Update app.py

app.py

@@ -6,9 +6,33 @@ import whisper
 from transformers import pipeline, MarianMTModel, MarianTokenizer
 import yt_dlp as youtube_dl
 
-
 # App Configuration
-st.set_page_config(page_title="Video-to-Text Summarization", layout="centered")
+st.set_page_config(page_title="Video-to-Text Summarization", layout="wide")
+
+# Navbar-like Section
+st.markdown("""
+    <style>
+        .nav-links {
+            display: flex;
+            justify-content: center;
+            gap: 20px;
+        }
+        .nav-links a {
+            text-decoration: none;
+            padding: 10px 20px;
+            background: #4CAF50;
+            color: white;
+            border-radius: 5px;
+        }
+    </style>
+""", unsafe_allow_html=True)
+
+st.markdown("""
+    <div class='nav-links'>
+        <a href='#local-upload'>Upload Local Video</a>
+        <a href='#youtube-upload'>Upload YouTube Video</a>
+    </div>
+""", unsafe_allow_html=True)
 
 # Header
 st.title("🎥 Smart Video-to-Text Summarization App")
@@ -23,24 +47,23 @@ This app helps you:
 if "video_path" not in st.session_state:
     st.session_state.video_path = None
 
-# 1. Upload Video Section
+# Upload Video Section
 st.header("Upload Your Video")
 
-# Choose upload option
-upload_option = st.selectbox("Select Upload Method", ["Local", "YouTube URL"])
+col1, col2 = st.columns(2)
 
-# Upload Local File
-if upload_option == "Local":
-    video_file = st.file_uploader("Upload your video file", type=["mp4", "mkv", "avi"])
+with col1:
+    st.subheader("📁 Upload Local Video")
+    video_file = st.file_uploader("Upload your video file", type=["mp4", "mkv", "avi"], key="local-upload")
     if video_file:
         with open("uploaded_video.mp4", "wb") as f:
             f.write(video_file.read())
         st.session_state.video_path = "uploaded_video.mp4"
         st.success("Video uploaded successfully!")
 
-# Download Video from YouTube
-elif upload_option == "YouTube URL":
-    youtube_url = st.text_input("Enter YouTube URL")
+with col2:
+    st.subheader("📺 Upload YouTube Video")
+    youtube_url = st.text_input("Enter YouTube URL", key="youtube-upload")
     if youtube_url:
         try:
             os.system(f"yt-dlp -o video.mp4 {youtube_url}")
@@ -49,12 +72,11 @@ elif upload_option == "YouTube URL":
         except Exception as e:
             st.error(f"Error downloading video: {str(e)}")
 
-# 2. Process Video Section (After Upload)
+# Process Video Section
 if st.session_state.video_path:
     st.header("Process Your Video")
     st.write(f"Processing {st.session_state.video_path}...")
-
-    # Extract Audio from Video
+    
     def extract_audio(video_path):
         try:
             audio = AudioSegment.from_file(video_path)
@@ -66,8 +88,7 @@ if st.session_state.video_path:
             return None
 
     audio_path = extract_audio(st.session_state.video_path)
-
-    # Real-time Audio Transcription
+    
     def transcribe_audio(audio_path):
         try:
             model = whisper.load_model("base")
@@ -81,11 +102,10 @@ if st.session_state.video_path:
     if audio_path:
         transcription = transcribe_audio(audio_path)
 
-# 3. Summarize and Translate
+# Summarize and Translate Section
 if 'transcription' in locals():
     st.header("Results")
 
-    # Summarize Text
     def summarize_text(text):
         try:
             summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
@@ -98,7 +118,6 @@ if 'transcription' in locals():
 
     summary = summarize_text(transcription)
 
-    # Translate Text
     def translate_text(text, src_lang="en", tgt_lang="es"):
         try:
             model_name = f"Helsinki-NLP/opus-mt-{src_lang}-{tgt_lang}"
@@ -117,4 +136,4 @@ if 'transcription' in locals():
         translated_summary = translate_text(summary, tgt_lang=target_language)
 
 else:
-    st.info("Please upload a video to start the process.")
+    st.info("Please upload a video to start the process.")