Build a Multi-Agent DSA Solver

Analytics Vidhya · Beginner ·🤖 AI Agents & Automation ·2mo ago

Key Takeaways

Builds a Multi-Agent DSA Solver using Python and the AutoGen Console for UI debugging

Original Description

Description: In the grand finale of this crash course, we build a complex Multi-Agent System: The DSA Problem Solver. We coordinate three specialized agents (Solver, Reviewer, and Editor) using a Round Robin Team. Learn about termination conditions, human-in-the-loop feedback, and how to use the AutoGen Console for beautiful UI debugging. What we build: DSA Solver: Writes the initial Python code. Code Reviewer: Analyzes time/space complexity. Code Editor: Refines the code based on feedback. Chapters: 0:00 Final Project Overview: DSA Solver Team 2:15 Defining Specialized Agent Personas 4:30 Round Robin Group Chat Explained 6:15 Human-in-the-Loop: Adding UserProxy 8:45 Setting Termination Conditions (Text Mention) 11:00 Debugging with the AutoGen Console UI 14:30 Live Demo: Solving LeetCode Problems 17:00 Course Wrap-up & Next Steps
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Chapters (8)

Final Project Overview: DSA Solver Team
2:15 Defining Specialized Agent Personas
4:30 Round Robin Group Chat Explained
6:15 Human-in-the-Loop: Adding UserProxy
8:45 Setting Termination Conditions (Text Mention)
11:00 Debugging with the AutoGen Console UI
14:30 Live Demo: Solving LeetCode Problems
17:00 Course Wrap-up & Next Steps
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