Ready to automate your paper hunt with AI?
In this step-by-step coding tutorial you’ll learn—line by line—how to build a web app that uses two collaborative agents to:
🔍 Search ArXiv for the most relevant papers on any topic
📝 Summarize each paper’s core problem and solution
📑 Generate a cohesive research report from those papers
All in Python, using AutoGen 0.5, OpenAI o3-mini, and Streamlit.
🎯⏱ What You’ll Learn & Timestamps
00:00 - Demo: See the “Paper Hunter” App in Action
02:26 - Defining the Arxiv Search AI Agent (`AssistantAgent`) and OpenAI o3-mini LLM in Autogen 0.5
07:43 - Using Arxiv API in Python to search for papers in Arxiv
20:05 - Defining the Researcher AI Agent (`AssistantAgent`) to generate a research report
22:15 - Defining the team of agents (`RoundRobinGroupChat`) in AutoGen 0.5
35:25 Defining title, text input and chat input elements in Streamlit
36:52 Connecting the AI agents to the UI (Streamlit web app)
43:47 Testing the AI agents with some examples to look for papers
46:24 Final words (DO IT YOURSELF!!!)
👥 Who’s This For?
- Python developers automating research workflows
- Grad students streamlining literature reviews
- AI enthusiasts exploring multi-agent agentic AI
📺 More Exciting Agentic Tutorials Like This:
https://www.youtube.com/watch?v=c-WAkBEla48&list=PLEe-UC96P-yaND7e6NsapElGTKfXq_cew&index=3&pp=0gcJCR0AztywvtLA
🤝 Stay Connected
Subscribe 🔔 for weekly hands-on Agentic AI tutorials!
📦 GitHub Code & Resources:
https://github.com/M-H-Amini/YouTube/tree/master/Agentic/6_Arxiv
Have questions? Drop a comment—let’s build together!
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