app.py

import gradio as gr
import os
from dotenv import load_dotenv
from tool import YouTubeTranscriptExtractor, TranscriptSummarizer, TranscriptToDocx

# Load environment variables
load_dotenv()

youtube_tool = YouTubeTranscriptExtractor()
docx_tool = TranscriptToDocx()
#summarizer_tool = TranscriptSummarizer()
import sys
print(sys.version)
def process_youtube_video(video_url, hf_api_key, gemini_api_key, model_name, existing_docx_path=None):
    # Initialize tools
    summarizer_tool = TranscriptSummarizer(
        hf_api_key=hf_api_key,
        gemini_api_key=gemini_api_key,
        model_name=model_name
    )

    # Get video title
    from pytubefix import YouTube
    try:
        yt = YouTube(video_url)
        video_title = yt.title
    except Exception:
        video_title = "YouTube Video"

    # Extract transcript and detect language
    transcript_result = youtube_tool.forward(video_url=video_url)

    # Parse the formatted string response
    # Format: "LANGUAGE:lang||transcript_text"
    try:
        if "LANGUAGE:" in transcript_result and "||" in transcript_result:
            parts = transcript_result.split("||", 1)
            language = parts[0].replace("LANGUAGE:", "").strip()
            transcript = parts[1]
            print(f"Detected language: {language}")
        else:
            # Fallback if we didn't get the expected format
            transcript = transcript_result
            language = "en"
            print("Warning: Could not detect language, using English as default")
    except Exception as e:
        transcript = transcript_result if isinstance(transcript_result, str) else "Error extracting transcript"
        language = "en"
        print(f"Warning: Error parsing transcript data: {str(e)}, using English as default")

    # Generate summary and get image URL
    summary_and_blog = summarizer_tool.forward(transcript=transcript, language=language)
    try:
        if "\n\nImage URL: " in summary_and_blog:
            summary, image_url = summary_and_blog.split("\n\nImage URL: ")
        else:
            summary = summary_and_blog
            image_url = None
    except Exception:
        summary = summary_and_blog
        image_url = None

    # Generate or update DOCX file
    # Handle the file path from Gradio
    docx_file_path = None
    if existing_docx_path is not None and existing_docx_path != "" and existing_docx_path != []:
        # If it's a temporary file path from Gradio
        if isinstance(existing_docx_path, str) and os.path.exists(existing_docx_path):
            docx_file_path = existing_docx_path
        # If it's a file object from Gradio
        elif hasattr(existing_docx_path, 'name') and os.path.exists(existing_docx_path.name):
            docx_file_path = existing_docx_path.name
        # If it's a list (Gradio sometimes returns a list for file components)
        elif isinstance(existing_docx_path, list) and len(existing_docx_path) > 0 and existing_docx_path[0] is not None:
            if isinstance(existing_docx_path[0], str) and os.path.exists(existing_docx_path[0]):
                docx_file_path = existing_docx_path[0]
            elif hasattr(existing_docx_path[0], 'name') and os.path.exists(existing_docx_path[0].name):
                docx_file_path = existing_docx_path[0].name

    docx_path = docx_tool.forward(
        transcript=transcript,
        summary=summary,
        video_title=video_title,
        image_path=image_url,
        existing_docx_path=docx_file_path
    )

    return transcript, summary, image_url, docx_path

with gr.Blocks() as demo:
    gr.Markdown("# YouTube Transcript Summarizer and Blog Content Generator")
    gr.Markdown("Enter a YouTube video URL and Hugging Face API Key to extract the transcript, summarize it, and generate blog content with an image and DOCX file. Optionally, you can provide an existing DOCX file to update.")

    # Information about API keys
    gr.Markdown("### API Keys and Model Configuration")
    gr.Markdown("You need to provide both a Hugging Face API key (for image generation) and a Gemini API key (for summarization). You can now enter your Gemini API key directly in the UI or set it in the .env file.")

    with gr.Row():
        with gr.Column():
            video_url = gr.Textbox(label="YouTube Video URL")

            # API Keys
            gr.Markdown("#### API Keys")
            hf_api_key = gr.Textbox(label="Hugging Face API Key", type="password")
            gemini_api_key = gr.Textbox(
                label="Gemini API Key",
                type="password",
                value=os.getenv("GEMINI_API_KEY", "")
            )

            # Model Selection
            model_name = gr.Dropdown(
                label="Gemini Model",
                choices=["gemini-2.0-flash", "gemini-1.5-pro", "gemini-1.5-flash"],
                value="gemini-2.0-flash"
            )

            existing_docx = gr.File(label="Existing DOCX file (optional)", file_types=[".docx"])
            submit_btn = gr.Button("Process Video")

        with gr.Column():
            transcript_output = gr.Textbox(label="Transcript")
            summary_output = gr.Textbox(label="Summary and Blog Content")
            image_output = gr.Image(label="Generated Image", image_mode="RGBA")
            docx_output = gr.File(label="Generated DOCX File")

    submit_btn.click(
        fn=process_youtube_video,
        inputs=[video_url, hf_api_key, gemini_api_key, model_name, existing_docx],
        outputs=[transcript_output, summary_output, image_output, docx_output]
    )

iface = demo

iface.launch()