Update README.md

README.md

@@ -1,63 +1,74 @@
-# Live Company News Analyzer 
-**A project by Sara Nimje - [Visit Portfolio Website](https://saranimje.github.io/)**
-This application fetches live news articles for a company, analyzes sentiment, summarizes content, and converts it into Hindi audio. 
-## Objective:
-I have developed a web-based application that extracts key details from multiple news articles related to a given company. The application performs sentiment analysis, conducts a comparative analysis, and generates a text-to-speech (TTS) output in Hindi. Users can input a company name and receive a structured sentiment report along with an audio summary, making the information more accessible and insightful.
-# Project Setup
-## Installation:
-
- - Clone this repository -
-`git clone https://github.com/saranimje/news-summarizer.git `
-- Navigate to directory -
-`cd news-summarizer`
-
- - Install Dependencies - 
- `pip install -r requirements.txt`
-    
- - Run Gradio App - 
- `python app.py`
-    
- - Run API (Optional) - 
- `uvicorn api:app --reload`
-
-# Model Details
-## Summarization Model
- - Uses transformers from Hugging Face.
- - Model: `google/long-t5-tglobal-base`
-
-## Sentiment Analysis
-Uses default sentiment-analysis pipeline from Hugging Face.
-
-## Topic Modelling
--   Uses TF-IDF vectorization with NMF (Non-Negative Matrix Factorization) to extract key topics from news articles.
--   Utilizes cosine similarity to measure relationships between articles.
-
-## Text-to-Speech 
-Uses `gTTS (Google Text-to-Speech)`
-## Translation
-Uses `GoogleTranslator` (source: English, target: Hindi).
-
-
-# API Development
-This project includes a **FastAPI-based API** to fetch news articles and analyze them.
-## **Endpoints:**
-**1. Home**
--   `GET /`
--   Returns: `{"message": "News Summarization API is running!"}`   
-**2. Fetch News**
--   `GET /news/?company_name=Tesla&article_number=5`
--   Returns JSON output containing news articles and analysis.
-# API Development
-## Using Postman or Curl:
-1.  Open **Postman** or any API testing tool.
-2.  Send a `GET` request to:
-   ` http://127.0.0.1:8000/news/?company_name=Tesla&article_number=5`
-3.  View JSON response with news articles and summaries.
-
-## Third-Party API Usage
--   **News Sources**: Google Search (`googlesearch` Python module).
--   **Libraries Used**:
-    - `requests` for API calls
-    - `gensim`, `deep_translator`, `nltk` for text processing.
-    - `googlesearch` to fetch news links.
+---
+title: "News Summarizer"
+emoji: "📰"
+colorFrom: "blue"
+colorTo: "green"
+sdk: "gradio"
+sdk_version: "3.50.2"  # Update if needed
+app_file: "app.py"
+pinned: false
+---
+
+# Live Company News Analyzer 
+**A project by Sara Nimje - [Visit Portfolio Website](https://saranimje.github.io/)**
+This application fetches live news articles for a company, analyzes sentiment, summarizes content, and converts it into Hindi audio. 
+## Objective:
+I have developed a web-based application that extracts key details from multiple news articles related to a given company. The application performs sentiment analysis, conducts a comparative analysis, and generates a text-to-speech (TTS) output in Hindi. Users can input a company name and receive a structured sentiment report along with an audio summary, making the information more accessible and insightful.
+# Project Setup
+## Installation:
+
+ - Clone this repository -
+`git clone https://github.com/saranimje/news-summarizer.git `
+- Navigate to directory -
+`cd news-summarizer`
+
+ - Install Dependencies - 
+ `pip install -r requirements.txt`
+    
+ - Run Gradio App - 
+ `python app.py`
+    
+ - Run API (Optional) - 
+ `uvicorn api:app --reload`
+
+# Model Details
+## Summarization Model
+ - Uses transformers from Hugging Face.
+ - Model: `google/long-t5-tglobal-base`
+
+## Sentiment Analysis
+Uses default sentiment-analysis pipeline from Hugging Face.
+
+## Topic Modelling
+-   Uses TF-IDF vectorization with NMF (Non-Negative Matrix Factorization) to extract key topics from news articles.
+-   Utilizes cosine similarity to measure relationships between articles.
+
+## Text-to-Speech 
+Uses `gTTS (Google Text-to-Speech)`
+## Translation
+Uses `GoogleTranslator` (source: English, target: Hindi).
+
+
+# API Development
+This project includes a **FastAPI-based API** to fetch news articles and analyze them.
+## **Endpoints:**
+**1. Home**
+-   `GET /`
+-   Returns: `{"message": "News Summarization API is running!"}`   
+**2. Fetch News**
+-   `GET /news/?company_name=Tesla&article_number=5`
+-   Returns JSON output containing news articles and analysis.
+# API Development
+## Using Postman or Curl:
+1.  Open **Postman** or any API testing tool.
+2.  Send a `GET` request to:
+   ` http://127.0.0.1:8000/news/?company_name=Tesla&article_number=5`
+3.  View JSON response with news articles and summaries.
+
+## Third-Party API Usage
+-   **News Sources**: Google Search (`googlesearch` Python module).
+-   **Libraries Used**:
+    - `requests` for API calls
+    - `gensim`, `deep_translator`, `nltk` for text processing.
+    - `googlesearch` to fetch news links.
     - `feedparser` for RSS feeds.