Boost Productivity with FREE AI in VSCode (Llama 3 Copilot)

Mervin Praison
25 Apr 202405:39

TLDRThe video introduces Llama 3, an AI integration for Visual Studio Code (VSCode) that significantly boosts productivity in coding. By downloading Llama 3 locally, developers can create a private co-pilot without the need for manual code writing, fixing, or refactoring, which can be time-consuming and error-prone. The video demonstrates how to integrate Llama 3 with VSCode, showing how it can generate boilerplate code, fix bugs, and refactor code on the fly, leading to increased productivity and code quality while reducing errors. The host guides viewers through the installation process, including downloading the necessary extensions and setting up the AI copilot with Llama 3. The video concludes with a live demonstration of writing a Flask API, connecting it to a SQLite database, and documenting the code, all facilitated by Llama 3's AI capabilities.

Takeaways

  • 🚀 **Integrating AI**: You can integrate Llama 3, an AI assistant, into your VS Code application to boost productivity.
  • 💡 **Code Assistance**: With Llama 3, you can generate boilerplate code, fix errors, and refactor code directly within VS Code.
  • 📚 **Documentation**: The AI can also help document your code by adding relevant comments for better understanding.
  • 🔍 **Efficiency**: Searching online for code is not needed; everything can be done in VS Code, increasing efficiency.
  • ✅ **Quality Improvement**: Using AI reduces manual coding errors and enhances code quality.
  • 📈 **Productivity Boost**: The integration of AI in coding processes leads to higher productivity.
  • 📝 **Quick Code Fixes**: Llama 3 can quickly identify and fix bugs in your code selection.
  • 🔗 **Database Integration**: The script demonstrates how to connect code with a SQLite database using AI assistance.
  • 🔧 **Refactoring**: AI can refactor your code, making it cleaner and more efficient.
  • 🔑 **Extension Settings**: To use Llama 3, you need to set it up in the VS Code extension settings.
  • 🎓 **Learning Resource**: The video serves as a tutorial for beginners and experienced users alike on leveraging AI in coding.

Q & A

  • What is the main purpose of integrating Llama 3 with VS Code?

    -The main purpose of integrating Llama 3 with VS Code is to enhance productivity by automating code writing, fixing, and refactoring, which leads to increased code quality and reduced errors.

  • How does using Llama 3 in VS Code improve a developer's workflow?

    -Using Llama 3 in VS Code improves a developer's workflow by providing quick boilerplate code creation, on-the-fly code fixing and refactoring, and automating documentation, which saves time and effort.

  • What is the first step to install Llama 3 in VS Code?

    -The first step to install Llama 3 in VS Code is to download it locally on your computer using the command `olama`.

  • How can one access the extension settings for Llama 3 in VS Code?

    -You can access the extension settings for Llama 3 in VS Code by clicking on the extension icon, then selecting the 'Extension Settings' from the dropdown menu.

  • What command is used to download the Llama 3 model for use in VS Code?

    -The commands used to download the Llama 3 model are `olama pull llama 38b` and `olama pull llama 3 instruct`.

  • How does Llama 3 assist in generating a Flask API code?

    -Llama 3 assists in generating a Flask API code by providing a starting point or boilerplate code when prompted by the user, which can then be extended and customized.

  • What is the process to connect the generated Flask API code to a SQLite database?

    -To connect the generated Flask API code to a SQLite database, you can ask Llama 3 to modify the code to include a connection to the database, and it will provide the necessary code to establish this connection.

  • How can Llama 3 help in fixing errors in the code?

    -Llama 3 can help in fixing errors by selecting the problematic code and using the 'Fix bug in selected code' feature, which identifies the error and suggests the correct code to replace it.

  • What is the command to refactor the selected code in VS Code using Llama 3?

    -The command to refactor the selected code is not explicitly mentioned, but the process involves using the shortcut panel in VS Code and selecting the 'Refactor selected code' option.

  • How does Llama 3 assist in documenting the code?

    -Llama 3 assists in documenting the code by adding relevant comments when the 'Document selected code' button is clicked, making the code easier to understand.

  • What are the benefits of subscribing to the YouTube channel mentioned in the script?

    -Subscribing to the YouTube channel allows viewers to stay updated with the latest videos on Artificial Intelligence, including tutorials and insights on using AI with VS Code and other development tools.

  • How long did it take to create a functioning API that interacts with a database using Llama 3 in the script?

    -According to the script, it took approximately 5 minutes to create a functioning API that interacts with a database using Llama 3 in VS Code.

Outlines

00:00

🚀 Integrating Llama 3 with VS Code for Enhanced Productivity

This paragraph introduces the integration of Llama 3 into Visual Studio Code (VS Code), a popular code editor. It contrasts manual coding with the use of AI, which can increase productivity, improve code quality, and reduce errors. The speaker, excited about the topic, guides viewers on how to download and implement Llama 3 in VS Code. The process includes downloading Llama 3 locally, enabling the Code GPT co-pilot extension, and choosing the correct model for AI assistance. The paragraph concludes with the speaker inviting viewers to subscribe to their YouTube channel for more content on Artificial Intelligence.

05:00

📝 Automating Code Tasks with Llama 3 in VS Code

The second paragraph demonstrates the practical use of Llama 3 in VS Code. It shows how to generate boilerplate code for a Flask API, connect to a SQLite database, fix errors, and refactor code—all through AI-assisted commands within VS Code. The speaker also illustrates how to document code by adding comments for better understanding. The paragraph concludes with the speaker expressing enthusiasm about the capabilities of Llama 3 and promising more informative videos on the topic. The viewer is encouraged to like, share, and subscribe for further updates.

Mindmap

Keywords

💡Llama 3

Llama 3 is an AI model that can be integrated into the Visual Studio Code (VSCode) application to enhance coding productivity. It is used to generate code, fix errors, and refactor code automatically, which is a significant improvement over manual coding practices. In the video, Llama 3 is downloaded and set up to work with VSCode, showcasing its ability to create a Flask API and connect it to a SQLite database.

💡Visual Studio Code (VSCode)

VSCode is a popular code editor tool that is used for developing and managing source code files. It is extensible and supports a wide range of programming languages. In the context of the video, VSCode is the platform where Llama 3 is integrated to provide AI-driven coding assistance.

💡AI

Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. In the video, AI is utilized through Llama 3 to automate various coding tasks, thereby increasing productivity and reducing errors.

💡Code Generation

Code generation is the process of automatically creating source code. In the video, Llama 3 is used to generate boilerplate code for a Flask API, demonstrating how AI can expedite the initial stages of software development.

💡Code Refactoring

Code refactoring is the process of restructuring existing computer code without changing its external behavior to improve nonfunctional attributes of the software. The video shows how Llama 3 can refactor code, making it more efficient and easier to understand.

💡Code Quality

Code quality refers to the level of excellence of source code in terms of its readability, efficiency, maintainability, and flexibility. The video emphasizes how using Llama 3 can enhance code quality by automating error correction and code restructuring.

💡Flask API

A Flask API is a web application framework used for developing APIs (Application Programming Interfaces) with Python. In the video, the AI generates a basic Flask API code, which serves as a starting point for further development and integration with a database.

💡SQLite Database

SQLite is a C-language library that implements a small, fast, self-contained, high-reliability, full-featured SQL database engine. It is used in the video to demonstrate how the generated Flask API code can be connected to a database to manage data.

💡Code GPt

Code GPT is an extension for VSCode that integrates with Llama 3, allowing users to leverage AI for coding tasks. It is mentioned in the video as a tool that facilitates the use of Llama 3 within the VSCode environment.

💡Error Fixing

Error fixing involves identifying and correcting mistakes in the source code. The video script illustrates how Llama 3 can automatically detect and fix errors, such as a missing semicolon, in the code, which streamlines the debugging process.

💡Documentation

In the context of programming, documentation refers to the process of adding comments and explanations to the source code to make it understandable to other developers. The video demonstrates how Llama 3 can help document code by adding relevant comments, which is crucial for maintaining and scaling the software.

💡Productivity

Productivity in the context of the video refers to the efficiency and effectiveness of the coding process. By using Llama 3, the video argues that developers can achieve higher productivity by reducing manual coding tasks and leveraging AI to automate common programming chores.

Highlights

Integrate Llama 3 in VS Code to boost productivity with AI assistance.

Download Llama 3 locally to create a private co-pilot for coding without relying on manual code fixes and refactoring.

Llama 3 integration in VS Code provides code explanations, refactoring, and documentation capabilities.

VS Code is a popular code editor tool that can be enhanced with AI for improved coding efficiency.

AI can generate boilerplate code, fix errors, and refactor code on the fly, leading to increased productivity and code quality.

Subscribe to the YouTube channel for more videos on Artificial Intelligence.

Download VS Code from its official website and Llama from ama.com to start using AI in your coding workflow.

Search for 'Code GPT' in the VS Code extensions area and install it for AI-powered coding assistance.

Enable Code GPT Co-Pilot and select the Llama model for auto-completion and coding support.

Download the Llama 3 models 'llama 38b' and 'llama 3 instruct' for seamless integration with VS Code.

Create a file in VS Code and use the Code GPT icon to select the Llama provider and model for coding.

Generate a Flask API code quickly using AI, and extend it further for specific requirements.

Connect the generated code to a SQLite database and modify it to establish a direct connection with simple code insertion.

Use the 'fix bug in selected code' feature to identify and correct errors in your code.

Refactor your code efficiently with the help of AI by using the 'refactor selected code' shortcut.

Document your code by using the AI to add relevant comments for better understanding and readability.

Complete API creation that interacts with the database and responds to user queries in just 5 minutes with AI assistance.

Stay tuned for more videos on leveraging AI in coding with regular updates on the YouTube channel.