import os
import openai
import streamlit as st
from youtube_transcript_api import YouTubeTranscriptApi
from langchain.text_splitter import RecursiveCharacterTextSplitter
from dotenv import load_dotenv
from fpdf import FPDF

# Set Streamlit page configuration
st.set_page_config(
    page_title="YouTube Video Summarizer",
    page_icon="🎥",
    layout="centered",
    initial_sidebar_state="expanded",
)

# Custom CSS for styling
st.markdown(
    """
    <style>
    body {
        background-color: #f4f4f4;
        font-family: Arial, sans-serif;
    }
    .stButton>button {
        background-color: #ff6347;
        color: white;
        border-radius: 10px;
        font-weight: bold;
    }
    .stSlider {
        color: #ff6347;
    }
    </style>
    """,
    unsafe_allow_html=True
)

# Function to get the transcript from YouTube
def get_transcript(youtube_url):
    video_id = youtube_url.split("v=")[-1]
    transcript_list = YouTubeTranscriptApi.list_transcripts(video_id)
    
    try:
        transcript = transcript_list.find_manually_created_transcript()
        language_code = transcript.language_code
    except:
        try:
            generated_transcripts = [trans for trans in transcript_list if trans.is_generated]
            transcript = generated_transcripts[0]
            language_code = transcript.language_code
        except:
            raise Exception("No suitable transcript found.")
    
    full_transcript = " ".join([part['text'] for part in transcript.fetch()])
    return full_transcript, language_code

# Function to summarize with OpenAI using LangChain
def summarize_with_openai(transcript, language_code, model_name='gpt-3.5-turbo'):
    text_splitter = RecursiveCharacterTextSplitter(chunk_size=2000, chunk_overlap=0)
    texts = text_splitter.split_text(transcript)
    text_to_summarize = " ".join(texts[:4])  # Adjust this as needed

    system_prompt = 'I want you to act as a Life Coach that can create good summaries!'
    prompt = f'''Summarize the following text in {language_code}.
    Text: {text_to_summarize}
    
    Add a title to the summary in {language_code}. 
    Include an INTRODUCTION, BULLET POINTS, and a CONCLUSION in {language_code}.'''

    response = openai.ChatCompletion.create(
        model=model_name,
        messages=[
            {'role': 'system', 'content': system_prompt},
            {'role': 'user', 'content': prompt}
        ],
        temperature=1
    )

    return response['choices'][0]['message']['content']

# Function to create a PDF
def create_pdf(summary):
    pdf = FPDF()
    pdf.add_page()
    pdf.set_font("Arial", size=12)
    pdf.multi_cell(200, 10, summary)
    pdf_output = "summary.pdf"
    pdf.output(pdf_output)
    return pdf_output

# Main function for the app
def main():
    st.title('🎥 YouTube Video Summarizer')

    # Slider input for OpenAI API key
    st.sidebar.title("API Configuration")
    api_key = st.sidebar.text_input("Enter OpenAI API Key:", type="password")
    openai.api_key = api_key

    # Input for YouTube video link
    st.sidebar.title("Video Settings")
    youtube_link = st.text_input("Enter the YouTube video link:")
    
    if youtube_link and api_key:
        # Start button
        if st.button("Start Summarizing 🚀"):
            try:
                progress = st.progress(0)
                st.write("Fetching transcript...")

                transcript, language_code = get_transcript(youtube_link)
                progress.progress(40)

                st.write("Summarizing transcript...")
                summary = summarize_with_openai(transcript, language_code)
                progress.progress(80)

                # Display summary
                st.markdown("### Summary:")
                st.write(summary)

                # Generate PDF and provide download link
                pdf_file = create_pdf(summary)
                with open(pdf_file, "rb") as file:
                    st.download_button(
                        label="Download Summary as PDF 📄",
                        data=file,
                        file_name="summary.pdf",
                        mime="application/pdf"
                    )

                progress.progress(100)
            except Exception as e:
                st.error(f"Error: {str(e)}")

if __name__ == "__main__":
    main()