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# app.py

import streamlit as st
import time
import re
import os
import tempfile
import pypdf
from pydub import AudioSegment

from utils import (
    generate_script,
    generate_audio_mp3,
    truncate_text,
    extract_text_from_url,
    transcribe_youtube_video,
    research_topic
)
from prompts import SYSTEM_PROMPT

def parse_user_edited_transcript(edited_text: str):
    """
    Looks for lines like:
        **Jane**: Hello
        **John**: Sure, I'd love to talk about that.
    Returns a list of (speaker, text).
    """
    pattern = r"\*\*(Jane|John)\*\*:\s*(.+)"
    matches = re.findall(pattern, edited_text)
    if not matches:
        # If user changed the format drastically, treat entire text as Jane
        return [("Jane", edited_text)]
    return matches

def regenerate_audio_from_dialogue(dialogue_items):
    """
    Re-generates multi-speaker audio from user-edited text.
    Returns final audio bytes and updated transcript.
    """
    audio_segments = []
    transcript = ""
    crossfade_duration = 50  # in ms

    for speaker, line_text in dialogue_items:
        audio_file = generate_audio_mp3(line_text, speaker)
        seg = AudioSegment.from_file(audio_file, format="mp3")
        audio_segments.append(seg)
        transcript += f"**{speaker}**: {line_text}\n\n"
        os.remove(audio_file)

    if not audio_segments:
        return None, "No audio segments were generated."

    # Combine with crossfade
    combined = audio_segments[0]
    for seg in audio_segments[1:]:
        combined = combined.append(seg, crossfade=crossfade_duration)

    with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as temp_audio:
        combined.export(temp_audio.name, format="mp3")
        final_mp3_path = temp_audio.name

    # Read bytes and return them (so we have a real .mp3 to download)
    with open(final_mp3_path, "rb") as f:
        audio_bytes = f.read()
    os.remove(final_mp3_path)

    return audio_bytes, transcript

def generate_podcast(file, url, video_url, research_topic_input, tone, length):
    """
    Creates a multi-speaker podcast from:
      - PDF
      - URL
      - YouTube video
      - or a research topic input.
    Returns (audio_bytes, transcript_str).
    """
    sources = [bool(file), bool(url), bool(video_url), bool(research_topic_input)]
    if sum(sources) > 1:
        return None, "Provide only one input (PDF, URL, YouTube, or Research topic)."
    if not any(sources):
        return None, "Please provide at least one source."

    text = ""
    if file:
        # Handle PDF
        try:
            if not file.name.lower().endswith('.pdf'):
                return None, "Please upload a PDF file."
            reader = pypdf.PdfReader(file.name)
            text = " ".join(page.extract_text() for page in reader.pages if page.extract_text())
        except Exception as e:
            return None, f"Error reading PDF: {str(e)}"
    elif url:
        # Handle URL
        try:
            text = extract_text_from_url(url)
            if not text:
                return None, "Failed to extract text from URL."
        except Exception as e:
            return None, f"Error extracting text from URL: {str(e)}"
    elif video_url:
        # Handle YouTube
        try:
            text = transcribe_youtube_video(video_url)
            if not text:
                return None, "Failed to transcribe YouTube video."
        except Exception as e:
            return None, f"Error transcribing YouTube video: {str(e)}"
    elif research_topic_input:
        # Handle research topic
        try:
            text = research_topic(research_topic_input)
            if not text:
                return None, f"Sorry, no information found on '{research_topic_input}'."
        except Exception as e:
            return None, f"Error researching topic: {str(e)}"

    # Generate the multi-speaker script
    try:
        text = truncate_text(text)
        script = generate_script(SYSTEM_PROMPT, text, tone, length)
    except Exception as e:
        return None, f"Error generating script: {str(e)}"

    audio_segments = []
    transcript = ""
    crossfade_duration = 50  # ms

    try:
        for item in script.dialogue:
            audio_file = generate_audio_mp3(item.text, item.speaker)
            seg = AudioSegment.from_file(audio_file, format="mp3")
            audio_segments.append(seg)
            transcript += f"**{item.speaker}**: {item.text}\n\n"
            os.remove(audio_file)

        if not audio_segments:
            return None, "No audio segments generated."

        combined = audio_segments[0]
        for seg in audio_segments[1:]:
            combined = combined.append(seg, crossfade=crossfade_duration)

        with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as temp_audio:
            combined.export(temp_audio.name, format="mp3")
            final_mp3_path = temp_audio.name

        # Convert final mp3 to bytes
        with open(final_mp3_path, "rb") as f:
            audio_bytes = f.read()
        os.remove(final_mp3_path)

        return audio_bytes, transcript
    except Exception as e:
        return None, f"Error generating audio: {str(e)}"

def main():
    # Moved set_page_config to the very top of all Streamlit commands
    st.set_page_config(
        page_title="MyPod - AI-based Podcast Generator",
        layout="centered"
    )

    # Enable "light or dark" theme via custom CSS
    st.markdown(
        """
        <style>
        :root {
          color-scheme: light dark;
        }
        body {
          background-color: #f0f2f6;
          color: #222;
        }
        .css-18e3th9 {
            background-color: #e8eaf2;
        }
        .stButton>button {
            background-color: #0066cc;
            color: white;
            border-radius: 8px;
        }
        .stProgress>div>div>div>div {
            background-color: #0066cc;
        }
        </style>
        """,
        unsafe_allow_html=True
    )

    st.title("๐ŸŽ™ MyPod - AI-based Podcast Generator")

    st.markdown(
        "Welcome to **MyPod**, your go-to AI-powered podcast generator! ๐ŸŽ‰\n\n"
        "MyPod transforms your documents, webpages, YouTube videos, or research topics into a more human-sounding, conversational podcast.\n"
        "Select a tone and a duration range. The script will be on-topic, concise, and respect your chosen length.\n\n"
        "### How to use:\n"
        "1. **Provide one source:** PDF, URL, YouTube link (Requires User Auth - Work in Progress), or a Topic to Research.\n"
        "2. **Choose the tone and the target duration.**\n"
        "3. **Click 'Generate Podcast'** to produce your podcast.\n\n"
        "**After** the audio is generated, you can **edit** the transcript \n"
        "and **re-generate** the audio with your edits if needed.\n\n"
        "**Research a Topic:** Please be as detailed as possible in your topic statement. If it's too niche or specific, "
        "you might not get the desired outcome. We'll fetch information from Wikipedia and RSS feeds (BBC, CNN, Associated Press, "
        "NDTV, Times of India, The Hindu, Economic Times, Google News) or the LLM knowledge base to get recent info about the topic.\n\n"
        "**Token Limit:** Up to ~2,048 tokens are supported. Long inputs may be truncated.\n"
        "**Note:** YouTube transcription uses Whisper on CPU and may take longer for very long videos.\n\n"
        "โณ**Please be patient while your podcast is being generated.** This process involves content analysis, script creation, "
        "and high-quality audio synthesis, which may take a few minutes.\n\n"
        "๐Ÿ”ฅ **Ready to create your personalized podcast?** Give it a try now and let the magic happen! ๐Ÿ”ฅ"
    )

    col1, col2 = st.columns(2)
    with col1:
        file = st.file_uploader("Upload PDF (.pdf only)", type=["pdf"])
        url = st.text_input("Or Enter URL")
        video_url = st.text_input("Or Enter YouTube Link")
    with col2:
        research_topic_input = st.text_input("Or Research a Topic")
        tone = st.radio("Tone", ["Humorous", "Formal", "Casual", "Youthful"], index=2)
        length = st.radio("Length", ["1-3 Mins", "3-5 Mins", "5-10 Mins", "10-20 Mins"], index=0)

    # Use session_state to avoid losing results if user clicks away
    if "audio_bytes" not in st.session_state:
        st.session_state["audio_bytes"] = None
    if "transcript" not in st.session_state:
        st.session_state["transcript"] = None

    generate_button = st.button("Generate Podcast")

    if generate_button:
        # Show a pseudo progress bar for user engagement
        progress_bar = st.progress(0)
        progress_text = st.empty()

        # Steps to pretend some progress:
        progress_text.write("Alright, let's get started...")
        progress_bar.progress(10)
        time.sleep(1.0)

        progress_text.write("Working on the magic. Hang tight!")
        progress_bar.progress(40)
        time.sleep(1.0)

        progress_text.write("Almost done. Adding a dash of awesomeness...")
        progress_bar.progress(70)
        time.sleep(1.0)

        audio_bytes, transcript = generate_podcast(
            file, url, video_url, research_topic_input, tone, length
        )

        time.sleep(1.0)
        progress_bar.progress(100)
        progress_text.write("Done!")

        if audio_bytes is None:
            st.error(transcript)
            # Clear session state
            st.session_state["audio_bytes"] = None
            st.session_state["transcript"] = None
        else:
            st.success("Podcast generated successfully!")
            st.session_state["audio_bytes"] = audio_bytes
            st.session_state["transcript"] = transcript

    # Check if we have a stored result
    if st.session_state["audio_bytes"]:
        # Show the audio
        st.audio(st.session_state["audio_bytes"], format='audio/mp3')
        # Provide a download button with .mp3 extension
        st.download_button(
            label="Download Podcast (MP3)",
            data=st.session_state["audio_bytes"],
            file_name="my_podcast.mp3",
            mime="audio/mpeg"
        )

        # Show the transcript in a text area for editing
        st.markdown("### Generated Transcript (Editable)")
        edited_text = st.text_area(
            "Feel free to tweak lines, fix errors, or reword anything.",
            value=st.session_state["transcript"],
            height=300
        )

        # Regenerate button
        if st.button("Regenerate Audio From Edited Text"):
            regen_bar = st.progress(0)
            regen_text = st.empty()

            regen_text.write("Let's do this revision!")
            regen_bar.progress(25)
            time.sleep(1.0)

            regen_text.write("Cooking up fresh audio...")
            regen_bar.progress(60)
            time.sleep(1.0)

            # Parse & regenerate
            dialogue_items = parse_user_edited_transcript(edited_text)
            new_audio_bytes, new_transcript = regenerate_audio_from_dialogue(dialogue_items)

            regen_bar.progress(90)
            time.sleep(1.0)

            if new_audio_bytes is None:
                regen_bar.progress(100)
                st.error(new_transcript)
            else:
                regen_bar.progress(100)
                regen_text.write("All set!")
                st.success("Regenerated audio below:")

                # Store updated
                st.session_state["audio_bytes"] = new_audio_bytes
                st.session_state["transcript"] = new_transcript

                st.audio(new_audio_bytes, format='audio/mp3')
                st.download_button(
                    label="Download Edited Podcast (MP3)",
                    data=new_audio_bytes,
                    file_name="my_podcast_edited.mp3",
                    mime="audio/mpeg"
                )
                st.markdown(new_transcript)


if __name__ == "__main__":
    main()