LangChain Agents
Master LangChain, the most popular framework for building production-ready AI agents
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You've mastered LangChain agents! Check off each concept below to track your understanding. When you've mastered all 15 takeaways, you'll unlock the next module.
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0%LangChain is the most popular framework for building AI agents, with millions of downloads
Reduces agent development from 200+ lines to 10-20 lines of battle-tested code
4 core components: LLM (brain), Tools (actions), Memory (context), Agent Executor (orchestrator)
LLM handles reasoning and planning; supports OpenAI, Anthropic, local models, and more
Tools enable agents to take actions - built-in library plus custom function support
Memory systems include ConversationBuffer, Summary, Vector, and Entity memory
AgentExecutor orchestrates the agent loop with automatic error handling and retries
4 main agent types: Zero-Shot ReAct, ReAct, Conversational, OpenAI Functions
Zero-Shot ReAct is most flexible; use for prototyping with multiple unknown tools
OpenAI Functions is most reliable; use for production systems with structured outputs
Conversational agents have built-in memory for natural multi-turn dialogues
Always set max_iterations (5-10) to prevent infinite agent loops in production
Write clear tool descriptions - LLM uses them to decide when to call each tool
Use callbacks and LangSmith for observability, debugging, and production monitoring
LangChain agents power real-world systems from startups to Fortune 500 companies
Complete all 15 takeaways to finish this module and unlock the next one!