https://github.com/aws-samples/draw-an-app
This project uses AWS Bedrock's Claude 3 Sonnet model to convert hand-drawn UI sketches into working web applications.
https://github.com/aws-samples/draw-an-app
aws bedrock claude-3-5-sonnet generative-ai nextjs
Last synced: 3 months ago
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This project uses AWS Bedrock's Claude 3 Sonnet model to convert hand-drawn UI sketches into working web applications.
- Host: GitHub
- URL: https://github.com/aws-samples/draw-an-app
- Owner: aws-samples
- License: mit-0
- Created: 2025-02-03T06:32:55.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2025-02-11T17:17:52.000Z (8 months ago)
- Last Synced: 2025-02-11T18:28:36.986Z (8 months ago)
- Topics: aws, bedrock, claude-3-5-sonnet, generative-ai, nextjs
- Language: Python
- Homepage:
- Size: 1.95 MB
- Stars: 1
- Watchers: 4
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
README
# Draw-an-App - Sketch to Reality
This project uses AWS Bedrock's Claude 3 Sonnet model to convert hand-drawn UI sketches into working web applications. It supports two modes of operation:
1. Real-time webcam capture for immediate sketching and conversion
2. Image upload through a user-friendly Streamlit interface
## Prerequisites
### Node.js Setup
- Node.js 18.x or higher
#### Windows Installation
1. Download the Node.js installer from [official website](https://nodejs.org/)
2. Run the installer (.msi file)
3. Follow the installation wizard
4. Verify installation:
```cmd
node --version
npm --version
```
#### macOS/Linux Installation
Using package manager:
```bash
# For macOS (using Homebrew)
brew install node
# For Ubuntu/Debian
curl -fsSL https://deb.nodesource.com/setup_18.x | sudo -E bash -
sudo apt-get install -y nodejs
# For other Linux distributions, check your package manager
```
### Python Setup
- Python 3.8 or higher
- Webcam (for webcam-based flow)
- AWS Account with Bedrock access
- Access to Claude 3 Sonnet model in AWS Bedrock
- Git
#### Windows Installation
1. Download Python installer from [python.org](https://www.python.org/downloads/)
2. Run the installer
3. **Important**: Check "Add Python to PATH" during installation
4. Verify installation:
```cmd
python --version
pip --version
```
#### macOS/Linux Installation
```bash
# macOS (using Homebrew)
brew install python
# Ubuntu/Debian
sudo apt-get update
sudo apt-get install python3 python3-pip
# Verify installation
python3 --version
pip3 --version
```
## Architecture
The system follows this flow:
1. **Image Input**: The application supports two methods:
- OpenCV webcam capture for real-time sketching
- Streamlit-based image upload interface
2. **Image Processing**: The captured/uploaded image is processed and converted to a format suitable for analysis.
3. **Claude 3 Integration**: The processed image is sent to AWS Bedrock's Claude 3 Sonnet model along with carefully crafted prompts that guide the model to:
- Analyze and understand the UI elements in the sketch
- Generate appropriate Next.js components and code
- Ensure the generated code follows best practices
4. **Code Generation**: Claude 3 generates the necessary Next.js components, styles, and functionality based on the sketch.
5. **Application Update**: The system automatically:
- Updates the Next.js application files
- Applies any necessary styling
- Implements required functionality
- Hot-reloads the development server
6. **Live Preview**: The changes are immediately visible in the running Next.js application, providing instant feedback on the generated code.
7. **Future Updates**: The developers can use the Amazon Q for Developer for future updates to the generated code.
## Environment Setup
1. Clone the repository:
```bash
git clone
cd draw-an-app
```
2. Create and activate a virtual environment:
Windows:
```cmd
python -m venv venv
.\venv\Scripts\activate
```
macOS/Linux:
```bash
python3 -m venv venv
source venv/bin/activate
```
3. Install required Python packages:
Windows:
```cmd
pip install -r src\requirements.txt
```
macOS/Linux:
```bash
pip install -r src/requirements.txt
```
4. Install Node.js dependencies:
Windows/macOS/Linux:
```bash
cd blank-nextjs-app
npm install
cd ..
```
## AWS Bedrock Configuration
1. Configure AWS credentials:
Windows (PowerShell):
```powershell
$env:AWS_ACCESS_KEY_ID="your_access_key"
$env:AWS_SECRET_ACCESS_KEY="your_secret_key"
$env:AWS_DEFAULT_REGION="us-west-2" # or your preferred region
```
macOS/Linux:
```bash
export AWS_ACCESS_KEY_ID=your_access_key
export AWS_SECRET_ACCESS_KEY=your_secret_key
export AWS_DEFAULT_REGION=us-west-2 # or your preferred region
```
Alternatively, you can configure AWS credentials using the AWS CLI:
```bash
aws configure
```
2. Verify Bedrock Access:
- Ensure you have access to the Claude 3 Sonnet model in AWS Bedrock
- Verify your AWS account has the necessary permissions to invoke the Bedrock runtime
## System Check
Before running the application, verify:
1. Your webcam is properly connected and accessible (if using webcam flow)
2. You have access to AWS Bedrock's Claude 3 Sonnet model
3. AWS credentials are properly configured
## Usage
### Method 1: Webcam-based Flow
1. Start the Next.js development server:
Windows/macOS/Linux:
```bash
cd blank-nextjs-app
npm install
npm run dev
```
Keep this server running to view your generated applications at http://localhost:3000
2. In a new terminal, run the webcam-based application:
Windows:
```cmd
# Make sure you're in the project root directory and venv is activated
python src\main_v2.py
```
macOS/Linux:
```bash
# Make sure you're in the project root directory and venv is activated
python src/main_v2.py
```
3. When the webcam window opens:
- Press SPACE to capture and process an image
- Press Q to quit the application
### Method 2: Streamlit Interface
1. Start the Next.js development server (if not already running):
```bash
cd blank-nextjs-app
npm install
npm run dev
```
2. In a new terminal, launch the Streamlit interface:
Windows:
```cmd
# Make sure you're in the project root directory and venv is activated
streamlit run src\main_streamlit.py
```
macOS/Linux:
```bash
# Make sure you're in the project root directory and venv is activated
streamlit run src/main_streamlit.py
```
3. Using the Streamlit interface:
- Upload your UI sketch image (supported formats: JPG, JPEG)
- Click "Generate App" to process the image
- The interface will show both original and processed images
- Progress indicators will keep you informed of the generation process
- View the generated application at http://localhost:3000
## Project Structure
```
draw-an-app/
├── src/ # Source code directory
│ ├── main_v2.py # Webcam-based application
│ ├── main_streamlit.py # Streamlit-based application
│ └── utils/ # Utility modules
│ ├── aws_utils.py # AWS-related utilities
│ ├── camera_utils.py # Camera handling utilities
│ ├── image_utils.py # Image processing utilities
│ └── project_utils.py # Project-specific utilities
│ ├── prompt_system.txt # System prompt for Claude
│ ├── prompt_assistant.txt # Assistant prompt for Claude
│ ├── requirements.txt # Python dependencies
├── nextjs-app-template/ # Template for generated web applications
└── blank-nextjs-app/ # Working directory for generated applications
```
## Troubleshooting
1. Node.js Issues:
- Verify Node.js installation: `node --version`
- Clear npm cache: `npm cache clean --force`
- Delete node_modules and reinstall: `rm -rf node_modules && npm install`
2. Webcam Issues (for webcam-based flow):
- Ensure your webcam is properly connected
- Check if other applications are using the webcam
- Try different camera indices if multiple cameras are present
3. AWS Bedrock Access:
- Verify AWS credentials are correctly set
- Ensure you have access to the Claude 3 Sonnet model
- Check AWS region configuration
4. Python Environment:
- Ensure virtual environment is activated
- Verify all dependencies are installed correctly
- Check Python version compatibility
5. Streamlit Interface Issues:
- Ensure Streamlit is installed correctly (`pip install streamlit`)
- Check if the uploaded image is in a supported format
- Verify the image file size is not too large
## License
This code sample is licensed under the MIT-0 License. See the LICENSE file.
- [Changelog](CHANGELOG.md) of the project.
- [License](LICENSE) of the project.
- [Code of Conduct](CODE_OF_CONDUCT.md) of the project.
- [CONTRIBUTING](CONTRIBUTING.md#security-issue-notifications) for more information.
## Authors
- [Vikram Shitole](https://www.linkedin.com/in/vikram-aws/)
- [SureshKumar K V](https://www.linkedin.com/in/sureshkumarkv-in/)
## ⚠️ Precautions ⚠️
Before you begin using the solution, there are certain precautions you must take into account:
- Cost Management with Bedrock: Be mindful of the costs associated with AWS resources.
- This is a sample: the code provided in this repository shouldn't be used for production workloads without further reviews and adaptation.