Build Quick UIs with Mesop: Google’s New UI Maker

In this video, Sam Witteveen introduces Mesop, Google’s new UI maker, designed to help developers quickly build web UIs with Python. Mesop is particularly useful for engineers who lack front-end skills and need to create user interfaces to test their LLM (Large Language Model) applications. The video covers the features, components, and practical use cases of Mesop, including a detailed demo of building a chatbot using LangChain and Groq.

Sam explains the importance of quickly getting your app into the hands of users for feedback and mentions the limitations of existing tools like Streamlit and Gradio. Mesop, developed by Google engineers in their spare time, aims to fill this gap by providing a framework that allows for rapid UI development. The framework is open-source and currently in version 0.8.

The video walks through various high-level and low-level components available in Mesop, such as chat interfaces, text-to-image examples, buttons, text inputs, and more. Sam demonstrates how to set up a simple chat interface using Mesop, showing the minimal code required to get started. He also highlights the backend functionality, which builds a Flask app on the fly.

The tutorial progresses to a more advanced example where Sam integrates Mesop with LangChain and Groq to create a chatbot with memory capabilities. He explains how to set up the Groq API, configure the LangChain components, and build the chat interface using Mesop. The chatbot retains conversation history and responds based on previous interactions, showcasing the power of combining Mesop with LLMs for practical applications.

Sam concludes by discussing potential future use cases, such as integrating RAG (Retrieval-Augmented Generation) and logging chat interactions to a database. He encourages viewers to experiment with Mesop and provides links to the necessary resources, including GitHub repositories and documentation.

Overall, the video serves as a comprehensive guide to getting started with Mesop and demonstrates its potential for rapid prototyping and testing of LLM applications.