import nest_asyncio
nest_asyncio.apply()

import streamlit as st
from transformers import pipeline
from gtts import gTTS
import io
from streamlit.components.v1 import html
import asyncio

if not asyncio.get_event_loop().is_running():
    asyncio.set_event_loop(asyncio.new_event_loop())
    
# Initialize session state
if 'processed_data' not in st.session_state:
    st.session_state.processed_data = {
        'scenario': None,
        'story': None,
        'audio': None
    }
if 'timer_started' not in st.session_state:
    st.session_state.timer_started = False
if 'timer_frozen' not in st.session_state:
    st.session_state.timer_frozen = False

# Timer component that uses localStorage to check for a freeze flag
def timer():
    return """
    <div id="timer" style="font-size:16px;color:#666;margin-bottom:10px;">⏱️ Elapsed: 00:00</div>
    <script>
    (function() {
        var start = Date.now();
        var timerElement = document.getElementById('timer');
        // Clear any previous freeze flag
        localStorage.removeItem("freezeTimer");
        var interval = setInterval(function() {
            // Check if freeze flag is set in localStorage.
            if(localStorage.getItem("freezeTimer") === "true"){
                clearInterval(interval);
                timerElement.style.color = '#00cc00'; // Change color to indicate frozen.
                return;
            }
            var elapsed = Date.now() - start;
            var minutes = Math.floor(elapsed / 60000);
            var seconds = Math.floor((elapsed % 60000) / 1000);
            timerElement.innerHTML = '⏱️ Elapsed: ' + 
                (minutes < 10 ? '0' : '') + minutes + ':' + 
                (seconds < 10 ? '0' : '') + seconds;
        }, 1000);
    })();
    </script>
    """

# Page setup
st.set_page_config(page_title="Your Image to Audio Story", page_icon="🦜")
st.header("Turn Your Image to a Short Audio Story for Children")

# Model loading
@st.cache_resource
def load_models():
    return {
        "img_model": pipeline("image-to-text", "cnmoro/tiny-image-captioning"),
        "story_model": pipeline("text-generation", "Qwen/Qwen2.5-0.5B-Instruct")
    }

models = load_models()

# Processing functions
def img2text(url):
    return models["img_model"](url)[0]["generated_text"]

def text2story(text):
    prompt = f"Generate a 100-word story about: {text}"
    messages = [
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": prompt}
    ]
    response = models["story_model"](
        messages,
        max_new_tokens=100,
        do_sample=True,
        temperature=0.7
    )[0]["generated_text"]
    return response[2]["content"]

def text2audio(story_text):
    audio_io = io.BytesIO()
    tts = gTTS(text=story_text, lang='en', slow=False)
    tts.write_to_fp(audio_io)
    audio_io.seek(0)
    return {'audio': audio_io, 'sampling_rate': 16000}

# UI components
uploaded_file = st.file_uploader("Select an Image After the Models are Loaded...")

if uploaded_file is not None:
    # Inject the timer only once, right after image upload.
    if not st.session_state.timer_started and not st.session_state.timer_frozen:
        st.session_state.timer_started = True
        html(timer(), height=50)
    
    # Initialize progress containers
    status_text = st.empty()
    progress_bar = st.progress(0)
    
    try:
        # Save uploaded file
        bytes_data = uploaded_file.getvalue()
        with open(uploaded_file.name, "wb") as file:
            file.write(bytes_data)

        if st.session_state.get('current_file') != uploaded_file.name:
            st.session_state.current_file = uploaded_file.name

            # Display image
            st.image(uploaded_file, caption="Uploaded Image", use_container_width=True)

            # Stage 1: Image to Text
            status_text.markdown("**🖼️ Generating caption...**")
            progress_bar.progress(0)
            st.session_state.processed_data['scenario'] = img2text(uploaded_file.name)
            progress_bar.progress(33)

            # Stage 2: Text to Story
            status_text.markdown("**📖 Generating story...**")
            progress_bar.progress(33)
            st.session_state.processed_data['story'] = text2story(
                st.session_state.processed_data['scenario']
            )
            progress_bar.progress(66)

            # Stage 3: Story to Audio
            status_text.markdown("**🔊 Synthesizing audio...**")
            progress_bar.progress(66)
            st.session_state.processed_data['audio'] = text2audio(
                st.session_state.processed_data['story']
            )
            progress_bar.progress(100)

            status_text.success("**✅ Generation complete!**")
            # Immediately freeze the timer by setting the freeze flag.
            html("<script>localStorage.setItem('freezeTimer', 'true');</script>", height=0)
            st.session_state.timer_frozen = True
    except Exception as e:
        html("<script>document.getElementById('timer').remove();</script>")
        status_text.error(f"**❌ Error:** {str(e)}")
        progress_bar.empty()
        raise e

    st.write("**Caption:**", st.session_state.processed_data['scenario'])
    st.write("**Story:**", st.session_state.processed_data['story'])

# Optionally, you can still have the Play Audio button.
if st.button("Play Audio of the Story Generated"):
    if st.session_state.processed_data.get('audio'):
        # Since the timer is already frozen by now, just play the audio.
        audio_data = st.session_state.processed_data['audio']
        st.audio(audio_data['audio'].getvalue(), format="audio/mp3")
    else:
        st.warning("Please generate a story first!")