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CodVid.AI - Instagram Analytics Platform

A premium, production-ready Streamlit mobile web app for Instagram analytics and tracking, built with a focus on minimalistic design and AI-powered insights. Built based on the functionality from the demo notebooks.

Features

πŸ” Authentication

  • User signup and login system
  • Secure session management
  • Account deletion capability

πŸ“Š Instagram Profile Tracking

  • Own Profile Tracking: Track your own Instagram profiles
  • Competitor Analysis: Track unlimited competitor profiles
  • Automatic Scraping: Scheduled scraping with configurable intervals
  • Manual Scraping: Force immediate data collection
  • Performance Metrics: Likes, comments, views analysis
  • Sentiment Analysis: AI-powered comment sentiment analysis

πŸ“ Project Management

  • Project Creation: Create multiple projects for different campaigns
  • AI Chat Integration: Interactive AI chat for each project
  • Reel Tracking: Track specific Instagram reels within projects

πŸ“ˆ Analytics & Visualization

  • Performance Charts: Interactive charts for likes, comments, views
  • Sentiment Distribution: Pie charts for sentiment analysis
  • Data Tables: Detailed post and comment data
  • Real-time Updates: Live data refresh capabilities

User Journey Flow

  1. Sign Up/Login: Users create an account or log in
  2. Dashboard: Manage Instagram profile tracking tasks
    • Create tracking tasks for own profiles (limited to one)
    • Create unlimited competitor tracking tasks
    • View all tracked profiles with status and last scrape info
  3. Profile Details: Click on any profile to see detailed analytics
    • View scraped data and performance metrics
    • Force manual scraping
    • Configure automatic scraping intervals
    • View sentiment analysis results
  4. Projects: Navigate to project management
    • Create new projects
    • Access project-specific features
  5. Project Features:
    • Explorer Page: Interactive AI chat for project-specific assistance
    • Tracker Page: Track specific Instagram reels within the project

Installation & Setup

Prerequisites

  • Python 3.8 or higher
  • pip package manager

Installation

  1. Clone or navigate to the web_app directory

    cd web_app
  2. Install dependencies

    pip install -r requirements.txt
  3. Run the application

    streamlit run main.py
  4. Access the app

    • Open your browser and go to http://localhost:8501
    • The app will automatically open in your default browser

API Configuration

The app is configured to use the development backend by default:

  • Base URL: https://codvid-ai-backend-development.up.railway.app

To change the environment, modify the APIClient initialization in main.py:

api_client = APIClient("https://codvid-ai-backend-production.up.railway.app")  # Production
# or
api_client = APIClient("http://localhost:8080")  # Local

Usage Guide

Getting Started

  1. Create Account: Sign up with your email and password
  2. Login: Access your dashboard
  3. Add Instagram Profiles: Create tracking tasks for profiles you want to monitor
  4. View Analytics: Click on any profile to see detailed analytics
  5. Create Projects: Organize your work into projects
  6. Use AI Chat: Get AI assistance for your projects
  7. Track Reels: Add specific reels to track within projects

Key Features

Profile Tracking

  • Own Profile: Track your own Instagram profile (limited to one)
  • Competitors: Track unlimited competitor profiles
  • Automatic Updates: Set scraping intervals (0.5 to 30 days)
  • Manual Updates: Force immediate scraping when needed

Analytics Dashboard

  • Performance Metrics: Total likes, comments, views
  • Post Analysis: Recent posts with engagement data
  • Sentiment Analysis: AI-powered comment sentiment analysis
  • Visual Charts: Interactive charts for data visualization

Project Management

  • Multiple Projects: Create and manage multiple projects
  • AI Integration: Chat with AI for project-specific assistance
  • Reel Tracking: Track specific Instagram reels within projects

Technical Architecture

Frontend

  • Streamlit: Modern web framework for data apps
  • Mobile-Responsive: Optimized for mobile devices
  • Interactive UI: Real-time updates and user interactions

Backend Integration

  • RESTful API: Integration with the backend services
  • Authentication: JWT token-based authentication
  • Real-time Data: Live data fetching and updates

Data Visualization

  • Plotly: Interactive charts and graphs
  • Pandas: Data manipulation and analysis
  • Real-time Updates: Live data refresh capabilities

File Structure

web_app/
β”œβ”€β”€ main.py                 # Main application entry point
β”œβ”€β”€ requirements.txt        # Python dependencies
β”œβ”€β”€ README.md              # This file
└── pages/                 # Page modules
    β”œβ”€β”€ __init__.py        # Package initialization
    β”œβ”€β”€ login.py           # Authentication page
    β”œβ”€β”€ dashboard.py       # Main dashboard
    β”œβ”€β”€ profile_details.py # Profile analytics
    β”œβ”€β”€ projects.py        # Project management
    β”œβ”€β”€ project_chat.py    # AI chat interface
    └── project_tracker.py # Reel tracking interface

Mobile Optimization

The app is optimized for mobile devices with:

  • Responsive Design: Adapts to different screen sizes
  • Touch-Friendly: Large buttons and touch targets
  • Mobile Navigation: Simplified navigation for mobile
  • Fast Loading: Optimized for mobile network speeds

Troubleshooting

Common Issues

  1. Connection Errors: Check if the backend server is running
  2. Authentication Issues: Ensure correct email/password
  3. Data Not Loading: Try refreshing the page or force scraping
  4. Mobile Display Issues: Use landscape mode for better viewing

Support

For technical support or feature requests, please refer to the original demo notebooks for implementation details.

Development

Adding New Features

  1. Create new page module in pages/ directory
  2. Update main.py to include the new page routing
  3. Test thoroughly with different data scenarios
  4. Update documentation as needed

Code Style

  • Follow PEP 8 Python style guidelines
  • Use descriptive variable and function names
  • Add comments for complex logic
  • Maintain consistent formatting

License

This project is based on the demo notebooks and follows the same licensing terms.

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