api.py

from flask import Flask, request, jsonify, send_file
import requests
from bs4 import BeautifulSoup
import trafilatura
import json
import os
import tempfile
from io import BytesIO
from gtts import gTTS
from utils import (
    search_news_articles,
    extract_article_content,
    perform_sentiment_analysis,
    extract_topics,
    generate_comparative_analysis,
    summarize_sentiment
)

app = Flask(__name__)

@app.route('/news/<company_name>', methods=['GET'])
def get_company_news(company_name):
    """
    Fetch news articles about a specific company
    """
    try:
        # Search for news articles
        articles = search_news_articles(company_name)
        
        if not articles or len(articles) == 0:
            return jsonify({"error": "No articles found"}), 404
            
        # Process articles to extract content
        processed_articles = []
        
        for article in articles[:10]:  # Limit to 10 articles
            article_data = extract_article_content(article)
            if article_data:
                processed_articles.append(article_data)
                
        return jsonify({"articles": processed_articles})
        
    except Exception as e:
        return jsonify({"error": str(e)}), 500

@app.route('/analyze', methods=['POST'])
def analyze_content():
    """
    Perform sentiment analysis and comparative analysis on articles
    """
    try:
        data = request.json
        if not data or 'company' not in data or 'articles' not in data:
            return jsonify({"error": "Invalid request data"}), 400
            
        company_name = data['company']
        articles = data['articles']
        
        if len(articles) == 0:
            return jsonify({"error": "No articles provided for analysis"}), 400
            
        # Perform sentiment analysis on each article
        for article in articles:
            if 'Summary' in article:
                sentiment = perform_sentiment_analysis(article['Summary'])
                article['Sentiment'] = sentiment
                
                # Extract topics
                article['Topics'] = extract_topics(article['Summary'])
                
        # Generate comparative analysis
        comparative_analysis = generate_comparative_analysis(articles)
        
        # Generate final sentiment summary
        final_summary = summarize_sentiment(company_name, articles, comparative_analysis)
        
        # Construct response
        response = {
            "Company": company_name,
            "Articles": articles,
            "Comparative Sentiment Score": comparative_analysis,
            "Final Sentiment Analysis": final_summary
        }
        
        return jsonify(response)
        
    except Exception as e:
        return jsonify({"error": str(e)}), 500

@app.route('/tts', methods=['POST'])
def text_to_speech():
    """
    Convert text to speech in multiple languages
    Supported languages: Hindi, English, Spanish, French, German, Japanese, Chinese, Russian, Arabic, Italian
    """
    try:
        data = request.json
        if not data or 'text' not in data:
            return jsonify({"error": "No text provided"}), 400
            
        text = data['text']
        # Default to Hindi if no language specified
        language = data.get('language', 'hi')
        
        # Map of supported languages
        language_map = {
            'hi': 'Hindi',
            'en': 'English',
            'es': 'Spanish',
            'fr': 'French',
            'de': 'German',
            'ja': 'Japanese',
            'zh-CN': 'Chinese',
            'ru': 'Russian',
            'ar': 'Arabic',
            'it': 'Italian'
        }
        
        # Validate language
        if language not in language_map:
            return jsonify({
                "error": f"Unsupported language code: {language}",
                "supported_languages": language_map
            }), 400
            
        # Create a temporary file to store the audio
        temp_file = tempfile.NamedTemporaryFile(delete=False, suffix='.mp3')
        
        # Generate TTS in the specified language
        tts = gTTS(text=text, lang=language, slow=False)
        tts.save(temp_file.name)
        
        # Send the audio file
        return send_file(
            temp_file.name,
            mimetype='audio/mp3',
            as_attachment=True,
            download_name=f'speech_{language}.mp3'
        )
        
    except Exception as e:
        return jsonify({"error": str(e)}), 500

if __name__ == '__main__':
    app.run(host='0.0.0.0', port=7860, debug=True)