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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()
def process_youtube_video(video_url, hf_api_key, existing_docx_path=None):
# Initialize tools
summarizer_tool = TranscriptSummarizer(hf_api_key=hf_api_key)
# 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.")
# Check if Gemini API key is set
gemini_api_key = os.getenv("GEMINI_API_KEY")
if not gemini_api_key or gemini_api_key == "your_gemini_api_key_here":
gr.Markdown("⚠️ **Warning**: Gemini API key is not set in the .env file. Please add your Gemini API key to the .env file to use the summarization feature.")
with gr.Row():
with gr.Column():
video_url = gr.Textbox(label="YouTube Video URL")
hf_api_key = gr.Textbox(label="Hugging Face API Key", type="password")
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, existing_docx],
outputs=[transcript_output, summary_output, image_output, docx_output]
)
iface = demo
iface.launch()
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