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import os
import threading
import time
import requests
import streamlit as st
import uvicorn
from fastapi import FastAPI
from utils import process_news
import asyncio
import sys
if sys.platform == "win32":
asyncio.set_event_loop_policy(asyncio.WindowsSelectorEventLoopPolicy())
import spacy
try:
spacy.load("en_core_web_sm")
except OSError:
import os
os.system("python -m spacy download en_core_web_sm")
# FastAPI app setup
api = FastAPI(title="News Summarization & TTS API")
@api.get("/")
def read_root():
return {"message": "Welcome to the News Summarization & TTS API"}
@api.get("/news/{company_name}")
def get_news(company_name: str):
return process_news(company_name)
# # Function to run FastAPI in a separate thread
# def run_fastapi():
# uvicorn.run(api, host="0.0.0.0", port=8000)
# # Start FastAPI in a separate thread
# threading.Thread(target=run_fastapi, daemon=True).start()
# # Streamlit app setup
API_URL = "http://127.0.0.1:8000" # Since FastAPI runs in the same Space
st.title("News Summarization and Hindi TTS Application")
company = st.text_input("Enter Company Name", "")
if st.button("Fetch News"):
if company.strip() == "":
st.warning("Please enter a valid company name.")
else:
with st.spinner("Fetching and processing news..."):
time.sleep(2) # Give FastAPI some time to start
try:
response = requests.get(f"{API_URL}/news/{company}")
if response.status_code == 200:
data = response.json()
st.header(f"News for {data['company']}")
for article in data["articles"]:
st.subheader(article.get("title", "No Title"))
st.markdown(f"**URL:** [Read More]({article.get('url', '#')})")
st.markdown(f"**Date:** {article.get('date', 'N/A')}")
st.markdown(f"**Sentiment:** {article.get('sentiment', 'Neutral')} (Score: {article.get('score', 0):.2f})")
st.markdown(f"**Excerpt:** {article.get('content','')[:300]}...")
st.markdown("---")
st.subheader("Comparative Sentiment Analysis")
comp_sent = data.get("comparative_sentiment", {})
st.write({k: comp_sent[k] for k in ["Positive", "Negative", "Neutral"]})
if "graph" in comp_sent and os.path.exists(comp_sent["graph"]):
st.image(comp_sent["graph"], caption="Sentiment Analysis Graph")
st.subheader("Final Combined Summary")
st.write(data.get("final_summary", "No summary available."))
st.subheader("Hindi Summary")
st.write(data.get("hindi_summary", ""))
st.subheader("Hindi Summary Audio")
audio_path = data.get("tts_audio", None)
if audio_path and os.path.exists(audio_path):
with open(audio_path, "rb") as audio_file:
st.audio(audio_file.read(), format='audio/mp3')
else:
st.error("Audio file not found or TTS generation failed.")
else:
st.error("Failed to fetch news from the API. Please try again.")
except requests.exceptions.ConnectionError:
st.error("API is not running yet. Please wait a moment and try again.")
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