id stringlengths 14 15 | text stringlengths 49 2.47k | source stringlengths 61 166 |
|---|---|---|
9c01371aed57-3 | **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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.openai_functions_agent.base.OpenAIFunctionsAgent.html |
6a17435c0aad-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 |
57ddeb916dfc-0 | langchain.agents.agent_toolkits.openapi.toolkit.OpenAPIToolkit¶
class langchain.agents.agent_toolkits.openapi.toolkit.OpenAPIToolkit[source]¶
Bases: BaseToolkit
Toolkit for interacting with an OpenAPI API.
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.agent_toolkits.openapi.toolkit.OpenAPIToolkit.html |
57ddeb916dfc-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.openapi.toolkit.OpenAPIToolkit.html |
57ddeb916dfc-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.openapi.toolkit.OpenAPIToolkit.html |
3548dbfe0bdd-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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.vectorstore.base.create_vectorstore_router_agent.html |
b0097833a41d-0 | langchain.agents.react.base.ReActTextWorldAgent¶
class langchain.agents.react.base.ReActTextWorldAgent[source]¶
Bases: ReActDocstoreAgent
Agent for the ReAct TextWorld chain.
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.react.base.ReActTextWorldAgent.html |
b0097833a41d-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.react.base.ReActTextWorldAgent.html |
b0097833a41d-2 | classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto... | https://api.python.langchain.com/en/latest/agents/langchain.agents.react.base.ReActTextWorldAgent.html |
b0097833a41d-3 | 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¶
property llm_prefix: str¶
Prefix to append the LLM call with.
property observation_prefix: str¶
Prefix to append the observation with.
property... | https://api.python.langchain.com/en/latest/agents/langchain.agents.react.base.ReActTextWorldAgent.html |
746a72040927-0 | langchain.agents.agent_toolkits.conversational_retrieval.openai_functions.create_conversational_retrieval_agent¶
langchain.agents.agent_toolkits.conversational_retrieval.openai_functions.create_conversational_retrieval_agent(llm: BaseLanguageModel, tools: List[BaseTool], remember_intermediate_steps: bool = True, memory... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.conversational_retrieval.openai_functions.create_conversational_retrieval_agent.html |
d35e61b4c17e-0 | langchain.agents.agent_toolkits.jira.toolkit.JiraToolkit¶
class langchain.agents.agent_toolkits.jira.toolkit.JiraToolkit[source]¶
Bases: BaseToolkit
Jira 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 a valid mod... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.jira.toolkit.JiraToolkit.html |
d35e61b4c17e-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.jira.toolkit.JiraToolkit.html |
d35e61b4c17e-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.jira.toolkit.JiraToolkit.html |
b7827ec4dcc2-0 | langchain.agents.agent_toolkits.csv.base.create_csv_agent¶
langchain.agents.agent_toolkits.csv.base.create_csv_agent(llm: BaseLanguageModel, path: Union[str, List[str]], pandas_kwargs: Optional[dict] = None, **kwargs: Any) → AgentExecutor[source]¶
Create csv agent by loading to a dataframe and using pandas agent.
Examp... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.csv.base.create_csv_agent.html |
15b635aca409-0 | langchain.agents.load_tools.get_all_tool_names¶
langchain.agents.load_tools.get_all_tool_names() → List[str][source]¶
Get a list of all possible tool names. | https://api.python.langchain.com/en/latest/agents/langchain.agents.load_tools.get_all_tool_names.html |
749ac61ebc77-0 | langchain.agents.openai_functions_multi_agent.base.OpenAIMultiFunctionsAgent¶
class langchain.agents.openai_functions_multi_agent.base.OpenAIMultiFunctionsAgent[source]¶
Bases: BaseMultiActionAgent
An Agent driven by OpenAIs function powered API.
Parameters
llm – This should be an instance of ChatOpenAI, specifically a... | https://api.python.langchain.com/en/latest/agents/langchain.agents.openai_functions_multi_agent.base.OpenAIMultiFunctionsAgent.html |
749ac61ebc77-1 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.openai_functions_multi_agent.base.OpenAIMultiFunctionsAgent.html |
749ac61ebc77-2 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.openai_functions_multi_agent.base.OpenAIMultiFunctionsAgent.html |
749ac61ebc77-3 | **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¶
Return response when agent has been stopped due to max iterations.
save(file_path: Union[Path, str]) → None¶
Save the a... | https://api.python.langchain.com/en/latest/agents/langchain.agents.openai_functions_multi_agent.base.OpenAIMultiFunctionsAgent.html |
8d8ad252f0e4-0 | 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 |
8d8ad252f0e4-1 | 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 |
8d8ad252f0e4-2 | 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 |
7561ed76a370-0 | langchain.agents.conversational_chat.output_parser.ConvoOutputParser¶
class langchain.agents.conversational_chat.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 Validation... | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational_chat.output_parser.ConvoOutputParser.html |
7561ed76a370-1 | 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.conversational_chat.output_parser.ConvoOutputParser.html |
7561ed76a370-2 | 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.conversational_chat.output_parser.ConvoOutputParser.html |
7561ed76a370-3 | Structured output.
parse_with_prompt(completion: str, prompt: PromptValue) → Any¶
Parse the output of an LLM call with the input prompt for context.
The prompt is largely provided in the event the OutputParser wants
to retry or fix the output in some way, and needs information from
the prompt to do so.
Parameters
compl... | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational_chat.output_parser.ConvoOutputParser.html |
7561ed76a370-4 | eg. [“langchain”, “llms”, “openai”]
property lc_secrets: Dict[str, str]¶
Return a map of constructor argument names to secret ids.
eg. {“openai_api_key”: “OPENAI_API_KEY”}
property lc_serializable: bool¶
Return whether or not the class is serializable. | https://api.python.langchain.com/en/latest/agents/langchain.agents.conversational_chat.output_parser.ConvoOutputParser.html |
2ac0260fdec4-0 | 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 |
c974e6a35dc1-0 | langchain.agents.agent_toolkits.github.toolkit.GitHubToolkit¶
class langchain.agents.agent_toolkits.github.toolkit.GitHubToolkit[source]¶
Bases: BaseToolkit
GitHub 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 a... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.github.toolkit.GitHubToolkit.html |
c974e6a35dc1-1 | 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.github.toolkit.GitHubToolkit.html |
c974e6a35dc1-2 | 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.github.toolkit.GitHubToolkit.html |
22f34c3931b8-0 | 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 |
22f34c3931b8-1 | 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 |
22f34c3931b8-2 | 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 |
22f34c3931b8-3 | 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 |
22f34c3931b8-4 | 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 |
22f34c3931b8-5 | 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 |
22f34c3931b8-6 | 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 |
22f34c3931b8-7 | 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 |
22f34c3931b8-8 | 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 |
2c32c956ec9f-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 |
b6850590bfdb-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 |
118d989421e3-0 | langchain.agents.schema.AgentScratchPadChatPromptTemplate¶
class langchain.agents.schema.AgentScratchPadChatPromptTemplate[source]¶
Bases: ChatPromptTemplate
Chat prompt template for the agent scratchpad.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input... | https://api.python.langchain.com/en/latest/agents/langchain.agents.schema.AgentScratchPadChatPromptTemplate.html |
118d989421e3-1 | 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.schema.AgentScratchPadChatPromptTemplate.html |
118d989421e3-2 | Create a chat prompt template from a variety of message formats.
Examples
Instantiation from a list of message templates:
template = ChatPromptTemplate.from_messages([
("human", "Hello, how are you?"),
("ai", "I'm doing well, thanks!"),
("human", "That's good to hear."),
])
Instantiation from mixed message ... | https://api.python.langchain.com/en/latest/agents/langchain.agents.schema.AgentScratchPadChatPromptTemplate.html |
118d989421e3-3 | Create a chat prompt template from a template string.
Creates a chat template consisting of a single message assumed to be from
the human.
Parameters
template – template string
**kwargs – keyword arguments to pass to the constructor.
Returns
A new instance of this class.
invoke(input: Dict, config: langchain.schema.run... | https://api.python.langchain.com/en/latest/agents/langchain.agents.schema.AgentScratchPadChatPromptTemplate.html |
118d989421e3-4 | to be a subset of the input variables.
Returns
A new ChatPromptTemplate.
Example
from langchain.prompts import ChatPromptTemplate
template = ChatPromptTemplate.from_messages(
[
("system", "You are an AI assistant named {name}."),
("human", "Hi I'm {user}"),
("ai", "Hi there, {user}, I'm {nam... | https://api.python.langchain.com/en/latest/agents/langchain.agents.schema.AgentScratchPadChatPromptTemplate.html |
118d989421e3-5 | property lc_attributes: Dict¶
Return a list of attribute names that should be included in the
serialized kwargs. These attributes must be accepted by the
constructor.
property lc_namespace: List[str]¶
Return the namespace of the langchain object.
eg. [“langchain”, “llms”, “openai”]
property lc_secrets: Dict[str, str]¶
... | https://api.python.langchain.com/en/latest/agents/langchain.agents.schema.AgentScratchPadChatPromptTemplate.html |
51e941348e23-0 | langchain.agents.agent.LLMSingleActionAgent¶
class langchain.agents.agent.LLMSingleActionAgent[source]¶
Bases: BaseSingleActionAgent
Base class for single action agents.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a va... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent.LLMSingleActionAgent.html |
51e941348e23-1 | 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.agent.LLMSingleActionAgent.html |
51e941348e23-2 | 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent.LLMSingleActionAgent.html |
51e941348e23-3 | property input_keys: List[str]¶
Return the input keys.
Returns
List of input keys.
property return_values: List[str]¶
Return values of the agent.
Examples using LLMSingleActionAgent¶
Plug-and-Plai
Wikibase Agent
SalesGPT - Your Context-Aware AI Sales Assistant With Knowledge Base
Custom Agent with PlugIn Retrieval
Cust... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent.LLMSingleActionAgent.html |
2f0c2b287ecf-0 | langchain.agents.agent_toolkits.sql.toolkit.SQLDatabaseToolkit¶
class langchain.agents.agent_toolkits.sql.toolkit.SQLDatabaseToolkit[source]¶
Bases: BaseToolkit
Toolkit for interacting with SQL databases.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.sql.toolkit.SQLDatabaseToolkit.html |
2f0c2b287ecf-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.sql.toolkit.SQLDatabaseToolkit.html |
2f0c2b287ecf-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.sql.toolkit.SQLDatabaseToolkit.html |
0657240ea066-0 | langchain.agents.agent_toolkits.spark.base.create_spark_dataframe_agent¶
langchain.agents.agent_toolkits.spark.base.create_spark_dataframe_agent(llm: BaseLLM, df: Any, callback_manager: Optional[BaseCallbackManager] = None, prefix: str = '\nYou are working with a spark dataframe in Python. The name of the dataframe is ... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.spark.base.create_spark_dataframe_agent.html |
1ae87c7263f4-0 | langchain.agents.tools.InvalidTool¶
class langchain.agents.tools.InvalidTool[source]¶
Bases: BaseTool
Tool that is run when invalid tool name is encountered by 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... | https://api.python.langchain.com/en/latest/agents/langchain.agents.tools.InvalidTool.html |
1ae87c7263f4-1 | These tags will be associated with each call to this tool,
and passed as arguments to the handlers defined in callbacks.
You can use these to eg identify a specific instance of a tool with its use case.
param verbose: bool = False¶
Whether to log the tool’s progress.
__call__(tool_input: str, callbacks: Optional[Union[... | https://api.python.langchain.com/en/latest/agents/langchain.agents.tools.InvalidTool.html |
1ae87c7263f4-2 | 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.tools.InvalidTool.html |
1ae87c7263f4-3 | 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.tools.InvalidTool.html |
1ae87c7263f4-4 | stream(input: Input, config: Optional[RunnableConfig] = None) → Iterator[Output]¶
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_fallbacks(fallbacks: ~typing.Sequence[~langchain.schema.... | https://api.python.langchain.com/en/latest/agents/langchain.agents.tools.InvalidTool.html |
978375457ba6-0 | langchain.agents.agent_toolkits.spark_sql.toolkit.SparkSQLToolkit¶
class langchain.agents.agent_toolkits.spark_sql.toolkit.SparkSQLToolkit[source]¶
Bases: BaseToolkit
Toolkit for interacting with Spark SQL.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the inp... | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.spark_sql.toolkit.SparkSQLToolkit.html |
978375457ba6-1 | 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.spark_sql.toolkit.SparkSQLToolkit.html |
978375457ba6-2 | 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.spark_sql.toolkit.SparkSQLToolkit.html |
8391c5633fbb-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 |
8391c5633fbb-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 |
8391c5633fbb-2 | Return history buffer.
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: ... | https://api.python.langchain.com/en/latest/agents/langchain.agents.openai_functions_agent.agent_token_buffer_memory.AgentTokenBufferMemory.html |
8391c5633fbb-3 | eg. {“openai_api_key”: “OPENAI_API_KEY”}
property lc_serializable: bool¶
Return whether or not the class is serializable. | https://api.python.langchain.com/en/latest/agents/langchain.agents.openai_functions_agent.agent_token_buffer_memory.AgentTokenBufferMemory.html |
1f24ad2f05ac-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 |
1f24ad2f05ac-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 |
1f24ad2f05ac-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 |
1f24ad2f05ac-3 | Construct an SQL agent from an LLM and tools.
Examples using create_sql_agent¶
CnosDB
SQL Database Agent | https://api.python.langchain.com/en/latest/agents/langchain.agents.agent_toolkits.sql.base.create_sql_agent.html |
fdd4fb6a0eff-0 | langchain.retrievers.metal.MetalRetriever¶
class langchain.retrievers.metal.MetalRetriever[source]¶
Bases: BaseRetriever
Retriever that uses the Metal API.
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/retrievers/langchain.retrievers.metal.MetalRetriever.html |
fdd4fb6a0eff-1 | :param query: string to find relevant documents for
:param callbacks: Callback manager or list of callbacks
:param tags: Optional list of tags associated with the retriever. Defaults to None
These tags will be associated with each call to this retriever,
and passed as arguments to the handlers defined in callbacks.
Par... | https://api.python.langchain.com/en/latest/retrievers/langchain.retrievers.metal.MetalRetriever.html |
fdd4fb6a0eff-2 | 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/retrievers/langchain.retrievers.metal.MetalRetriever.html |
fdd4fb6a0eff-3 | 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/retrievers/langchain.retrievers.metal.MetalRetriever.html |
fdd4fb6a0eff-4 | classmethod validate(value: Any) → Model¶
with_fallbacks(fallbacks: ~typing.Sequence[~langchain.schema.runnable.Runnable[~langchain.schema.runnable.Input, ~langchain.schema.runnable.Output]], *, exceptions_to_handle: ~typing.Tuple[~typing.Type[BaseException]] = (<class 'Exception'>,)) → RunnableWithFallbacks[Input, Out... | https://api.python.langchain.com/en/latest/retrievers/langchain.retrievers.metal.MetalRetriever.html |
7b43abcc6f0a-0 | langchain.retrievers.document_compressors.embeddings_filter.EmbeddingsFilter¶
class langchain.retrievers.document_compressors.embeddings_filter.EmbeddingsFilter[source]¶
Bases: BaseDocumentCompressor
Document compressor that uses embeddings to drop documents
unrelated to the query.
Create a new model by parsing and val... | https://api.python.langchain.com/en/latest/retrievers/langchain.retrievers.document_compressors.embeddings_filter.EmbeddingsFilter.html |
7b43abcc6f0a-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/retrievers/langchain.retrievers.document_compressors.embeddings_filter.EmbeddingsFilter.html |
7b43abcc6f0a-2 | classmethod from_orm(obj: Any) → Model¶
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_n... | https://api.python.langchain.com/en/latest/retrievers/langchain.retrievers.document_compressors.embeddings_filter.EmbeddingsFilter.html |
f1c3fcb62d55-0 | langchain.retrievers.arxiv.ArxivRetriever¶
class langchain.retrievers.arxiv.ArxivRetriever[source]¶
Bases: BaseRetriever, ArxivAPIWrapper
Retriever for Arxiv.
It wraps load() to get_relevant_documents().
It uses all ArxivAPIWrapper arguments without any change.
Create a new model by parsing and validating input data fr... | https://api.python.langchain.com/en/latest/retrievers/langchain.retrievers.arxiv.ArxivRetriever.html |
f1c3fcb62d55-1 | async aget_relevant_documents(query: str, *, callbacks: Callbacks = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → List[Document]¶
Asynchronously get documents relevant to a query.
:param query: string to find relevant documents for
:param callbacks: Callback manager... | https://api.python.langchain.com/en/latest/retrievers/langchain.retrievers.arxiv.ArxivRetriever.html |
f1c3fcb62d55-2 | Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally... | https://api.python.langchain.com/en/latest/retrievers/langchain.retrievers.arxiv.ArxivRetriever.html |
f1c3fcb62d55-3 | These tags will be associated with each call to this retriever,
and passed as arguments to the handlers defined in callbacks.
Parameters
metadata – Optional metadata associated with the retriever. Defaults to None
This metadata will be associated with each call to this retriever,
and passed as arguments to the handlers... | https://api.python.langchain.com/en/latest/retrievers/langchain.retrievers.arxiv.ArxivRetriever.html |
f1c3fcb62d55-4 | 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¶
run(query: str) → str¶
Performs an arxiv search and A single string
with the publish date, title, authors, and su... | https://api.python.langchain.com/en/latest/retrievers/langchain.retrievers.arxiv.ArxivRetriever.html |
f1c3fcb62d55-5 | serialized kwargs. These attributes must be accepted by the
constructor.
property lc_namespace: List[str]¶
Return the namespace of the langchain object.
eg. [“langchain”, “llms”, “openai”]
property lc_secrets: Dict[str, str]¶
Return a map of constructor argument names to secret ids.
eg. {“openai_api_key”: “OPENAI_API_K... | https://api.python.langchain.com/en/latest/retrievers/langchain.retrievers.arxiv.ArxivRetriever.html |
9ee76524e7d4-0 | langchain.retrievers.pubmed.PubMedRetriever¶
class langchain.retrievers.pubmed.PubMedRetriever[source]¶
Bases: BaseRetriever, PubMedAPIWrapper
Retriever for PubMed API.
It wraps load() to get_relevant_documents().
It uses all PubMedAPIWrapper arguments without any change.
Create a new model by parsing and validating in... | https://api.python.langchain.com/en/latest/retrievers/langchain.retrievers.pubmed.PubMedRetriever.html |
9ee76524e7d4-1 | Asynchronously get documents relevant to a query.
:param query: string to find relevant documents for
:param callbacks: Callback manager or list of callbacks
:param tags: Optional list of tags associated with the retriever. Defaults to None
These tags will be associated with each call to this retriever,
and passed as a... | https://api.python.langchain.com/en/latest/retrievers/langchain.retrievers.pubmed.PubMedRetriever.html |
9ee76524e7d4-2 | 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/retrievers/langchain.retrievers.pubmed.PubMedRetriever.html |
9ee76524e7d4-3 | and passed as arguments to the handlers defined in callbacks.
Returns
List of relevant documents
invoke(input: str, config: Optional[RunnableConfig] = None) → List[Document]¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = Non... | https://api.python.langchain.com/en/latest/retrievers/langchain.retrievers.pubmed.PubMedRetriever.html |
9ee76524e7d4-4 | retrieve_article(uid: str, webenv: str) → dict¶
run(query: str) → str¶
Run PubMed search and get the article meta information.
See https://www.ncbi.nlm.nih.gov/books/NBK25499/#chapter4.ESearch
It uses only the most informative fields of article meta information.
classmethod schema(by_alias: bool = True, ref_template: u... | https://api.python.langchain.com/en/latest/retrievers/langchain.retrievers.pubmed.PubMedRetriever.html |
9ee76524e7d4-5 | Return a map of constructor argument names to secret ids.
eg. {“openai_api_key”: “OPENAI_API_KEY”}
property lc_serializable: bool¶
Return whether or not the class is serializable.
Examples using PubMedRetriever¶
PubMed | https://api.python.langchain.com/en/latest/retrievers/langchain.retrievers.pubmed.PubMedRetriever.html |
a87568fc668b-0 | langchain.retrievers.document_compressors.chain_filter.LLMChainFilter¶
class langchain.retrievers.document_compressors.chain_filter.LLMChainFilter[source]¶
Bases: BaseDocumentCompressor
Filter that drops documents that aren’t relevant to the query.
Create a new model by parsing and validating input data from keyword ar... | https://api.python.langchain.com/en/latest/retrievers/langchain.retrievers.document_compressors.chain_filter.LLMChainFilter.html |
a87568fc668b-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... | https://api.python.langchain.com/en/latest/retrievers/langchain.retrievers.document_compressors.chain_filter.LLMChainFilter.html |
a87568fc668b-2 | classmethod from_orm(obj: Any) → Model¶
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_n... | https://api.python.langchain.com/en/latest/retrievers/langchain.retrievers.document_compressors.chain_filter.LLMChainFilter.html |
3dbe526a7e52-0 | langchain.retrievers.multi_query.LineList¶
class langchain.retrievers.multi_query.LineList[source]¶
Bases: BaseModel
List of lines.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param lines: List[str] [Req... | https://api.python.langchain.com/en/latest/retrievers/langchain.retrievers.multi_query.LineList.html |
3dbe526a7e52-1 | 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/retrievers/langchain.retrievers.multi_query.LineList.html |
3dbe526a7e52-2 | 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/retrievers/langchain.retrievers.multi_query.LineList.html |
02558f13006d-0 | langchain.retrievers.pinecone_hybrid_search.hash_text¶
langchain.retrievers.pinecone_hybrid_search.hash_text(text: str) → str[source]¶
Hash a text using SHA256.
Parameters
text – Text to hash.
Returns
Hashed text. | https://api.python.langchain.com/en/latest/retrievers/langchain.retrievers.pinecone_hybrid_search.hash_text.html |
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