app.py

# app.py

import streamlit as st
from utils import (
    generate_script, 
    generate_audio_mp3,  # Updated import
    truncate_text, 
    extract_text_from_url, 
    transcribe_youtube_video, 
    research_topic
)
from prompts import SYSTEM_PROMPT  # Ensure this module exists
import pypdf
from pydub import AudioSegment
import tempfile
import os

def generate_podcast(file, url, video_url, research_topic_input, tone, length):
    print("[LOG] generate_podcast called")
    
    # Check that only one input source is used
    sources = [bool(file), bool(url), bool(video_url), bool(research_topic_input)]
    if sum(sources) > 1:
        print("[ERROR] Multiple input sources provided.")
        return None, "Please provide either a PDF file, a URL, a YouTube link, or a Research topic - not multiple."
    if not any(sources):
        print("[ERROR] No input source provided.")
        return None, "Please provide at least one source."

    text = ""
    if file:
        try:
            print("[LOG] Reading PDF file:", file.name)
            if not file.name.lower().endswith('.pdf'):
                print("[ERROR] Uploaded file is not a 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())
            print("[LOG] PDF text extraction successful.")
        except Exception as e:
            print("[ERROR] Error reading PDF file:", e)
            return None, f"Error reading PDF file: {str(e)}"
    elif url:
        try:
            print("[LOG] Using URL input")
            text = extract_text_from_url(url)
            if not text:
                print("[ERROR] Failed to extract text from URL.")
                return None, "Failed to extract text from the provided URL."
        except Exception as e:
            print("[ERROR] Error extracting text from URL:", e)
            return None, f"Error extracting text from URL: {str(e)}"
    elif video_url:
        try:
            print("[LOG] Using YouTube video input")
            text = transcribe_youtube_video(video_url)
            if not text:
                print("[ERROR] Failed to transcribe YouTube video.")
                return None, "Failed to transcribe the provided YouTube video."
        except Exception as e:
            print("[ERROR] Error transcribing YouTube video:", e)
            return None, f"Error transcribing YouTube video: {str(e)}"
    elif research_topic_input:
        try:
            print("[LOG] Researching topic:", research_topic_input)
            text = research_topic(research_topic_input)
            if not text:
                print("[ERROR] No information found for the topic.")
                return None, f"Sorry, I couldn't find recent information on '{research_topic_input}'."
        except Exception as e:
            print("[ERROR] Error researching topic:", e)
            return None, f"Error researching topic: {str(e)}"
    else:
        print("[ERROR] No valid input source detected.")
        return None, "Please provide a PDF file, URL, YouTube link, or Research topic."

    try:
        text = truncate_text(text)
        script = generate_script(SYSTEM_PROMPT, text, tone, length)
    except Exception as e:
        print("[ERROR] Error generating script:", e)
        return None, f"Error generating script: {str(e)}"

    audio_segments = []
    transcript = ""

    try:
        print("[LOG] Generating audio segments...")
        # Define crossfade duration in milliseconds
        crossfade_duration = 50  # 50ms crossfade for smooth transitions

        for i, item in enumerate(script.dialogue):
            try:
                audio_file = generate_audio_mp3(item.text, item.speaker)  # Updated function call
                line_audio = AudioSegment.from_file(audio_file, format="mp3")  # Changed format to mp3
                audio_segments.append(line_audio)
                transcript += f"**{item.speaker}**: {item.text}\n\n"
                os.remove(audio_file)
            except Exception as e:
                print(f"[ERROR] Error generating audio for dialogue item {i+1}: {e}")
                continue

        if not audio_segments:
            print("[ERROR] No audio segments were generated.")
            return None, "No audio segments were generated."

        print("[LOG] Combining audio segments with crossfades...")
        # Initialize combined audio with the first segment
        combined = audio_segments[0]

        # Append remaining segments with crossfade
        for seg in audio_segments[1:]:
            combined = combined.append(seg, crossfade=crossfade_duration)

        with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as temp_audio:  # Changed suffix to mp3
            combined.export(temp_audio.name, format="mp3")  # Changed format to mp3
            print("[LOG] Podcast generated:", temp_audio.name)
            return temp_audio.name, transcript

    except Exception as e:
        print("[ERROR] Error generating audio:", e)
        return None, f"Error generating audio: {str(e)}"

def main():
    # Set Streamlit page config
    st.set_page_config(
        page_title="MyPod - AI based Podcast Generator",
        layout="centered"
    )

    st.title("🎙 MyPod - AI-based Podcast Generator")
    st.markdown(
        """
        <style>
        .main {
            background-color: #f9f9f9;
        }
        .block-container {
            padding: 2rem;
            border-radius: 10px;
            background-color: #ffffff;
            box-shadow: 0 0 10px rgba(0,0,0,0.1);
        }
        </style>
        """,
        unsafe_allow_html=True
    )

    st.markdown(
        "Welcome to **MyPod**, your go-to AI-powered podcast generator! 🎉\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"
        "**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"
        "⏳**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"
        "🔥 **Ready to create your personalized podcast?** Give it a try now and let the magic happen! 🔥"
    )

    st.write("---")

    # Create 2 columns for inputs
    col1, col2 = st.columns(2)

    with col1:
        file = st.file_uploader("Upload PDF (Only .pdf)", type=["pdf"])
        url = st.text_input("Or Enter URL")
        video_url = st.text_input("Or Enter YouTube Link (Requires User Auth - Work in Progress)")

    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
        )

    st.write("")
    generate_button = st.button("Generate Podcast")

    if generate_button:
        # Run the generate_podcast function
        with st.spinner("Generating your podcast, please wait..."):
            podcast_file, transcript = generate_podcast(
                file, url, video_url, research_topic_input, tone, length
            )
        
        if podcast_file is None:
            st.error(transcript)
        else:
            st.success("Podcast generated successfully!")
            audio_file = open(podcast_file, 'rb')
            audio_bytes = audio_file.read()
            audio_file.close()

            st.audio(audio_bytes, format='audio/mp3')
            st.markdown(transcript)

            # Clean up the temp file
            os.remove(podcast_file)

if __name__ == "__main__":
    main()