updated the home and info pages

src/streamlit_app.py

@@ -2,46 +2,106 @@ import streamlit as st
 from downloader import download_video
 from extractor import extract_audio
 from detector import detect_accent
-
 import asyncio
+
+# Setup async event loop
 try:
     asyncio.get_running_loop()
 except RuntimeError:
     loop = asyncio.new_event_loop()
     asyncio.set_event_loop(loop)
 
+st.set_page_config(page_title="Accentometer", page_icon="🎙️")
+
+# Sidebar navigation
+st.sidebar.title("🎙️ Accentometer")
+page = st.sidebar.radio("", ["Home", "Info"])
+
+# ---------------------------
+# Page 1: Home
+# ---------------------------
+if page == "Home":
+    st.title("🎙️ Accentometer")
+
+    # ✅ Example video links
+    st.markdown("### 🎧 Try with these example MP4 links:")
+
+    st.text("Australian:   https://docs.google.com/uc?export=download&id=12dKoO-jgWgjor_aQpovbtwOulMQBEEps")
+    st.text("British:   https://docs.google.com/uc?export=download&id=10aiY_0dnsWXqhxeNL54n5LYe6l4XquR8")
+    st.text("American:   https://docs.google.com/uc?export=download&id=1k1wfSxmQ-ZbYCKNZrb0aF8xfM6JWEfKQ")
+
+    st.markdown("<br><br>", unsafe_allow_html=True)
+    
+    st.write("Paste a direct public MP4 video URL to **classify the English accent, get transcript**.")
+
+    video_url = st.text_input("Direct Video URL (MP4 only):")
+
+    if st.button("Analyze"):
+        if not video_url:
+            st.error("Please provide a valid MP4 video URL.")
+        else:
+            try:
+                with st.spinner("Downloading video..."):
+                    video_file_path = download_video(video_url)
+
+                with st.spinner("Extracting audio..."):
+                    audio_file = extract_audio(video_file_path)
+
+                with st.spinner("Transcribing & detecting accent..."):
+                    accent, confidence, transcript = detect_accent(audio_file)
+
+                st.success(f"Accent: **{accent}**")
+                st.metric(label="Confidence", value=f"{confidence}%")
+                st.text_area("Transcript", transcript, height=150, disabled=True)
+
+            except Exception as e:
+                st.error(f"Error: {str(e)}")
+
+
+# ---------------------------
+# Page 2: Info
+# ---------------------------
+elif page == "Info":
+
+    st.title("ℹ️ About Accentometer")
+
+    st.markdown("""
+    ### 🧠 What is Accentometer?
+
+    **Accentometer** is a simple **demo** application for English accent classification.  
+    It doesn't use any advanced machine learning or deep learning models beyond basic heuristics.
+
+    ---
+
+    ### ⚙️ How It Works
+
+    1. **Video Downloader**  
+    Accepts only **direct MP4 links**.  
+    (Loom URLs aren’t supported in this free demo version — integration would require a paid Loom API or other backend setup.)
 
-st.set_page_config(page_title="Accent Detector", page_icon="🎙️")
+    2. **Audio Extraction**  
+    Uses the `moviepy` library to extract the audio from the video.
 
-st.title("🎙️ English Accent Classifier")
-st.write("Paste a public Loom or MP4 link to get an English accent classification.")
+    3. **Speech-to-Text**  
+    Applies the `openai/whisper-base` model from Hugging Face to transcribe the audio into text.
 
-# Input option (URL only)
-video_url = st.text_input("Video URL (MP4 or Loom):")
+    4. **Accent Detection**  
+    Runs simple **hand-crafted heuristic rules** over the transcribed text to classify the accent into:
+    - 🇺🇸 American
+    - 🇬🇧 British
+    - 🇦🇺 Australian
+    - 🇮🇳 Indian
+    - ❓ Unknown
 
-# When user clicks Analyze
-if st.button("Analyze"):
+    ---
 
-    if not video_url:
-        st.error("Please provide a video URL.")
-    else:
-        try:
-            # Step 1: Download video
-            with st.spinner("Downloading video..."):
-                video_file_path = download_video(video_url)
+    ### 🚀 Possible Improvements
 
-            # Step 2: Extract audio
-            with st.spinner("Extracting audio..."):
-                audio_file = extract_audio(video_file_path)
+    If you're interested in expanding this demo into a more robust application:
 
-            # Step 3: Detect accent
-            with st.spinner("Transcribing & detecting accent..."):
-                accent, confidence, transcript = detect_accent(audio_file)
+    - **Support More Input Options**: Upload local MP4 files, YouTube links, Loom links (via API), Additional video formats, etc.
+    - **Improve Accent Detection**: Train a custom model using a labeled accent dataset, or integrate a model like `accent-id-commonaccent_xlsr-en-english`, or other approaches.
 
-            # Display results
-            st.success(f"Accent: **{accent}**")
-            st.metric(label="Confidence", value=f"{confidence}%")
-            st.text_area("Transcript", transcript, height=150, disabled=True)
+    ---
+    """)
 
-        except Exception as e:
-            st.error(f"Error: {str(e)}")