Open-Source AI Agent Can Build FULL STACK Apps (FREE “Devin” Alternative)
TLDRIn this video, the creator demonstrates how to build a full-stack application using the AI platform GPT pilot, now known as Pythagora. The process is simplified with an open-source command line interface and the Visual Studio Code plugin. The video showcases the installation process, setting up the environment, and adding features like user dashboard avatars and sound notifications for chat messages. The creator emphasizes the time-saving benefits and cost-effectiveness of using Pythagora for rapid application development, even for non-developers.
Takeaways
- 🚀 The video discusses building a full-stack application using the latest functionalities of GPT and Pythagora (formerly GPT Pilot).
- 📋 The process begins by installing the command line interface version of GPT Pilot and setting up the environment with VNV for Python.
- 🔄 The script outlines cloning a repository, changing directory, and managing the Python environment for the project.
- 📦 The video demonstrates installing project requirements and setting up an environment file for the application.
- 🔧 The use of the VS Code plugin for Pythagora is highlighted, which simplifies the interaction with the AI and the development process.
- 🔑 The importance of using an API key from OpenAI and setting up the endpoint for GPT 4 is emphasized.
- 💬 The application development process is interactive, with the AI refining the project idea and defining the functional specifications.
- 👥 The video describes creating a real-time chat application that allows multiple participants and includes features like user names, message history, and emoji support.
- 🔄 The AI assists in iterating on the codebase, adding features like user avatars and sound notifications for received messages.
- 🛠️ Debugging is made easier with AI support, guiding through the process of identifying and fixing issues in the code.
- 💰 The cost of using GPT tokens for building the application is discussed, with the video creator highlighting the time and financial savings.
- 📌 The video concludes by encouraging viewers to explore Pythagora for their development needs and provides links for further engagement.
Q & A
What is the main topic of the video?
-The main topic of the video is about building a full-stack application using AI, specifically with the open-source tool GPT pilot (now known as Pythagora).
What are the key features of the chat application that the creator wants to build?
-The key features of the chat application include real-time chat between two people through the browser, a chat history, emoji support, message timestamps, and spam flagging.
How does the creator plan to handle user accounts for the chat application?
-The creator plans to skip user accounts and allow users to set their names temporarily for each chat session, making it a free-for-all chat environment.
What is the role of the Pythagora VS Code plugin?
-The Pythagora VS Code plugin allows users to interact with AI to build and iterate on codebases, providing a seamless development experience with features like code writing, reviewing, and debugging.
How does the AI assist in debugging issues in the application?
-The AI assists in debugging by asking a series of questions to narrow down the issue, suggesting code changes, and providing step-by-step instructions for testing and verifying the fixes.
What additional features does the creator plan to add to the chat application?
-The creator plans to add features such as displaying user avatars on the user dashboard and implementing sound notifications for incoming chat messages.
How does the AI handle the development process for adding new features?
-The AI handles the development process by first understanding the requirements, suggesting code changes, reviewing the code, and then asking the user to verify and test the changes in a step-by-step manner.
What is the significance of using an open-source model like GPT 4?
-Using an open-source model like GPT 4 allows for flexibility in choosing the AI service provider and potentially reduces costs by using freely available models or by replacing the endpoint with another service that matches the required interface.
How much did it cost to build a full-stack application in the creator's previous video?
-In the creator's previous video, it cost about $10 to $12 to build a full-stack application using GPT tokens.
What is the role of the Code Monkey agent in the development process?
-The Code Monkey agent is responsible for writing and updating the code based on the user's instructions and AI suggestions, as well as reviewing the code changes.
How does the AI ensure that the user is satisfied with the implemented features?
-The AI ensures user satisfaction by providing a human test phase where the user can verify the functionality of the implemented features and make sure they work as expected before moving on to the next task.
Outlines
🚀 Introduction to Full Stack Application with AI
The video begins with the creator expressing excitement about the new functionalities of GPT, now known as pythagora, which simplifies the process of building full stack applications. The creator plans to demonstrate the installation of the command line interface version of pythagora, which is open source and free. The video is sponsored by pythagora, formerly GPT pilot, and the creator intends to show how to clone the repository, set up the environment, and install the necessary requirements. The process includes navigating to a specific folder, cloning the repo, changing directory, and initializing the database. The creator also mentions the ability to use different open source models and the importance of the API key for using GPT 4.
🛠️ Building a Real-Time Chat Application
In this segment, the creator shifts focus to building a real-time chat application using pythagora, aiming to allow two people to chat with each other through the browser. The creator discusses the need for technologies like websockets and the decision to use Node.js as the framework. The project is named 'chat app', and the creator provides detailed specifications for the app, including the ability for users to set temporary names, store conversation history, and use emojis. The creator also considers future possibilities of allowing multiple participants and implementing spam prevention measures. The AI assists in refining the project idea and developing a functional specification.
🔧 Debugging and Feature Addition to an Existing Application
The creator demonstrates how to add new features to an existing application built with pythagora. They discuss the need to update the user dashboard to display avatars and to add sound notifications for received messages in chat rooms. The creator interacts with the AI to identify and fix a bug related to avatar URL processing on the front end. The AI provides a step-by-step debugging process, leading to the successful display of the avatar image. The creator then proceeds to add sound notifications for incoming chat messages, again with the assistance of the AI, and tests the feature across different web browsers.
🎉 Conclusion and Appreciation for pythagora
The creator concludes by showcasing the ease of adding new features to an existing application using pythagora. They emphasize the seamless integration of AI in the development process, which simplifies both building an application from scratch and iterating on existing code. The creator expresses gratitude to pythagora for sponsoring the video and encourages viewers to check out their open-source project and engage with their community on Discord. The video ends with a call to action for viewers to like and subscribe for more content.
Mindmap
Keywords
💡Full Stack Application
💡GPT Pilot
💡Open Source
💡VS Code Plugin
💡Node.js
💡WebSockets
💡Database
💡API Key
💡Environment Variables
💡Real-Time Chat
💡Emoji Support
Highlights
The video discusses the creation of a full-stack application using AI, specifically GPT Pilot (now Pythagora), which has been updated with additional functionality.
The new interface of Pythagora is easier to use, and the agents work better, allowing for the addition of features to applications.
Pythagora is completely open source and free to use, which is a significant advantage for developers and creators.
The video provides a step-by-step guide on how to install Pythagora's command line interface version and set up the environment for development.
The process of cloning the repository and managing the Python environment with VNV is detailed, providing clarity for users unfamiliar with these steps.
The video demonstrates how to install all the necessary requirements for the project using pip, simplifying the setup process.
The renaming of the example environment file to 'M' is shown, which will be used for the project setup.
The importance of entering the API key and endpoint for OpenAI is emphasized, as it is crucial for connecting to the GPT-4 model.
The video outlines the process of initializing the database and starting the application, which is a key part of setting up the full-stack application.
The concept of the chat application is introduced, aiming to allow real-time communication between users without the need for user accounts.
The AI assists in refining the project idea by suggesting features such as emoji support, message history, and spam flagging.
The video highlights the ability to iterate on existing code bases using the Pythagora VS Code plugin, showcasing its practical application for developers.
The cost-effectiveness of using Pythagora for building full-stack applications is discussed, with the previous project costing around $10-$12.
The video demonstrates the debugging process with AI, showing how it can assist in resolving issues with the application's code.
The addition of new features such as avatar display and sound notifications for chat messages is shown, illustrating the iterative development process.
The video emphasizes the seamless integration of AI in the development process, from building the application to adding new features and debugging.
