import os
from uuid import uuid4
from agno.agent import Agent
from agno.run.agent import RunOutput
from agno.models.openai import OpenAIChat
from agno.tools.firecrawl import FirecrawlTools
from elevenlabs import ElevenLabs
import streamlit as st

# Streamlit Setup
st.set_page_config(page_title="📰 ➡️ 🎙️ Blog to Podcast", page_icon="🎙️")
st.title("📰 ➡️ 🎙️ Blog to Podcast Agent")

# API Keys (Runtime Input)
st.sidebar.header("🔑 API Keys")
openai_key = st.sidebar.text_input("OpenAI API Key", type="password")
elevenlabs_key = st.sidebar.text_input("ElevenLabs API Key", type="password")
firecrawl_key = st.sidebar.text_input("Firecrawl API Key", type="password")

# Blog URL Input
url = st.text_input("Enter Blog URL:", "")

# Generate Button
if st.button("🎙️ Generate Podcast", disabled=not all([openai_key, elevenlabs_key, firecrawl_key])):
    if not url.strip():
        st.warning("Please enter a blog URL")
    else:
        with st.spinner("Scraping blog and generating podcast..."):
            try:
                # Set API keys
                os.environ["OPENAI_API_KEY"] = openai_key
                os.environ["FIRECRAWL_API_KEY"] = firecrawl_key
                
                # Create agent for scraping and summarization
                agent = Agent(
                    name="Blog Summarizer",
                    model=OpenAIChat(id="gpt-4o"),
                    tools=[FirecrawlTools()],
                    instructions=[
                        "Scrape the blog URL and create a concise, engaging summary (max 2000 characters) suitable for a podcast.",
                        "The summary should be conversational and capture the main points."
                    ],
                )
                
                # Get summary
                response: RunOutput = agent.run(f"Scrape and summarize this blog for a podcast: {url}")
                summary = response.content if hasattr(response, 'content') else str(response)
                
                if summary:
                    # Initialize ElevenLabs client and generate audio
                    client = ElevenLabs(api_key=elevenlabs_key)
                    
                    # Generate audio using text_to_speech.convert
                    audio_generator = client.text_to_speech.convert(
                        text=summary,
                        voice_id="JBFqnCBsd6RMkjVDRZzb",
                        model_id="eleven_multilingual_v2"
                    )
                    
                    # Collect audio chunks if it's a generator
                    audio_chunks = []
                    for chunk in audio_generator:
                        if chunk:
                            audio_chunks.append(chunk)
                    audio_bytes = b"".join(audio_chunks)
                    
                    # Display audio
                    st.success("Podcast generated! 🎧")
                    st.audio(audio_bytes, format="audio/mp3")
                    
                    # Download button
                    st.download_button(
                        "Download Podcast",
                        audio_bytes,
                        "podcast.mp3",
                        "audio/mp3"
                    )
                    
                    # Show summary
                    with st.expander("📄 Podcast Summary"):
                        st.write(summary)
                else:
                    st.error("Failed to generate summary")
                    
            except Exception as e:
                st.error(f"Error: {e}")