b60431e800fa-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.bm25.BM25Retriever.html |
b60431e800fa-5 | classmethod from_orm(obj: Any) → Model¶
classmethod from_texts(texts: ~typing.Iterable[str], metadatas: ~typing.Optional[~typing.Iterable[dict]] = None, bm25_params: ~typing.Optional[~typing.Dict[str, ~typing.Any]] = None, preprocess_func: ~typing.Callable[[str], ~typing.List[str]] = <function default_preprocessing_fun... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.bm25.BM25Retriever.html |
b60431e800fa-6 | 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.bm25.BM25Retriever.html |
b60431e800fa-7 | 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.bm25.BM25Retriever.html |
b60431e800fa-8 | 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.bm25.BM25Retriever.html |
b60431e800fa-9 | 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.bm25.BM25Retriever.html |
b60431e800fa-10 | 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.bm25.BM25Retriever.html |
d31d36819c67-0 | langchain.retrievers.self_query.pinecone.PineconeTranslator¶
class langchain.retrievers.self_query.pinecone.PineconeTranslator[source]¶
Translate Pinecone internal query language elements to valid filters.
Attributes
allowed_comparators
Subset of allowed logical comparators.
allowed_operators
Subset of allowed logical ... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.self_query.pinecone.PineconeTranslator.html |
60e63b158cae-0 | langchain.retrievers.you.YouRetriever¶
class langchain.retrievers.you.YouRetriever[source]¶
Bases: BaseRetriever
You retriever that uses You.com’s search API.
To connect to the You.com api requires an API key which
you can get by emailing api@you.com.
You can check out our docs at https://documentation.you.com.
You nee... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.you.YouRetriever.html |
60e63b158cae-1 | Default implementation runs ainvoke in parallel using asyncio.gather.
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(... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.you.YouRetriever.html |
60e63b158cae-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.you.YouRetriever.html |
60e63b158cae-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.you.YouRetriever.html |
60e63b158cae-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.you.YouRetriever.html |
60e63b158cae-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.you.YouRetriever.html |
60e63b158cae-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.you.YouRetriever.html |
60e63b158cae-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.you.YouRetriever.html |
60e63b158cae-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.you.YouRetriever.html |
60e63b158cae-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.you.YouRetriever.html |
27e647846a08-0 | langchain.retrievers.self_query.base.SelfQueryRetriever¶
class langchain.retrievers.self_query.base.SelfQueryRetriever[source]¶
Bases: BaseRetriever, BaseModel
Retriever that uses a vector store and an LLM to generate
the vector store queries.
Create a new model by parsing and validating input data from keyword argumen... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.self_query.base.SelfQueryRetriever.html |
27e647846a08-1 | use case.
param use_original_query: bool = False¶
Use original query instead of the revised new query from LLM
param vectorstore: langchain.schema.vectorstore.VectorStore [Required]¶
The underlying vector store from which documents will be retrieved.
param verbose: bool = False¶
async abatch(inputs: List[Input], config... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.self_query.base.SelfQueryRetriever.html |
27e647846a08-2 | 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.
async astream(input: Input, config: Optional[RunnableConfig... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.self_query.base.SelfQueryRetriever.html |
27e647846a08-3 | 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 runs invoke in parallel using a thread pool executor.
The default implementation of batch w... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.self_query.base.SelfQueryRetriever.html |
27e647846a08-4 | 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] = None, deep: bool = False) → Model¶
Duplicate a model, optionally... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.self_query.base.SelfQueryRetriever.html |
27e647846a08-5 | Get a pydantic model that can be used to validate input to the runnable.
Runnables that leverage the configurable_fields and configurable_alternatives
methods will have a dynamic input schema that depends on which
configuration the runnable is invoked with.
This method allows to get an input schema for a specific confi... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.self_query.base.SelfQueryRetriever.html |
27e647846a08-6 | and passed as arguments to the handlers defined in callbacks.
Parameters
metadata – 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.
Returns
List of relevant documents
invoke... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.self_query.base.SelfQueryRetriever.html |
27e647846a08-7 | 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, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool =... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.self_query.base.SelfQueryRetriever.html |
27e647846a08-8 | classmethod validate(value: Any) → Model¶
with_config(config: Optional[RunnableConfig] = None, **kwargs: Any) → Runnable[Input, Output]¶
Bind config to a Runnable, returning a new Runnable.
with_fallbacks(fallbacks: Sequence[Runnable[Input, Output]], *, exceptions_to_handle: Tuple[Type[BaseException], ...] = (<class 'E... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.self_query.base.SelfQueryRetriever.html |
27e647846a08-9 | Create a new Runnable that retries the original runnable on exceptions.
Parameters
retry_if_exception_type – A tuple of exception types to retry on
wait_exponential_jitter – Whether to add jitter to the wait time
between retries
stop_after_attempt – The maximum number of attempts to make before giving up
Returns
A new ... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.self_query.base.SelfQueryRetriever.html |
27e647846a08-10 | Chroma
Vectara
Docugami
Perform context-aware text splitting
Milvus
Weaviate
DashVector
Elasticsearch
Pinecone
Supabase
Redis
MyScale
Deep Lake
Qdrant | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.self_query.base.SelfQueryRetriever.html |
f7f58253807b-0 | langchain.retrievers.llama_index.LlamaIndexGraphRetriever¶
class langchain.retrievers.llama_index.LlamaIndexGraphRetriever[source]¶
Bases: BaseRetriever
LlamaIndex graph data structure retriever.
It is used for question-answering with sources over an LlamaIndex
graph data structure.
Create a new model by parsing and va... | lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.llama_index.LlamaIndexGraphRetriever.html |
f7f58253807b-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.retrievers.llama_index.LlamaIndexGraphRetriever.html |
f7f58253807b-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.llama_index.LlamaIndexGraphRetriever.html |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.