id stringlengths 14 15 | text stringlengths 44 2.47k | source stringlengths 61 181 |
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7a947c6d9114-10 | 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/agents/langchain.agents.react.base.ReActChain.html |
7a947c6d9114-11 | 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/agents/langchain.agents.react.base.ReActChain.html |
39c6b575ef83-0 | langchain.agents.agent_toolkits.spark_sql.base.create_spark_sql_agent¶ | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.spark_sql.base.create_spark_sql_agent.html |
39c6b575ef83-1 | langchain.agents.agent_toolkits.spark_sql.base.create_spark_sql_agent(llm: BaseLanguageModel, toolkit: SparkSQLToolkit, callback_manager: Optional[BaseCallbackManager] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, prefix: str = 'You are an agent designed to interact with Spa... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.spark_sql.base.create_spark_sql_agent.html |
39c6b575ef83-2 | Input: the input to the action\nObservation: the result of the action\n... (this Thought/Action/Action Input/Observation can repeat N times)\nThought: I now know the final answer\nFinal Answer: the final answer to the original input question', input_variables: Optional[List[str]] = None, top_k: int = 10, max_iterations... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.spark_sql.base.create_spark_sql_agent.html |
39c6b575ef83-3 | Construct a Spark SQL agent from an LLM and tools.
Examples using create_spark_sql_agent¶
Spark SQL | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.spark_sql.base.create_spark_sql_agent.html |
c20e7bdcbce3-0 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.openapi.spec.reduce_openapi_spec.html |
7c761d819517-0 | langchain.agents.agent_toolkits.nla.toolkit.NLAToolkit¶
class langchain.agents.agent_toolkits.nla.toolkit.NLAToolkit[source]¶
Bases: BaseToolkit
Natural Language API Toolkit.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.nla.toolkit.NLAToolkit.html |
7c761d819517-1 | 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/agents/langchain.agents.agent_toolkits.nla.toolkit.NLAToolkit.html |
7c761d819517-2 | Get the tools for all the API operations.
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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.nla.toolkit.NLAToolkit.html |
b33d391963c8-0 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational.base.ConversationalAgent.html |
b33d391963c8-1 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational.base.ConversationalAgent.html |
b33d391963c8-2 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational.base.ConversationalAgent.html |
b33d391963c8-3 | 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]¶ | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational.base.ConversationalAgent.html |
b33d391963c8-4 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational.base.ConversationalAgent.html |
b33d391963c8-5 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational.base.ConversationalAgent.html |
b33d391963c8-6 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational.base.ConversationalAgent.html |
b33d391963c8-7 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational.base.ConversationalAgent.html |
b33d391963c8-8 | 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¶
... | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational.base.ConversationalAgent.html |
c7dcd30d6c73-0 | 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: ... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent.ExceptionTool.html |
c7dcd30d6c73-1 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent.ExceptionTool.html |
c7dcd30d6c73-2 | 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/agents/langchain.agents.agent.ExceptionTool.html |
c7dcd30d6c73-3 | 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/agents/langchain.agents.agent.ExceptionTool.html |
c7dcd30d6c73-4 | 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 = False, encoder: Optional[Cal... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent.ExceptionTool.html |
c7dcd30d6c73-5 | Run the tool.
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
stream(input: Input, config: Optional[RunnableConfig] = None, **kwargs... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent.ExceptionTool.html |
c7dcd30d6c73-6 | property InputType: Type[langchain.schema.runnable.utils.Input]¶
property OutputType: Type[langchain.schema.runnable.utils.Output]¶
property args: dict¶
property input_schema: Type[pydantic.main.BaseModel]¶
The tool’s input schema.
property is_single_input: bool¶
Whether the tool only accepts a single input.
property o... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent.ExceptionTool.html |
c2438d10bc12-0 | langchain.agents.agent_toolkits.sql.base.create_sql_agent¶ | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.sql.base.create_sql_agent.html |
c2438d10bc12-1 | langchain.agents.agent_toolkits.sql.base.create_sql_agent(llm: BaseLanguageModel, toolkit: SQLDatabaseToolkit, agent_type: AgentType = AgentType.ZERO_SHOT_REACT_DESCRIPTION, callback_manager: Optional[BaseCallbackManager] = None, prefix: str = 'You are an agent designed to interact with a SQL database.\nGiven an input ... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.sql.base.create_sql_agent.html |
c2438d10bc12-2 | I now know the final answer\nFinal Answer: the final answer to the original input question', input_variables: Optional[List[str]] = None, top_k: int = 10, max_iterations: Optional[int] = 15, max_execution_time: Optional[float] = None, early_stopping_method: str = 'force', verbose: bool = False, agent_executor_kwargs: O... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.sql.base.create_sql_agent.html |
c2438d10bc12-3 | Construct an SQL agent from an LLM and tools.
Examples using create_sql_agent¶
CnosDB
SQL Database
Set env var OPENAI_API_KEY or load from a .env file
SQL | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.sql.base.create_sql_agent.html |
ca3fa8448587-0 | langchain.agents.agent_toolkits.openapi.planner.create_openapi_agent¶
langchain.agents.agent_toolkits.openapi.planner.create_openapi_agent(api_spec: ReducedOpenAPISpec, requests_wrapper: TextRequestsWrapper, llm: BaseLanguageModel, shared_memory: Optional[ReadOnlySharedMemory] = None, callback_manager: Optional[BaseCal... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.openapi.planner.create_openapi_agent.html |
f1524b766eb4-0 | langchain.agents.structured_chat.base.StructuredChatAgent¶
class langchain.agents.structured_chat.base.StructuredChatAgent[source]¶
Bases: Agent
Structured Chat Agent.
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 vali... | https://api.python.langchain.com/en/latest/agents/langchain.agents.structured_chat.base.StructuredChatAgent.html |
f1524b766eb4-1 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.structured_chat.base.StructuredChatAgent.html |
f1524b766eb4-2 | deep – set to True to make a deep copy of the model
Returns
new model instance
classmethod create_prompt(tools: Sequence[BaseTool], prefix: str = 'Respond to the human as helpfully and accurately as possible. You have access to the following tools:', suffix: str = 'Begin! Reminder to ALWAYS respond with a valid json bl... | https://api.python.langchain.com/en/latest/agents/langchain.agents.structured_chat.base.StructuredChatAgent.html |
f1524b766eb4-3 | dict(**kwargs: Any) → Dict¶
Return dictionary representation of agent.
classmethod from_llm_and_tools(llm: BaseLanguageModel, tools: Sequence[BaseTool], callback_manager: Optional[BaseCallbackManager] = None, output_parser: Optional[AgentOutputParser] = None, prefix: str = 'Respond to the human as helpfully and accurat... | https://api.python.langchain.com/en/latest/agents/langchain.agents.structured_chat.base.StructuredChatAgent.html |
f1524b766eb4-4 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.structured_chat.base.StructuredChatAgent.html |
f1524b766eb4-5 | 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¶
... | https://api.python.langchain.com/en/latest/agents/langchain.agents.structured_chat.base.StructuredChatAgent.html |
adaa93b87cd8-0 | langchain.agents.agent_toolkits.python.base.create_python_agent¶
langchain.agents.agent_toolkits.python.base.create_python_agent(llm: BaseLanguageModel, tool: PythonREPLTool, agent_type: AgentType = AgentType.ZERO_SHOT_REACT_DESCRIPTION, callback_manager: Optional[BaseCallbackManager] = None, verbose: bool = False, pre... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.python.base.create_python_agent.html |
0fd02aefe4e6-0 | langchain.agents.chat.base.ChatAgent¶
class langchain.agents.chat.base.ChatAgent[source]¶
Bases: Agent
Chat Agent.
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 allowed_tools: Optional[List[str]] = N... | https://api.python.langchain.com/en/latest/agents/langchain.agents.chat.base.ChatAgent.html |
0fd02aefe4e6-1 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.chat.base.ChatAgent.html |
0fd02aefe4e6-2 | deep – set to True to make a deep copy of the model
Returns
new model instance
classmethod create_prompt(tools: Sequence[BaseTool], system_message_prefix: str = 'Answer the following questions as best you can. You have access to the following tools:', system_message_suffix: str = 'Begin! Reminder to always use the exac... | https://api.python.langchain.com/en/latest/agents/langchain.agents.chat.base.ChatAgent.html |
0fd02aefe4e6-3 | dict(**kwargs: Any) → Dict¶
Return dictionary representation of agent.
classmethod from_llm_and_tools(llm: BaseLanguageModel, tools: Sequence[BaseTool], callback_manager: Optional[BaseCallbackManager] = None, output_parser: Optional[AgentOutputParser] = None, system_message_prefix: str = 'Answer the following questions... | https://api.python.langchain.com/en/latest/agents/langchain.agents.chat.base.ChatAgent.html |
0fd02aefe4e6-4 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.chat.base.ChatAgent.html |
0fd02aefe4e6-5 | 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¶
... | https://api.python.langchain.com/en/latest/agents/langchain.agents.chat.base.ChatAgent.html |
19f7deebc63d-0 | langchain.agents.agent_toolkits.openapi.spec.ReducedOpenAPISpec¶
class langchain.agents.agent_toolkits.openapi.spec.ReducedOpenAPISpec(servers: List[dict], description: str, endpoints: List[Tuple[str, str, dict]])[source]¶
A reduced OpenAPI spec.
This is a quick and dirty representation for OpenAPI specs.
servers¶
The ... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.openapi.spec.ReducedOpenAPISpec.html |
e472a39608e0-0 | langchain.agents.loading.load_agent¶
langchain.agents.loading.load_agent(path: Union[str, Path], **kwargs: Any) → Union[BaseSingleActionAgent, BaseMultiActionAgent][source]¶
Unified method for loading an agent from LangChainHub or local fs.
Parameters
path – Path to the agent file.
**kwargs – Additional key word argume... | https://api.python.langchain.com/en/latest/agents/langchain.agents.loading.load_agent.html |
71105f501384-0 | langchain.agents.agent_iterator.BaseAgentExecutorIterator¶
class langchain.agents.agent_iterator.BaseAgentExecutorIterator[source]¶
Base class for AgentExecutorIterator.
Methods
__init__()
build_callback_manager()
__init__()¶
abstract build_callback_manager() → None[source]¶ | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_iterator.BaseAgentExecutorIterator.html |
cd7bdec84ed5-0 | langchain.agents.openai_functions_agent.agent_token_buffer_memory.AgentTokenBufferMemory¶
class langchain.agents.openai_functions_agent.agent_token_buffer_memory.AgentTokenBufferMemory[source]¶
Bases: BaseChatMemory
Memory used to save agent output AND intermediate steps.
Create a new model by parsing and validating in... | https://api.python.langchain.com/en/latest/agents/langchain.agents.openai_functions_agent.agent_token_buffer_memory.AgentTokenBufferMemory.html |
cd7bdec84ed5-1 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.openai_functions_agent.agent_token_buffer_memory.AgentTokenBufferMemory.html |
cd7bdec84ed5-2 | 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/agents/langchain.agents.openai_functions_agent.agent_token_buffer_memory.AgentTokenBufferMemory.html |
cd7bdec84ed5-3 | String buffer of memory.
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”}
... | https://api.python.langchain.com/en/latest/agents/langchain.agents.openai_functions_agent.agent_token_buffer_memory.AgentTokenBufferMemory.html |
074f4cd8beb0-0 | langchain.agents.react.output_parser.ReActOutputParser¶
class langchain.agents.react.output_parser.ReActOutputParser[source]¶
Bases: AgentOutputParser
Output parser for the ReAct agent.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be par... | https://api.python.langchain.com/en/latest/agents/langchain.agents.react.output_parser.ReActOutputParser.html |
074f4cd8beb0-1 | Default implementation of astream, which calls ainvoke.
Subclasses should override this method if they support streaming output.
async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[... | https://api.python.langchain.com/en/latest/agents/langchain.agents.react.output_parser.ReActOutputParser.html |
074f4cd8beb0-2 | 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__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config... | https://api.python.langchain.com/en/latest/agents/langchain.agents.react.output_parser.ReActOutputParser.html |
074f4cd8beb0-3 | 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/agents/langchain.agents.react.output_parser.ReActOutputParser.html |
074f4cd8beb0-4 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.react.output_parser.ReActOutputParser.html |
074f4cd8beb0-5 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.react.output_parser.ReActOutputParser.html |
0375b6e51e7f-0 | langchain.agents.conversational_chat.base.ConversationalChatAgent¶
class langchain.agents.conversational_chat.base.ConversationalChatAgent[source]¶
Bases: Agent
An agent designed to hold a conversation in addition to using tools.
Create a new model by parsing and validating input data from keyword arguments.
Raises Val... | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational_chat.base.ConversationalChatAgent.html |
0375b6e51e7f-1 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational_chat.base.ConversationalChatAgent.html |
0375b6e51e7f-2 | deep – set to True to make a deep copy of the model
Returns
new model instance
classmethod create_prompt(tools: Sequence[BaseTool], system_message: 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 p... | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational_chat.base.ConversationalChatAgent.html |
0375b6e51e7f-3 | Create a prompt for this class.
dict(**kwargs: Any) → Dict¶
Return dictionary representation of agent. | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational_chat.base.ConversationalChatAgent.html |
0375b6e51e7f-4 | classmethod from_llm_and_tools(llm: BaseLanguageModel, tools: Sequence[BaseTool], callback_manager: Optional[BaseCallbackManager] = None, output_parser: Optional[AgentOutputParser] = None, system_message: str = 'Assistant is a large language model trained by OpenAI.\n\nAssistant is designed to be able to assist with a ... | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational_chat.base.ConversationalChatAgent.html |
0375b6e51e7f-5 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational_chat.base.ConversationalChatAgent.html |
0375b6e51e7f-6 | 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¶
... | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational_chat.base.ConversationalChatAgent.html |
2e568774e36e-0 | langchain.agents.conversational.output_parser.ConvoOutputParser¶
class langchain.agents.conversational.output_parser.ConvoOutputParser[source]¶
Bases: AgentOutputParser
Output parser for the conversational agent.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if t... | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational.output_parser.ConvoOutputParser.html |
2e568774e36e-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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational.output_parser.ConvoOutputParser.html |
2e568774e36e-2 | Default implementation of batch, which calls invoke N times.
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) → Mode... | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational.output_parser.ConvoOutputParser.html |
2e568774e36e-3 | namespace is [“langchain”, “llms”, “openai”]
invoke(input: Union[str, BaseMessage], config: Optional[RunnableConfig] = None) → T¶
classmethod is_lc_serializable() → bool¶
Is this class serializable?
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, ... | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational.output_parser.ConvoOutputParser.html |
2e568774e36e-4 | 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¶
parse_result(result: List[Generation], *, partial: bool = False) → T¶
Parse a list of candidate model Generations... | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational.output_parser.ConvoOutputParser.html |
2e568774e36e-5 | to_json_not_implemented() → SerializedNotImplemented¶
transform(input: Iterator[Input], config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → Iterator[Output]¶
Default implementation of transform, which buffers input and then calls stream.
Subclasses should override this method if they can start producing... | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational.output_parser.ConvoOutputParser.html |
2e568774e36e-6 | For example,{“openai_api_key”: “OPENAI_API_KEY”}
property output_schema: Type[pydantic.main.BaseModel]¶ | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational.output_parser.ConvoOutputParser.html |
a8d9b23a98d2-0 | langchain.agents.agent_toolkits.json.toolkit.JsonToolkit¶
class langchain.agents.agent_toolkits.json.toolkit.JsonToolkit[source]¶
Bases: BaseToolkit
Toolkit for interacting with a JSON spec.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot b... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.json.toolkit.JsonToolkit.html |
a8d9b23a98d2-1 | 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/agents/langchain.agents.agent_toolkits.json.toolkit.JsonToolkit.html |
a8d9b23a98d2-2 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.json.toolkit.JsonToolkit.html |
19f00347e1bf-0 | langchain.agents.output_parsers.react_single_input.ReActSingleInputOutputParser¶
class langchain.agents.output_parsers.react_single_input.ReActSingleInputOutputParser[source]¶
Bases: AgentOutputParser
Parses ReAct-style LLM calls that have a single tool input.
Expects output to be in one of two formats.
If the output s... | https://api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.react_single_input.ReActSingleInputOutputParser.html |
19f00347e1bf-1 | Parameters
text – String output of a language model.
Returns
Structured output.
async aparse_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 ... | https://api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.react_single_input.ReActSingleInputOutputParser.html |
19f00347e1bf-2 | Default implementation of atransform, which buffers input and calls astream.
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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.react_single_input.ReActSingleInputOutputParser.html |
19f00347e1bf-3 | Return dictionary representation of output parser.
classmethod from_orm(obj: Any) → Model¶
get_format_instructions() → str[source]¶
Instructions on how the LLM output should be formatted.
classmethod get_lc_namespace() → List[str]¶
Get the namespace of the langchain object.
For example, if the class is langchain.llms.o... | https://api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.react_single_input.ReActSingleInputOutputParser.html |
19f00347e1bf-4 | Parse text into agent action/finish.
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/agents/langchain.agents.output_parsers.react_single_input.ReActSingleInputOutputParser.html |
19f00347e1bf-5 | 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/agents/langchain.agents.output_parsers.react_single_input.ReActSingleInputOutputParser.html |
19f00347e1bf-6 | 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: Type[pydantic.main.BaseModel]¶ | https://api.python.langchain.com/en/latest/agents/langchain.agents.output_parsers.react_single_input.ReActSingleInputOutputParser.html |
873bd7c3d3ce-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 | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_iterator.rebuild_callback_manager_on_set.html |
f62fb80c9072-0 | langchain.agents.format_scratchpad.log.format_log_to_str¶
langchain.agents.format_scratchpad.log.format_log_to_str(intermediate_steps: List[Tuple[AgentAction, str]], observation_prefix: str = 'Observation: ', llm_prefix: str = 'Thought: ') → str[source]¶
Construct the scratchpad that lets the agent continue its thought... | https://api.python.langchain.com/en/latest/agents/langchain.agents.format_scratchpad.log.format_log_to_str.html |
cef383f0a6c7-0 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchChain.html |
cef383f0a6c7-1 | 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]... | https://api.python.langchain.com/en/latest/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchChain.html |
cef383f0a6c7-2 | 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 langchain.... | https://api.python.langchain.com/en/latest/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchChain.html |
cef383f0a6c7-3 | 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/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchChain.html |
cef383f0a6c7-4 | 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/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchChain.html |
cef383f0a6c7-5 | 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:
await chain.arun("What's the temperature in Boise, I... | https://api.python.langchain.com/en/latest/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchChain.html |
cef383f0a6c7-6 | 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 implementation of atransform, which buffers input and calls astream.
Subcla... | https://api.python.langchain.com/en/latest/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchChain.html |
cef383f0a6c7-7 | 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(**kwargs: Any) → Dict¶
Dictionary representation of chain.
Expects Chain._chain_type property to be implemented and for memory to benull.
Parameters
**kwargs – Keyword arguments passed to defaul... | https://api.python.langchain.com/en/latest/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchChain.html |
cef383f0a6c7-8 | Enables iteration over steps taken to reach final output.
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 ... | https://api.python.langchain.com/en/latest/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchChain.html |
cef383f0a6c7-9 | Validate and prepare chain inputs, including adding inputs from memory.
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, inc... | https://api.python.langchain.com/en/latest/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchChain.html |
cef383f0a6c7-10 | 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/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchChain.html |
cef383f0a6c7-11 | 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/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchChain.html |
aabc91ab499f-0 | langchain.agents.agent_toolkits.vectorstore.toolkit.VectorStoreInfo¶
class langchain.agents.agent_toolkits.vectorstore.toolkit.VectorStoreInfo[source]¶
Bases: BaseModel
Information about a VectorStore.
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/agents/langchain.agents.agent_toolkits.vectorstore.toolkit.VectorStoreInfo.html |
aabc91ab499f-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/agents/langchain.agents.agent_toolkits.vectorstore.toolkit.VectorStoreInfo.html |
aabc91ab499f-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/agents/langchain.agents.agent_toolkits.vectorstore.toolkit.VectorStoreInfo.html |
9352da846865-0 | langchain.agents.self_ask_with_search.base.SelfAskWithSearchAgent¶
class langchain.agents.self_ask_with_search.base.SelfAskWithSearchAgent[source]¶
Bases: Agent
Agent for the self-ask-with-search paper.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input d... | https://api.python.langchain.com/en/latest/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchAgent.html |
9352da846865-1 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.self_ask_with_search.base.SelfAskWithSearchAgent.html |
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