⚡ Trend Predator: AI-Powered Viral Content Engine

🌐 Live Demo

https://trendpredictor.streamlit.app/

🚀 Project Overview

Trend Predator is a real-time intelligence tool designed for content creators, marketers, and social media managers. It automates the entire workflow of finding viral topics and creating engaging scripts.

In simple terms: It finds what's hot and writes your next viral Reel for you.

✨ Key Features

• 🕵️ Real-Time Trend Scanning: Fetches the top trending topics live from Google News India across multiple niches (Tech, Sports, Entertainment, etc.).
• 🧠 AI Script Generation: Uses Google's Gemini 2.0 Flash AI model to instantly generate viral-worthy 30-second Reel scripts (Hook, Value, Call-to-Action) in Hinglish.
• 🔒 Secure Admin Login: Protected by a password authentication system to prevent unauthorized access.
• 🗄️ Persistent Database: Stores trending data in a local SQLite database, building a historical record of what went viral.
• 🎨 Modern Dark UI: A sleek, professional, "Cyberpunk" styled interface built with Streamlit for a premium user experience.

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🛠️ Tech Stack

This project is a full-stack Python application built with modern libraries.

Component	Technology	Purpose
Frontend & Backend	Streamlit	The core framework for building the web app, UI, and handling logic.
AI Model	Google Gemini API	Powers the intelligent script generation capability.
Data Scraping	requests & xml.etree	Fetches and parses real-time RSS feeds from Google News.
Database	SQLite3	A lightweight, file-based database to store trend history.
Deployment	Streamlit Community Cloud	Hosts the live application directly from GitHub.

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⚙️ How It Works (Architecture)

1. User Login: The user authenticates via a secure password screen.
2. Niche Selection: The user selects a category (e.g., "Tech") from the dashboard.
3. Data Scraping: The scraper.py module hits Google News RSS feeds using custom headers to mimic a real browser and fetches the latest headlines.
4. Data Storage: The fetched topics are instantly saved into the SQLite database (trends.db) via db_manager.py.
5. Dashboard Update: The Streamlit app reads the latest data from the DB and displays it as elegant cards.
6. AI Magic: When the user clicks "Generate Script", the topic is sent to ai_agent.py, which prompts the Gemini AI to write a tailored script, which is then displayed on the UI.

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🖥️ Installation & Local Run

Follow these steps to run the project on your local machine.

Prerequisites

• Python 3.8 or higher installed.
• A Google Cloud account with a Gemini API Key.

Steps

1. Clone the Repository

   git clone [https://github.com/YOUR_USERNAME/trend-predator.git](https://github.com/YOUR_USERNAME/trend-predator.git)
   cd trend-predator

2. Create & Activate Virtual Environment (Optional but recommended)

   # Windows
   python -m venv venv
   .\venv\Scripts\activate
   
   # Mac/Linux
   python3 -m venv venv
   source venv/bin/activate

3. Install Dependencies

   pip install -r requirements.txt

4. Set Up Secrets (API Key & Password) Create a new folder named .streamlit in the root directory and inside it, create a file named secrets.toml. Add your credentials:

   .streamlit/secrets.toml

   GEMINI_API_KEY = "YOUR_ACTUAL_GEMINI_API_KEY_HERE"
   ADMIN_PASSWORD = "Set_Your_Desired_Password_Here"

5. Run the App

   streamlit run app.py

   The app should now open in your browser at http://localhost:8501. Use the password you set in secrets.toml to log in.

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🤝 Contribution

Feel free to fork this repository, create a new branch, and submit a pull request. Any contributions, bug fixes, or feature enhancements are welcome!

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📄 License

This project is open-source and available under the MIT License.

Engineered with ❤️ by a CS Engineer.