AdSage AI 🧠

AdSage AI is a next-generation marketing intelligence dashboard that uses multi-persona AI agents to predict, analyze, and optimize your social media campaigns. Whether you are validating a creative before launch or analyzing live performance, AdSage provides deep strategic insights.

✨ Key Features

🚀 Pre-Launch Simulation

• Predictive Analysis: Upload your creative (Image + Text) to simulate reactions from distinct demographics (Gen-Z Youth vs. Corporate Professionals).
• Pros & Cons: Get an honest, unfiltered list of strengths and weaknesses before you post.
• Visual Critique: The AI "sees" your image and critiques aesthetics, branding, and vibe.

📊 Post-Launch Analytics

• URL Intelligence: Paste any post link (LinkedIn/Instagram) to extract context and simulate realistic audience feedback.
• Deep Insight: Analyze sentiment, engagement potential, and virality velocity.
• Strategic Breakdown: Understand why a post worked or failed with "Tone Analysis" and "Hashtag Strategy".

⚡ Actionable Optimization

• Apply Suggestions: Don't just get advice—implement it. Click "Apply Suggestions" to have the AI:
  • ✍️ Rewrite your copy for better engagement.
  • 🎨 Generate new visuals using Google's Imagen 3 model based on strategic feedback.

🛠️ Tech Stack

• Frontend: HTML5, CSS3 (Glassmorphism UI), Vanilla JavaScript.
• Backend: Python (Flask).
• AI Core:
  • Google Gemini 2.5 Flash (Reasoning & Multimodal Analysis).
  • Google Imagen 3 (High-fidelity Image Generation).
  • Agentic Workflow: Custom multi-agent system (Youth Agent, Adult Agent, Chief Strategist).

🚀 Getting Started

Prerequisites

• Python 3.10+
• A Google Cloud Project with Gemini API access.

Installation

1. Clone the Repository

   git clone https://github.com/yourusername/RigtusHuddle.git
   cd AdSage-AI

2. Backend Setup Navigate to the agent directory and set up the environment:

   cd backend/agent
   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   pip install -r requirements.txt  # Install flask, google-generativeai, pillow, python-dotenv, requests, beautifulsoup4

3. Environment Variables Create a .env file in backend/agent/ and add your API key:

   GEMINI_API_KEY=your_api_key_here

4. Run the Server

   python server.py
   # Server runs on http://127.0.0.1:5000

5. Launch Frontend Simply open the UI/index.html file in your preferred web browser.

📂 Project Structure

RigtusHuddle/
├── UI/                     # Frontend Application
│   ├── index.html          # Landing & Selection Page
│   ├── dashboard.html      # Main Analytics Dashboard
│   ├── style.css           # Futuristic Styling
│   └── app.js              # Client Logic & API Integration
└── backend/
    └── agent/              # Python Agent Server
        ├── server.py       # Flask API Endpoints
        ├── agent_core.py   # Multi-Agent Logic & Gemini Integration
        └── prompts/        # System Instructions for Persona Agents