Mastering LLM Agent Frameworks: LangGraph, AG2, CrewAI, Semantic Kernel for AI Development
Unlock the power of Large Language Model (LLM) agents and build sophisticated AI applications with this in-depth tutorial! For developers, AI enthusiasts, and students, we deep dive into four leading LLM agent frameworks: LangGraph, AG2, CrewAI, and Semantic Kernel. Learn their core concepts and practical implementations with hands-on Python examples, enabling you to create autonomous AI systems, advanced chatbots, and multi-agent workflows.
*What you'll learn:*
*LangGraph:* Build stateful, multi-agent applications with memory (checkpointers), human-in-the-loop controls (interrupts), custom state, and even "time travel" to revisit conversation states. See a basic chatbot with web search (Tavily) integration.
*AG2:* Create production-ready AI agents focused on "Conversable Agents," covering orchestration, human-in-the-loop, tool integration, and structured outputs. We build a financial compliance assistant.
*CrewAI:* Explore this lean Python framework for building AI agent "Crews" (teams of agents) and "Flows" (event-driven workflow orchestration). Master project setup, defining agents/tasks in YAML, and leveraging conditional logic (@Or, @And, @Router decorators). Uses SerperDev tool.
*Semantic Kernel:* Understand the "kernel" as a central hub for managing AI services (like Google Gemini & OpenAI chat completion) and plugins (tools). Explore the Chat Completion Agent with a practical menu helper plugin, and learn about its agent architecture.
This video is packed with hands-on code examples and aims to provide a solid foundation for anyone looking to build advanced AI solutions.
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Check out additional resources: LangGraph server/platform quickstarts, Google Agent Development Kit for multi-agent AI workflows and deployments.
Timestamps:
[0:00] Introduction
[0:39] LangGraph Overview & Setup
[2:38] LangGraph: Building a Basic Chatbot
[9:29] LangGraph: Adding Tools
[13:15] LangGraph: Adding Memory
[14:15] LangGraph: Human-in-the-Loop
[18:18] LangGraph: Customizing State
[22:28] LangGraph: Time Travel
[26:53] AG2 Overview & Setup
[30:09] AG2: Financial Compliance Example
[43:31] CrewAI Overview & Setup
[51:21] CrewAI: Building Agents & Tasks
[54:53] CrewAI: Introduction to Flows
[1:15:08] Semantic Kernel Overview & Setup
[1:18:13] Semantic Kernel: Chat Completion Agent Example
[1:30:27] Semantic Kernel: Agent Architecture
[1:32:23] Conclusion & Google ADK
LangGraph:
https://langchain-ai.github.io/langgr...
Tavily: https://app.tavily.com/home
AG2:
https://docs.ag2.ai/0.9.1post0/
https://docs.ag2.ai/0.9.1post0/docs/u...
https://docs.ag2.ai/0.9.1post0/docs/u...
CrewAI:
https://docs.crewai.com/introduction
https://docs.crewai.com/installation
https://docs.crewai.com/quickstart
https://docs.crewai.com/concepts/flows
uv:
https://docs.astral.sh/uv/
Serper:
https://serper.dev/api-key
Semantic Kernel (Microsoft):
https://learn.microsoft.com/en-us/sem...
https://learn.microsoft.com/en-us/sem...
https://learn.microsoft.com/en-us/sem...
https://learn.microsoft.com/en-us/sem...
https://learn.microsoft.com/en-us/sem...
https://learn.microsoft.com/en-us/sem...
Google ADK Docs:
https://google.github.io/adk-docs/
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