Aider + Llama-3.1 (405B) + NextJS + Supabase : Generate FULL-STACK Apps with Llama-3.1 405B for FREE

AICodeKing
26 Jul 202408:08

TLDRIn this video, the creator explores using the 405B model of Llama 3.1 with AER to develop full-stack apps for free, comparing it to Claude 3.5 Sonet. They attempt to build a task management board with NextJS and Supabase, limited to 20 prompts. Despite initial errors and issues with authentication and routing, they manage to create a functional, albeit simple, one-page application with drag-and-drop features. The creator concludes that Llama 3.1's context accuracy is lacking compared to Claude, and recommends against using it for app development due to the similar cost and superior alternatives like Deepseek.

Takeaways

  • 😀 The video is about using the Llama-3.1 405B model with Aider to create production-ready applications for free.
  • 🤖 The creator is excited to test if the 405B model can produce applications as capable as Claude 3.5 Sonet.
  • 🚀 The 405B model is chosen for its potential and because it's the most used variant, but it cannot be hosted due to size limitations.
  • 💻 The video demonstrates using the together AI API for the Llama-3.1 model, which offers a free credit for testing.
  • 🛠 The project involves creating a simple command-style project task management board using NextJS and Supabase.
  • 📝 The creator limits the use to 20 prompts, a similar approach to creating with Claude, to check the model's capabilities.
  • 🔑 The process includes getting an API key, installing Aider, configuring it with the together AI API, and setting up the environment.
  • 💡 The video shows the initial setup of a NextJS project and the use of Aider to generate code and database structures.
  • 🛑 The creator encounters several errors during the development process, which are addressed by asking Aider for fixes.
  • 🔄 Despite issues with authentication and routing, the final application allows for task management and drag-and-drop functionality.
  • 🎨 The video also covers enhancing the user interface with a glassy effect and animations for a cooler look.
  • 👎 The overall experience with the Llama-3.1 405B model is considered not good due to frequent errors and context accuracy issues.
  • 📉 The video concludes that the Llama-3.1 405B model is not recommended for full-stack app creation compared to other models like Claude 3.5 Sonet or Deepseek.

Q & A

  • What is the main focus of the video?

    -The main focus of the video is to explore the capabilities of the Llama-3.1 405B model with AER to create production-ready applications and compare it with other frontier models like GPT 40 and Claude.

  • Why can't the host use the 45b model directly?

    -The host can't use the 45b model directly because of its size and resource requirements, which are beyond the host's capabilities, but they can use the API for the model.

  • What API does the host decide to use for the Llama-3.1 405B model?

    -The host decides to use the together AI API for the Llama-3.1 405B model because it provides a free credit, which should be sufficient for testing purposes.

  • What is the programming language and framework used in the video?

    -The programming language and framework used in the video are JavaScript with NextJS and Supabase.

  • What type of application is the host trying to create?

    -The host is trying to create a simple Kanban-style project task management board, similar to Trello, to test the capabilities of the Llama-3.1 405B model.

  • How many prompts does the host limit the creation process to?

    -The host limits the creation process to 20 prompts, as that's the number it takes to create something fully working with Claude.

  • What issue did the host encounter with the initial setup of the project?

    -The host encountered an error during the initial setup of the project, which was related to a file that was supposed to be imported but was never created.

  • What feature did the host ask AER to implement that was not initially present?

    -The host asked AER to implement a drag and drop system for moving tasks between boards, which was not initially present in the application.

  • What aesthetic changes did the host request for the application?

    -The host requested to make the application look cooler with a glassy effect and additional background animation, as well as making the ad form appear with an animation.

  • What was the host's final assessment of the Llama-3.1 405B model for application development?

    -The host's final assessment was that the experience with the Llama-3.1 405B model was not good due to numerous errors and issues with context accuracy, and they would not recommend it for application development tasks.

  • What alternative did the host suggest for creating applications?

    -The host suggested using Deep Seek as an alternative for creating applications, as it is better and cheaper than the Llama-3.1 405B model and even GPT-40.

Outlines

00:00

🤖 Testing Llama 3.1 405b Model with AER for Application Development

The video begins with the host's excitement about experimenting with the Llama 3.1 405b model using the AER API to determine if it can create production-ready applications comparable to Claude 3.5 Sonet. The host plans to use the 405b model exclusively, leveraging a free credit from the together AI API. The project involves creating a simple Kanban-style task management board using Next.js and Superbase, with a self-imposed limit of 20 prompts to mirror the efficiency of Claude. The host guides viewers through setting up the environment, installing AER, configuring it with the together AI API, and initiating a Next.js project. The first prompt is sent to AER to generate the initial code structure for the Superbase tables, which, after some back-and-forth with AER to fix errors, eventually leads to a working application framework.

05:03

🛠️ Challenges and Reflections on Developing with Llama 3.1 405b Model

In the second paragraph, the host discusses the challenges faced while developing the application with the Llama 3.1 405b model. Despite the model's potential, the host encounters numerous errors, many of which require manual intervention to resolve. The host notes that the model struggles with context accuracy, particularly in creating and linking multiple pages, which contrasts with the superior performance of the Claude 3.5 Sonet model. After several attempts and fixes, including removing problematic authentication parts and enhancing the UI with a drag-and-drop feature and aesthetic improvements, the host concludes that the Llama 3.1 405b model is not recommended for application development due to its high error rate and lack of context retention. The host suggests Deepseek as a more cost-effective alternative for application creation. The video ends with a call for viewer feedback and an invitation to support the channel.

Mindmap

Keywords

💡Aider

Aider is a code interpreter and AI assistant designed to help developers write and debug code. In the context of this video, Aider is used in conjunction with the Llama-3.1 405B model to attempt the creation of a full-stack application. The script mentions installing Aider and configuring it with the Together AI API, which is central to the video's demonstration of generating code.

💡Llama-3.1 405B

Llama-3.1 405B refers to a specific model of an AI language model, presumably with the capacity of 405 billion parameters. The video aims to test this model's ability to generate production-ready applications, comparing its performance with other advanced models like GPT-40 and Claude. The script discusses using the 405B model via the Together AI API for the task at hand.

💡NextJS

NextJS is a popular React framework for building user interfaces and web applications. In the video, the creator uses NextJS as the frontend technology for developing the task management board application. The script describes the process of creating a NextJS project and integrating it with the AI-generated code.

💡Supabase

Supabase is an open-source alternative to Firebase that provides backend services for web and mobile applications. The video script mentions using Supabase to create and manage the database for the application being developed, highlighting its role in full-stack application development.

💡API

API stands for Application Programming Interface, which is a set of rules and protocols that allows different software applications to communicate with each other. The video discusses using the Together AI API to access the Llama-3.1 405B model, emphasizing the importance of APIs in leveraging AI capabilities.

💡Environment Variable

Environment variables are used in programming to store information that can affect the way an application runs. In the script, the creator sets environment variables for the OpenAI base URL and the Together AI API key, which are crucial for configuring Aider to work with the Llama-3.1 405B model.

💡Task Management Board

A task management board is a tool used to organize and track tasks, often visually represented in a format similar to Trello. The video's main project is a simple 'Kanban-style' task management board, which serves as a test case for the AI's ability to generate a functional application.

💡Prompts

In the context of AI, prompts are the inputs or questions given to the model to generate responses or perform tasks. The script mentions limiting the creation of the application to 20 prompts, which is a constraint set to compare the efficiency of the Llama-3.1 405B model with other models like Claude.

💡Drag and Drop

Drag and drop is a user interface feature that allows users to move items within a graphical interface by clicking, holding, dragging, and releasing them. The video script describes adding a drag and drop system to the task management board as an enhancement requested from Aider.

💡Authentication

Authentication is the process of verifying the identity of a user or device. In the script, the creator encounters issues when implementing authentication in the application, which leads to multiple errors and the need for Aider to fix them.

💡Context Accuracy

Context accuracy refers to the ability of an AI model to correctly understand and retain the context of a conversation or task over multiple interactions. The video script discusses the Llama-3.1 405B model's struggle with context accuracy, especially when compared to the Claude 3.5 Sonet model.

Highlights

Introduction of a new video exploring the capabilities of Llama-3.1 405B model with AER for full-stack app development.

Comparison of Llama-3.1 405B with frontier models like GPT 40 and Claude to assess its ability to create production-ready applications.

Utilization of the together AI API for the 405B model due to free credit availability, enabling a cost-free trial.

Choice of NextJS and Supabase as the development stack for the project, aligning with the creator's usual practices.

The project's goal is to create a simple Kanban-style project task management board, similar to Trello.

Limitation of using only 20 prompts to build the application, a challenge to match the efficiency of Claude.

Instructions on obtaining an API key from the together AI site and setting up the AER environment.

Creation of a NextJS project and the initial setup for AER with the Llama 3.1 405B model.

First prompt to AER for generating the initial code and structure for Supabase tables.

Encountering and resolving an error during the application run by interacting with AER.

The necessity to manually fix issues due to AER's inability to resolve errors autonomously.

Implementation of a drag and drop system for task management through AER's assistance.

Aesthetic enhancement of the application's interface with a glassy effect and animations.

Further customization of the application to improve its visual appeal and user experience.

Challenges faced with authentication integration and the model's context accuracy issues.

Comparison of the Llama-3.1 405B model's performance with Claude 3.5 Sonet, highlighting the latter's superior context retention.

Recommendation against using the Llama-3.1 405B model for full-stack app development due to its limitations and cost.

Invitation for viewers to share their thoughts in the comments and to support the channel through donations and subscriptions.