Validata

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🖼 Screenshot

Validata UI/UX

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🎉 What’s New in v1.0.0

• AI-Powered News Verification: Leverage Google Gemini for deep article analysis.
• Multi-Source Analysis: Compare articles from various news outlets using NewsAPI.
• Real-Time Fact Checking: Automated claim verification to identify potential misinformation.
• Credibility Scoring: Get an overall credibility score for articles and sources.
• Bias Detection: Analyze political bias and sensationalism levels.
• Interactive Frontend: User-friendly Streamlit interface for seamless interaction.

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✨ All Features

• Article URL Verification: Paste a news article URL to get a comprehensive AI-powered analysis.
• News Topic Search: Search for any news topic to get a neutral summary and source diversity analysis from multiple sources.
• Detailed Credibility Reports: Receive scores for source reputation, writing quality, evidence quality, objectivity, and transparency.
• Claim Identification: Automatically identify and assess the verifiability of factual claims.
• Manipulation Tactic Detection: Highlight potential manipulation tactics used in articles.
• Similar Article Discovery: Find related articles from other sources for cross-referencing.
• Source Distribution Analysis: Understand the diversity of sources in news searches.
• Media Literacy Tips: Get actionable advice to improve your critical thinking skills.

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📁 Folder Structure

fake-news-detector/
├── .env                        # Environment variables for API keys
├── LICENSE                     # Project license
├── pyproject.toml              # Project metadata and dependencies (PEP 621)
├── README.md                   # Main project README
├── requirements.txt            # Python dependencies
├── assets/                     # Project assets (logos, banners, screenshots)
│   ├── validata-banner.png
│   ├── validata-logo.png
│   └── screenshots/
│       └── screenshot.png
├── backend/                    # FastAPI backend for AI services
│   ├── app.py                  # Main FastAPI application
│   ├── api/                    # API endpoints
│   │   ├── __init__.py
│   │   ├── search.py           # News search endpoint
│   │   └── verification.py     # Article verification endpoint
│   ├── services/               # Core AI and data extraction services
│   │   ├── __init__.py
│   │   ├── article_extractor.py # Extracts content from URLs
│   │   ├── credibility_scorer.py # Scores article credibility using Gemini
│   │   ├── fact_checker.py     # Fact-checks claims using Gemini
│   │   └── news_searcher.py    # Searches news using NewsAPI
│   └── utils/                  # Utility functions
│       ├── __init__.py
│       └── helpers.py          # General helper functions
├── docs/                       # Project documentation
│   ├── CHANGELOG.md
│   ├── CODE_OF_CONDUCT.md
│   ├── CONTRIBUTING.md
│   ├── README.md               
│   ├── SECURITY.md
│   ├── STATUS.md
│   └── USAGE.md
└── frontend/                   # Streamlit frontend application
    ├── api_client.py           # Handles communication with the backend API
    ├── app.py                  # Main Streamlit application
    ├── charts.py               # Plotly chart generation
    ├── display.py              # Functions for displaying results
    ├── error_components.py     # Custom error messages and solutions
    └── styles.py               # Custom CSS styling for Streamlit

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🕹 Usage

Prerequisites

• Python 3.8+
• pip (Python package installer)
• API Keys:
  • Google Gemini API Key: For FactChecker and CredibilityScorer services.
  • NewsAPI Key: For NewsSearcher service.

Installation

1. Clone the repository:

   git clone https://github.com/nova-cortex/validata.git
   cd validata

2. Set up environment variables: Create a .env file in the root directory of the project and add your API keys:

   GEMINI_API_KEY="YOUR_GEMINI_API_KEY"
   NEWSAPI_KEY="YOUR_NEWSAPI_KEY"
   BACKEND_URL="http://localhost:8000" # Default, change if your backend runs on a different host/port
   

3. Install dependencies:

   pip install -r requirements.txt

Running the Application

1. Start the Backend Server: Open a terminal, navigate to the backend directory, and run:

   cd backend
   python app.py

   You should see output indicating Uvicorn running on http://0.0.0.0:8000.

2. Start the Frontend Application: Open a new terminal, navigate to the frontend directory, and run:

   cd frontend
   streamlit run app.py

   This will open the Validata application in your web browser, usually at http://localhost:8501.

For more detailed documentation, see our USAGE.md

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🤝 Contributing

Please see our Contributing Guide for details.

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Code of Conduct

This project follows our Code of Conduct. Please read it before contributing.

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📋 Roadmap

• Enhance AI models for deeper analysis and nuanced understanding.
• Integrate more news sources and fact-checking databases.
• Develop user authentication and personalized dashboards.
• Implement browser extensions for direct article verification.
• Expand language support for global news analysis.

See the open issues for a full list of proposed features and known issues.

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📝 Changelog

All notable changes to this project are documented in CHANGELOG.md.

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📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

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🙏 Acknowledgments

• Google Gemini API for advanced AI capabilities.
• NewsAPI for comprehensive news article access.
• Newspaper3k for robust article extraction.
• Streamlit for the interactive web application framework.
• Plotly for dynamic data visualizations.

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📞 Support

• 📧 Email: ujjwalkrai@gmail.com
• 🐛 Issues: Validata Issues
• 🔓 Security: Validata Security
• ⛏ Pull Request: Validata Pull Requests
• 📖 Docs: Validata Documentation
• 📃 Changelog: Validata Changelog

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🔗 Connect

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