A visually focused Streamlit application for AI image generation, prompt improvement, image enhancement, and interactive creative workflows powered by ClipDrop.
Overview • Features • Architecture • Tech Stack • Setup
ARTIFY is a Streamlit-based Generative AI application designed around AI-assisted image creation.
The application integrates ClipDrop APIs for image-generation workflows and uses Pillow (PIL) for image handling and enhancement. It also includes custom Streamlit styling, local visual assets, configuration loading, and secure API-key lookup through environment variables or Streamlit secrets.
The project is designed to turn a text prompt into a more polished creative workflow through an interactive web interface.
| Feature | Description |
|---|---|
| 🎨 AI Image Generation | Generate images through ClipDrop-powered workflows |
| ✍️ Prompt Improvement | Improve prompts before generation |
| 🖼️ Image Processing | Process generated images with Pillow |
| ✨ Quality Enhancement | Apply contrast, color, and sharpening enhancements |
| 🧩 Multiple API Keys | Supports more than one ClipDrop API key |
| 🔐 Secure Configuration | Reads secrets from environment variables / Streamlit secrets |
| 🎛️ Custom UI | Styled Streamlit interface with custom CSS |
| 📥 Image Output | Supports displaying and downloading generated content |
| 🖼️ Custom Background | Uses project imagery as part of the visual interface |
┌────────────────────┐
│ User Prompt │
└──────────┬─────────┘
│
▼
┌────────────────────┐
│ Prompt Improvement │
│ Workflow │
└──────────┬─────────┘
│
▼
┌────────────────────┐
│ ClipDrop API │
│ Image Generation │
└──────────┬─────────┘
│
▼
┌────────────────────┐
│ PIL / Pillow │
│ Image Processing │
└──────────┬─────────┘
│
▼
┌────────────────────┐
│ Quality Enhancement│
│ Contrast / Color │
│ Sharpening │
└──────────┬─────────┘
│
▼
┌────────────────────┐
│ Streamlit Output │
│ Preview / Download │
└────────────────────┘
ARTIFY uses Pillow-based processing to enhance generated images.
The source code includes enhancement workflows involving:
- 🎚️ Contrast adjustment
- 🌈 Color enhancement
- ✨ Sharpening
- 🌫️ Gaussian blur in selected processing routines
- 💡 Brightness adjustment
- 🖼️ Image copying and conversion utilities
These operations are used to improve or process image output after generation.
ARTIFY is designed to avoid hard-coding API credentials directly into the application.
The application checks for ClipDrop credentials through:
Environment Variables
│
├── CLIPDROP_API_KEY
│
└── CLIPDROP_API_KEY_2
│
▼
Streamlit Secrets
│
▼
ClipDrop API
Use environment variables or Streamlit secrets rather than committing credentials to source control.
Example:
CLIPDROP_API_KEY=your_key_here
CLIPDROP_API_KEY_2=your_second_key_here
⚠️ Never commit real API keys to a public repository.
The application uses custom Streamlit CSS to create a more visual, application-like experience.
The interface includes styling for:
- 🌈 Gradient header
- 🎨 Custom application background
- 🧊 Translucent input components
- 🔘 Styled action buttons
- 📥 Styled download controls
- 📐 Wide-layout presentation
- 🖼️ Custom background imagery
The styling is implemented directly in the Streamlit application.
ARTIFY/
│
├── 📂 .streamlit/
│ └── ⚙️ Streamlit configuration / secrets
│
├── 📂 images/
│ └── 🖼️ Application imagery
│
├── 🐍 src.py
├── 📦 requirements.txt
└── 📘 README.md
git clone https://github.com/Divakar1326/ARTIFY.git
cd ARTIFYpython -m venv .venv
.venv\Scripts�ctivatepython3 -m venv .venv
source .venv/bin/activatepip install -r requirements.txtConfigure the required ClipDrop API credentials using environment variables or Streamlit secrets.
Example:
CLIPDROP_API_KEY=your_key_here
CLIPDROP_API_KEY_2=your_second_key_herestreamlit run src.pyUses an external image-generation API to build an AI-assisted creative workflow.
Combines generated output with programmatic image-processing operations using Pillow.
Uses environment variables and Streamlit secrets rather than embedding API keys directly in the application.
The project goes beyond a bare script by implementing a customized Streamlit interface with application-specific styling.
- Python application development
- Generative AI API integration
- Streamlit UI development
- API credential management
- Image processing with Pillow
- Prompt-oriented workflows
- Image enhancement
- Configuration handling
- File and binary image processing
- Custom CSS styling inside Streamlit
Potential extensions include:
- 🖼️ Gallery/history for generated images
- 💾 Persistent image storage
- 🧠 More advanced prompt optimization
- 🎨 Generation presets and styles
- 📊 Usage analytics and generation history
- ⚡ Better API error handling and retry logic
- 🚀 Public cloud deployment
- 👤 User accounts and personalized generation history
ARTIFY relies on external image-generation services, so functionality depends on the availability and usage limits of the configured API.
Generated images and API responses may also depend on the specific capabilities and policies of the external provider.
B.Tech CSE — Artificial Intelligence & Data Science
AI/ML • Generative AI • Python • Computer Vision
⭐ If you find ARTIFY useful, consider starring the repository.
Imagine ✨ Generate 🎨 Enhance 🖼️