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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 keys. Please refer to the RunnableConfig for more details. Retur...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.arxiv.ArxivRetriever.html
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them as Documents, and returns them in a List. Parameters query – a plaintext search query 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 = No...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.arxiv.ArxivRetriever.html
ea550367bfb8-8
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...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.arxiv.ArxivRetriever.html
ea550367bfb8-9
The Run object contains information about the run, including its id, type, input, output, error, start_time, end_time, and any tags or metadata added to the run. with_retry(*, retry_if_exception_type: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,), wait_exponential_jitter: bool = True, stop_af...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.arxiv.ArxivRetriever.html
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A map of constructor argument names to secret ids. For example,{“openai_api_key”: “OPENAI_API_KEY”} property output_schema: Type[pydantic.main.BaseModel]¶ The type of output this runnable produces specified as a pydantic model. Examples using ArxivRetriever¶ Arxiv
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.arxiv.ArxivRetriever.html
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langchain.retrievers.self_query.dashvector.DashvectorTranslator¶ class langchain.retrievers.self_query.dashvector.DashvectorTranslator[source]¶ Logic for converting internal query language elements to valid filters. Attributes allowed_comparators allowed_operators map_dict Methods __init__() visit_comparison(comparison...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.self_query.dashvector.DashvectorTranslator.html
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langchain.retrievers.google_cloud_documentai_warehouse.GoogleDocumentAIWarehouseRetriever¶ class langchain.retrievers.google_cloud_documentai_warehouse.GoogleDocumentAIWarehouseRetriever[source]¶ Bases: BaseRetriever A retriever based on Document AI Warehouse. Documents should be created and documents should be uploade...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.google_cloud_documentai_warehouse.GoogleDocumentAIWarehouseRetriever.html
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use case. 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 batch works well for IO bound...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.google_cloud_documentai_warehouse.GoogleDocumentAIWarehouseRetriever.html
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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.google_cloud_documentai_warehouse.GoogleDocumentAIWarehouseRetriever.html
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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_cloud_documentai_warehouse.GoogleDocumentAIWarehouseRetriever.html
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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_cloud_documentai_warehouse.GoogleDocumentAIWarehouseRetriever.html
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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_cloud_documentai_warehouse.GoogleDocumentAIWarehouseRetriever.html
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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_cloud_documentai_warehouse.GoogleDocumentAIWarehouseRetriever.html
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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_cloud_documentai_warehouse.GoogleDocumentAIWarehouseRetriever.html
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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_cloud_documentai_warehouse.GoogleDocumentAIWarehouseRetriever.html
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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.google_cloud_documentai_warehouse.GoogleDocumentAIWarehouseRetriever.html
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langchain.retrievers.elastic_search_bm25.ElasticSearchBM25Retriever¶ class langchain.retrievers.elastic_search_bm25.ElasticSearchBM25Retriever[source]¶ Bases: BaseRetriever Elasticsearch retriever that uses BM25. To connect to an Elasticsearch instance that requires login credentials, including Elastic Cloud, use the E...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.elastic_search_bm25.ElasticSearchBM25Retriever.html
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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. param tags: Optional[List[str]] = None¶ Optional list of tags associated with the retriever. Defaults to None These tags will be associated with each call to this retrieve...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.elastic_search_bm25.ElasticSearchBM25Retriever.html
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: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 arguments to the handlers defined in callbacks. Parameters metadata – Optional metadata associated with the retriever. Defaults to None This metadata will be a...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.elastic_search_bm25.ElasticSearchBM25Retriever.html
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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 can be applied in order to construct state. async atransform(input: AsyncIterator[Input], config: Optional[RunnableConfig] = None, *...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.elastic_search_bm25.ElasticSearchBM25Retriever.html
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configurable_fields(**kwargs: Union[ConfigurableField, ConfigurableFieldSingleOption, ConfigurableFieldMultiOption]) → RunnableSerializable[Input, Output]¶ classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶ Creates a new model setting __dict__ and __fields_set__ from trusted or pre-vali...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.elastic_search_bm25.ElasticSearchBM25Retriever.html
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b – BM25 parameter b. Returns: 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, exclude_defaults: bool = False, exclude_none: bool...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.elastic_search_bm25.ElasticSearchBM25Retriever.html
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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[Dict[str, Any]] = None, run_name: Optional[str] = None, **kwargs: Any) → L...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.elastic_search_bm25.ElasticSearchBM25Retriever.html
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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.elastic_search_bm25.ElasticSearchBM25Retriever.html
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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.elastic_search_bm25.ElasticSearchBM25Retriever.html
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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.elastic_search_bm25.ElasticSearchBM25Retriever.html
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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.elastic_search_bm25.ElasticSearchBM25Retriever.html
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langchain.retrievers.multi_query.LineList¶ class langchain.retrievers.multi_query.LineList[source]¶ Bases: BaseModel List of lines. 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] [Req...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.multi_query.LineList.html
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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.multi_query.LineList.html
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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.multi_query.LineList.html
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langchain.retrievers.google_vertex_ai_search.GoogleVertexAIMultiTurnSearchRetriever¶ class langchain.retrievers.google_vertex_ai_search.GoogleVertexAIMultiTurnSearchRetriever[source]¶ Bases: BaseRetriever, _BaseGoogleVertexAISearchRetriever Google Vertex AI Search retriever for multi-turn conversations. Create a new mo...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.google_vertex_ai_search.GoogleVertexAIMultiTurnSearchRetriever.html
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These tags 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 specific instance of a retriever with its use case. async abatch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, ...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.google_vertex_ai_search.GoogleVertexAIMultiTurnSearchRetriever.html
5e28bc533be4-2
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] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶ Def...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.google_vertex_ai_search.GoogleVertexAIMultiTurnSearchRetriever.html
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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.google_vertex_ai_search.GoogleVertexAIMultiTurnSearchRetriever.html
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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.google_vertex_ai_search.GoogleVertexAIMultiTurnSearchRetriever.html
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Parameters config – A config to use when generating the schema. Returns A pydantic model that can be used to validate input. classmethod get_lc_namespace() → List[str]¶ Get the namespace of the langchain object. For example, if the class is langchain.llms.openai.OpenAI, then the namespace is [“langchain”, “llms”, “open...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.google_vertex_ai_search.GoogleVertexAIMultiTurnSearchRetriever.html
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and passed as arguments to the handlers defined in callbacks. Returns List of relevant documents invoke(input: str, config: Optional[RunnableConfig] = None) → List[Document]¶ Transform a single input into an output. Override to implement. Parameters input – The input to the runnable. config – A config to use when invok...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.google_vertex_ai_search.GoogleVertexAIMultiTurnSearchRetriever.html
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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.google_vertex_ai_search.GoogleVertexAIMultiTurnSearchRetriever.html
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Bind config to a Runnable, returning a new Runnable. with_fallbacks(fallbacks: Sequence[Runnable[Input, Output]], *, exceptions_to_handle: Tuple[Type[BaseException], ...] = (<class 'Exception'>,)) → RunnableWithFallbacksT[Input, Output]¶ Add fallbacks to a runnable, returning a new Runnable. Parameters fallbacks – A se...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.google_vertex_ai_search.GoogleVertexAIMultiTurnSearchRetriever.html
5e28bc533be4-9
between retries stop_after_attempt – The maximum number of attempts to make before giving up Returns A new Runnable that retries the original runnable on exceptions. with_types(*, input_type: Optional[Type[Input]] = None, output_type: Optional[Type[Output]] = None) → Runnable[Input, Output]¶ Bind input and output types...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.google_vertex_ai_search.GoogleVertexAIMultiTurnSearchRetriever.html
4cb31c391d18-0
langchain.retrievers.self_query.supabase.SupabaseVectorTranslator¶ class langchain.retrievers.self_query.supabase.SupabaseVectorTranslator[source]¶ Translate Langchain filters to Supabase PostgREST 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.supabase.SupabaseVectorTranslator.html
bdcc7d3e419b-0
langchain.retrievers.google_vertex_ai_search.GoogleVertexAISearchRetriever¶ class langchain.retrievers.google_vertex_ai_search.GoogleVertexAISearchRetriever[source]¶ Bases: BaseRetriever, _BaseGoogleVertexAISearchRetriever Google Vertex AI Search retriever. For a detailed explanation of the Vertex AI Search concepts an...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.google_vertex_ai_search.GoogleVertexAISearchRetriever.html
bdcc7d3e419b-1
The maximum number of extractive segments returned in each search result. Currently one segment will be returned for each SearchResult. 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 ...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.google_vertex_ai_search.GoogleVertexAISearchRetriever.html
bdcc7d3e419b-2
These tags 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 specific instance of a retriever with its use case. async abatch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, ...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.google_vertex_ai_search.GoogleVertexAISearchRetriever.html
bdcc7d3e419b-3
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] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶ Def...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.google_vertex_ai_search.GoogleVertexAISearchRetriever.html
bdcc7d3e419b-4
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.google_vertex_ai_search.GoogleVertexAISearchRetriever.html
bdcc7d3e419b-5
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.google_vertex_ai_search.GoogleVertexAISearchRetriever.html
bdcc7d3e419b-6
Parameters config – A config to use when generating the schema. Returns A pydantic model that can be used to validate input. classmethod get_lc_namespace() → List[str]¶ Get the namespace of the langchain object. For example, if the class is langchain.llms.openai.OpenAI, then the namespace is [“langchain”, “llms”, “open...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.google_vertex_ai_search.GoogleVertexAISearchRetriever.html
bdcc7d3e419b-7
and passed as arguments to the handlers defined in callbacks. Returns List of relevant documents invoke(input: str, config: Optional[RunnableConfig] = None) → List[Document]¶ Transform a single input into an output. Override to implement. Parameters input – The input to the runnable. config – A config to use when invok...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.google_vertex_ai_search.GoogleVertexAISearchRetriever.html
bdcc7d3e419b-8
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.google_vertex_ai_search.GoogleVertexAISearchRetriever.html
bdcc7d3e419b-9
Bind config to a Runnable, returning a new Runnable. with_fallbacks(fallbacks: Sequence[Runnable[Input, Output]], *, exceptions_to_handle: Tuple[Type[BaseException], ...] = (<class 'Exception'>,)) → RunnableWithFallbacksT[Input, Output]¶ Add fallbacks to a runnable, returning a new Runnable. Parameters fallbacks – A se...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.google_vertex_ai_search.GoogleVertexAISearchRetriever.html
bdcc7d3e419b-10
between retries stop_after_attempt – The maximum number of attempts to make before giving up Returns A new Runnable that retries the original runnable on exceptions. with_types(*, input_type: Optional[Type[Input]] = None, output_type: Optional[Type[Output]] = None) → Runnable[Input, Output]¶ Bind input and output types...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.google_vertex_ai_search.GoogleVertexAISearchRetriever.html
8a6ff1d2a193-0
langchain.retrievers.tavily_search_api.TavilySearchAPIRetriever¶ class langchain.retrievers.tavily_search_api.TavilySearchAPIRetriever[source]¶ Bases: BaseRetriever Tavily Search API retriever. Create a new model by parsing and validating input data from keyword arguments. Raises ValidationError if the input data canno...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.tavily_search_api.TavilySearchAPIRetriever.html
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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.tavily_search_api.TavilySearchAPIRetriever.html
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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.tavily_search_api.TavilySearchAPIRetriever.html
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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.tavily_search_api.TavilySearchAPIRetriever.html
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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.tavily_search_api.TavilySearchAPIRetriever.html
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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.tavily_search_api.TavilySearchAPIRetriever.html
8a6ff1d2a193-6
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.tavily_search_api.TavilySearchAPIRetriever.html
8a6ff1d2a193-7
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.tavily_search_api.TavilySearchAPIRetriever.html
8a6ff1d2a193-8
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.tavily_search_api.TavilySearchAPIRetriever.html
8a6ff1d2a193-9
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.tavily_search_api.TavilySearchAPIRetriever.html
ca214976538d-0
langchain.retrievers.self_query.chroma.ChromaTranslator¶ class langchain.retrievers.self_query.chroma.ChromaTranslator[source]¶ Translate Chroma internal query language elements to valid filters. Attributes allowed_comparators Subset of allowed logical comparators. allowed_operators Subset of allowed logical operators....
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.self_query.chroma.ChromaTranslator.html
4153cdb96e36-0
langchain.retrievers.kendra.RetrieveResultItem¶ class langchain.retrievers.kendra.RetrieveResultItem[source]¶ Bases: ResultItem Retrieve API result item. 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...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.kendra.RetrieveResultItem.html
4153cdb96e36-1
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.kendra.RetrieveResultItem.html
4153cdb96e36-2
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 = None, encoding: unicode = 'utf8', proto...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.kendra.RetrieveResultItem.html
567a1ef34aac-0
langchain.retrievers.llama_index.LlamaIndexRetriever¶ class langchain.retrievers.llama_index.LlamaIndexRetriever[source]¶ Bases: BaseRetriever LlamaIndex retriever. It is used for the question-answering with sources over an LlamaIndex data structure. Create a new model by parsing and validating input data from keyword ...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.llama_index.LlamaIndexRetriever.html
567a1ef34aac-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.LlamaIndexRetriever.html
567a1ef34aac-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.LlamaIndexRetriever.html
567a1ef34aac-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.llama_index.LlamaIndexRetriever.html
567a1ef34aac-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.llama_index.LlamaIndexRetriever.html
567a1ef34aac-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.llama_index.LlamaIndexRetriever.html
567a1ef34aac-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.llama_index.LlamaIndexRetriever.html
567a1ef34aac-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.llama_index.LlamaIndexRetriever.html
567a1ef34aac-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.llama_index.LlamaIndexRetriever.html
567a1ef34aac-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.llama_index.LlamaIndexRetriever.html
ec2a79b777ce-0
langchain.retrievers.self_query.vectara.VectaraTranslator¶ class langchain.retrievers.self_query.vectara.VectaraTranslator[source]¶ Translate Vectara internal query language elements to valid filters. Attributes allowed_comparators Subset of allowed logical comparators. allowed_operators Subset of allowed logical opera...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.self_query.vectara.VectaraTranslator.html
f6b2c6014238-0
langchain.retrievers.vespa_retriever.VespaRetriever¶ class langchain.retrievers.vespa_retriever.VespaRetriever[source]¶ Bases: BaseRetriever Vespa 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. p...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.vespa_retriever.VespaRetriever.html
f6b2c6014238-1
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.vespa_retriever.VespaRetriever.html
f6b2c6014238-2
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.vespa_retriever.VespaRetriever.html
f6b2c6014238-3
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.vespa_retriever.VespaRetriever.html
f6b2c6014238-4
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.vespa_retriever.VespaRetriever.html
f6b2c6014238-5
_filter (Optional[str]) – Document filter condition expressed in YQL. Defaults to None. yql (Optional[str]) – Full YQL query to be used. Should not be specified if _filter or sources are specified. Defaults to None. kwargs (Any) – Keyword arguments added to query body. Returns Instantiated VespaRetriever. Return type V...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.vespa_retriever.VespaRetriever.html
f6b2c6014238-6
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[Dict[str, Any]] = None, run_name: Optional[str] = None, **kwargs: Any) → List[Document]¶ Retrieve documents relevant to a query. :param qu...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.vespa_retriever.VespaRetriever.html
f6b2c6014238-7
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.vespa_retriever.VespaRetriever.html
f6b2c6014238-8
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.vespa_retriever.VespaRetriever.html
f6b2c6014238-9
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.vespa_retriever.VespaRetriever.html
f6b2c6014238-10
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.vespa_retriever.VespaRetriever.html
2a253278fb22-0
langchain.retrievers.multi_query.LineListOutputParser¶ class langchain.retrievers.multi_query.LineListOutputParser[source]¶ Bases: PydanticOutputParser Output parser for a list of lines. param pydantic_object: Type[T] [Required]¶ The pydantic model to parse. async abatch(inputs: List[Input], config: Optional[Union[Runn...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.multi_query.LineListOutputParser.html
2a253278fb22-1
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.multi_query.LineListOutputParser.html
2a253278fb22-2
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.multi_query.LineListOutputParser.html
2a253278fb22-3
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.multi_query.LineListOutputParser.html
2a253278fb22-4
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.multi_query.LineListOutputParser.html
2a253278fb22-5
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.multi_query.LineListOutputParser.html
2a253278fb22-6
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.multi_query.LineListOutputParser.html
2a253278fb22-7
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.multi_query.LineListOutputParser.html
2a253278fb22-8
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.multi_query.LineListOutputParser.html
037670bd4845-0
langchain.retrievers.kendra.combined_text¶ langchain.retrievers.kendra.combined_text(item: ResultItem) → str[source]¶ Combine a ResultItem title and excerpt into a single string. Parameters item – the ResultItem of a Kendra search. Returns A combined text of the title and excerpt of the given item.
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.kendra.combined_text.html
88124270eb7a-0
langchain.retrievers.zilliz.ZillizRetreiver¶ langchain.retrievers.zilliz.ZillizRetreiver(*args: Any, **kwargs: Any) → ZillizRetriever[source]¶ Deprecated ZillizRetreiver. Please use ZillizRetriever (‘i’ before ‘e’) instead. Parameters *args – **kwargs – Returns ZillizRetriever
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.zilliz.ZillizRetreiver.html
f87c3ac7a53e-0
langchain.retrievers.kendra.AdditionalResultAttribute¶ class langchain.retrievers.kendra.AdditionalResultAttribute[source]¶ Bases: BaseModel Additional result 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 va...
lang/api.python.langchain.com/en/latest/retrievers/langchain.retrievers.kendra.AdditionalResultAttribute.html