langchain.agents.agent_types.AgentType¶
class langchain.agents.agent_types.AgentType(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)[source]¶
Enumerator with the Agent types.
ZERO_SHOT_REACT_DESCRIPTION = 'zero-shot-react-description'¶
REACT_DOCSTORE = 'react-docstore'¶
SELF_ASK_WITH_SEARCH = 'self-ask-with-search'¶
CONVERSATIONAL_REACT_DESCRIPTION = 'conversational-react-description'¶
CHAT_ZERO_SHOT_REACT_DESCRIPTION = 'chat-zero-shot-react-description'¶
CHAT_CONVERSATIONAL_REACT_DESCRIPTION = 'chat-conversational-react-description'¶
STRUCTURED_CHAT_ZERO_SHOT_REACT_DESCRIPTION = 'structured-chat-zero-shot-react-description'¶
OPENAI_FUNCTIONS = 'openai-functions'¶
OPENAI_MULTI_FUNCTIONS = 'openai-multi-functions'¶
Examples using AgentType¶
ChatGPT Plugins
Google Serper API
Human as a tool
AWS Lambda API
OpenWeatherMap API
Search Tools
Zapier Natural Language Actions API
ArXiv API Tool
Metaphor Search
GraphQL tool
Shell Tool
Zep Memory
Dynamodb Chat Message History
Argilla
Streamlit
WandB Tracing
Aim
Weights & Biases
MLflow
Google Serper
Flyte
ClearML
Log, Trace, and Monitor Langchain LLM Calls
Portkey
CSV Agent
Jira
Document Comparison
Python Agent
Azure Cognitive Services Toolkit
SQL Database Agent
Natural Language APIs
Gmail Toolkit
Github Toolkit
PlayWright Browser Toolkit
Office365 Toolkit
Pandas Dataframe Agent
Multion Toolkit
Amadeus Toolkit
Amazon API Gateway
Debugging
LangSmith Walkthrough
Comparing Chain Outputs
Agent VectorDB Question Answering Benchmarking
Agent Trajectory
Multi-modal outputs: Image & Text