Upload api.py

api.py

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+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
+    }