api.py

from fastapi import FastAPI, HTTPException
from fastapi.responses import JSONResponse, StreamingResponse
import uvicorn
from src.utils import extract_news, analyze_sentiment, extract_keywords_keybert, generate_hindi_speech
from src.comparison import comparison_analysis
from src.summarization import summarize_overall_sentiment
from typing import Dict

app = FastAPI()


@app.get("/")
def home() -> Dict[str, str]:
    """Home route for API"""
    return {"message": "Welcome to the News Analysis API!"}


@app.get("/news-analysis/")
def get_news_analysis(company: str) -> JSONResponse:
    """Extracts news, analyzes sentiment, and provides a JSON response."""
    articles = extract_news(company)[:10]  # Extract first 10 articles
    
    if not articles:
        raise HTTPException(status_code=404, detail="No articles found for the given company.")

    news_data = {
        "Company": company,
        "Articles": [
            {
                "Title": article.get("title", "No Title"),
                "Summary": article.get("summary", "No Summary"),
                "Sentiment": analyze_sentiment(article.get("summary", "")),  # Sentiment analysis
                "Topics": extract_keywords_keybert(article.get("summary", ""))  # Extract topics
            }
            for article in articles
        ]
    }

    return JSONResponse(content=news_data)


@app.get("/comparative-analyst/")
def get_comparative_analysis(company: str) -> JSONResponse:
    """Performs comparative sentiment analysis for a given company."""
    articles = extract_news(company)[:10]
    
    if len(articles) < 10:
        raise HTTPException(status_code=400, detail="Not enough articles for a full comparison.")

    comparison_data = comparison_analysis(articles)  # Perform comparative analysis

    return JSONResponse(content=comparison_data)


@app.get("/generate-audio/")
def generate_audio(company: str) -> StreamingResponse:
    """Generates a Hindi audio summary using LLM response."""
    articles = extract_news(company)[:10]

    if not articles:
        raise HTTPException(status_code=404, detail="No articles found for the given company.")

    summary_text = summarize_overall_sentiment(articles)  # Generate summary text
    audio_buffer = generate_hindi_speech(summary_text)  # Convert summary to speech

    return StreamingResponse(
        audio_buffer,
        media_type="audio/mpeg",
        headers={"Content-Disposition": "attachment; filename=hindi_summary.mp3"}
    )


@app.get("/search-news/")
def search_news(company: str, keyword: str = None, sentiment: str = None):
    """Search for articles based on keyword or sentiment."""

    articles = extract_news(company)[:10]
    if not articles:
        raise HTTPException(status_code=404, detail="No articles found.")

    filtered_articles = []
    for article in articles:
        if keyword and keyword.lower() not in article["summary"].lower():
            continue
        if sentiment and analyze_sentiment(article["summary"]).lower() != sentiment.lower():
            continue
        filtered_articles.append(article)

    return JSONResponse(content={"Company": company, "Filtered Articles": filtered_articles})

if __name__ == "__main__":
    uvicorn.run(app, host="127.0.0.1", port=8000)