NewsCredible

NewsCredible is an AI-powered platform for analyzing the credibility, bias, and factual accuracy of news articles. The core of the project is the Article Analyzer, which leverages advanced machine learning and NLP models to provide in-depth content analysis, helping users identify misinformation and bias in news content.

🚀 Main Features

• Article Analyzer: Analyze news articles for bias, credibility, and factual accuracy using state-of-the-art AI models.
• Content Analysis API: FastAPI backend exposes endpoints for content analysis, fact-checking, and media verification.
• Bias Detection: Detects potential bias in text using custom and pre-trained models.
• Fact-Check Lookup: Cross-references claims with fact-checking databases.
• Media Verification: Tools for verifying images and videos in news articles.

🗂️ Project Structure

NewsCredible/
├── backend/
│   ├── app/
│   │   ├── main.py                # FastAPI entrypoint
│   │   ├── routers/
│   │   │   ├── content.py         # Article/content analysis endpoints
│   │   │   └── ...
│   │   ├── services/
│   │   │   ├── content_analyzer.py # Core logic for article analysis
│   │   │   └── ...
│   │   └── models/
│   │       └── bias_tokenizer.py
│   └── ...
├── frontend/
│   └── src/
│       ├── components/
│       │   └── ArticleAnalyzerTool.tsx # Main UI for article analysis
│       └── pages/
│           └── ArticleAnalyzer.tsx     # Article Analyzer page
└── ...

🧠 Article Analyzer (Core Focus)

The Article Analyzer is the centerpiece of NewsCredible. It allows users to submit news articles and receive:

• Bias and sentiment analysis
• Fact-checking results
• Media (image/video) verification
• Detailed credibility scoring

The backend logic is primarily in backend/app/services/content_analyzer.py and exposed via the /api/v1/content endpoints in backend/app/routers/content.py.

The frontend provides an interactive UI in frontend/src/components/ArticleAnalyzerTool.tsx and frontend/src/pages/ArticleAnalyzer.tsx.

🛠️ Getting Started

Prerequisites

• Python 3.9+
• Node.js 18+
• (Optional) Docker

Backend Setup

cd backend
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -r requirements.txt
uvicorn app.main:app --host 0.0.0.0 --port 8000

Frontend Setup

cd frontend
npm install
npm run dev

Docker (Full Stack)

docker build -t newscredible .
docker run -p 8000:8000 newscredible

📚 API Overview

• POST /api/v1/content/analyze — Analyze an article for bias, credibility, and facts
• GET /api/v1/content/summary — Get a summary of an article
• See backend/app/routers/content.py for all endpoints

🤝 Contributing

1. Fork the repo and create your branch (git checkout -b feature/your-feature)
2. Commit your changes (git commit -am 'Add new feature')
3. Push to the branch (git push origin feature/your-feature)
4. Open a Pull Request

📄 License

This project is licensed under the MIT License.

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NewsCredible — Empowering readers with AI-driven news analysis.