Build ENTIRE Apps With A Single Prompt - FREE Open-Source Devika Tutorial

Matthew Berman
3 Apr 202412:26

TLDRThe video showcases the rapid development of an AI coding assistant named DEA, which is a fully-featured open-source clone of Devon. The assistant is designed to facilitate AI-assisted coding, offering a user interface that includes a chat, a browser, and a terminal for logs. The video demonstrates the creation of a simple calculator app using DEA and highlights its capabilities, such as supporting various models and search engines. The tutorial also guides viewers on how to install and use DEA, emphasizing its potential for growth despite some current bugs. The presenter expresses excitement about the future of AI coding assistants and encourages viewers to support the project.

Takeaways

  • 🚀 Successfully recreated one of Devon's main demos in DEA, showcasing its capabilities as an AI coding assistant.
  • 🌟 DEA is an open-source clone of Devon, offering a fully featured platform for AI-assisted coding with continuous improvements.
  • 💻 The interface combines a chat on the left and a browser/terminal on the right, providing a comprehensive environment for coding with AI.
  • 🔧 Early project status with a rapidly evolving interface, now more functional and supporting more models and search engines.
  • 🛠️ Demonstrated building a calculator app with a UI using zero-shot prompting, highlighting the ease of use and AI's planning capabilities.
  • 📈 Mentioned potential race condition issues with certain models like Gro, indicating areas for future optimization.
  • 🔍 Supports various models including Claud, Gemini, Mistol, and Open AI's GPT 4 and 3.5, offering diverse options for users.
  • 📝 Provided a step-by-step guide on installing and using DEA, including setting up the environment and selecting models and search engines.
  • 🔗 Showed how to integrate with Google search and other services for a more enhanced experience.
  • 💡 Highlighted the potential of running DEA projects completely locally using models like olama, for offline functionality.
  • 🎥 The video serves as both a demonstration of DEA's capabilities and a tutorial on how to set up and use the AI coding assistant effectively.

Q & A

  • What is the main topic of the video?

    -The main topic of the video is the demonstration and installation process of an AI coding assistant called DEA, which is an open-source clone of Devon.

  • What does DEA stand for?

    -The video does not explicitly state what DEA stands for, but it refers to it as an AI coding assistant similar to Devon.

  • What are some of the features of the DEA interface?

    -The DEA interface features a chat on the left, a browser and terminal on the right, logs for visibility, and settings for customization.

  • How has the DEA project evolved recently?

    -The DEA project has evolved rapidly, with improvements in the interface design, support for more models and search engines, and overall progress in a short period of time.

  • What application does the presenter build to demonstrate DEA's capabilities?

    -The presenter builds a simple calculator application with a UI to demonstrate DEA's capabilities in coding with AI.

  • What are some of the models and search engines supported by DEA?

    -DEA supports models like Claud, Gemini Gro, and Mistol, and allows users to select different search engines, including Google.

  • What is the process for installing DEA?

    -The installation process involves cloning the DEA GitHub repository, creating a new Python environment, installing required packages, and setting up the backend and frontend servers.

  • What issue did the presenter encounter with the Game of Life project?

    -The presenter encountered a Playwright Sync API issue when trying to run the Game of Life project with the Gro model, which they suspected was due to a race condition.

  • How can DEA be run completely locally?

    -DEA can be run completely locally by installing and using the local models like Mistol through the Olamin server and configuring the environment variables accordingly.

  • What was the presenter's overall impression of the DEA project?

    -The presenter was impressed with the rapid progress and potential of the DEA project, despite acknowledging that it is still a bit buggy.

  • How does the presenter conclude the video?

    -The presenter concludes the video by expressing excitement for the future of AI coding assistants and thanks the DEA team and contributors for their work on the project.

Outlines

00:00

🚀 Introduction to DEA: An AI Coding Assistant

The paragraph introduces DEA, an open-source clone of Devon, a fully featured AI coding assistant. The speaker shares their experience with getting DEA up and running, highlighting the rapid progress of the project. They demonstrate the interface, which includes a chat, browser, terminal, logs, and settings. The speaker also showcases a simple calculator app built using DEA's zero-shot capabilities, emphasizing the potential of the project despite its early stage. They walk through the steps of installing and using DEA, including setting up the environment and selecting models and search engines.

05:01

🛠️ Setting Up and Running DEA with Different Models

In this paragraph, the speaker continues their tutorial on DEA by explaining how to set up and run the backend and frontend of the application. They guide the user through opening a new terminal, activating the DEA environment, and spinning up the backend with Python. The speaker also covers the process of dealing with the loading of sentence Transformer models and handling errors related to using the Gro model. They then demonstrate how to run DEA with different models like Grock Mixol and how to power it with OLAMA, showcasing the versatility and speed of the AI coding assistant.

10:02

🎮 Creating 'Game of Life' with DEA and Local Models

The speaker concludes their tutorial by showing how to create a 'Game of Life' application using DEA. They guide the user through the process of selecting a project, choosing a search engine, and selecting a model. The speaker encounters a bug when using Grock Mixol but successfully creates the game using Chat GPT. They then explain how to set up DEA completely locally by installing OLAMA and running the backend server. The speaker demonstrates the local functionality by creating a 'Game of Life 2' project, which runs successfully. Despite some bugs, the speaker expresses excitement about the progress of AI coding assistants and encourages viewers to support the project.

Mindmap

Keywords

💡DEA

DEA stands for an AI coding assistant that is being showcased in the video. It is a tool designed to help users write and develop code with the aid of artificial intelligence. In the context of the video, DEA is presented as an open-source clone of another AI coding assistant, Devon. The DEA is used to demonstrate the capability of AI in automating and streamlining the coding process.

💡AI coding assistant

An AI coding assistant is a software tool that uses artificial intelligence to aid in the writing and debugging of computer code. These assistants can help automate repetitive tasks, provide suggestions, and even write code snippets based on user input. In the video, the AI coding assistant is central to the theme, as it is used to create applications and demonstrate the potential of AI in software development.

💡Zero-shot

Zero-shot learning is a machine learning technique where a model is able to make predictions about unseen classes or tasks without any prior training on those specific tasks. In the context of the video, the AI coding assistant is shown to perform zero-shot tasks, such as building an app, without needing to be explicitly trained for that particular task.

💡Vim

Vim is a highly configurable text editor used for efficiently creating and changing any kind of text. It is widely used by programmers for coding and is known for its modal editing system. In the video, Vim is mentioned as the tool used by the AI coding assistant to perform the coding tasks.

💡Search engines

Search engines are information retrieval systems designed to help find information on the World Wide Web. They are indispensable tools for locating data and resources online. In the context of the video, the AI coding assistant can interface with different search engines to gather information needed for coding tasks, such as fetching libraries or finding examples of code.

💡Open-source

Open-source refers to a type of software licensing where the source code is released to the public, allowing anyone to view, use, modify, and distribute the software. The open-source nature of the DEA AI coding assistant, as mentioned in the video, means that it is freely available for the community to contribute to and improve upon.

💡Environment setup

Environment setup refers to the process of configuring the software, tools, and dependencies required for a particular project or application to run. In the context of the video, environment setup is crucial for the DEA AI coding assistant to function correctly, as it involves installing the necessary Python environment and other dependencies.

💡Playwright

Playwright is an open-source automation library that allows you to automate tasks in the web browser. It is used for automating user interactions, testing web applications, and scraping web data. In the video, the installation of Playwright is part of the process of setting up the DEA environment, which is necessary for certain coding tasks.

💡Bun

Bun is a command-line tool used to run JavaScript or TypeScript files directly, without the need for a build process or a bundler. It simplifies the process of executing code and is often used in development environments. In the video, Bun is mentioned as part of the process to start the front-end server for the DEA project.

💡Environment variables

Environment variables are values that can be set in the operating system and used by software to determine the configuration and behavior of a program. They are crucial in development as they allow for customization of the application without modifying the source code. In the video, setting environment variables is a necessary step to configure the DEA AI coding assistant with the correct API keys and search engine details.

💡Model selection

Model selection refers to the process of choosing the appropriate machine learning model for a given task. In the context of the video, the DEA AI coding assistant supports multiple models, such as GPT-3.5, GPT-4, and other AI models, which can be selected based on the user's needs or preferences.

Highlights

Recreation of Devon's main demo in DEA, showcasing the rapid development and potential of AI coding assistants.

The interface of DEA is described as having a chat on the left, browser and terminal on the right, with logs and settings for comprehensive coding experience.

The project's progress is highlighted by the improved interface and increased support for various models and search engines.

A calculator app is built using zero-shot prompting, demonstrating the AI's capability to understand and execute tasks without prior examples.

The AI outlines a plan to build a calculator app with a UI, showcasing its ability to strategize and plan coding tasks.

Despite being in its early stages, the project is moving fast, with significant improvements made in just a few days.

The video provides a tutorial on installing and using DEA, including cloning the repository and setting up the environment.

Support for multiple search engines and models, including Google, is detailed, along with instructions on how to set them up.

The demonstration includes a live coding session using Vim, showing the practical application of the AI coding assistant in real-world scenarios.

The potential of the project is emphasized by the successful creation of a simple application in under a minute.

Instructions on how to install DEA and its dependencies using Conda and npm are provided, along with troubleshooting tips.

The video shows how to integrate Playwright for browser automation, demonstrating the versatility of DEA in web development.

The process of setting up the backend server and frontend using Bun is explained, highlighting the full-stack capabilities of DEA.

The video addresses a bug in DEA related to using Gro, showing the project's active development and continuous improvement.

A demonstration of running DEA with local models under OLAMA, emphasizing the potential for completely offline coding assistance.

The video concludes by acknowledging the contributions of the DEA team and expressing excitement for the future of AI coding assistants.

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