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SayyedAli/
NEWS-Summarizer_And_TTS

Name: NEWS-Summarizer_And_TTS
Availability: InStock

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News Summarizer and Talk-to-Speech Model

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.

Features

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).

Project Structure

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.

Tech Stack

Languages

Python (Version 3.7+ recommended)

Libraries

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.

APIs Used

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.

Installation and Setup

Prerequisites

Python 3.7+ - Download from python.org
Git - Install from git-scm.com
Internet - Required for news fetching, translation, and text-to-speech conversion.

Steps to Set Up

Clone the Repository
bash
1git clone https://github.com/AliSayyed123/News-Summarizer-and-Talk-to-Speech-model.git 2cd News-Summarizer-and-Talk-to-Speech-model
Install Dependencies
pip install -r requirements.txt

Running the Project

Option 1: Run the Streamlit Web App

Provides a web-based UI to interact with the model.

streamlit run app.py

Option 2: Run the API Server

Starts the FastAPI server using Uvicorn.

uvicorn api:app --reload

Usage

Use the Streamlit Web App for an interactive experience.
Use the FastAPI server to integrate the service into other applications.

Contributing

Feel free to contribute by forking the repository and submitting pull requests.

For any issues or improvements, open a GitHub issue or reach out to the maintainers.

SayyedAli/NEWS-Summarizer_And_TTS