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+# News Sentiment Analysis & Hindi Text-to-Speech (TTS) Web Application
+
+## Objective
+This project is a web-based application that:
+- Extracts key details from multiple news articles about a **user-provided company**
+- Performs **sentiment analysis**
+- Conducts **comparative sentiment analysis**
+- Generates a **Hindi Text-to-Speech (TTS)** audio report
+- Provides a user-friendly interface for interaction
+
+The tool allows users to input a company name and receive a **structured sentiment report** along with **audio output**.
+
+---
+
+## Features
+1. **News Extraction**: Scrapes and displays the title, summary, and metadata from at least 10 unique news articles (non-JavaScript pages) using **BeautifulSoup (bs4)**.
+2. **Sentiment Analysis**: Determines the sentiment (positive, negative, neutral) of each article.
+3. **Comparative Analysis**: Compares sentiment across articles to visualize sentiment distribution.
+4. **Hindi TTS Generation**: Converts summarized insights into Hindi audio using an open-source TTS model.
+5. **User Interface**: Simple web UI built with **Streamlit** or **Gradio**.
+6. **API Communication**: Frontend and backend communicate via **REST APIs**.
+7. **Deployment**: Live deployment on **Hugging Face Spaces**.
+8. **Documentation**: Complete setup and usage guide.
+
+---
+
+## Project Setup
+
+### Clone the Repository
+```bash
+git clone https://github.com/yourusername/news-sentiment-tts.git
+cd news-sentiment-tts
+```
+
+### Create Virtual Environment & Install Dependencies
+```bash
+python -m venv venv
+source venv/bin/activate  # On Windows: venv\Scripts\activate
+pip install -r requirements.txt
+```
+
+### Run the Application Locally
+```bash
+streamlit run app.py
+```
+```bash
+python api.py
+```
+_or_
+```bash
+python app.py  # If using Gradio
+```
+
+### Deployment
+The app is deployed on Hugging Face Spaces:
+```
+https://huggingface.co/spaces/yourusername/news-sentiment-tts
+```
+
+---
+
+## Model Details
+
+| Task                  | Model Used                          | Description |
+|-----------------------|-------------------------------------|------------|
+| **Summarization**     | `transformers.pipeline('summarization')` | Hugging Face pre-trained model for article summary generation |
+| **Sentiment Analysis**| `transformers.pipeline('sentiment-analysis')` | Classifies article sentiment into Positive/Negative/Neutral |
+| **Text-to-Speech**    | Coqui TTS / `indic-tts`             | Open-source TTS model to generate Hindi speech from text |
+
+---
+
+## API Development & Usage
+
+### Backend APIs:
+- **Endpoint**: `/analyze_news`
+  - **Method**: POST
+  - **Input**: `{"company": "Company Name"}`
+  - **Output**: List of news articles with metadata
+
+### Testing with Postman:
+1. Set API base URL as `http://localhost:8000/`
+2. Select appropriate endpoints and POST body
+3. Test responses for JSON or audio file streaming
+
+---
+
+## Third-Party API Usage
+| API/Library            | Purpose                                               |
+|------------------------|--------------------------------------------------------|
+| **News scraping**      | BeautifulSoup (no external news APIs used)             |
+| **Hugging Face models**| Sentiment analysis & summarization                    |
+| **gtts** | Hindi Text-to-Speech generation                     |
+
+---
+
+## Assumptions & Limitations
+- **Scraping Limitations**: Only static, non-JS websites are scraped due to `BeautifulSoup` limitations. Also newsorg pi is also used.
+- **Article Count**: A minimum of 10 articles is targeted, but the count may vary based on search results.
+- **Language Support**: Sentiment analysis is primarily in English, TTS is specifically Hindi.
+- **Deployment**: Optimized for Hugging Face Spaces; heavy TTS models may experience latency. Due to flask being used hugging face is not able to run two files at a time
+
+---
+
+## Dependencies
+```text
+beautifulsoup4
+requests
+transformers
+torch
+streamlit
+gtts
+scikit-learn
+```
+
+---