AgentType#

class langchain.agents.agent_types.AgentType(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)[source]#

Deprecated since version 0.1.0: LangChain agents will continue to be supported, but it is recommended for new use cases to be built with LangGraph. LangGraph offers a more flexible and full-featured framework for building agents, including support for tool-calling, persistence of state, and human-in-the-loop workflows. For details, refer to the LangGraph documentation as well as guides for Migrating from AgentExecutor and LangGraph’s Pre-built ReAct agent. It will not be removed until langchain==1.0.

An enum for agent types.

See documentation: https://python.langchain.com/docs/modules/agents/agent_types/

ZERO_SHOT_REACT_DESCRIPTION = 'zero-shot-react-description'#

A zero shot agent that does a reasoning step before acting.

REACT_DOCSTORE = 'react-docstore'#

A zero shot agent that does a reasoning step before acting.

This agent has access to a document store that allows it to look up relevant information to answering the question.

An agent that breaks down a complex question into a series of simpler questions.

This agent uses a search tool to look up answers to the simpler questions in order to answer the original complex question.

CONVERSATIONAL_REACT_DESCRIPTION = 'conversational-react-description'#
CHAT_ZERO_SHOT_REACT_DESCRIPTION = 'chat-zero-shot-react-description'#

A zero shot agent that does a reasoning step before acting.

This agent is designed to be used in conjunction

CHAT_CONVERSATIONAL_REACT_DESCRIPTION = 'chat-conversational-react-description'#
STRUCTURED_CHAT_ZERO_SHOT_REACT_DESCRIPTION = 'structured-chat-zero-shot-react-description'#

An zero-shot react agent optimized for chat models.

This agent is capable of invoking tools that have multiple inputs.

OPENAI_FUNCTIONS = 'openai-functions'#

An agent optimized for using open AI functions.

OPENAI_MULTI_FUNCTIONS = 'openai-multi-functions'#

Examples using AgentType