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GenAI Agents is a large, tutorial-driven repository that teaches you how to design, build, and experiment with generative AI agents. It spans a spectrum from simple conversational bots and basic question-answering agents to complex multi-agent systems that coordinate on research, education, business workflows, and creative tasks. The implementations leverage modern frameworks such as LangChain, LangGraph, AutoGen, PydanticAI, CrewAI, and more, showing how each can be wired into realistic agent workflows. The repo is structured by categories like beginner agents, framework tutorials, educational agents, business agents, creative agents, analysis agents, news bots, shopping assistants, task management agents, QA bots, and advanced systems such as controllable RAG agents. For each agent, you typically get an overview, implementation notes, and external resources (blog posts, videos, documentation) to deepen understanding.
Features
- Wide catalog of AI agent implementations organized by use case and complexity
- Tutorials covering major frameworks like LangChain, LangGraph, AutoGen, MCP, and CrewAI
- Beginner-friendly agents for conversation, Q&A, and simple data analysis
- Advanced multi-agent examples for research assistance, learning, and professional workflows
- Rich supporting materials including blog posts, videos, and detailed implementation notes
- Community-oriented design with contribution guidelines and an active Discord community
Project Samples
