Aider + Llama-3.1 (405B) + NextJS + Supabase : Generate FULL-STACK Apps with Llama-3.1 405B for FREE
TLDRIn this video, the creator explores the capabilities of the Llama-3.1 405B model with Aider to develop a full-stack application for free. Using NextJS and Supabase, the goal is to build a task management board similar to Trello within the constraints of 20 prompts. Despite numerous errors and the need for manual intervention, the final product is functional but lacks the seamless experience of other models like Claude 3.5 Sonet. The creator concludes that the Llama-3.1 405B model is not recommended for application development due to its context accuracy issues and suggests alternatives like Deepseek for better results.
Takeaways
- 😀 The video is about using the Llama-3.1 405B model with Aider to create production-ready applications for free.
- 🤖 The presenter aims to test if the 405B model can create applications as efficiently as other frontier models like Claude 3.5 Sonet.
- 🚀 The video demonstrates the process of using the Aider API with Together AI for application development.
- 📝 The presenter chooses to use NextJS and Supabase for the project, which is a common choice for full-stack app generation.
- 🔨 The project goal is to create a simple command-style project task management board similar to Trello.
- 🎯 The presenter limits the use to 20 prompts to challenge the model's capability, as it takes the same number with Claude.
- 🛠️ The video includes troubleshooting steps when the application encounters errors during development.
- 🔄 The presenter experiences issues with authentication and routing, which require manual intervention to fix.
- 💻 The final application is a single-page app with drag-and-drop functionality for task management.
- 🎨 The video also covers enhancing the app's aesthetics with a glassy effect and background animations.
- 🚨 The presenter concludes that the experience with Llama-3.1 405B was not as good as with Claude, due to frequent errors and context accuracy issues.
- 📉 The video suggests that other models like Deep Seek might be better for app creation and are more cost-effective compared to Llama-3.1 405B.
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 creator host the 45b model?
-The creator can't host the 45b model because it requires significant resources, which are presumably not available to the creator, unlike someone like Zuckerberg who has the necessary resources.
What API does the creator plan to use for the Llama-3.1 405B model?
-The creator plans to use the together AI API for the Llama-3.1 405B model because it offers a free credit which should be sufficient to test the model's capabilities.
What is the project the creator is building in the video?
-The creator is building a simple Kanban-style project task management board, similar to Trello, using NextJS and Supabase.
How many prompts does the creator limit the application creation to?
-The creator limits the application creation to 20 prompts, as it takes that number to create something fully working with Claude.
What issues did the creator encounter while creating the application?
-The creator encountered multiple errors, including problems with authentication and issues with generating and routing multiple pages correctly. The context accuracy of the Llama-3.1 405B model was not as good as expected.
How did the creator address the authentication issue in the application?
-The creator initially asked AER to fix the authentication issue, but when it persisted, they decided to remove the authentication part to get the application working.
What additional features did the creator ask AER to implement?
-The creator asked AER to implement a drag and drop system for moving tasks between boards and to enhance the visual appeal of the application with a 'cool' glassy effect and background animation.
What was the final outcome of the application creation process?
-The final outcome was a one-page application with a drag and drop feature for tasks between boards. However, the creator expressed dissatisfaction with the experience due to numerous errors and the model's inability to handle multiple pages effectively.
What recommendation does the creator have regarding the use of the Llama-3.1 405B model for application creation?
-The creator does not recommend using the Llama-3.1 405B model for application creation due to the issues encountered and suggests that other models like Claude 3.5 Sonet or Deepseek might be better and cheaper alternatives.
Outlines
🤖 Testing Llama 3.1 405b Model with AER for Application Development
The video begins with the host expressing excitement about testing the Llama 3.1 405b model in conjunction with AER to determine if it can create production-ready applications comparable to Claude 3.5 Sonet. The host plans to use the model exclusively, leveraging the Together AI API for free credits. 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 and database structure for Superbase. Despite initial errors, the host interacts with AER to troubleshoot and advance the project.
🛠️ Challenges and Conclusions from Developing with Llama 3.1 405b Model
In the second paragraph, the host discusses the challenges faced while developing the application using the Llama 3.1 405b model. Despite multiple attempts and interventions to fix errors, the host finds the experience frustrating, particularly with issues related to context accuracy and page routing. The host contrasts this with the superior performance of Claude 3.5 Sonet, which was able to create a more complex application with fewer prompts and less intervention. The final product, while functional, is described as lacking in aesthetics and complexity. The host concludes by advising against the use of the Llama 3.1 405b model for application development due to its limitations and recommends alternatives like Deepseek for a more cost-effective and efficient experience. The video ends with a call to action for feedback and support for the channel.
Mindmap
Keywords
💡Aider
💡Llama-3.1 405B
💡NextJS
💡Supabase
💡API Key
💡Environment Variable
💡Task Management Board
💡Prompts
💡Drag and Drop
💡Authentication
💡Context Accuracy
Highlights
Introduction to creating production-ready applications with Llama-3.1 405B model.
Comparison of Llama-3.1 405B with frontier models like GPT 40 and Claude.
Utilization of the together AI API for free credit and testing purposes.
Decision to use NextJS and Supabase for application development.
Limitation to 20 prompts to match the efficiency of Claude's application creation.
Instructions on obtaining API key from together AI and setting up AER.
Creating a NextJS project and configuring environment variables for AER.
First prompt to Llama-3.1 405B for generating initial code and database structure.
Encountering and resolving errors in the application setup.
Implementation of a drag and drop system for task management.
Aesthetic enhancements to improve the user interface of the application.
Challenges faced with authentication and context accuracy in the model.
Comparison of Llama-3.1 405B with Claude 3.5 Sonet in terms of context retention and routing.
Final application outcome with a simple task management board and drag-and-drop functionality.
Discussion on the overall experience and recommendation against using Llama-3.1 405B for full-stack app creation.
Mention of Deep Seek as a more cost-effective alternative for application creation.
Call to action for viewer feedback, donations, likes, and subscriptions.
