Here’s a detailed explanation of how the project works along with instructions on how to run it on your computer. 🚀

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📝 Project Overview

🎯 Objective

The project aims to summarize Hindi news articles by extracting content from supported websites and generating concise summaries using state-of-the-art models like:

• BART: Fine-tuned for Hindi text summarization.
• mT5: A multilingual model that supports Hindi summarization.

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⚙️ How It Works

1. Input: News Article URL

• The user provides a URL of a news article (e.g., from Amarujala).
• The URL is passed to the API.

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2. API Endpoint

• The API endpoint accepts the URL and a model name (BART or T5).
• API Endpoint:

https://hf.space/embed/d0r1h/Hindi_News_Summarizer/+/api/predict/

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3. Fetching and Preprocessing

• The system scrapes the news article content.
• Cleans and preprocesses the text to remove unwanted elements like ads, HTML tags, and irrelevant sections.

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4. Summarization Model

• The preprocessed text is passed to the selected model (BART or T5).
• The model generates a concise summary of the article in Hindi.

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5. Sentiment Analysis (Optional)

• Sentiment analysis is performed to classify the summary as Positive, Negative, or Neutral.

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6. WordCloud Generation (Optional)

• A word cloud is generated from the summarized text to visualize key topics.

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7. Output

• The final output includes:
  • Title
  • Summary
  • Sentiment
  • Key Topics
  • Optional: WordCloud Visualization

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🖥️ How to Run the Project Locally

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✅ Step 1: Clone the Repository

git clone https://github.com/Divyateja2709/akaike.git

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✅ Step 2: Navigate to Project Directory

cd akaike

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✅ Step 3: Create a Virtual Environment

# Windows
python -m venv venv
venv\Scripts\activate

# Mac/Linux
python3 -m venv venv
source venv/bin/activate

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✅ Step 4: Install Required Dependencies

pip install -r requirements.txt

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✅ Step 5: Run the Application

python app.py

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✅ Step 6: Access the Application

• Open your browser and go to:

http://127.0.0.1:5000

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🔥 API Usage Instructions

1. Send POST Request to API

import requests

# API endpoint
api_endpoint = "https://hf.space/embed/d0r1h/Hindi_News_Summarizer/+/api/predict/"

# News article URL
news_url = "https://www.amarujala.com/uttar-pradesh/shamli/up-news-heroin-caught-in-shaheen-bagh-of-delhi-is-connection-to-kairana-and-muzaffarnagar?src=tlh\u0026position=3"

# API Request
response = requests.post(
    url=api_endpoint,
    json={"data": [news_url, "BART"]}
)

# Get the summarized output
summary = response.json()['data'][0]
print(summary)

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🎨 WordCloud Usage

To generate a WordCloud for summarized Hindi text:

from wordcloud import WordCloud
import matplotlib.pyplot as plt

def plot_wordcloud(text):
    wordcloud = WordCloud(font_path='path_to_hindi_font.ttf', width=800, height=400, background_color='white').generate(text)
    plt.figure(figsize=(10, 5))
    plt.imshow(wordcloud, interpolation='bilinear')
    plt.axis('off')
    plt.show()

# Generate WordCloud for the summarized text
plot_wordcloud(summary)

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📚 Troubleshooting and Notes

• Make sure Python version >= 3.8 is installed.
• Verify that all dependencies from requirements.txt are installed properly.
• If facing issues, deactivate the virtual environment and reactivate it:

# Deactivate
deactivate

# Activate again
venv\Scripts\activate

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🎉 Done!

Now the application is running locally, and you can start summarizing Hindi news articles. 🚀