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

Discover how to boost your coding productivity with the integration of Llama 3 into Visual Studio Code (VSCode). This video tutorial guides you through the process of downloading and setting up Llama 3, an AI assistant, to enhance your coding experience. By utilizing Llama 3, you can quickly generate boilerplate code, fix errors, and refactor code on the fly, leading to increased productivity and improved code quality. The step-by-step guide covers installing the necessary extensions, configuring settings, and using Llama 3 to write a Flask API, connect to a SQLite database, and document your code with ease. The video also demonstrates how to fix common errors and refactor code for better readability. With Llama 3, coding becomes more efficient and less prone to human error, making it an invaluable tool for developers.

Takeaways

• 🚀 **Integrating Llama 3 with VSCode**: You can enhance your VSCode experience by integrating Llama 3, a powerful AI assistant, to boost productivity.
• 💡 **AI as a Code Companion**: Using AI like Llama 3 can help in creating boilerplate code, fixing errors, and refactoring, leading to increased productivity and code quality.
• 📚 **VSCode and Llama 3**: VSCode is a popular code editor, and with Llama 3, you can automate many coding tasks without manually writing or fixing code.
• 🔍 **Code GPT Extension**: The Code GPT extension in VSCode allows you to utilize the capabilities of Llama 3 for various coding tasks.
• 📦 **Downloading and Installing**: To use Llama 3, you need to download it from a specific website and install the extension in VSCode.
• 🔧 **Settings Configuration**: After installing the extension, you configure the settings to enable Llama 3 and select the appropriate model for code assistance.
• ✅ **Immediate Code Generation**: Llama 3 can generate code snippets for specific tasks, such as creating a Flask API, almost instantly.
• 🔗 **Database Connectivity**: The AI can assist in connecting and managing database interactions by generating the necessary code to interface with SQL databases.
• 🛠️ **Error Fixing and Code Refactoring**: Llama 3 can identify and fix errors in your code and help refactor it for better structure and readability.
• 📝 **Code Documentation**: The AI can automatically add comments and documentation to your code, making it easier for understanding and maintenance.
• ⏰ **Efficiency and Speed**: With Llama 3, you can significantly reduce the time spent on coding tasks, creating a functional API that interacts with a database in minutes.
• 📈 **Quality Improvement**: Leveraging AI in coding reduces the likelihood of errors and enhances the overall quality of the codebase.

Q & A

What is the main purpose of integrating Llama 3 into VSCode?

The main purpose is to enhance productivity by automating code writing, fixing, and refactoring, which leads to increased code quality and reduced errors.

How does Llama 3 help in preventing reduced productivity and code quality when coding manually?

Llama 3 acts as a code companion in VSCode, allowing users to generate boilerplate code, fix errors, and refactor code on the fly, thus preventing the mentioned issues.

What is the first step to start using Llama 3 with VSCode?

The first step is to download and install VSCode if not already installed, and then download Llama from the specified website.

How can one search for and install the Code GPT extension in VSCode?

In VSCode, click on the extension icon on the left-hand side, search for 'Code GPT', select the option with 1 million downloads, and then install it.

What settings need to be configured for the Code GPT extension after installation?

After installation, click on the extension settings icon, choose 'Olama' as the provider from the dropdown list, enable 'Code GPT Co-Pilot', and select 'Ollama Llama 3' for auto-complete.

How does the process of downloading Llama 3 models work in the terminal?

In the terminal, type 'o Lama P llama 38b' and press enter, followed by 'o Lama pull llama 3 instruct' to download the necessary models.

What is the benefit of using the Llama 38b model in coding?

The Llama 38b model is a powerful AI model that assists in generating, fixing, and refactoring code, making the coding process more efficient and less prone to errors.

How can one create a new file in VSCode for coding?

On the left-hand side of the VSCode interface, click the icon to create a new file, name it (e.g., 'app.py'), and then press enter.

What does the Code GPT icon on the left-hand side of VSCode allow users to do?

The Code GPT icon allows users to select the provider (Olama) and choose the model (Llama 38b) to start generating and working with code.

How can Llama 3 assist in generating a Flask API code?

By selecting the Llama 38b model through the Code GPT interface and asking for a 'Flask API code', Llama 3 will generate a response with an example code snippet that can be used as a starting point.

What is the process to connect the generated code to a SQL Lite database?

After generating the initial code, select the code, go back to the Code GPT interface, and ask to connect the data to a SQL Lite database. The AI will provide code to facilitate this connection.

How can users fix errors in their code using Llama 3?

Users can select the erroneous part of the code, click the home button in the Code GPT interface, and choose the 'Fix bug in selected code' option to automatically identify and correct the error.

What is the benefit of refactoring code using Llama 3?

Refactoring code with Llama 3 improves the structure and readability of the code, making it easier to understand and maintain.

How can Llama 3 assist in documenting the code?

By selecting the code and using the 'Document selected code' feature in the Code GPT interface, Llama 3 can automatically add relevant comments to the code for better understanding.

Outlines

00:00

🚀 Integrating Llama 3 with VS Code for Enhanced Productivity

This paragraph introduces the integration of Llama 3, an AI companion, with Visual Studio Code (VS Code) to improve coding efficiency. It contrasts manual coding, which is time-consuming and error-prone, with the benefits of using AI to generate boilerplate code, fix errors, and refactor code on the fly. The speaker expresses excitement about demonstrating how to implement AI in VS Code and invites viewers to subscribe to their YouTube channel for more content on Artificial Intelligence. The process of downloading VS Code, installing the Olama extension, and setting it up with Llama 3 is outlined step by step. The paragraph concludes with a demonstration of how to use the AI to generate a Flask API, connect it to a SQLite database, fix errors, and refactor code.

05:00

📚 Documenting and Refactoring Code with Llama 3 in VS Code

The second paragraph focuses on the advanced features of Llama 3 within VS Code, such as refactoring and documenting code. It demonstrates how to refactor selected code with ease and how to add relevant comments to the code for better understanding. The paragraph also shows how to quickly create a functional API that interacts with a database and responds to user queries within a short timeframe. The speaker expresses enthusiasm about the capabilities of Llama 3 and hints at creating more videos on similar topics. The paragraph ends with a call to action, encouraging viewers to like, share, and subscribe to the channel.

Keywords

Llama 3

Llama 3 is an AI model mentioned in the video that can be integrated into Visual Studio Code (VSCode) to enhance coding productivity. It is used to generate code, fix errors, and refactor code on the fly, which significantly improves the efficiency and quality of the code written by developers.

VSCode

VSCode, or Visual Studio Code, is a popular code editor used by developers worldwide. It is known for its rich ecosystem of extensions and support for a wide range of programming languages. In the context of the video, VSCode is the platform where the Llama 3 AI is integrated to assist with coding tasks.

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 used as a code companion within VSCode to automate and streamline various coding processes, such as generating boilerplate code, fixing bugs, and refactoring.

Code Generation

Code generation is the process of automatically creating code using AI. In the video, Llama 3 is used to quickly generate boilerplate code for a Flask API, which is a significant time-saver and productivity booster for developers.

Code Refactoring

Refactoring is the process of restructuring existing computer code without changing its external behavior. In the context of the video, Llama 3 assists in refactoring code to improve its readability, structure, and maintainability, which is crucial for long-term code health.

Code Fixing

Code fixing involves correcting errors or bugs in the code. The video demonstrates how Llama 3 can identify and fix errors, such as a missing semicolon, within the selected code block, which is a valuable feature for maintaining code quality.

SQL Light Database

A SQL Light database is a type of database management system that uses Structured Query Language (SQL) for managing data. In the video, the AI is used to generate code that connects a Flask API to a SQL Light database, showcasing the AI's ability to handle database integration.

Flask API

A Flask API is a web application that uses the Flask framework to handle HTTP requests and provide responses. The video uses the creation of a Flask API as an example to demonstrate how Llama 3 can generate and modify code to interact with databases and respond to user queries.

Documentation

Documentation in coding refers to the process of adding comments and explanations to the code to make it more understandable. The video shows how Llama 3 can automatically document selected code by adding relevant comments, which is essential for code maintenance and collaboration.

Extensions

Extensions in VSCode are add-ons that extend the functionality of the editor. The video guides viewers on how to install the Code GPT extension, which integrates Llama 3 into VSCode, allowing users to utilize AI capabilities within their development environment.

Productivity

Productivity in the context of the video refers to the efficiency and effectiveness of a developer's work. By using Llama 3 in VSCode, developers can increase their productivity by automating repetitive tasks, reducing errors, and improving code quality.

Highlights

Integrate Llama 3 into VS Code to boost productivity.

Download Llama 3 locally to create a private co-pilot without AI.

Manual coding without AI leads to reduced productivity and increased errors.

Use Llama 3 to get code explanations, refactoring, and documentation within VS Code.

Visual Studio Code is a popular code editor that can be enhanced with AI.

Create quick boilerplate code, fix code, and refactor with AI assistance.

Increase productivity, code quality, and reduce errors with AI integration.

Step-by-step guide on implementing AI in VS Code with Llama 3.

Subscribe to the YouTube channel for more AI-related content.

Download VS Code and Olama for setting up the AI co-pilot.

Search for 'Code GPT' in the VS Code extensions to install the necessary tool.

Enable Code GPT co-pilot and select 'Olama' as the provider for AI assistance.

Download Llama 3 models 'llama 38b' and 'llama 3 instruct' for functionality.

Create a file in VS Code and start coding with AI-generated boilerplate.

AI can generate a Flask API code as a starting point for development.

Connect and import data to a SQLite database using AI-generated code.

Directly connect code to a SQLite database with AI assistance.

AI can identify and fix errors in the selected code.

Refactor code easily using AI and insert it back into the project.

Document code with relevant comments using AI for better understanding.

Complete API development to interact with the database and respond to user queries in minutes.