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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") | |
| def read_root(): | |
| return {"message": "Welcome to the News Summarization & TTS API"} | |
| 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.") | |