langchain.agents.initialize.initialize_agent¶
langchain.agents.initialize.initialize_agent(tools: Sequence[BaseTool], llm: BaseLanguageModel, agent: Optional[AgentType] = None, callback_manager: Optional[BaseCallbackManager] = None, agent_path: Optional[str] = None, agent_kwargs: Optional[dict] = None, *, tags: Optional[Sequence[str]] = None, **kwargs: Any) → AgentExecutor[source]¶
Load an agent executor given tools and LLM.
Parameters
tools – List of tools this agent has access to.
llm – Language model to use as the agent.
agent – Agent type to use. If None and agent_path is also None, will default to
AgentType.ZERO_SHOT_REACT_DESCRIPTION.
callback_manager – CallbackManager to use. Global callback manager is used if
not provided. Defaults to None.
agent_path – Path to serialized agent to use.
agent_kwargs – Additional key word arguments to pass to the underlying agent
tags – Tags to apply to the traced runs.
**kwargs – Additional key word arguments passed to the agent executor
Returns
An agent executor
Examples using initialize_agent¶
ChatGPT Plugins
Google Serper
Human as a tool
Yahoo Finance News
AWS Lambda
Google Drive
OpenWeatherMap
Search Tools
Eleven Labs Text2Speech
Zapier Natural Language Actions
ArXiv
Metaphor Search
GraphQL
Gradio
SceneXplain
Eden AI
Dall-E Image Generator
Shell (bash)
Zep Memory
Xata chat memory
Dynamodb Chat Message History
LLMonitor
Argilla
Streamlit
Comet
Aim
Weights & Biases
SageMaker Tracking
MLflow
Flyte
WandB Tracing
ClearML
Log, Trace, and Monitor
Portkey
Jira
Document Comparison
Azure Cognitive Services