📰 AI-Powered News Research Tool

Overview

This project utilizes LangChain and Large Language Models (LLMs) to analyze and summarize news articles from URLs. It provides efficient retrieval-augmented generation (RAG) and question-answering (QA) capabilities, helping users extract meaningful insights from articles.

Features

• Automated article analysis using NLP techniques.
• RetrievalQA and SourceChain implementation for accurate summaries.
• Hosted on Streamlit for real-time access.
• User-friendly interface for seamless news exploration.

Technologies Used

• LangChain & LLMs – Text processing & analysis.
• Python & Pandas – Data handling.
• Streamlit – Interactive web deployment.

Installation

git clone https://github.com/Lingesh-7/News-Research-Tool
cd News-Research-Tool
pip install -r requirements.txt

Usage

1. Running the News Analysis

python analyze.py --url "https://example.com/news_article"

2. Web-Based News Retrieval (Streamlit App)

streamlit run app.py

Results

The tool extracts key insights from news articles and generates summaries & answers to user queries in real time.

Future Improvements

• Enhance fact-checking capabilities for credibility analysis.
• Expand dataset for better contextual understanding.
• Integrate multi-source comparison for diverse viewpoints.