Introduction
Managing development environments can be a headache, but with Daytona, it’s as easy as running a single command. In this post, I’ll walk you through building an AI-powered Flask application using Pydantic and the OpenAI API in a Daytona-managed environment. This project is also a submission for Challenge 023: Take Daytona for a Spin!
What is Daytona?
Daytona is an open-source development environment manager that makes setting up and managing consistent dev environments a breeze. With daytona create, you can spin up a fully configured environment tailored for your project.
Project Overview
Tech Stack:
- Python/Flask: For building the backend.
- Pydantic: For validating and managing data.
- Tailwind CSS: To create a responsive and modern UI.
- OpenAI API: To power AI-driven responses.
Key Features:
- AI-Powered Prompt Responses: Use OpenAI to generate real-time responses to user inputs.
- Responsive Design: Built with Tailwind CSS to ensure mobile and desktop usability.
- Daytona Integration: Seamlessly manage development environments.
How to Set It Up
Step 1: Install Daytona
Follow the Daytona installation guide to install and configure Daytona on your machine.
Step 2: Clone the Repository
Use Daytona to clone the project repository:
daytona create https://github.com/palsayantan007/Daytona-Pydantic-ai-App.git
Step 3: Configure Environment Variables
Create a .env file based on .env.example and add your OpenAI API key:
OPENAI_API_KEY=your_openai_api_key_here
Step 4: Install Dependencies
Inside the Daytona workspace, install the required Python packages:
pip install -r requirements.txt
Step 5: Run the Application
Start the Flask app:
python app.py
Visit http://localhost:8080 in your browser to interact with the app.
Features Breakdown
-
Daytona for Environment Management
- The project uses a
devcontainer.jsonto define a consistent and containerized dev environment. - Easily run and test the app in a pre-configured workspace with Daytona.
- The project uses a
-
AI-Powered Prompt Generator
- Users can input prompts, and the app generates real-time responses via OpenAI’s API.
- Example prompt: "Write a haiku about AI."
-
Responsive Design
- Tailwind CSS ensures the app is visually appealing and fully responsive on all devices.
Why Choose Daytona?
-
Ease of Use: A single command (
daytona create) handles the entire dev environment setup. - Consistency: Every collaborator gets the same environment, reducing "it works on my machine" issues.
- Scalability: Integrates seamlessly with complex projects.
Contributing
Feel free to fork the project, suggest improvements, or contribute to its development. Once your sample is ready, open a PR to submit it to the Daytona Samples Index.
Final Thoughts
Daytona is a game-changer for developers looking to simplify their workflow. Combining it with Flask, Pydantic, and the OpenAI API shows its versatility and ease of use.
If you're participating in Challenge 023, I hope this post inspires you to take Daytona for a spin and unlock its full potential!
Resources
- Daytona Documentation: https://github.com/daytonaio/daytona
- GitHub Repository: Daytona-Pydantic-ai-App
- OpenAI API: OpenAI Docs
Let’s Connect
If you have any questions or need help with your Daytona setup, drop a comment below or reach out on Discord. Let’s make Challenge 023 a success together!
Happy coding! 🚀
Let me know if you’d like me to tailor this further! 😊
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