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K2-k2/VibeCraft-AI

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App README

📸 VibeCraft AI: AI-Powered Social Media Engineering

VibeCraft AI is a professional-grade multimodal application designed to bridge the gap between visual content and high-engagement social media copy. By leveraging Google's Gemini 2.5 Flash model, the app analyzes images and crafts three distinct caption variations based on user-selected "vibes."

🚀 Key Features

  • —Multimodal Analysis: Deep image understanding to extract context, mood, and visual elements.
  • —Vibe Selection: Tailor content for different niches (Gen-Z, Professional, Aesthetic, Savage, etc.).
  • —Triple Draft Output: Provides three unique variations for every image to ensure creative variety.
  • —Professional UI: A mobile-responsive, sleek interface built with Streamlit and custom CSS/JS.
  • —One-Click Copy: Integrated JavaScript clipboard functionality for seamless content migration.

🛠️ Tech Stack

  • —Core Engine: Python 3.10+
  • —LLM: Google Gemini 2.5 Flash (Generative AI)
  • —Frontend: Streamlit
  • —Custom Styling: CSS Flexbox (for responsive branding) & JavaScript (for clipboard API).
  • —Image Processing: Pillow (PIL)

📖 How It Works

  1. 1.Image Input: User uploads a visual asset (JPG/PNG).
  2. 2.Vibe Definition: User selects a target brand voice from the sidebar.
  3. 3.Contextual Analysis: The Gemini 2.5 Flash model processes the image and user prompt simultaneously.
  4. 4.Creative Synthesis: The AI generates three structured drafts, each with a unique "Feel" header.
  5. 5.Clipboard Export: User copies their preferred draft using the custom-built JS button.

⚙️ Installation & Setup

If you want to run this locally:-

  1. 1.Clone the repository:
bash
   git clone [https://huggingface.co/spaces/K2-k2/VibeCraft-AI](https://huggingface.co/spaces/K2-k2/VibeCraft-AI)

2. Install dependencies:

pip install -r requirements.txt

  1. 1.Set up your environment variable: Create a .env file or export GOOGLEAPIKEY_N.
  1. 1.Run the app:
bash
   streamlit run app.py

# Developed with ❤️ by Kesar Agarwal 

   

   
   


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