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A newer version of the Streamlit SDK is available: 1.56.0

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metadata 
title: Ai Image Prompt Generator
emoji: 🖼
colorFrom: purple
colorTo: red
sdk: streamlit
app_file: streamlit_app.py
pinned: false
license: mit

AI Image Prompt Generator 🖼️

A modern Gradio app for building, enhancing, and visualizing creative prompts for AI text-to-image models.

  • Prompt Generator: Build detailed prompts step by step using dropdowns and custom attributes.
  • Prompt Enhancement: Refine your prompt with Google Gemini for more creative, detailed results.
  • Image Generation: Instantly generate images from your prompt using Stable Diffusion XL Turbo (via diffusers).
  • Modern UI: Features a beautiful animated background and copy-to-clipboard buttons for easy workflow.

Features

  • 🎨 Prompt Builder: Select styles, subjects, moods, and more, or add your own custom attributes.
  • ✨ Prompt Enhancement: Click 'Refine Prompt' to rewrite your prompt with Gemini (Google Generative AI).
  • 🖼️ Image Generation: Click 'Generate Image' to visualize your prompt using SDXL Turbo.
  • 📋 Copy Buttons: Quickly copy your prompt or enhanced prompt for use in other tools.
  • 🌈 Animated UI: Enjoy a modern, glowing background and clean layout.

Usage

  1. Select or add prompt options in each category.
  2. View your prompt in the Prompt Preview section.
  3. Refine your prompt with the 'Refine Prompt' button (optional).
  4. Generate an image from your prompt with the 'Generate Image' button.
  5. Copy your prompt or enhanced prompt as needed.

Running Locally

  1. Clone this repo and install requirements:
    pip install -r requirements.txt
  2. Set your Gemini API key:
    export GEMINI_API_KEY=your-gemini-api-key
  3. Run the app:
    python gradio_app.py

Hugging Face Spaces

  • This app is ready for deployment on Hugging Face Spaces.
  • Set your GEMINI_API_KEY as a secret in the Space settings.
  • The app file is gradio_app.py.

Requirements

  • gradio
  • google-generativeai
  • diffusers
  • torch
  • Pillow
  • pyperclip

License

MIT

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference