InstaExplorer XAI Dashboard

An AI-powered Instagram Analytics & Explainable AI Dashboard.

Features • Tech Stack • Installation • Usage

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🎯 About The Project

InstaExplorer is a cutting-edge analytics tool designed for public Instagram accounts. By fetching real-time account metrics and feeding them into an Explainable AI (XAI) engine, this dashboard provides creators and marketers with clear, actionable insights on how to improve Retention, increase Virality, and discover the Optimal Engagement Times for their audience.

Note: Due to Instagram's aggressive anti-scraping measures, the backend features a robust fallback mechanism that generates simulated, highly realistic AI insights when live scraping is blocked.

✨ Features

• Explainable AI (XAI) Insights: Get human-readable advice on why certain reels perform better and how to adjust your content strategy.
• Premium Dark Mode UI: Built with Next.js using custom glassmorphism CSS, neon accents, and modern typography.
• Interactive Visualizations: Seamless chart rendering using recharts to map historical engagement.
• Resilient Data Collection: Python instaloader wrapper with an intelligent mockup fallback.
• Lightning Fast API: Powered by FastAPI to serve AI inferences instantaneously.

🔄 System Architecture & Workflow

graph TD;
    A[User] -->|Inputs Instagram Handle| B(Next.js Dashboard)
    B -->|API Request/XHR| C{Python FastAPI Backend}
    C --> D[Instaloader Scraper]
    D -- Success --> E[Parse Real Metrics]
    D -- Blocked/Rate Limited --> F[Generate Mock Data]
    E --> G((XAI Engine))
    F --> G
    G -->|Analyzes Post Density| H[Generate Retention Rules]
    G -->|Extracts Peak Metrics| I[Identify Virality Vectors]
    H --> J[Final JSON Response]
    I --> J
    J -->|Returned to Frontend| B
    B -->|Renders Visuals| K[Charts & Insights Layout]

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🛠️ Tech Stack

Frontend:

• Next.js (React Framework)
• Vanilla CSS Modules (Custom Premium Dashboard UI)
• Recharts (Data Visualization)
• Lucide React (Icons)

Backend:

• Python 3
• FastAPI (API Framework)
• instaloader (Instagram Data Scraping)
• scikit-learn & shap (Machine Learning / XAI dependencies)

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💻 Installation

To run this project locally, you will need Node.js and Python installed on your machine.

1. Clone the repository

git clone https://github.com/Anshbhardwaj29/InstaExplorer.git
cd InstaExplorer

2. Setup the Python Backend

# Navigate to the backend directory
cd backend

# (Optional but recommended) Create a virtual environment
python -m venv venv
venv\Scripts\activate  # On Windows

# Install the dependencies
pip install -r requirements.txt

3. Setup the Next.js Frontend

# Open a new terminal and navigate to the frontend directory
cd frontend

# Install Node modules
npm install

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🚀 Usage

You need to run both the Frontend and Backend servers simultaneously to use the dashboard.

Start the Backend API:

cd backend
python main.py

The API will start at http://localhost:8000

Start the Frontend Dashboard:

cd frontend
npm run dev

The web app will start at http://localhost:3000

Once both servers are running, open your browser and navigate to http://localhost:3000. Enter any public Instagram handle (e.g., nike) to generate your AI insights!

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🔮 Future Roadmap

• Integrate Official Facebook/Instagram Graph API.
• Connect Gemini LLM to process SHAP values directly.
• Add PostgreSQL database integration to save user historical queries.
• Expand analytics tracking to TikTok and YouTube Shorts.