api.py

from fastapi import FastAPI
from pydantic import BaseModel
from utils import fetch_news, generate_tts_hindi
import shutil

app = FastAPI()

class CompanyRequest(BaseModel):
    company_name: str

@app.post("/get_news_and_sentiment")
async def get_news_and_sentiment(request: CompanyRequest):
    company_name = request.company_name
    articles = fetch_news(company_name)
    
    # Comparative Sentiment Analysis
    sentiment_distribution = {'Positive': 0, 'Negative': 0, 'Neutral': 0}
    for article in articles:
        sentiment_distribution[article['Sentiment']] += 1
    
    # Prepare comparative analysis
    coverage_diff = []
    for i in range(1, len(articles)):
        coverage_diff.append({
            "Comparison": f"Article {i} vs Article {i+1}",
            "Impact": f"Impact of coverage for {articles[i]['Sentiment']} vs {articles[i-1]['Sentiment']}"
        })

    # Generate TTS in Hindi
    tts_file = generate_tts_hindi(f"Sentiment report for {company_name}.", "output.mp3")
    
    return {
        'Company': company_name,
        'Articles': articles,
        'Comparative Sentiment Score': sentiment_distribution,
        'Coverage Differences': coverage_diff,
        'Final Sentiment': f"Final sentiment about {company_name}: Positive" if sentiment_distribution['Positive'] > sentiment_distribution['Negative'] else "Negative",
        'Audio': tts_file
    }