Build DeepSeek-R1 Application with GUI and Run Locally on Windows - Embed your AI into GUI and App

Описание: #deepseek #machinelearning #ollama #streamlit
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In this machine learning and AI tutorial, we explain how to create a simple DeepSeek-R1 application and Graphics User Interface (GUI), and how to run this application locally on a Windows computer. The application is developed in Python, by using DeepSeek-R1, Ollama, and Streamlit.

DeepSeek-R1 belongs to the class of reasoning models. Reasoning models perform better at complex reasoning problems and tasks compared to the classical large language models. Complex reasoning problems are problems that appear in mathematics, science, and coding.

According to the information given on GitHub page of DeepSeek, the performance of DeepSeek-R1 is comparable to the performance of OpenAI-o1. However, DeepSeek-R1 is released under the MIT license, which means that you can also use this model in a commercial setting

In this tutorial, we present a proof-of-concept for building a desktop app that is based on DeepSeek-R1. The application is deliberately kept as simple as possible in order not to blur the main ideas with too many complex programing details. You can use this tutorial as the basis of the development of your own applications that integrate AI, graphics, sound, animation, etc.

We are using Streamlit to develop the GUI and to embed the AI model. Streamlit is an open source Python framework for quickly creating interactive data applications. Streamlit is designed for data scientists and machine learning engineers. You can quickly learn how to use this framework and you do not need to have a front-end development experience.

The solution presented in this tutorial is a “quick and dirty” solution. In the future video tutorials, we will delve deeper into the AI app development.