import streamlit as st import requests import json import base64 import io import tempfile from streamlit_lottie import st_lottie, st_lottie_spinner import streamlit.components.v1 as st1 import time def load_local_lottie(path): with open(path, 'r') as file: return json.load(file) # ✅ Only initialize the state if not already set if "loading_state" not in st.session_state: st.session_state.loading_state = True # ✅ Show loading animation only once at first load if st.session_state.loading_state: with st_lottie_spinner(load_local_lottie('./src/Loading.json'), key='hello'): time.sleep(3) st.session_state.loading_state = False # ✅ App main UI st.title("Welcome to Spark Anime TTS Demo website.") st.markdown("#### This model is fined tuned on Spark TTS model and fined tuned on the AnimeVox dataset. (Stay tuned with demo chatbot)") text = st.text_area("Enter text to convert to speech:") character = st.selectbox("Select Character", [ 'Power', 'Asuna Yuuki', 'Shiro', 'Frieren', 'Mai Sakurajima', 'Megumin', 'Fern', 'Madoka Kaname', 'Homura Akemi', 'Momo Ayase', 'Mikasa Ackerman', 'Saber', 'Rin Tohsaka', 'Rem', 'Kurisu Makise', 'Lucy', 'Marin Kitagawa', 'Emilia', 'Makima' ]) if st.button("Play Audio"): with st_lottie_spinner(load_local_lottie('./src/voiceline.json'), key='download'): url = "https://8000-01jynw0agcdpzps7kn9c8gfs4p.cloudspaces.litng.ai/predict" data = {"prompt": text, "charecter": character} response = requests.post(url, json=data) audio_data = response.json()['audio'] audio_bytes = base64.b64decode(audio_data) with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as temp_file: temp_file.write(audio_bytes) temp_file_path = temp_file.name st.audio(temp_file_path, format="audio/mp3") st1.iframe("https://cloudhand-sdk-alecbidarans-projects.vercel.app/",height=200) st1.iframe(""" """,height=200)