app.py

import gradio as gr
from google import genai
from youtube_transcript_api import YouTubeTranscriptApi
from youtube_transcript_api._errors import NoTranscriptFound, VideoUnavailable, TranscriptsDisabled


def get_transcript(video_url, lang_sel, model_sel, api_key_input):
    client = genai.Client(api_key=api_key_input)

    try:
        video_id = video_url.split("v=")[1].split("&")[0]
        print(f"Extracted Video ID: {video_id}")  # Debugging

        transcript = YouTubeTranscriptApi.get_transcript(video_id)
        raw_text = " ".join([entry["text"] for entry in transcript])
        print(f"Retrieved Transcript: {raw_text[:500]}")  # Print first 500 characters

        if lang_sel != "English":
            prompt = f"Translate this text to {lang_sel} language: {raw_text}"
            response = client.models.generate_content(
                model=model_sel,
                contents=[prompt]
            )
            return response.text

        return raw_text

    except (NoTranscriptFound, VideoUnavailable, TranscriptsDisabled) as e:
        print(f"Transcript Retrieval Error: {e}")  # Debugging
        return f"⚠️ Error: {e}"


def process_transcript(video_url, word_count, model_sel, lang_sel, api_key_input):
    client = genai.Client(api_key=api_key_input)
    transcript = get_transcript(video_url, lang_sel, model_sel, api_key_input)
    prompt = f"Summarize this text in {lang_sel} language using {word_count} words: {transcript}"
    response = client.models.generate_content(
        model=model_sel,
        contents=[prompt]
    )
    return response.text

with gr.Blocks(theme=gr.themes.Default()) as demo:
    gr.Markdown("""
    # 🎬 YouTube Video Transcription & Summarization @SenasuDemir
    **Paste a YouTube link, select options, and generate transcriptions or summaries easily!**
    """)
    
    with gr.Row():
        api_key = gr.Textbox(
            placeholder="Enter your Gemini API Key",
            label="🔑 API Key",
            type="password",
            interactive=True
        )
    
    gr.Markdown("### 1️⃣ Enter Video URL")
    video_url = gr.Textbox(
        placeholder="Paste YouTube video link here...",
        label="📺 YouTube Video URL",
        interactive=True
    )
    
    gr.Markdown("### 2️⃣ Select Language & Model")
    with gr.Row():
        language_selection = gr.Radio(
            choices=["Turkish", "English", "Italian", "German"],
            value="English",
            label="🌍 Select Translation Language"
        )
        model_selection = gr.Dropdown(
            choices=["gemini-2.0-flash", "gemini-2.0-flash-lite", "gemini-1.5-flash", "gemini-1.5-pro"],
            value="gemini-2.0-flash",
            label="🤖 Choose AI Model"
        )
        word_count = gr.Slider(
            50, 500, step=10, value=80,
            label="🔢 Summary Word Count", 
            info="Choose a length between 50 and 500 words"
        )

    
    gr.Markdown("### 3️⃣ Get Transcript & Summarization")
    with gr.Row():
        trs_btn = gr.Button("📜 Get Transcript", variant="primary")
        sum_btn = gr.Button("✍️ Summarize", variant="secondary")
    
    with gr.Row():
        transkript_text = gr.Textbox(label="🎤 Video Transcription", lines=5, interactive=False)
        sum_text = gr.Textbox(label="📝 Summarized Text", lines=3, interactive=False)
    
    
    trs_btn.click(
        fn=get_transcript,
        inputs=[video_url, language_selection, model_selection, api_key],
        outputs=transkript_text
    )
    sum_btn.click(
        fn=process_transcript,
        inputs=[video_url, word_count, model_selection, language_selection, api_key],
        outputs=sum_text
    )

if __name__ == "__main__":
    demo.launch()