📰 Fake News Detection & News Summarization App

An AI-powered web application that summarizes the latest news articles and detects potential fake or misleading information using Generative AI, LangChain, and HuggingFace models.

This project aims to help users save time, stay informed, and verify the credibility of online news using cutting-edge NLP and retrieval-augmented techniques.

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🚀 Features

• 🔍 News Retrieval: Fetches the latest news articles based on user queries (e.g., “AI in Healthcare”).
• 🧠 News Summarization: Generates concise, human-like summaries using Meta Llama-3 (HuggingFace).
• 🧾 Fake News Detection: Uses a fine-tuned NLP model to analyze the credibility of each article.
• ⚡ Vector Search (FAISS): Retrieves the most relevant articles efficiently.
• 🧩 LangChain Integration: Chains LLMs and retrieval steps for intelligent response generation.
• 💬 FastAPI Backend: Provides a clean, fast, and scalable API for serving predictions and summaries.

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🧠 Tech Stack

Component	Technology Used
Backend API	FastAPI
Generative AI	LangChain + HuggingFace Transformers
Vector Database	FAISS
Summarization Model	Meta Llama-3
Fake News Model	HuggingFace (Fine-tuned classifier)
Programming Language	Python
Deployment	(optional: Streamlit / Render / HuggingFace Spaces)

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⚙️ How It Works

1. User enters a news topic or query.
2. App fetches the latest related articles from online sources.
3. Articles are embedded and indexed using FAISS.
4. Relevant articles are retrieved and passed to LangChain, which:
   • Summarizes each article using Meta Llama-3.
   • Runs the Fake News Detection Model to evaluate authenticity.
5. Results (summaries + credibility) are returned in a structured format.

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📦 Installation

# Clone the repository
git clone https://github.com/aliahmad552/fake_news_detection_and_summarization.git
cd fake_news_detection_and_summarization

# Create and activate virtual environment
python -m venv venv
source venv/bin/activate   # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Run FastAPI server
uvicorn app:app --reload

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📊 Example Output

Input Query: AI in Healthcare Output:

📰 Summarized News: AI is transforming healthcare through faster diagnosis and efficient data-driven treatment plans...

🧾 Fake News Probability: Low (92% Reliable)

🌍 Future Enhancements

💬 Add Chat-style Frontend UI

📈 Real-time Credibility Dashboard

🌐 Integration with live news APIs

🧠 Fine-tune models for domain-specific detection

💡 Why This Project?

In a world flooded with information, separating truth from noise has become essential. This project uses AI for good — helping people consume news intelligently, quickly, and responsibly.

👨‍💻 Author

Ali Ahmad

Data Scientist | AI Engineer | Generative AI Enthusiast