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Defaults to one that takes the most likely string but does not change it otherwise. param prompt: langchain.schema.prompt_template.BasePromptTemplate = PromptTemplate(input_variables=['history', 'input'], template='The following is a friendly conversation between a human and an AI. The AI is talkative and provides lots...
https://api.python.langchain.com/en/latest/chains/langchain.chains.conversation.base.ConversationChain.html
4dd36791f47f-2
Chain.input_keys except for inputs that will be set by the chain’s memory. return_only_outputs – Whether to return only outputs in the response. If True, only new keys generated by this chain will be returned. If False, both input keys and new keys generated by this chain will be returned. Defaults to False. callbacks ...
https://api.python.langchain.com/en/latest/chains/langchain.chains.conversation.base.ConversationChain.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.conversation.base.ConversationChain.html
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Generate LLM result from inputs. async ainvoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None, **kwargs: Any) → Dict[str, Any]¶ 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, ...
https://api.python.langchain.com/en/latest/chains/langchain.chains.conversation.base.ConversationChain.html
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Prepare prompts from inputs. async arun(*args: Any, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → Any¶ Convenience method for executing chain. The main difference between this method and Ch...
https://api.python.langchain.com/en/latest/chains/langchain.chains.conversation.base.ConversationChain.html
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# -> "The temperature in Boise is..." async astream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶ Default implementation of astream, which calls ainvoke. Subclasses should override this method if they support streaming output. async astream_log(input: Any, conf...
https://api.python.langchain.com/en/latest/chains/langchain.chains.conversation.base.ConversationChain.html
4dd36791f47f-7
Subclasses should override this method if they can batch more efficiently. bind(**kwargs: Any) → Runnable[Input, Output]¶ Bind arguments to a Runnable, returning a new Runnable. classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶ Creates a new model setting __dict__ and __fields_set__ fr...
https://api.python.langchain.com/en/latest/chains/langchain.chains.conversation.base.ConversationChain.html
4dd36791f47f-8
# -> {"_type": "foo", "verbose": False, ...} classmethod from_orm(obj: Any) → Model¶ classmethod from_string(llm: BaseLanguageModel, template: str) → LLMChain¶ Create LLMChain from LLM and template. generate(input_list: List[Dict[str, Any]], run_manager: Optional[CallbackManagerForChainRun] = None) → LLMResult¶ Generat...
https://api.python.langchain.com/en/latest/chains/langchain.chains.conversation.base.ConversationChain.html
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The unique identifier is a list of strings that describes the path to the object. map() → Runnable[List[Input], List[Output]]¶ Return a new Runnable that maps a list of inputs to a list of outputs, by calling invoke() with each input. classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encod...
https://api.python.langchain.com/en/latest/chains/langchain.chains.conversation.base.ConversationChain.html
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Returns A dictionary of all inputs, including those added by the chain’s memory. prep_outputs(inputs: Dict[str, str], outputs: Dict[str, str], return_only_outputs: bool = False) → Dict[str, str]¶ Validate and prepare chain outputs, and save info about this run to memory. Parameters inputs – Dictionary of chain inputs, ...
https://api.python.langchain.com/en/latest/chains/langchain.chains.conversation.base.ConversationChain.html
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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 'question' string: chain.run("What's the temperature in Boise, Idaho?")...
https://api.python.langchain.com/en/latest/chains/langchain.chains.conversation.base.ConversationChain.html
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Default implementation of transform, which buffers input and then calls stream. Subclasses should override this method if they can start producing output while input is still being generated. classmethod update_forward_refs(**localns: Any) → None¶ Try to update ForwardRefs on fields based on this Model, globalns and lo...
https://api.python.langchain.com/en/latest/chains/langchain.chains.conversation.base.ConversationChain.html
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For example,{“openai_api_key”: “OPENAI_API_KEY”} property output_schema: Type[pydantic.main.BaseModel]¶ Examples using ConversationChain¶ Entity Memory with SQLite storage Figma Bedrock Set env var OPENAI_API_KEY or load from a .env file: Agent Debates with Tools Multiple Memory classes Customizing Conversational Memor...
https://api.python.langchain.com/en/latest/chains/langchain.chains.conversation.base.ConversationChain.html
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langchain.chains.openai_functions.citation_fuzzy_match.QuestionAnswer¶ class langchain.chains.openai_functions.citation_fuzzy_match.QuestionAnswer[source]¶ Bases: BaseModel A question and its answer as a list of facts each one should have a source. each sentence contains a body and a list of sources. Create a new model...
https://api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.citation_fuzzy_match.QuestionAnswer.html
b0d37ca7420b-1
deep – set to True to make a deep copy of the model Returns new model instance dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, ex...
https://api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.citation_fuzzy_match.QuestionAnswer.html
b0d37ca7420b-2
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶ classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶ classmethod update_forward_refs(**localns: Any) → None¶ Try to update ForwardRefs on...
https://api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.citation_fuzzy_match.QuestionAnswer.html
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langchain.chains.query_constructor.ir.StructuredQuery¶ class langchain.chains.query_constructor.ir.StructuredQuery[source]¶ Bases: Expr A structured query. 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. par...
https://api.python.langchain.com/en/latest/chains/langchain.chains.query_constructor.ir.StructuredQuery.html
ec41c20505b1-1
deep – set to True to make a deep copy of the model Returns new model instance dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, ex...
https://api.python.langchain.com/en/latest/chains/langchain.chains.query_constructor.ir.StructuredQuery.html
ec41c20505b1-2
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶ classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶ classmethod update_forward_refs(**localns: Any) → None¶ Try to update ForwardRefs on...
https://api.python.langchain.com/en/latest/chains/langchain.chains.query_constructor.ir.StructuredQuery.html
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langchain.chains.flare.base.FlareChain¶ class langchain.chains.flare.base.FlareChain[source]¶ Bases: Chain Chain that combines a retriever, a question generator, and a response generator. Create a new model by parsing and validating input data from keyword arguments. Raises ValidationError if the input data cannot be p...
https://api.python.langchain.com/en/latest/chains/langchain.chains.flare.base.FlareChain.html
0cfc2a83b1e8-1
Minimum number of tokens between two low confidence spans. param num_pad_tokens: int = 2¶ Number of tokens to pad around a low confidence span. param output_parser: FinishedOutputParser [Optional]¶ Parser that determines whether the chain is finished. param question_generator_chain: QuestionGeneratorChain [Required]¶ C...
https://api.python.langchain.com/en/latest/chains/langchain.chains.flare.base.FlareChain.html
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Chain.input_keys except for inputs that will be set by the chain’s memory. return_only_outputs – Whether to return only outputs in the response. If True, only new keys generated by this chain will be returned. If False, both input keys and new keys generated by this chain will be returned. Defaults to False. callbacks ...
https://api.python.langchain.com/en/latest/chains/langchain.chains.flare.base.FlareChain.html
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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 generated by this chai...
https://api.python.langchain.com/en/latest/chains/langchain.chains.flare.base.FlareChain.html
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Call the chain on all inputs in the list. async arun(*args: Any, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → Any¶ Convenience method for executing chain. The main difference between this ...
https://api.python.langchain.com/en/latest/chains/langchain.chains.flare.base.FlareChain.html
0cfc2a83b1e8-5
# -> "The temperature in Boise is..." async astream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶ Default implementation of astream, which calls ainvoke. Subclasses should override this method if they support streaming output. async astream_log(input: Any, conf...
https://api.python.langchain.com/en/latest/chains/langchain.chains.flare.base.FlareChain.html
0cfc2a83b1e8-6
Subclasses should override this method if they can batch more efficiently. bind(**kwargs: Any) → Runnable[Input, Output]¶ Bind arguments to a Runnable, returning a new Runnable. classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶ Creates a new model setting __dict__ and __fields_set__ fr...
https://api.python.langchain.com/en/latest/chains/langchain.chains.flare.base.FlareChain.html
0cfc2a83b1e8-7
Creates a FlareChain from a language model. Parameters llm – Language model to use. max_generation_len – Maximum length of the generated response. **kwargs – Additional arguments to pass to the constructor. Returns FlareChain class with the given language model. classmethod from_orm(obj: Any) → Model¶ classmethod get_l...
https://api.python.langchain.com/en/latest/chains/langchain.chains.flare.base.FlareChain.html
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Return a new Runnable that maps a list of inputs to a list of outputs, by calling invoke() with each input. classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶ classmethod parse_obj(obj: Any) → Model¶ cl...
https://api.python.langchain.com/en/latest/chains/langchain.chains.flare.base.FlareChain.html
0cfc2a83b1e8-9
Convenience method for executing chain. The main difference between this method and Chain.__call__ is that this method expects inputs to be passed directly in as positional arguments or keyword arguments, whereas Chain.__call__ expects a single input dictionary with all the inputs Parameters *args – If the chain expect...
https://api.python.langchain.com/en/latest/chains/langchain.chains.flare.base.FlareChain.html
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Example chain.save(file_path="path/chain.yaml") 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: Optiona...
https://api.python.langchain.com/en/latest/chains/langchain.chains.flare.base.FlareChain.html
0cfc2a83b1e8-11
with_retry(*, retry_if_exception_type: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,), wait_exponential_jitter: bool = True, stop_after_attempt: int = 3) → Runnable[Input, Output]¶ property InputType: Type[langchain.schema.runnable.utils.Input]¶ property OutputType: Type[langchain.schema.runna...
https://api.python.langchain.com/en/latest/chains/langchain.chains.flare.base.FlareChain.html
a91fa8bf01a8-0
langchain.chains.router.multi_prompt.MultiPromptChain¶ class langchain.chains.router.multi_prompt.MultiPromptChain[source]¶ Bases: MultiRouteChain A multi-route chain that uses an LLM router chain to choose amongst prompts. Create a new model by parsing and validating input data from keyword arguments. Raises Validatio...
https://api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_prompt.MultiPromptChain.html
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param router_chain: RouterChain [Required]¶ Chain that routes inputs to destination chains. param silent_errors: bool = False¶ If True, use default_chain when an invalid destination name is provided. Defaults to False. param tags: Optional[List[str]] = None¶ Optional list of tags associated with the chain. Defaults to ...
https://api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_prompt.MultiPromptChain.html
a91fa8bf01a8-2
these runtime callbacks will propagate to calls to other objects. tags – List of string tags to pass to all callbacks. These will be passed in addition to tags passed to the chain during construction, but only these runtime tags will propagate to calls to other objects. metadata – Optional metadata associated with the ...
https://api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_prompt.MultiPromptChain.html
a91fa8bf01a8-3
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.multi_prompt.MultiPromptChain.html
a91fa8bf01a8-4
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.router.multi_prompt.MultiPromptChain.html
a91fa8bf01a8-5
Subclasses should override this method if they support streaming output. async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names: Optional[Sequence[...
https://api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_prompt.MultiPromptChain.html
a91fa8bf01a8-6
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.router.multi_prompt.MultiPromptChain.html
a91fa8bf01a8-7
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.router.multi_prompt.MultiPromptChain.html
a91fa8bf01a8-8
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.router.multi_prompt.MultiPromptChain.html
a91fa8bf01a8-9
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.router.multi_prompt.MultiPromptChain.html
a91fa8bf01a8-10
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.multi_prompt.MultiPromptChain.html
a91fa8bf01a8-11
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.router.multi_prompt.MultiPromptChain.html
fe2e31c52ad1-0
langchain.chains.graph_qa.nebulagraph.NebulaGraphQAChain¶ class langchain.chains.graph_qa.nebulagraph.NebulaGraphQAChain[source]¶ Bases: Chain Chain for question-answering against a graph by generating nGQL statements. Create a new model by parsing and validating input data from keyword arguments. Raises ValidationErro...
https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.nebulagraph.NebulaGraphQAChain.html
fe2e31c52ad1-1
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.graph_qa.nebulagraph.NebulaGraphQAChain.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.graph_qa.nebulagraph.NebulaGraphQAChain.html
fe2e31c52ad1-3
addition to tags passed to the chain during construction, but only these runtime tags will propagate to calls to other objects. metadata – Optional metadata associated with the chain. Defaults to None include_run_info – Whether to include run info in the response. Defaults to False. Returns A dict of named outputs. Sho...
https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.nebulagraph.NebulaGraphQAChain.html
fe2e31c52ad1-4
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.graph_qa.nebulagraph.NebulaGraphQAChain.html
fe2e31c52ad1-5
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.graph_qa.nebulagraph.NebulaGraphQAChain.html
fe2e31c52ad1-6
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.graph_qa.nebulagraph.NebulaGraphQAChain.html
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classmethod from_llm(llm: BaseLanguageModel, *, qa_prompt: BasePromptTemplate = PromptTemplate(input_variables=['context', 'question'], template="You are an assistant that helps to form nice and human understandable answers.\nThe information part contains the provided information that you must use to construct an answe...
https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.nebulagraph.NebulaGraphQAChain.html
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only the provided relationship types and properties in the schema.\nDo not use any other relationship types or properties that are not provided.\nSchema:\n{schema}\nNote: Do not include any explanations or apologies in your responses.\nDo not respond to any questions that might ask anything else than for you to constru...
https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.nebulagraph.NebulaGraphQAChain.html
fe2e31c52ad1-9
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.nebulagraph.NebulaGraphQAChain.html
fe2e31c52ad1-10
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.nebulagraph.NebulaGraphQAChain.html
fe2e31c52ad1-11
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.nebulagraph.NebulaGraphQAChain.html
fe2e31c52ad1-12
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.nebulagraph.NebulaGraphQAChain.html
fe2e31c52ad1-13
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.graph_qa.nebulagraph.NebulaGraphQAChain.html
c2e10e848fba-0
langchain.chains.openai_functions.base.convert_python_function_to_openai_function¶ langchain.chains.openai_functions.base.convert_python_function_to_openai_function(function: Callable) → Dict[str, Any][source]¶ Convert a Python function to an OpenAI function-calling API compatible dict. Assumes the Python function has ...
https://api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.base.convert_python_function_to_openai_function.html
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langchain.chains.natbot.base.NatBotChain¶ class langchain.chains.natbot.base.NatBotChain[source]¶ Bases: Chain Implement an LLM driven browser. Example from langchain.chains import NatBotChain natbot = NatBotChain.from_default("Buy me a new hat.") Create a new model by parsing and validating input data from keyword arg...
https://api.python.langchain.com/en/latest/chains/langchain.chains.natbot.base.NatBotChain.html
d8247727d1d8-1
param objective: str [Required]¶ Objective that NatBot is tasked with completing. 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 u...
https://api.python.langchain.com/en/latest/chains/langchain.chains.natbot.base.NatBotChain.html
d8247727d1d8-2
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.natbot.base.NatBotChain.html
d8247727d1d8-3
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.natbot.base.NatBotChain.html
d8247727d1d8-4
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. **kwargs – If the chain expects multiple inputs, ...
https://api.python.langchain.com/en/latest/chains/langchain.chains.natbot.base.NatBotChain.html
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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 can be applied in order to construct state. async atransform(input: As...
https://api.python.langchain.com/en/latest/chains/langchain.chains.natbot.base.NatBotChain.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...
https://api.python.langchain.com/en/latest/chains/langchain.chains.natbot.base.NatBotChain.html
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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 serializable? json(*, include: Optional[Union[Ab...
https://api.python.langchain.com/en/latest/chains/langchain.chains.natbot.base.NatBotChain.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.natbot.base.NatBotChain.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.natbot.base.NatBotChain.html
d8247727d1d8-10
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.natbot.base.NatBotChain.html
d8247727d1d8-11
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.natbot.base.NatBotChain.html
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langchain.chains.query_constructor.schema.AttributeInfo¶ class langchain.chains.query_constructor.schema.AttributeInfo[source]¶ Bases: BaseModel Information about a data source attribute. Create a new model by parsing and validating input data from keyword arguments. Raises ValidationError if the input data cannot be p...
https://api.python.langchain.com/en/latest/chains/langchain.chains.query_constructor.schema.AttributeInfo.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.schema.AttributeInfo.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.schema.AttributeInfo.html
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langchain.chains.llm_checker.base.LLMCheckerChain¶ class langchain.chains.llm_checker.base.LLMCheckerChain[source]¶ Bases: Chain Chain for question-answering with self-verification. Example from langchain.llms import OpenAI from langchain.chains import LLMCheckerChain llm = OpenAI(temperature=0.7) checker_chain = LLMCh...
https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_checker.base.LLMCheckerChain.html
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[Deprecated] LLM wrapper to use. 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 saves any returned variables. There...
https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_checker.base.LLMCheckerChain.html
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will be printed to the console. Defaults to langchain.verbose value. __call__(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, run_name...
https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_checker.base.LLMCheckerChain.html
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Default implementation of abatch, which calls ainvoke N times. 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: Optiona...
https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_checker.base.LLMCheckerChain.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.llm_checker.base.LLMCheckerChain.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.llm_checker.base.LLMCheckerChain.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.llm_checker.base.LLMCheckerChain.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, ...} classmethod from_llm(llm: BaseLanguageModel, create_draft_answer_prompt: PromptTemplate = PromptTemplate(in...
https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_checker.base.LLMCheckerChain.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.llm_checker.base.LLMCheckerChain.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.llm_checker.base.LLMCheckerChain.html
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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 'question' string: chain.run("What's the temperature in Boise, Idaho?")...
https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_checker.base.LLMCheckerChain.html
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Default implementation of transform, which buffers input and then calls stream. Subclasses should override this method if they can start producing output while input is still being generated. classmethod update_forward_refs(**localns: Any) → None¶ Try to update ForwardRefs on fields based on this Model, globalns and lo...
https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_checker.base.LLMCheckerChain.html
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langchain.chains.openai_functions.qa_with_structure.create_qa_with_structure_chain¶ langchain.chains.openai_functions.qa_with_structure.create_qa_with_structure_chain(llm: BaseLanguageModel, schema: Union[dict, Type[BaseModel]], output_parser: str = 'base', prompt: Optional[Union[PromptTemplate, ChatPromptTemplate]] = ...
https://api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.qa_with_structure.create_qa_with_structure_chain.html
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langchain.chains.graph_qa.kuzu.KuzuQAChain¶ class langchain.chains.graph_qa.kuzu.KuzuQAChain[source]¶ Bases: Chain Chain for question-answering against a graph by generating Cypher statements for Kùzu. Create a new model by parsing and validating input data from keyword arguments. Raises ValidationError if the input da...
https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.kuzu.KuzuQAChain.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.graph_qa.kuzu.KuzuQAChain.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.graph_qa.kuzu.KuzuQAChain.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.graph_qa.kuzu.KuzuQAChain.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.graph_qa.kuzu.KuzuQAChain.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.graph_qa.kuzu.KuzuQAChain.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.graph_qa.kuzu.KuzuQAChain.html
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classmethod from_llm(llm: BaseLanguageModel, *, qa_prompt: BasePromptTemplate = PromptTemplate(input_variables=['context', 'question'], template="You are an assistant that helps to form nice and human understandable answers.\nThe information part contains the provided information that you must use to construct an answe...
https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.kuzu.KuzuQAChain.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.kuzu.KuzuQAChain.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.kuzu.KuzuQAChain.html
0a3e58198646-10
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.kuzu.KuzuQAChain.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.kuzu.KuzuQAChain.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.graph_qa.kuzu.KuzuQAChain.html
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langchain.chains.combine_documents.base.BaseCombineDocumentsChain¶ class langchain.chains.combine_documents.base.BaseCombineDocumentsChain[source]¶ Bases: Chain, ABC Base interface for chains combining documents. Subclasses of this chain deal with combining documents in a variety of ways. This base class exists to add ...
https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.base.BaseCombineDocumentsChain.html