Building a VS Code Extension with DeepSeek R1 Integration

In today's video, you'll learn how to build a VS Code extension from scratch, integrating DeepSeek R1, a low-cost open-source reasoning model, into your own custom AI assistant. By the end of this tutorial, you'll be able to cancel your $200 ChatBT Pro subscription and experience the sweet taste of freedom known as open source.

Introduction to DeepSeek R1

DeepSeek R1 is a powerful open-source reasoning model that's on par with Open AI's models. However, if you use the web UI, you're agreeing to send your prompts, keystrokes, and data to China. To get around this, you can run the model locally, which requires no internet connection. This is exactly what you'll learn how to do in this tutorial.

Introduction to building a VS Code extension with DeepSeek R1 integration

Building the VS Code Extension

To start building the extension, you'll need to create a new project using the official VS Code starter template. This template includes a basic structure for your extension, including an extension.ts file that imports the global VS Code object. This object provides access to the entire VS Code API, allowing you to customize essentially anything in the editor.

Creating a new VS Code extension project

Running the Extension Locally

Once you've created the project, you can start the extension locally using the npx command. This will take you through a series of questions, but you can stick with the default options. After that, you'll have a basic extension up and running.

Running the extension locally

Generating the Project

To generate the project, you'll need to run the npx command with the --generate flag. This will create a new project with the basic structure for your extension.

Generating the project

Customizing the Extension

Now that you have the basic extension up and running, you can start customizing it. You can register a command that will execute a callback function when triggered. This callback function can use the VS Code window to show an error message or perform other actions.

Customizing the extension

Integrating DeepSeek R1

To integrate DeepSeek R1 into your extension, you'll need to use a tool called Ollama. Ollama is a utility that allows you to download and run open-source AI models, including DeepSeek R1.

Integrating DeepSeek R1 into the extension

Creating the Chat Dialogue

To create the chat dialogue, you'll need to define a function that will generate the HTML content for the chat window. This function will include a text area and a button that will send the user's input to the DeepSeek R1 model.

Creating the chat dialogue

Connecting to the DeepSeek R1 Model

To connect to the DeepSeek R1 model, you'll need to use the Ollama API. This API provides a way to send input to the model and receive output in response.

Connecting to the DeepSeek R1 model

Conclusion

In conclusion, building a VS Code extension with DeepSeek R1 integration is a fun and rewarding project. By following the steps outlined in this tutorial, you can create your own custom AI assistant that runs locally on your machine. With this extension, you can experience the sweet taste of freedom known as open source and cancel your $200 ChatBT Pro subscription. Thank you for watching, and I'll see you in the next one!