id stringlengths 14 16 | text stringlengths 13 2.7k | source stringlengths 57 178 |
|---|---|---|
1a5dc8f333a1-8 | The type of input this runnable accepts specified as a type annotation.
property OutputType: Type[langchain.schema.output_parser.T]¶
The type of output this runnable produces specified as a type annotation.
property config_specs: List[langchain.schema.runnable.utils.ConfigurableFieldSpec]¶
List configurable fields for ... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.conversational_chat.output_parser.ConvoOutputParser.html |
0dd0302800ae-0 | langchain.agents.openai_functions_agent.base.OpenAIFunctionsAgent¶
class langchain.agents.openai_functions_agent.base.OpenAIFunctionsAgent[source]¶
Bases: BaseSingleActionAgent
An Agent driven by OpenAIs function powered API.
Parameters
llm – This should be an instance of ChatOpenAI, specifically a model
that supports ... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.openai_functions_agent.base.OpenAIFunctionsAgent.html |
0dd0302800ae-1 | Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.openai_functions_agent.base.OpenAIFunctionsAgent.html |
0dd0302800ae-2 | Construct an agent from an LLM and tools.
classmethod from_orm(obj: Any) → Model¶
get_allowed_tools() → List[str][source]¶
Get allowed tools.
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_d... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.openai_functions_agent.base.OpenAIFunctionsAgent.html |
0dd0302800ae-3 | **kwargs – User inputs.
Returns
Action specifying what tool to use.
return_stopped_response(early_stopping_method: str, intermediate_steps: List[Tuple[AgentAction, str]], **kwargs: Any) → AgentFinish[source]¶
Return response when agent has been stopped due to max iterations.
save(file_path: Union[Path, str]) → None¶
Sa... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.openai_functions_agent.base.OpenAIFunctionsAgent.html |
002ed64dfe06-0 | langchain.agents.agent.AgentOutputParser¶
class langchain.agents.agent.AgentOutputParser[source]¶
Bases: BaseOutputParser[Union[AgentAction, AgentFinish]]
Base class for parsing agent output into agent action/finish.
async abatch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None,... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent.AgentOutputParser.html |
002ed64dfe06-1 | to be different candidate outputs for a single model input.
Returns
Structured output.
async astream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶
Default implementation of astream, which calls ainvoke.
Subclasses should override this method if they support str... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent.AgentOutputParser.html |
002ed64dfe06-2 | Default implementation runs invoke in parallel using a thread pool executor.
The default implementation of batch works well for IO bound runnables.
Subclasses should override this method if they can batch more efficiently;
e.g., if the underlying runnable uses an API which supports a batch mode.
bind(**kwargs: Any) → R... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent.AgentOutputParser.html |
002ed64dfe06-3 | Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creat... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent.AgentOutputParser.html |
002ed64dfe06-4 | methods will have a dynamic output schema that depends on which
configuration the runnable is invoked with.
This method allows to get an output schema for a specific configuration.
Parameters
config – A config to use when generating the schema.
Returns
A pydantic model that can be used to validate output.
invoke(input:... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent.AgentOutputParser.html |
002ed64dfe06-5 | The unique identifier is a list of strings that describes the path
to the object.
map() → Runnable[List[Input], List[Output]]¶
Return a new Runnable that maps a list of inputs to a list of outputs,
by calling invoke() with each input.
abstract parse(text: str) → Union[AgentAction, AgentFinish][source]¶
Parse text into ... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent.AgentOutputParser.html |
002ed64dfe06-6 | classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
stream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → Iterator[Output]¶
Default implementation of stream, which calls invoke.
Subclasses should override t... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent.AgentOutputParser.html |
002ed64dfe06-7 | fallback in order, upon failures.
with_listeners(*, on_start: Optional[Listener] = None, on_end: Optional[Listener] = None, on_error: Optional[Listener] = None) → Runnable[Input, Output]¶
Bind lifecycle listeners to a Runnable, returning a new Runnable.
on_start: Called before the runnable starts running, with the Run ... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent.AgentOutputParser.html |
002ed64dfe06-8 | The type of output this runnable produces specified as a type annotation.
property config_specs: List[langchain.schema.runnable.utils.ConfigurableFieldSpec]¶
List configurable fields for this runnable.
property input_schema: Type[pydantic.main.BaseModel]¶
The type of input this runnable accepts specified as a pydantic ... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent.AgentOutputParser.html |
bf9827ebddb1-0 | langchain.agents.structured_chat.output_parser.StructuredChatOutputParserWithRetries¶
class langchain.agents.structured_chat.output_parser.StructuredChatOutputParserWithRetries[source]¶
Bases: AgentOutputParser
Output parser with retries for the structured chat agent.
param base_parser: langchain.agents.agent.AgentOutp... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.structured_chat.output_parser.StructuredChatOutputParserWithRetries.html |
bf9827ebddb1-1 | Parse a list of candidate model Generations into a specific format.
The return value is parsed from only the first Generation in the result, whichis assumed to be the highest-likelihood Generation.
Parameters
result – A list of Generations to be parsed. The Generations are assumed
to be different candidate outputs for ... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.structured_chat.output_parser.StructuredChatOutputParserWithRetries.html |
bf9827ebddb1-2 | Subclasses should override this method if they can start producing output while
input is still being generated.
batch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Optional[Any]) → List[Output]¶
Default implementation runs invoke... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.structured_chat.output_parser.StructuredChatOutputParserWithRetries.html |
bf9827ebddb1-3 | Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.structured_chat.output_parser.StructuredChatOutputParserWithRetries.html |
bf9827ebddb1-4 | Returns
A pydantic model that can be used to validate input.
classmethod get_lc_namespace() → List[str]¶
Get the namespace of the langchain object.
For example, if the class is langchain.llms.openai.OpenAI, then the
namespace is [“langchain”, “llms”, “openai”]
get_output_schema(config: Optional[RunnableConfig] = None) ... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.structured_chat.output_parser.StructuredChatOutputParserWithRetries.html |
bf9827ebddb1-5 | classmethod is_lc_serializable() → bool¶
Is this class serializable?
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defa... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.structured_chat.output_parser.StructuredChatOutputParserWithRetries.html |
bf9827ebddb1-6 | parse_result(result: List[Generation], *, partial: bool = False) → T¶
Parse a list of candidate model Generations into a specific format.
The return value is parsed from only the first Generation in the result, whichis assumed to be the highest-likelihood Generation.
Parameters
result – A list of Generations to be pars... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.structured_chat.output_parser.StructuredChatOutputParserWithRetries.html |
bf9827ebddb1-7 | input is still being generated.
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate(value: Any) → Model¶
with_config(config: Optional[RunnableConfig] = None, **kwargs: Any) → Runnable[Input, Output]¶
Bind config to a... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.structured_chat.output_parser.StructuredChatOutputParserWithRetries.html |
bf9827ebddb1-8 | added to the run.
with_retry(*, retry_if_exception_type: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,), wait_exponential_jitter: bool = True, stop_after_attempt: int = 3) → Runnable[Input, Output]¶
Create a new Runnable that retries the original runnable on exceptions.
Parameters
retry_if_exc... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.structured_chat.output_parser.StructuredChatOutputParserWithRetries.html |
bf9827ebddb1-9 | property output_schema: Type[pydantic.main.BaseModel]¶
The type of output this runnable produces specified as a pydantic model. | lang/api.python.langchain.com/en/latest/agents/langchain.agents.structured_chat.output_parser.StructuredChatOutputParserWithRetries.html |
89c47c511e23-0 | langchain.agents.agent_iterator.AgentExecutorIterator¶
class langchain.agents.agent_iterator.AgentExecutorIterator(agent_executor: AgentExecutor, inputs: Any, callbacks: Callbacks = None, *, tags: Optional[list[str]] = None, include_run_info: bool = False, async_: bool = False)[source]¶
Iterator for AgentExecutor.
Init... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_iterator.AgentExecutorIterator.html |
89c47c511e23-1 | raise_stopiteration(output: Any) → NoReturn[source]¶
Raise a StopIteration exception with the given output.
reset() → None[source]¶
Reset the iterator to its initial state, clearing intermediate steps,
iterations, and time elapsed.
update_iterations() → None[source]¶
Increment the number of iterations and update the ti... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_iterator.AgentExecutorIterator.html |
b225848ea780-0 | langchain.agents.agent_toolkits.vectorstore.base.create_vectorstore_router_agent¶
langchain.agents.agent_toolkits.vectorstore.base.create_vectorstore_router_agent(llm: BaseLanguageModel, toolkit: VectorStoreRouterToolkit, callback_manager: Optional[BaseCallbackManager] = None, prefix: str = 'You are an agent designed t... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.vectorstore.base.create_vectorstore_router_agent.html |
1289cf2f5ad1-0 | langchain.agents.mrkl.base.ChainConfig¶
class langchain.agents.mrkl.base.ChainConfig(action_name: str, action: Callable, action_description: str)[source]¶
Configuration for chain to use in MRKL system.
Parameters
action_name – Name of the action.
action – Action function to call.
action_description – Description of the... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.mrkl.base.ChainConfig.html |
a1c5cb58c55c-0 | langchain.agents.agent_toolkits.openapi.toolkit.RequestsToolkit¶
class langchain.agents.agent_toolkits.openapi.toolkit.RequestsToolkit[source]¶
Bases: BaseToolkit
Toolkit for making REST requests.
Security Note: This toolkit contains tools to make GET, POST, PATCH, PUT,and DELETE requests to an API.
Exercise care in wh... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.openapi.toolkit.RequestsToolkit.html |
a1c5cb58c55c-1 | exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, i... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.openapi.toolkit.RequestsToolkit.html |
a1c5cb58c55c-2 | classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmet... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.openapi.toolkit.RequestsToolkit.html |
131e8842afa5-0 | langchain.agents.agent_toolkits.amadeus.toolkit.AmadeusToolkit¶
class langchain.agents.agent_toolkits.amadeus.toolkit.AmadeusToolkit[source]¶
Bases: BaseToolkit
Toolkit for interacting with Amadeus which offers APIs for travel search.
Create a new model by parsing and validating input data from keyword arguments.
Raise... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.amadeus.toolkit.AmadeusToolkit.html |
131e8842afa5-1 | deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, ex... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.amadeus.toolkit.AmadeusToolkit.html |
131e8842afa5-2 | classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmet... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.amadeus.toolkit.AmadeusToolkit.html |
ace7ce8b66bf-0 | langchain.agents.react.base.ReActChain¶
class langchain.agents.react.base.ReActChain[source]¶
Bases: AgentExecutor
[Deprecated] Chain that implements the ReAct paper.
Initialize with the LLM and a docstore.
param agent: Union[BaseSingleActionAgent, BaseMultiActionAgent] [Required]¶
The agent to run for creating a plan ... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.react.base.ReActChain.html |
ace7ce8b66bf-1 | param max_execution_time: Optional[float] = None¶
The maximum amount of wall clock time to spend in the execution
loop.
param max_iterations: Optional[int] = 15¶
The maximum number of steps to take before ending the execution
loop.
Setting to ‘None’ could lead to an infinite loop.
param memory: Optional[BaseMemory] = N... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.react.base.ReActChain.html |
ace7ce8b66bf-2 | param verbose: bool [Optional]¶
Whether or not run in verbose mode. In verbose mode, some intermediate logs
will be printed to the console. Defaults to the global verbose value,
accessible via langchain.globals.get_verbose().
__call__(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False, callbacks: Opt... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.react.base.ReActChain.html |
ace7ce8b66bf-3 | 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 runs ainvoke in parallel ... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.react.base.ReActChain.html |
ace7ce8b66bf-4 | 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... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.react.base.ReActChain.html |
ace7ce8b66bf-5 | 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, ... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.react.base.ReActChain.html |
ace7ce8b66bf-6 | Stream all output from a runnable, as reported to the callback system.
This includes all inner runs of LLMs, Retrievers, Tools, etc.
Output is streamed as Log objects, which include a list of
jsonpatch ops that describe how the state of the run has changed in each
step, and the final state of the run.
The jsonpatch ops... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.react.base.ReActChain.html |
ace7ce8b66bf-7 | Returns
A pydantic model that can be used to validate config.
configurable_alternatives(which: ConfigurableField, default_key: str = 'default', **kwargs: Union[Runnable[Input, Output], Callable[[], Runnable[Input, Output]]]) → RunnableSerializable[Input, Output]¶
configurable_fields(**kwargs: Union[ConfigurableField, C... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.react.base.ReActChain.html |
ace7ce8b66bf-8 | method.
Returns
A dictionary representation of the chain.
Example
chain.dict(exclude_unset=True)
# -> {"_type": "foo", "verbose": False, ...}
classmethod from_agent_and_tools(agent: Union[BaseSingleActionAgent, BaseMultiActionAgent], tools: Sequence[BaseTool], callbacks: Optional[Union[List[BaseCallbackHandler], BaseCa... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.react.base.ReActChain.html |
ace7ce8b66bf-9 | Parameters
config – A config to use when generating the schema.
Returns
A pydantic model that can be used to validate output.
invoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None, **kwargs: Any) → Dict[str, Any]¶
Transform a single input into an output. Override to implement.
Parameters
input – The inp... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.react.base.ReActChain.html |
ace7ce8b66bf-10 | A unique identifier for this class for serialization purposes.
The unique identifier is a list of strings that describes the path
to the object.
lookup_tool(name: str) → BaseTool¶
Lookup tool by name.
map() → Runnable[List[Input], List[Output]]¶
Return a new Runnable that maps a list of inputs to a list of outputs,
by ... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.react.base.ReActChain.html |
ace7ce8b66bf-11 | Returns
A dict of the final chain outputs.
run(*args: Any, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → Any¶
Convenience method for executing chain.
The main difference between this method... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.react.base.ReActChain.html |
ace7ce8b66bf-12 | save(file_path: Union[Path, str]) → None¶
Raise error - saving not supported for Agent Executors.
save_agent(file_path: Union[Path, str]) → None¶
Save the underlying agent.
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool ... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.react.base.ReActChain.html |
ace7ce8b66bf-13 | Add fallbacks to a runnable, returning a new Runnable.
Parameters
fallbacks – A sequence of runnables to try if the original runnable fails.
exceptions_to_handle – A tuple of exception types to handle.
Returns
A new Runnable that will try the original runnable, and then each
fallback in order, upon failures.
with_liste... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.react.base.ReActChain.html |
ace7ce8b66bf-14 | Bind input and output types to a Runnable, returning a new Runnable.
property InputType: Type[langchain.schema.runnable.utils.Input]¶
The type of input this runnable accepts specified as a type annotation.
property OutputType: Type[langchain.schema.runnable.utils.Output]¶
The type of output this runnable produces speci... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.react.base.ReActChain.html |
cd74e287046f-0 | langchain.agents.loading.load_agent_from_config¶
langchain.agents.loading.load_agent_from_config(config: dict, llm: Optional[BaseLanguageModel] = None, tools: Optional[List[Tool]] = None, **kwargs: Any) → Union[BaseSingleActionAgent, BaseMultiActionAgent][source]¶
Load agent from Config Dict.
Parameters
config – Config... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.loading.load_agent_from_config.html |
ed7a7a610d24-0 | langchain.agents.conversational.base.ConversationalAgent¶
class langchain.agents.conversational.base.ConversationalAgent[source]¶
Bases: Agent
An agent that holds a conversation in addition to using tools.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the inpu... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.conversational.base.ConversationalAgent.html |
ed7a7a610d24-1 | Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creat... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.conversational.base.ConversationalAgent.html |
ed7a7a610d24-2 | classmethod create_prompt(tools: Sequence[BaseTool], prefix: str = 'Assistant is a large language model trained by OpenAI.\n\nAssistant is designed to be able to assist with a wide range of tasks, from answering simple questions to providing in-depth explanations and discussions on a wide range of topics. As a language... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.conversational.base.ConversationalAgent.html |
ed7a7a610d24-3 | say to the Human, or if you do not need to use a tool, you MUST use the format:\n\n```\nThought: Do I need to use a tool? No\n{ai_prefix}: [your response here]\n```', ai_prefix: str = 'AI', human_prefix: str = 'Human', input_variables: Optional[List[str]] = None) → PromptTemplate[source]¶ | lang/api.python.langchain.com/en/latest/agents/langchain.agents.conversational.base.ConversationalAgent.html |
ed7a7a610d24-4 | Create prompt in the style of the zero-shot agent.
Parameters
tools – List of tools the agent will have access to, used to format the
prompt.
prefix – String to put before the list of tools.
suffix – String to put after the list of tools.
ai_prefix – String to use before AI output.
human_prefix – String to use before h... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.conversational.base.ConversationalAgent.html |
ed7a7a610d24-5 | classmethod from_llm_and_tools(llm: BaseLanguageModel, tools: Sequence[BaseTool], callback_manager: Optional[BaseCallbackManager] = None, output_parser: Optional[AgentOutputParser] = None, prefix: str = 'Assistant is a large language model trained by OpenAI.\n\nAssistant is designed to be able to assist with a wide ran... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.conversational.base.ConversationalAgent.html |
ed7a7a610d24-6 | Input: the input to the action\nObservation: the result of the action\n```\n\nWhen you have a response to say to the Human, or if you do not need to use a tool, you MUST use the format:\n\n```\nThought: Do I need to use a tool? No\n{ai_prefix}: [your response here]\n```', ai_prefix: str = 'AI', human_prefix: str = 'Hum... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.conversational.base.ConversationalAgent.html |
ed7a7a610d24-7 | Construct an agent from an LLM and tools.
classmethod from_orm(obj: Any) → Model¶
get_allowed_tools() → Optional[List[str]]¶
get_full_inputs(intermediate_steps: List[Tuple[AgentAction, str]], **kwargs: Any) → Dict[str, Any]¶
Create the full inputs for the LLMChain from intermediate steps.
json(*, include: Optional[Unio... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.conversational.base.ConversationalAgent.html |
ed7a7a610d24-8 | Parameters
intermediate_steps – Steps the LLM has taken to date,
along with observations
callbacks – Callbacks to run.
**kwargs – User inputs.
Returns
Action specifying what tool to use.
return_stopped_response(early_stopping_method: str, intermediate_steps: List[Tuple[AgentAction, str]], **kwargs: Any) → AgentFinish¶
... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.conversational.base.ConversationalAgent.html |
c1537e294c64-0 | langchain.agents.format_scratchpad.log_to_messages.format_log_to_messages¶
langchain.agents.format_scratchpad.log_to_messages.format_log_to_messages(intermediate_steps: List[Tuple[AgentAction, str]], template_tool_response: str = '{observation}') → List[BaseMessage][source]¶
Construct the scratchpad that lets the agent... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.format_scratchpad.log_to_messages.format_log_to_messages.html |
ee82e16ebdb0-0 | langchain.agents.agent.RunnableAgent¶
class langchain.agents.agent.RunnableAgent[source]¶
Bases: BaseSingleActionAgent
Agent powered by runnables.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param runnab... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent.RunnableAgent.html |
ee82e16ebdb0-1 | Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep – set to True to make a deep co... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent.RunnableAgent.html |
ee82e16ebdb0-2 | 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¶
plan(intermediate_steps: List[Tuple[AgentAction, str]], callbacks: Optional[Union[List[BaseCallbackHandler], Base... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent.RunnableAgent.html |
ee82e16ebdb0-3 | property input_keys: List[str]¶
Return the input keys.
Returns
List of input keys.
property return_values: List[str]¶
Return values of the agent. | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent.RunnableAgent.html |
b99c98e51a5b-0 | langchain.agents.agent_toolkits.gmail.toolkit.GmailToolkit¶
class langchain.agents.agent_toolkits.gmail.toolkit.GmailToolkit[source]¶
Bases: BaseToolkit
Toolkit for interacting with Gmail.
Security Note: This toolkit contains tools that can read and modifythe state of a service; e.g., by reading, creating, updating, de... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.gmail.toolkit.GmailToolkit.html |
b99c98e51a5b-1 | deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, ex... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.gmail.toolkit.GmailToolkit.html |
b99c98e51a5b-2 | classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmet... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.gmail.toolkit.GmailToolkit.html |
1214e23a0687-0 | langchain.agents.agent_toolkits.openapi.spec.reduce_openapi_spec¶
langchain.agents.agent_toolkits.openapi.spec.reduce_openapi_spec(spec: dict, dereference: bool = True) → ReducedOpenAPISpec[source]¶
Simplify/distill/minify a spec somehow.
I want a smaller target for retrieval and (more importantly)
I want smaller resul... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.openapi.spec.reduce_openapi_spec.html |
a5c16fdcf8dd-0 | langchain.agents.agent_toolkits.base.BaseToolkit¶
class langchain.agents.agent_toolkits.base.BaseToolkit[source]¶
Bases: BaseModel, ABC
Base Toolkit representing a collection of related tools.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.base.BaseToolkit.html |
a5c16fdcf8dd-1 | Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
classmethod from_orm(obj: Any) → Model¶
abstract get_tools() → List[BaseTool][source]¶
Get the tools in the toolkit.
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optiona... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.base.BaseToolkit.html |
a5c16fdcf8dd-2 | Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate(value: Any) → Model¶ | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.base.BaseToolkit.html |
acebb795810e-0 | langchain.agents.agent_iterator.rebuild_callback_manager_on_set¶
langchain.agents.agent_iterator.rebuild_callback_manager_on_set(setter_method: Callable[[...], None]) → Callable[[...], None][source]¶
Decorator to force setters to rebuild callback mgr | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_iterator.rebuild_callback_manager_on_set.html |
2c8d4fc63d80-0 | langchain.agents.agent_toolkits.playwright.toolkit.PlayWrightBrowserToolkit¶
class langchain.agents.agent_toolkits.playwright.toolkit.PlayWrightBrowserToolkit[source]¶
Bases: BaseToolkit
Toolkit for PlayWright browser tools.
Security Note: This toolkit provides code to control a web-browser.
Careful if exposing this to... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.playwright.toolkit.PlayWrightBrowserToolkit.html |
2c8d4fc63d80-1 | Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.playwright.toolkit.PlayWrightBrowserToolkit.html |
2c8d4fc63d80-2 | Get the tools in the toolkit.
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_defaults: bool = False, exclude_none: bool ... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.playwright.toolkit.PlayWrightBrowserToolkit.html |
a0be5d393eb2-0 | langchain.agents.format_scratchpad.openai_functions.format_to_openai_function_messages¶
langchain.agents.format_scratchpad.openai_functions.format_to_openai_function_messages(intermediate_steps: Sequence[Tuple[AgentAction, str]]) → List[BaseMessage][source]¶
Convert (AgentAction, tool output) tuples into FunctionMessag... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.format_scratchpad.openai_functions.format_to_openai_function_messages.html |
95de9e9c498d-0 | langchain.agents.agent.ExceptionTool¶
class langchain.agents.agent.ExceptionTool[source]¶
Bases: BaseTool
Tool that just returns the 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.
param args_schema: ... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent.ExceptionTool.html |
95de9e9c498d-1 | param verbose: bool = False¶
Whether to log the tool’s progress.
__call__(tool_input: str, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None) → str¶
Make tool callable.
async abatch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_excep... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent.ExceptionTool.html |
95de9e9c498d-2 | Subclasses should override this method if they support streaming output.
async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, diff: bool = True, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names:... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent.ExceptionTool.html |
95de9e9c498d-3 | e.g., if the underlying runnable uses an API which supports a batch mode.
bind(**kwargs: Any) → Runnable[Input, Output]¶
Bind arguments to a Runnable, returning a new Runnable.
config_schema(*, include: Optional[Sequence[str]] = None) → Type[BaseModel]¶
The type of config this runnable accepts specified as a pydantic m... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent.ExceptionTool.html |
95de9e9c498d-4 | exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, i... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent.ExceptionTool.html |
95de9e9c498d-5 | Returns
A pydantic model that can be used to validate output.
invoke(input: Union[str, Dict], config: Optional[RunnableConfig] = None, **kwargs: Any) → Any¶
Transform a single input into an output. Override to implement.
Parameters
input – The input to the runnable.
config – A config to use when invoking the runnable.
... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent.ExceptionTool.html |
95de9e9c498d-6 | by calling invoke() with each input.
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = No... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent.ExceptionTool.html |
95de9e9c498d-7 | 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... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent.ExceptionTool.html |
95de9e9c498d-8 | added to the run.
with_retry(*, retry_if_exception_type: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,), wait_exponential_jitter: bool = True, stop_after_attempt: int = 3) → Runnable[Input, Output]¶
Create a new Runnable that retries the original runnable on exceptions.
Parameters
retry_if_exc... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent.ExceptionTool.html |
95de9e9c498d-9 | A map of constructor argument names to secret ids.
For example,{“openai_api_key”: “OPENAI_API_KEY”}
property output_schema: Type[pydantic.main.BaseModel]¶
The type of output this runnable produces specified as a pydantic model. | lang/api.python.langchain.com/en/latest/agents/langchain.agents.agent.ExceptionTool.html |
183b16db1561-0 | langchain.agents.self_ask_with_search.base.SelfAskWithSearchChain¶
class langchain.agents.self_ask_with_search.base.SelfAskWithSearchChain[source]¶
Bases: AgentExecutor
[Deprecated] Chain that does self-ask with search.
Initialize only with an LLM and a search chain.
param agent: Union[BaseSingleActionAgent, BaseMultiA... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchChain.html |
183b16db1561-1 | If a callable function, the function will be called with the exception
as an argument, and the result of that function will be passed to the agentas an observation.
param max_execution_time: Optional[float] = None¶
The maximum amount of wall clock time to spend in the execution
loop.
param max_iterations: Optional[int]... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchChain.html |
183b16db1561-2 | The valid tools the agent can call.
param trim_intermediate_steps: Union[int, Callable[[List[Tuple[AgentAction, str]]], List[Tuple[AgentAction, str]]]] = -1¶
param verbose: bool [Optional]¶
Whether or not run in verbose mode. In verbose mode, some intermediate logs
will be printed to the console. Defaults to the global... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchChain.html |
183b16db1561-3 | include_run_info – Whether to include run info in the response. Defaults
to False.
Returns
A dict of named outputs. Should contain all outputs specified inChain.output_keys.
async abatch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwar... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchChain.html |
183b16db1561-4 | tags – List of string tags to pass to all callbacks. These will be passed in
addition to tags passed to the chain during construction, but only
these runtime tags will propagate to calls to other objects.
metadata – Optional metadata associated with the chain. Defaults to None
include_run_info – Whether to include run ... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchChain.html |
183b16db1561-5 | addition to callbacks passed to the chain during construction, but only
these runtime callbacks will propagate to calls to other objects.
tags – List of string tags to pass to all callbacks. These will be passed in
addition to tags passed to the chain during construction, but only
these runtime tags will propagate to c... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchChain.html |
183b16db1561-6 | Stream all output from a runnable, as reported to the callback system.
This includes all inner runs of LLMs, Retrievers, Tools, etc.
Output is streamed as Log objects, which include a list of
jsonpatch ops that describe how the state of the run has changed in each
step, and the final state of the run.
The jsonpatch ops... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchChain.html |
183b16db1561-7 | Returns
A pydantic model that can be used to validate config.
configurable_alternatives(which: ConfigurableField, default_key: str = 'default', **kwargs: Union[Runnable[Input, Output], Callable[[], Runnable[Input, Output]]]) → RunnableSerializable[Input, Output]¶
configurable_fields(**kwargs: Union[ConfigurableField, C... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchChain.html |
183b16db1561-8 | method.
Returns
A dictionary representation of the chain.
Example
chain.dict(exclude_unset=True)
# -> {"_type": "foo", "verbose": False, ...}
classmethod from_agent_and_tools(agent: Union[BaseSingleActionAgent, BaseMultiActionAgent], tools: Sequence[BaseTool], callbacks: Optional[Union[List[BaseCallbackHandler], BaseCa... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchChain.html |
183b16db1561-9 | Parameters
config – A config to use when generating the schema.
Returns
A pydantic model that can be used to validate output.
invoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None, **kwargs: Any) → Dict[str, Any]¶
Transform a single input into an output. Override to implement.
Parameters
input – The inp... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchChain.html |
183b16db1561-10 | A unique identifier for this class for serialization purposes.
The unique identifier is a list of strings that describes the path
to the object.
lookup_tool(name: str) → BaseTool¶
Lookup tool by name.
map() → Runnable[List[Input], List[Output]]¶
Return a new Runnable that maps a list of inputs to a list of outputs,
by ... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchChain.html |
183b16db1561-11 | Returns
A dict of the final chain outputs.
run(*args: Any, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → Any¶
Convenience method for executing chain.
The main difference between this method... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchChain.html |
183b16db1561-12 | save(file_path: Union[Path, str]) → None¶
Raise error - saving not supported for Agent Executors.
save_agent(file_path: Union[Path, str]) → None¶
Save the underlying agent.
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool ... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchChain.html |
183b16db1561-13 | Add fallbacks to a runnable, returning a new Runnable.
Parameters
fallbacks – A sequence of runnables to try if the original runnable fails.
exceptions_to_handle – A tuple of exception types to handle.
Returns
A new Runnable that will try the original runnable, and then each
fallback in order, upon failures.
with_liste... | lang/api.python.langchain.com/en/latest/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchChain.html |
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