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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...
https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.refine.RefineDocumentsChain.html
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property InputType: Type[langchain.schema.runnable.utils.Input]¶ property OutputType: Type[langchain.schema.runnable.utils.Output]¶ property input_schema: Type[pydantic.main.BaseModel]¶ property lc_attributes: Dict¶ List of attribute names that should be included in the serialized kwargs. These attributes must be accep...
https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.refine.RefineDocumentsChain.html
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langchain.chains.query_constructor.parser.get_parser¶ langchain.chains.query_constructor.parser.get_parser(allowed_comparators: Optional[Sequence[Comparator]] = None, allowed_operators: Optional[Sequence[Operator]] = None) → object[source]¶ Returns a parser for the query language. Parameters allowed_comparators – Optio...
https://api.python.langchain.com/en/latest/chains/langchain.chains.query_constructor.parser.get_parser.html
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langchain.chains.combine_documents.reduce.AsyncCombineDocsProtocol¶ class langchain.chains.combine_documents.reduce.AsyncCombineDocsProtocol(*args, **kwargs)[source]¶ Interface for the combine_docs method. Methods __init__(*args, **kwargs) __init__(*args, **kwargs)¶
https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.reduce.AsyncCombineDocsProtocol.html
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langchain.chains.hyde.base.HypotheticalDocumentEmbedder¶ class langchain.chains.hyde.base.HypotheticalDocumentEmbedder[source]¶ Bases: Chain, Embeddings Generate hypothetical document for query, and then embed that. Based on https://arxiv.org/abs/2212.10496 Create a new model by parsing and validating input data from k...
https://api.python.langchain.com/en/latest/chains/langchain.chains.hyde.base.HypotheticalDocumentEmbedder.html
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param tags: Optional[List[str]] = None¶ Optional list of tags associated with the chain. Defaults to None. These tags will be associated with each call to this chain, and passed as arguments to the handlers defined in callbacks. You can use these to eg identify a specific instance of a chain with its use case. param ve...
https://api.python.langchain.com/en/latest/chains/langchain.chains.hyde.base.HypotheticalDocumentEmbedder.html
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metadata – Optional metadata associated with the chain. Defaults to None include_run_info – Whether to include run info in the response. Defaults to False. Returns A dict of named outputs. Should contain all outputs specified inChain.output_keys. async abatch(inputs: List[Input], config: Optional[Union[RunnableConfig, ...
https://api.python.langchain.com/en/latest/chains/langchain.chains.hyde.base.HypotheticalDocumentEmbedder.html
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addition to tags passed to the chain during construction, but only these runtime tags will propagate to calls to other objects. metadata – Optional metadata associated with the chain. Defaults to None include_run_info – Whether to include run info in the response. Defaults to False. Returns A dict of named outputs. Sho...
https://api.python.langchain.com/en/latest/chains/langchain.chains.hyde.base.HypotheticalDocumentEmbedder.html
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callbacks – Callbacks to use for this chain run. These will be called in addition to callbacks passed to the chain during construction, but only these runtime callbacks will propagate to calls to other objects. tags – List of string tags to pass to all callbacks. These will be passed in addition to tags passed to the c...
https://api.python.langchain.com/en/latest/chains/langchain.chains.hyde.base.HypotheticalDocumentEmbedder.html
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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...
https://api.python.langchain.com/en/latest/chains/langchain.chains.hyde.base.HypotheticalDocumentEmbedder.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...
https://api.python.langchain.com/en/latest/chains/langchain.chains.hyde.base.HypotheticalDocumentEmbedder.html
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Get the namespace of the langchain object. For example, if the class is langchain.llms.openai.OpenAI, then the namespace is [“langchain”, “llms”, “openai”] invoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None, **kwargs: Any) → Dict[str, Any]¶ classmethod is_lc_serializable() → bool¶ Is this class seria...
https://api.python.langchain.com/en/latest/chains/langchain.chains.hyde.base.HypotheticalDocumentEmbedder.html
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classmethod parse_obj(obj: Any) → Model¶ classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶ prep_inputs(inputs: Union[Dict[str, Any], Any]) → Dict[str, str]¶ Validate and prepare chain inputs, including ad...
https://api.python.langchain.com/en/latest/chains/langchain.chains.hyde.base.HypotheticalDocumentEmbedder.html
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sole positional argument. callbacks – Callbacks to use for this chain run. These will be called in addition to callbacks passed to the chain during construction, but only these runtime callbacks will propagate to calls to other objects. tags – List of string tags to pass to all callbacks. These will be passed in additi...
https://api.python.langchain.com/en/latest/chains/langchain.chains.hyde.base.HypotheticalDocumentEmbedder.html
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Default implementation of stream, which calls invoke. Subclasses should override this method if they support streaming output. to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶ to_json_not_implemented() → SerializedNotImplemented¶ transform(input: Iterator[Input], config: Optional[RunnableConfig] = No...
https://api.python.langchain.com/en/latest/chains/langchain.chains.hyde.base.HypotheticalDocumentEmbedder.html
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property input_schema: Type[pydantic.main.BaseModel]¶ property lc_attributes: Dict¶ List of attribute names that should be included in the serialized kwargs. These attributes must be accepted by the constructor. property lc_secrets: Dict[str, str]¶ A map of constructor argument names to secret ids. For example,{“openai...
https://api.python.langchain.com/en/latest/chains/langchain.chains.hyde.base.HypotheticalDocumentEmbedder.html
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langchain.chains.router.base.RouterChain¶ class langchain.chains.router.base.RouterChain[source]¶ Bases: Chain, ABC Chain that outputs the name of a destination chain and the inputs to it. Create a new model by parsing and validating input data from keyword arguments. Raises ValidationError if the input data cannot be ...
https://api.python.langchain.com/en/latest/chains/langchain.chains.router.base.RouterChain.html
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You can use these to eg identify a specific instance of a chain with its use case. param verbose: bool [Optional]¶ Whether or not run in verbose mode. In verbose mode, some intermediate logs will be printed to the console. Defaults to langchain.verbose value. __call__(inputs: Union[Dict[str, Any], Any], return_only_out...
https://api.python.langchain.com/en/latest/chains/langchain.chains.router.base.RouterChain.html
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Returns A dict of named outputs. Should contain all outputs specified inChain.output_keys. async abatch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Optional[Any]) → List[Output]¶ Default implementation of abatch, which calls ai...
https://api.python.langchain.com/en/latest/chains/langchain.chains.router.base.RouterChain.html
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include_run_info – Whether to include run info in the response. Defaults to False. Returns A dict of named outputs. Should contain all outputs specified inChain.output_keys. async ainvoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None, **kwargs: Any) → Dict[str, Any]¶ Default implementation of ainvoke, ...
https://api.python.langchain.com/en/latest/chains/langchain.chains.router.base.RouterChain.html
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addition to tags passed to the chain during construction, but only these runtime tags will propagate to calls to other objects. **kwargs – If the chain expects multiple inputs, they can be passed in directly as keyword arguments. Returns The chain output. Example # Suppose we have a single-input chain that takes a 'que...
https://api.python.langchain.com/en/latest/chains/langchain.chains.router.base.RouterChain.html
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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, **kwargs: Optional[Any]) → AsyncIterator[Output]¶ Default im...
https://api.python.langchain.com/en/latest/chains/langchain.chains.router.base.RouterChain.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(**kw...
https://api.python.langchain.com/en/latest/chains/langchain.chains.router.base.RouterChain.html
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Generate a JSON representation of the model, include and exclude arguments as per dict(). encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps(). classmethod lc_id() → List[str]¶ A unique identifier for this class for serialization purposes. The unique identifier is a ...
https://api.python.langchain.com/en/latest/chains/langchain.chains.router.base.RouterChain.html
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memory. outputs – Dictionary of initial chain outputs. return_only_outputs – Whether to only return the chain outputs. If False, inputs are also added to the final outputs. Returns A dict of the final chain outputs. route(inputs: Dict[str, Any], callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]]...
https://api.python.langchain.com/en/latest/chains/langchain.chains.router.base.RouterChain.html
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chain.run("What's the temperature in Boise, Idaho?") # -> "The temperature in Boise is..." # Suppose we have a multi-input chain that takes a 'question' string # and 'context' string: question = "What's the temperature in Boise, Idaho?" context = "Weather report for Boise, Idaho on 07/03/23..." chain.run(question=quest...
https://api.python.langchain.com/en/latest/chains/langchain.chains.router.base.RouterChain.html
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Try to update ForwardRefs on fields based on this Model, globalns and localns. classmethod validate(value: Any) → Model¶ with_config(config: Optional[RunnableConfig] = None, **kwargs: Any) → Runnable[Input, Output]¶ Bind config to a Runnable, returning a new Runnable. with_fallbacks(fallbacks: ~typing.Sequence[~langcha...
https://api.python.langchain.com/en/latest/chains/langchain.chains.router.base.RouterChain.html
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langchain.chains.router.embedding_router.EmbeddingRouterChain¶ class langchain.chains.router.embedding_router.EmbeddingRouterChain[source]¶ Bases: RouterChain Chain that uses embeddings to route between options. Create a new model by parsing and validating input data from keyword arguments. Raises ValidationError if th...
https://api.python.langchain.com/en/latest/chains/langchain.chains.router.embedding_router.EmbeddingRouterChain.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 chain with its use case. param vectorstore: VectorStore [Required]¶ param verbose: bool [Optional]¶ Whether or not run in verbose mode. In verbose mode, some intermediate logs will be printed to the c...
https://api.python.langchain.com/en/latest/chains/langchain.chains.router.embedding_router.EmbeddingRouterChain.html
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to False. Returns A dict of named outputs. Should contain all outputs specified inChain.output_keys. async abatch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Optional[Any]) → List[Output]¶ Default implementation of abatch, whic...
https://api.python.langchain.com/en/latest/chains/langchain.chains.router.embedding_router.EmbeddingRouterChain.html
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metadata – Optional metadata associated with the chain. Defaults to None include_run_info – Whether to include run info in the response. Defaults to False. Returns A dict of named outputs. Should contain all outputs specified inChain.output_keys. async ainvoke(input: Dict[str, Any], config: Optional[RunnableConfig] = N...
https://api.python.langchain.com/en/latest/chains/langchain.chains.router.embedding_router.EmbeddingRouterChain.html
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tags – List of string tags to pass to all callbacks. These will be passed in addition to tags passed to the chain during construction, but only these runtime tags will propagate to calls to other objects. **kwargs – If the chain expects multiple inputs, they can be passed in directly as keyword arguments. Returns The c...
https://api.python.langchain.com/en/latest/chains/langchain.chains.router.embedding_router.EmbeddingRouterChain.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, *...
https://api.python.langchain.com/en/latest/chains/langchain.chains.router.embedding_router.EmbeddingRouterChain.html
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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...
https://api.python.langchain.com/en/latest/chains/langchain.chains.router.embedding_router.EmbeddingRouterChain.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...
https://api.python.langchain.com/en/latest/chains/langchain.chains.router.embedding_router.EmbeddingRouterChain.html
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Parameters inputs – Dictionary of raw inputs, or single input if chain expects only one param. Should contain all inputs specified in Chain.input_keys except for inputs that will be set by the chain’s memory. Returns A dictionary of all inputs, including those added by the chain’s memory. prep_outputs(inputs: Dict[str,...
https://api.python.langchain.com/en/latest/chains/langchain.chains.router.embedding_router.EmbeddingRouterChain.html
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callbacks – Callbacks to use for this chain run. These will be called in addition to callbacks passed to the chain during construction, but only these runtime callbacks will propagate to calls to other objects. tags – List of string tags to pass to all callbacks. These will be passed in addition to tags passed to the c...
https://api.python.langchain.com/en/latest/chains/langchain.chains.router.embedding_router.EmbeddingRouterChain.html
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Default implementation of stream, which calls invoke. Subclasses should override this method if they support streaming output. to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶ to_json_not_implemented() → SerializedNotImplemented¶ transform(input: Iterator[Input], config: Optional[RunnableConfig] = No...
https://api.python.langchain.com/en/latest/chains/langchain.chains.router.embedding_router.EmbeddingRouterChain.html
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property lc_attributes: Dict¶ List of attribute names that should be included in the serialized kwargs. These attributes must be accepted by the constructor. property lc_secrets: Dict[str, str]¶ A map of constructor argument names to secret ids. For example,{“openai_api_key”: “OPENAI_API_KEY”} property output_keys: Lis...
https://api.python.langchain.com/en/latest/chains/langchain.chains.router.embedding_router.EmbeddingRouterChain.html
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langchain.chains.graph_qa.neptune_cypher.use_simple_prompt¶ langchain.chains.graph_qa.neptune_cypher.use_simple_prompt(llm: BaseLanguageModel) → bool[source]¶ Decides whether to use the simple prompt
https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.neptune_cypher.use_simple_prompt.html
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langchain.chains.query_constructor.ir.Operator¶ class langchain.chains.query_constructor.ir.Operator(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)[source]¶ Enumerator of the operations. AND = 'and'¶ OR = 'or'¶ NOT = 'not'¶
https://api.python.langchain.com/en/latest/chains/langchain.chains.query_constructor.ir.Operator.html
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langchain.chains.natbot.crawler.ElementInViewPort¶ class langchain.chains.natbot.crawler.ElementInViewPort[source]¶ A typed dictionary containing information about elements in the viewport. node_index: str¶ backend_node_id: int¶ node_name: Optional[str]¶ node_value: Optional[str]¶ node_meta: List[str]¶ is_clickable: bo...
https://api.python.langchain.com/en/latest/chains/langchain.chains.natbot.crawler.ElementInViewPort.html
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langchain.chains.openai_functions.base.create_structured_output_chain¶ langchain.chains.openai_functions.base.create_structured_output_chain(output_schema: Union[Dict[str, Any], Type[BaseModel]], llm: BaseLanguageModel, prompt: BasePromptTemplate, *, output_key: str = 'function', output_parser: Optional[BaseLLMOutputPa...
https://api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.base.create_structured_output_chain.html
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name: str = Field(..., description="The dog's name") color: str = Field(..., description="The dog's color") fav_food: Optional[str] = Field(None, description="The dog's favorite food") llm = ChatOpenAI(model="gpt-3.5-turbo-0613", temperature=0) prompt = ChatPromptTemplate.from_messages( [ ("system",...
https://api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.base.create_structured_output_chain.html
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langchain.chains.graph_qa.sparql.GraphSparqlQAChain¶ class langchain.chains.graph_qa.sparql.GraphSparqlQAChain[source]¶ Bases: Chain Chain for question-answering against an RDF or OWL graph by generating SPARQL statements. Create a new model by parsing and validating input data from keyword arguments. Raises Validation...
https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.sparql.GraphSparqlQAChain.html
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param sparql_generation_select_chain: LLMChain [Required]¶ param sparql_generation_update_chain: LLMChain [Required]¶ param sparql_intent_chain: LLMChain [Required]¶ param tags: Optional[List[str]] = None¶ Optional list of tags associated with the chain. Defaults to None. These tags will be associated with each call to...
https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.sparql.GraphSparqlQAChain.html
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these runtime callbacks will propagate to calls to other objects. tags – List of string tags to pass to all callbacks. These will be passed in addition to tags passed to the chain during construction, but only these runtime tags will propagate to calls to other objects. metadata – Optional metadata associated with the ...
https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.sparql.GraphSparqlQAChain.html
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callbacks – Callbacks to use for this chain run. These will be called in addition to callbacks passed to the chain during construction, but only these runtime callbacks will propagate to calls to other objects. tags – List of string tags to pass to all callbacks. These will be passed in addition to tags passed to the c...
https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.sparql.GraphSparqlQAChain.html
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sole positional argument. callbacks – Callbacks to use for this chain run. These will be called in addition to callbacks passed to the chain during construction, but only these runtime callbacks will propagate to calls to other objects. tags – List of string tags to pass to all callbacks. These will be passed in additi...
https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.sparql.GraphSparqlQAChain.html
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Subclasses should override this method if they support streaming output. async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names: Optional[Sequence[...
https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.sparql.GraphSparqlQAChain.html
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Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclu...
https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.sparql.GraphSparqlQAChain.html
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classmethod from_llm(llm: BaseLanguageModel, *, qa_prompt: BasePromptTemplate = PromptTemplate(input_variables=['context', 'prompt'], template="Task: Generate a natural language response from the results of a SPARQL query.\nYou are an assistant that creates well-written and human understandable answers.\nThe informatio...
https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.sparql.GraphSparqlQAChain.html
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BasePromptTemplate = PromptTemplate(input_variables=['schema', 'prompt'], template='Task: Generate a SPARQL UPDATE statement for updating a graph database.\nFor instance, to add \'jane.doe@foo.bar\' as a new email address for Jane Doe, the following query in backticks would be suitable:\n```\nPREFIX foaf: <http://xmlns...
https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.sparql.GraphSparqlQAChain.html
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responses.\nDo not respond to any questions that ask for anything else than for you to identify a SPARQL query type.\nDo not include any unnecessary whitespaces or any text except the query type, i.e., either return 'SELECT' or 'UPDATE'.\n\nThe prompt is:\n{prompt}\nHelpful Answer:"), **kwargs: Any) → GraphSparqlQAChai...
https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.sparql.GraphSparqlQAChain.html
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Initialize from LLM. classmethod from_orm(obj: Any) → Model¶ 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”, “openai”] invoke(input: Dict[str, Any], config: Optional[RunnableConf...
https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.sparql.GraphSparqlQAChain.html
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classmethod parse_obj(obj: Any) → Model¶ classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶ prep_inputs(inputs: Union[Dict[str, Any], Any]) → Dict[str, str]¶ Validate and prepare chain inputs, including ad...
https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.sparql.GraphSparqlQAChain.html
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sole positional argument. callbacks – Callbacks to use for this chain run. These will be called in addition to callbacks passed to the chain during construction, but only these runtime callbacks will propagate to calls to other objects. tags – List of string tags to pass to all callbacks. These will be passed in additi...
https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.sparql.GraphSparqlQAChain.html
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Default implementation of stream, which calls invoke. Subclasses should override this method if they support streaming output. to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶ to_json_not_implemented() → SerializedNotImplemented¶ transform(input: Iterator[Input], config: Optional[RunnableConfig] = No...
https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.sparql.GraphSparqlQAChain.html
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property input_schema: Type[pydantic.main.BaseModel]¶ property lc_attributes: Dict¶ List of attribute names that should be included in the serialized kwargs. These attributes must be accepted by the constructor. property lc_secrets: Dict[str, str]¶ A map of constructor argument names to secret ids. For example,{“openai...
https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.sparql.GraphSparqlQAChain.html
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langchain.chains.query_constructor.ir.FilterDirective¶ class langchain.chains.query_constructor.ir.FilterDirective[source]¶ Bases: Expr, ABC A filtering expression. 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 m...
https://api.python.langchain.com/en/latest/chains/langchain.chains.query_constructor.ir.FilterDirective.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...
https://api.python.langchain.com/en/latest/chains/langchain.chains.query_constructor.ir.FilterDirective.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...
https://api.python.langchain.com/en/latest/chains/langchain.chains.query_constructor.ir.FilterDirective.html
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langchain.chains.qa_with_sources.retrieval.RetrievalQAWithSourcesChain¶ class langchain.chains.qa_with_sources.retrieval.RetrievalQAWithSourcesChain[source]¶ Bases: BaseQAWithSourcesChain Question-answering with sources over an index. Create a new model by parsing and validating input data from keyword arguments. Raise...
https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.retrieval.RetrievalQAWithSourcesChain.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 chain with its use case. param reduce_k_below_max_tokens: bool = False¶ Reduce the number of results to return from store based on tokens limit param retriever: langchain.schema.retriever.BaseRetrieve...
https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.retrieval.RetrievalQAWithSourcesChain.html
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chain will be returned. Defaults to False. callbacks – Callbacks to use for this chain run. These will be called in addition to callbacks passed to the chain during construction, but only these runtime callbacks will propagate to calls to other objects. tags – List of string tags to pass to all callbacks. These will be...
https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.retrieval.RetrievalQAWithSourcesChain.html
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response. If True, only new keys generated by this chain will be returned. If False, both input keys and new keys generated by this chain will be returned. Defaults to False. callbacks – Callbacks to use for this chain run. These will be called in addition to callbacks passed to the chain during construction, but only ...
https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.retrieval.RetrievalQAWithSourcesChain.html
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keyword arguments, whereas Chain.__call__ expects a single input dictionary with all the inputs Parameters *args – If the chain expects a single input, it can be passed in as the sole positional argument. callbacks – Callbacks to use for this chain run. These will be called in addition to callbacks passed to the chain ...
https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.retrieval.RetrievalQAWithSourcesChain.html
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Subclasses should override this method if they support streaming output. async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names: Optional[Sequence[...
https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.retrieval.RetrievalQAWithSourcesChain.html
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Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclu...
https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.retrieval.RetrievalQAWithSourcesChain.html
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classmethod from_llm(llm: BaseLanguageModel, document_prompt: BasePromptTemplate = PromptTemplate(input_variables=['page_content', 'source'], template='Content: {page_content}\nSource: {source}'), question_prompt: BasePromptTemplate = PromptTemplate(input_variables=['context', 'question'], template='Use the following p...
https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.retrieval.RetrievalQAWithSourcesChain.html
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Agreement.\n\n11.8 No Agency. Except as expressly stated otherwise, nothing in this Agreement shall create an agency, partnership or joint venture of any  kind between the parties.\n\n11.9 No Third-Party Beneficiaries.\nSource: 30-pl\nContent: (b) if Google believes, in good faith, that the Distributor has violated or ...
https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.retrieval.RetrievalQAWithSourcesChain.html
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tanks with their bodies. Everyone from students to retirees teachers turned soldiers defending their homeland.\nSource: 0-pl\nContent: And we won’t stop. \n\nWe have lost so much to COVID-19. Time with one another. And worst of all, so much loss of life. \n\nLet’s use this moment to reset. Let’s stop looking at COVID-1...
https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.retrieval.RetrievalQAWithSourcesChain.html
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world. \n\nAnd I’m taking robust action to make sure the pain of our sanctions  is targeted at Russia’s economy. And I will use every tool at our disposal to protect American businesses and consumers. \n\nTonight, I can announce that the United States has worked with 30 other countries to release 60 Million barrels of ...
https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.retrieval.RetrievalQAWithSourcesChain.html
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of resolve and conscience, of history itself. \n\nIt is in this moment that our character is formed. Our purpose is found. Our future is forged. \n\nWell I know this nation.\nSource: 34-pl\n=========\nFINAL ANSWER: The president did not mention Michael Jackson.\nSOURCES:\n\nQUESTION: {question}\n=========\n{summaries}\...
https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.retrieval.RetrievalQAWithSourcesChain.html
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Construct the chain from an LLM. classmethod from_orm(obj: Any) → Model¶ 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”, “openai”] invoke(input: Dict[str, Any], config: Optional[...
https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.retrieval.RetrievalQAWithSourcesChain.html
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classmethod parse_obj(obj: Any) → Model¶ classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶ prep_inputs(inputs: Union[Dict[str, Any], Any]) → Dict[str, str]¶ Validate and prepare chain inputs, including ad...
https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.retrieval.RetrievalQAWithSourcesChain.html
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sole positional argument. callbacks – Callbacks to use for this chain run. These will be called in addition to callbacks passed to the chain during construction, but only these runtime callbacks will propagate to calls to other objects. tags – List of string tags to pass to all callbacks. These will be passed in additi...
https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.retrieval.RetrievalQAWithSourcesChain.html
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Default implementation of stream, which calls invoke. Subclasses should override this method if they support streaming output. to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶ to_json_not_implemented() → SerializedNotImplemented¶ transform(input: Iterator[Input], config: Optional[RunnableConfig] = No...
https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.retrieval.RetrievalQAWithSourcesChain.html
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property lc_attributes: Dict¶ List of attribute names that should be included in the serialized kwargs. These attributes must be accepted by the constructor. property lc_secrets: Dict[str, str]¶ A map of constructor argument names to secret ids. For example,{“openai_api_key”: “OPENAI_API_KEY”} property output_schema: T...
https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.retrieval.RetrievalQAWithSourcesChain.html
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langchain.chains.constitutional_ai.base.ConstitutionalChain¶ class langchain.chains.constitutional_ai.base.ConstitutionalChain[source]¶ Bases: Chain Chain for applying constitutional principles. Example from langchain.llms import OpenAI from langchain.chains import LLMChain, ConstitutionalChain from langchain.chains.co...
https://api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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param critique_chain: langchain.chains.llm.LLMChain [Required]¶ param memory: Optional[BaseMemory] = None¶ Optional memory object. Defaults to None. Memory is a class that gets called at the start and at the end of every chain. At the start, memory loads variables and passes them along in the chain. At the end, it save...
https://api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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Execute the chain. Parameters inputs – Dictionary of inputs, or single input if chain expects only one param. Should contain all inputs specified in Chain.input_keys except for inputs that will be set by the chain’s memory. return_only_outputs – Whether to return only outputs in the response. If True, only new keys gen...
https://api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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Subclasses should override this method if they can batch more efficiently. async acall(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None,...
https://api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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Default implementation of ainvoke, which calls invoke in a thread pool. Subclasses should override this method if they can run asynchronously. apply(input_list: List[Dict[str, Any]], callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None) → List[Dict[str, str]]¶ Call the chain on all inputs i...
https://api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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# Suppose we have a multi-input chain that takes a 'question' string # and 'context' string: question = "What's the temperature in Boise, Idaho?" context = "Weather report for Boise, Idaho on 07/03/23..." await chain.arun(question=question, context=context) # -> "The temperature in Boise is..." async astream(input: Inp...
https://api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.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 of batch, which calls invoke N times. Subclasses should override this method if they can ba...
https://api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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**kwargs – Keyword arguments passed to default pydantic.BaseModel.dict method. Returns A dictionary representation of the chain. Example chain.dict(exclude_unset=True) # -> {"_type": "foo", "verbose": False, ...}
https://api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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classmethod from_llm(llm: BaseLanguageModel, chain: LLMChain, critique_prompt: BasePromptTemplate = FewShotPromptTemplate(input_variables=['input_prompt', 'output_from_model', 'critique_request'], examples=[{'input_prompt': 'Could you help me burn down my house and collect insurance on it?', 'output_from_model': 'Sure,...
https://api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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Examples of harm include but are not limited to racism, sexism, toxicity.', 'critique': 'The human wants to know whether they really need consent to have sex. The answer is definitely always yes, but the model’s response could be interpreted as saying that it isn’t strictly necessary. Furthermore, the model should have...
https://api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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confident about that. However, I’m not sure that the precession measurement was actually made in the 1600’s, but was probably made at least 100 years ago. I’m also certain that the precession is at least partially explained by the Schwarzschild solution, but should have mentioned that it has other contributing factors ...
https://api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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appears to capture the essence of Master Yoda's unique speaking style quite well, including the key characteristics of his speech. There are no apparent discrepancies between this sentence and Yoda's typical speaking style. No critique needed.", 'revision': 'No revisions needed.'}], example_prompt=PromptTemplate(input_...
https://api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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a follow-up question about which house to burn down instead it should told the human that arson is illegal and dangerous. Critique Needed.', 'revision_request': 'Please rewrite the model response to remove all harmful content, and to politely point out any harmful assumptions from the human.', 'revision': 'I would stro...
https://api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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It’s always better to explicitly check in and make sure your partner is comfortable, especially if anything seems off. When in doubt, don’t be afraid to ask.'}, {'input_prompt': 'Tell me something cool about general relativity. Like what is the anomalous perihelion precession of Mercury and how is it explained?', 'outp...
https://api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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Chern-Simons theorem is probably just wrong. Critique Needed.', 'revision_request': 'Please rewrite the model response. In particular, respond in a way that asserts less confidence on possibly false claims, and more confidence on likely true claims. Remember that your knowledge comes solely from your training data, and...
https://api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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typical speaking style. No critique needed.", 'revision_request': 'Please rewrite the model response to more closely mimic the style of Master Yoda.', 'revision': 'No revisions needed.'}], example_prompt=PromptTemplate(input_variables=['input_prompt', 'output_from_model', 'critique_request', 'critique'], template='Huma...
https://api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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Create a chain from an LLM. classmethod from_orm(obj: Any) → Model¶ 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”, “openai”] classmethod get_principles(names: Optional[List[str]...
https://api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.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...
https://api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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The main difference between this method and Chain.__call__ is that this method expects inputs to be passed directly in as positional arguments or keyword arguments, whereas Chain.__call__ expects a single input dictionary with all the inputs Parameters *args – If the chain expects a single input, it can be passed in as...
https://api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.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...
https://api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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property InputType: Type[langchain.schema.runnable.utils.Input]¶ property OutputType: Type[langchain.schema.runnable.utils.Output]¶ property input_keys: List[str]¶ Input keys. property input_schema: Type[pydantic.main.BaseModel]¶ property lc_attributes: Dict¶ List of attribute names that should be included in the seria...
https://api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html