ai-agents-for-beginners and Agent_In_Action

These are complements: the Microsoft course provides foundational educational content for building AI agents, while the FlyAIBox project offers practical implementation examples and code patterns that learners can apply to the concepts taught in the lessons.

Agent_In_Action
53
Established
Maintenance 23/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 10/25
Adoption 9/25
Maturity 13/25
Community 21/25
Stars: 53,826
Forks: 18,688
Downloads:
Commits (30d): 30
Language: Jupyter Notebook
License: MIT
Stars: 77
Forks: 33
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
No Package No Dependents
No Package No Dependents

About ai-agents-for-beginners

microsoft/ai-agents-for-beginners

12 Lessons to Get Started Building AI Agents

Structured curriculum covering agent fundamentals, reasoning patterns, and tool integration using Microsoft Agent Framework paired with Azure AI Foundry Agent Service V2. Each of the 12 lessons includes written content, Python code samples, and video walkthroughs demonstrating practical implementations. Available in 50+ languages with automated translation updates via GitHub Actions.

About Agent_In_Action

FlyAIBox/Agent_In_Action

Agentic AI 智能体开发实战

Implements a complete agentic AI system using LangGraph and MCP protocols, covering architecture (GAME framework with Goals/Actions/Memory/Environment), tool integration patterns, and production deployment via FastAPI + Streamlit with Docker. Includes six end-to-end projects spanning multi-agent orchestration, monitoring via Langfuse, and domain-specific model fine-tuning with LlamaFactory and vLLM inference optimization.

Scores updated daily from GitHub, PyPI, and npm data. How scores work