Build Agentic Assistants with OpenAI Function Calling: Part 2

​How to build, refactor, and extend your own agents - Alexey Grigorev

​Join us for a hands-on walkthrough of building a chat assistant powered by OpenAI’s function calling, led by Alexey Grigorev. This live session focuses on understanding the code behind agent-like assistants.

​During a previous workshop, Alexey demoed how to build such an assistant quickly. This time, we’ll slow down, go deeper, explaining the code line by line, refactoring it into a reusable library. We will also go over the MCP protocol and create a simple MCP client from scratch.

​By the end, you’ll better understand how this assistant works and gain a solid foundation to extend the same setup in your projects.

​What You'll Learn

• ​How OpenAI function calling works in practice
• ​Building a basic assistant in Jupyter, step by step
• ​Refactoring assistant logic into a clean, reusable Python class
• ​Extending function calling with MCP

​It will be a live demo with practical tips and a chance to ask your questions.
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​Thinking About LLM Zoomcamp?
​This workshop is part of the things and projects we do at LLM Zoomcamp, a free online course about real-life applications of LLMs. In 10 weeks, you will learn how to build an AI system that answers questions about your knowledge base.
​The course is now live. You can join it by registering here.
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​About the Speaker
​Alexey Grigorev is the Founder of DataTalks.Club and creator of the Zoomcamp series.
​Alexey is a seasoned software and ML engineer with over 10 years in engineering and 6+ years in machine learning. He has deployed large-scale ML systems at companies like OLX Group and Simplaex, authored several technical books including Machine Learning Bookcamp, and is a Kaggle Master with a 1st place finish in the NIPS'17 Criteo Challenge.
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Join our slack: https://datatalks.club/slack.html