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| import streamlit as st | |
| import requests | |
| import os | |
| import pandas as pd | |
| BACKEND_URL = "http://127.0.0.1:5000/analyze" | |
| st.title("π News Sentiment Analysis & TTS in Hindi") | |
| # Input field for company name | |
| company_name = st.text_input("Enter Company Name", "") | |
| if st.button("Analyze"): | |
| if not company_name: | |
| st.warning("β οΈ Please enter a company name.") | |
| else: | |
| st.info(f"Analyzing news for {company_name}...") | |
| response = requests.post( | |
| BACKEND_URL, | |
| json={"company_name": company_name} | |
| ) | |
| if response.status_code == 200: | |
| data = response.json() | |
| st.success("β Analysis Complete!") | |
| # β Display Sentiment Summary | |
| st.subheader("π Sentiment Summary") | |
| st.json(data["sentiment_summary"]) | |
| # β Display Articles | |
| st.subheader("π° Extracted Articles") | |
| df = pd.DataFrame(data["articles"]) | |
| for _, article in df.iterrows(): | |
| st.markdown(f"### [{article['title']}]({article['url']})") | |
| st.write(f"**Summary:** {article['summary']}") | |
| st.write("---") | |
| # β Display Hindi TTS Audio | |
| st.subheader("π Hindi TTS Audio Output") | |
| audio_file = "output/TestCompany_tts.mp3" | |
| if os.path.exists(audio_file): | |
| with open(audio_file, "rb") as audio: | |
| st.download_button( | |
| label="π Download Hindi TTS Audio", | |
| data=audio, | |
| file_name="Hindi_TTS.mp3", | |
| mime="audio/mpeg" | |
| ) | |
| st.audio(audio_file, format="audio/mp3") | |
| st.success("β Hindi TTS audio displayed successfully!") | |
| else: | |
| st.error("β TTS file not found.") | |
| else: | |
| st.error("β Error analyzing news. Please try again.") |