This project fetches news articles about a company, summarizes them, performs sentiment analysis, extracts key topics, and converts the summaries into Hindi audio. It has two versions: a web application using Streamlit and an API server using FastAPI.

Fetches news articles from Google News.

Summarizes articles into three sentences.

Performs sentiment analysis (Happy, Sad, or Neutral).

Extracts three main topics from each summary.

Converts summaries and overall analysis to Hindi audio.

Provides a web interface (Streamlit) or an API (FastAPI).

app.py - Streamlit application for an interactive UI.

api.py - FastAPI server for API-based access.

utils.py - Helper functions for fetching, summarizing, sentiment analysis, etc.

requirements.txt - List of required dependencies.

README.md - Documentation.

Python (Version 3.7+ recommended)

Streamlit - For building the web application.

FastAPI - For API-based access.

Pydantic - For API request validation.

Requests - To fetch web pages and articles.

BeautifulSoup4 - To parse HTML and extract news content.

VaderSentiment - For sentiment analysis.

gTTS (Google Text-to-Speech) - To generate Hindi audio.

Deep-Translator - To translate English summaries to Hindi.

NLTK - For text processing and topic extraction.

Uvicorn - To run the FastAPI server.

Google News (Unofficial) - Scraped using requests and BeautifulSoup4 to fetch article URLs. No API key required, but dependent on Google’s HTML structure.

Google Translate (via Deep-Translator) - Converts English text to Hindi.

Google Text-to-Speech (via gTTS) - Converts text summaries to Hindi audio.