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试用DataCamp for Business课程描述
Build AI Agents with LangGraph
Design and build your own agents with LangGraph! LangGraph is a core part of the LangChain ecosystem, and it's used to build production-ready AI agents with a high degree of customizability. LangGraph allows developers to build agents as graphs with nodes and edges, which allows information flow and decision pathways to be carefully mapped out, and reduces the room for unexpected errors to creep in.Explore Emerging Multi-Agent Architectures
Since the rise of AI agents, a handful of agentic design patterns have emerged, and you'll learn about two of the most popular: network (or decentralized) multi-agents and supervisor multi-agents. Manage multiple agents effectively by designing a supervisor agent to delegate tasks and encourage collaboration between the worker agents.Create Your Own Agentic Assistant
You'll use LangGraph to build an agentic assistant to gather information and stock performance data on Fortune 500 companies, and analyze it using visualizations!You'll see this agent progress from a simple single-agent system to a three-agent supervisor multi-agent! Join the growing number of AI builders and learn to design and build AI agents today!
先决条件
Designing Agentic Systems with LangChain1
Agents as Graphs
Learn to build AI agents the LangGraph way! Build a toolbox of tools to help your agent interact with APIs, retrieve data from CSV files, and run Python code! Begin to build a single-agent system using nodes and edges to connect the LLM and tools in a controlled and methodical way.
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LangGraph Multi-Agents
Since the rise of AI agents, a handful of agentic design patterns have emerged, and you'll learn about two of the most popular: swarm (or decentralized) multi-agents and supervisor multi-agents. You'll see that LangGraph provides a whole host of functionality to design multi-agents tailored to your specific use case.
Multi-Agent Systems with LangGraph
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