Aider + Llama-3.1 (405B) + NextJS + Supabase : Generate FULL-STACK Apps with Llama-3.1 405B for FREE
TLDRIn this video, the creator explores using the Llama-3.1 405B model with Aider to develop production-ready applications, comparing it to Claude 3.5 Sonet. They attempt to build a task management board with NextJS and Supabase, limited to 20 prompts. Despite facing numerous errors and needing to intervene, they manage to create a functional single-page app with drag-and-drop features. However, they conclude that the Llama-3.1 405B model falls short in context accuracy and recommend alternatives like Deepseek for better cost-effectiveness and ease of use.
Takeaways
- 😀 The video explores using the Llama 3.1 405B model with Aider to create production-ready applications.
- 🔍 The creator compares Llama 3.1 to other frontier models like GPT 40 and Claude, aiming to test its capabilities.
- 🚀 The video uses the Together AI API for the Llama 3.1 model, leveraging a free credit for the experiment.
- 💻 The project involves creating a NextJS and Supabase-based task management board, similar to Trello.
- 📝 The creator limits the use of prompts to 20, a benchmark set based on previous experiences with Claude.
- 🛠️ Initial setup includes obtaining an API key from Together AI and configuring Aider with environment variables.
- 💡 The first task is to create a NextJS project and configure Aider to interact with the Llama 3.1 model.
- 🔧 The video demonstrates troubleshooting errors and fixing issues with the application's code and structure.
- 🎨 Aider is used to enhance the application's UI, adding a glassy effect and animations for a more appealing design.
- 🚨 The creator notes significant challenges with error fixing and context accuracy, suggesting Llama 3.1 may not be ideal for complex app development.
- 👎 The final verdict is that the Llama 3.1 405B model is not recommended for full-stack app development due to its limitations and the availability of better alternatives like Claude 3.5 Sonet.
Q & A
What is the main purpose of the video?
-The main purpose of the video is to test the capabilities of the Llama-3.1 405B model with AER to create production-ready applications and compare its performance with other frontier models like GPT 40 and Claude.
Why can't the host use the full 45B model of Llama-3.1?
-The host can't use the full 45B model because of its size and resource requirements, which are beyond the host's capabilities, but they can use the API which is sufficient for testing purposes.
What is the free credit provided by Together AI used for?
-The free credit provided by Together AI is used to access and test the Llama-3.1 405B model API without incurring any cost.
What technologies will the host be using to create the application?
-The host will be using NextJS and Supabase to create the application, which is a common choice for full-stack application development.
What type of application is the host planning to create?
-The host is planning 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 themselves to for creating the application?
-The host limits themselves to creating the application with only 20 prompts, as that's the number it takes them to create something fully working with Claude.
What issue did the host encounter when trying to run the application for the first time?
-The host encountered an error when trying to run the application for the first time, which they had to ask AER to fix.
Why did the host have to remove the authentication part of the application?
-The host had to remove the authentication part because it was causing issues and breaking the application, despite multiple attempts to fix it through AER.
What feature did the host ask AER to add to improve the user interface of the application?
-The host asked AER to add a drag and drop system to improve the user interface of the application, making it more interactive.
What was the host's final assessment of the Llama-3.1 405B model's performance in creating the application?
-The host's final assessment was that the experience was not good, with too many errors and issues, especially with context accuracy and page routing. They wouldn't recommend using the Llama-3.1 405B model for this task.
Outlines
🤖 Exploring Llama 3.1 405b Model with AER for Application Development
The video starts with the host's excitement about testing the Llama 3.1 405b model using the AER API to determine if it can create production-ready applications like 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 task management board using Next.js and Superbase, with a goal to complete it in only 20 prompts, mirroring 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, with subsequent steps addressing errors and refining the application's functionality and aesthetics.
🛠️ Challenges and Reflections on Developing with Llama 3.1 405b Model
The second paragraph delves into the host's experience developing with the Llama 3.1 405b model, highlighting the numerous challenges faced. Despite the model's potential, the host encountered persistent errors, particularly with authentication and page routing, which required manual intervention to resolve. The host expresses dissatisfaction with the model's context accuracy and its inability to handle multiple pages effectively, contrasting it with the superior performance of Claude 3.5 Sonet. The final product, while functional, is described as lacking in complexity and polish compared to what could be achieved with Claude. The host concludes by advising against the use of the Llama 3.1 405b model for application development due to its limitations and comparable costs, suggesting alternatives like Deepseek for more efficient and cost-effective results. The video ends with a call to action for feedback, support, and subscription to the channel.
Mindmap
Keywords
💡Aider
💡Llama-3.1 (405B)
💡NextJS
💡Supabase
💡API Key
💡Environment Variable
💡Prompts
💡Task Management Board
💡Drag and Drop
💡Authentication
💡Context Accuracy
Highlights
Introduction to a video on using the 405B model with AER to create production-ready applications.
Comparison of the 405B model with frontier models like GPT 40 and Claude 3.5 Sonet for application creation.
Utilization of the together AI API for the 405B model due to free credit availability.
Explanation of the process to install and configure AER with the together AI API.
Creation of a NextJS project for the application development.
Initiation of the application development with the first detailed prompt to AER.
Instructions on creating an environment variable for the Open AI base URL and Together AI API key.
Development of a simple conand-style project task management board similar to Trello.
Limitation of the development process to 20 prompts to match the efficiency of Claude.
Encountering and resolving errors during the development process with AER's assistance.
Implementation of a drag and drop system for task management via AER's prompt.
Aesthetic enhancement of the application's interface with a glassy effect and animations.
Challenges faced with authentication and routing in the application development.
Finalization of the application with a simple one-page design and drag-and-drop functionality.
Reflection on the overall development experience with the 405B model, highlighting its limitations.
Comparison of the 405B model's performance with Claude 3.5 Sonet and other models in terms of context accuracy and cost.
Recommendation against using the Llama 3.1 405B model for full-stack application development due to its drawbacks.
Invitation for viewers to share their thoughts and support the channel through donations and subscriptions.