ashishpatel26/500-AI-Agents-Projects

What is this?

500-AI-Agents-Projects is a curated collection of 500+ AI agent projects — real-world examples, tutorials, and working code. It covers every major AI agent framework (LangGraph, CrewAI, AutoGen, Agno, LlamaIndex) and many industries (Healthcare, Finance, Education, Cybersecurity, and more).

Think of it as a showcase library: instead of explaining AI agents in theory, it points you to actual working implementations you can run and learn from.

Who is it for?

• Developers building their first or next AI agent
• Researchers surveying the AI agent landscape
• Teams evaluating which framework to use in production
• Students learning agent architectures from real examples

What's inside?

1. Working agents in an agents/ directory — each is self-contained with its own requirements.txt and .env.example, so you can run one in under 5 minutes without setting up a whole project.
2. Industry use cases — a table of ~25 examples (e.g., a health insights agent, an automated trading bot, a virtual tutor, a cybersecurity threat detector), each linking to the actual GitHub repository.
3. Framework comparison — a table that helps you choose between LangGraph, CrewAI, AutoGen, Agno, and LlamaIndex based on complexity, multi-agent support, streaming, and local LLM support.
4. Framework-wise listings — detailed tables of example projects for CrewAI and AutoGen (e.g., email auto-responder, stock analysis tool, group chat demos, code generation notebooks).
5. A bonus course — a crewai_mcp_course/ directory for learning.

How do you use it?

git clone https://github.com/ashishpatel26/500-AI-Agents-Projects.git
cd 500-AI-Agents-Projects
cd agents/01-web-research-agent
pip install -r requirements.txt
cp .env.example .env   # add your API key
python agent.py

No monorepo setup needed — each agent runs independently.

Key highlights

• MIT licensed — free to use and modify
• PRs welcome — the project invites contributions
• Quick decision guide in the README: just starting out → use Agno or CrewAI; need stateful graphs + RAG → LangGraph; building code-writing/research agents → AutoGen; enterprise document pipelines → LlamaIndex

What it is NOT

• It is not a framework itself — it's a curated index/collection pointing to many external projects.
• It is not a tutorial series — though it includes links to notebooks and a course directory.

Bottom line

If you want to see what AI agents can do in practice, compare frameworks, or find a starting point for your own agent, this repo gives you a large, organized map of real projects — with code you can actually run.

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All facts above are taken directly from the project's README.