Update app.py

app.py

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+import streamlit as st
+import youtube_dl
+from moviepy.editor import VideoFileClip
+import speech_recognition as sr
+from transformers import pipeline
+
+# Initialize the Hugging Face text generation pipeline (using GPT-Neo or GPT-2)
+generator = pipeline("text-generation", model="EleutherAI/gpt-neo-2.7B")
+
+def download_video(url):
+    ydl_opts = {
+        'format': 'bestvideo+bestaudio/best',
+        'outtmpl': 'downloaded_video.mp4'
+    }
+    with youtube_dl.YoutubeDL(ydl_opts) as ydl:
+        ydl.download([url])
+
+def trim_video(video_path, start_time, end_time):
+    video = VideoFileClip(video_path)
+    trimmed_video = video.subclip(start_time, end_time)
+    trimmed_video.write_videofile("trimmed_video.mp4")
+
+def transcribe_audio(video_path):
+    recognizer = sr.Recognizer()
+    with sr.AudioFile(video_path) as source:
+        audio = recognizer.record(source)
+    try:
+        text = recognizer.recognize_google(audio)  # This uses Google's free Web Speech API
+        return text
+    except sr.UnknownValueError:
+        return "Sorry, I could not understand the audio."
+    except sr.RequestError:
+        return "Error with the API request."
+
+def generate_subtitles(text):
+    # Use Hugging Face's GPT-Neo model for text generation
+    generated_text = generator(text, max_length=150, num_return_sequences=1)
+    return generated_text[0]['generated_text']
+
+# Streamlit Interface
+st.title("YouTube Video Trimmer and Subtitle Generator")
+url = st.text_input("Enter YouTube URL")
+start_time = st.selectbox("Select Start Time", [0, 15, 30, 60])
+end_time = st.selectbox("Select End Time", [15, 30, 60, 90])
+
+font_style = st.selectbox("Select Font Style", ["Arial", "Helvetica", "Times New Roman", "Courier"])
+
+if st.button("Generate"):
+    # Download and trim the video
+    download_video(url)
+    trim_video("downloaded_video.mp4", start_time, end_time)
+    
+    # Transcribe audio to text
+    transcription = transcribe_audio("trimmed_video.mp4")
+    
+    # Generate subtitles using Hugging Face's GPT model
+    subtitles = generate_subtitles(transcription)
+    
+    # Show trimmed video and generated subtitles
+    st.video("trimmed_video.mp4")
+    st.subheader("Subtitles:")
+    st.write(subtitles)