AutoGen Tutorial: Creating Custom AI Agents Made Simple

🚀 Autogen is a project by Microsoft that allows you to create as many autonomous agents as you want and have them work together.

🔧 Autogen is a framework that offers customizable and conversible agents, simplifying the orchestration, optimization, and automation of llm workflows.

🤝 With Autogen, you can define specialized AI agents with different roles and behaviors, enabling them to work together in a multi-agent conversation system.

💡 AutoGen allows for the creation of custom AI agents that can autonomously write and execute code.

🤖 AutoGen utilizes different types of agents, such as the user proxy agent and assistant agent, to automate the chat and code execution process.

🔧 The user proxy agent simulates user behavior and can run code itself, saving time and allowing for human feedback and intervention.

🚀 AutoGen is a tool that allows users to easily create custom AI agents.

💻 The tutorial demonstrates how to install the Pi AutoGen library and set up the API endpoint for the agents.

🔑 The user proxy agent and assistant agent communicate to complete tasks, with the assistant agent providing code suggestions and debugging.

🚀 The user proxy mode allows code to be executed without asking for approval.

🔀 The Max consecutive auto reply setting determines the number of back and forth exchanges before the task terminates.

📅 The assistant initiates a dialogue with the user proxy to determine the current date and compare the year-to-date gain for Meta and Tesla.

🔑 The assistant fixes a bug by correcting a variable issue and successfully executes the code.

💰 The assistant provides the year-to-date gains for two stocks, highlighting the potential increase in investment.

📊 The assistant guides the user in plotting a chart using the Matplotlib library in Python.

🚀 This tutorial demonstrates how to use AutoGen to create custom AI agents without programming knowledge.

💡 AutoGen enables users to teach AI new skills through natural agent interactions.

📝 The tutorial shows an example task of finding research papers, categorizing application domains, and creating a bar chart.

🔑 The video demonstrates how to use AI agents to analyze and summarize research papers.

📊 The tutorial shows how to generate a bar chart of application domains and the number of papers in each domain using Python and Matplotlib.

🔧 A recipe is created to automate the process and provide reusable Python functions for fetching papers and generating bar charts.