LangChain Agent Types

LangChain Agent Types are distinct architectural patterns that define how language models interact with tools and execute reasoning workflows within the LangChain framework. Traditional agent types include ReAct agents that implement reasoning and acting cycles for complex problem-solving, conversational agents optimized for chat-based interactions while maintaining tool access capabilities, and tool-calling agents that leverage structured function calling for precise external integrations. The core concept involves using language models to autonomously choose sequences of actions based on available tools and contextual requirements. ReAct agents excel at multi-hop reasoning tasks requiring multiple search actions and external tool calls, while conversational agents are designed for interactive dialogue scenarios where users expect natural conversation alongside tool functionality. However, legacy LangChain Agents have been deprecated since version 0.1.0, with LangGraph now recommended for new implementations due to its superior flexibility, stateful execution control, and full-featured agent building capabilities that provide more sophisticated orchestration patterns.