Update app.py

app.py

@@ -1,4 +1,4 @@
-import gradio as gr
+import streamlit as st
 import os
 import tempfile
 import requests
@@ -8,7 +8,7 @@ import matplotlib.pyplot as plt
 import torchaudio
 import torch
 
-# --- Load SpeechBrain ---
+# Load SpeechBrain
 try:
     from speechbrain.inference import EncoderClassifier
     speechbrain_classifier = EncoderClassifier.from_hparams(
@@ -17,10 +17,9 @@ try:
     )
     SPEECHBRAIN_LOADED = True
 except Exception as e:
-    print(f"Error loading SpeechBrain model: {e}. Simulated mode ON.")
+    st.warning(f"Error loading SpeechBrain model: {e}. Running in simulation mode.")
     SPEECHBRAIN_LOADED = False
 
-# --- Accent Analyzer Class ---
 class AccentAnalyzer:
     def __init__(self):
         self.accent_profiles = {
@@ -91,10 +90,9 @@ class AccentAnalyzer:
                 "all_scores": scores
             }
         except Exception as e:
-            print(f"Fallback to simulation: {e}")
+            st.warning(f"Fallback to simulation: {e}")
             return self._simulate_accent_classification(audio_path)
 
-# --- Download & Extract Audio ---
 def download_and_extract_audio(url):
     temp_dir = tempfile.mkdtemp()
     video_path = os.path.join(temp_dir, "video.mp4")
@@ -102,7 +100,7 @@ def download_and_extract_audio(url):
 
     if "youtube.com" in url or "youtu.be" in url:
         from pytubefix import YouTube
-        yt = YouTube(url, use_oauth=True, allow_oauth_cache=True, client="WEB")
+        yt = YouTube(url, use_po_token=True, client="WEB")
         stream = yt.streams.filter(progressive=True, file_extension='mp4').first()
         stream.download(output_path=temp_dir, filename="video.mp4")
     else:
@@ -112,41 +110,33 @@ def download_and_extract_audio(url):
                 for chunk in r.iter_content(chunk_size=8192):
                     f.write(chunk)
 
-    # Extract audio using ffmpeg
     subprocess.run([
         "ffmpeg", "-i", video_path, "-ar", "16000", "-ac", "1", "-f", "wav", audio_path, "-y"
     ], stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
 
     return audio_path
 
-# --- Gradio Function ---
-def analyze_from_url_gradio(url):
-    if not url:
-        return "Please enter a URL.", plt.figure()
-    try:
-        audio_path = download_and_extract_audio(url)
-        analyzer = AccentAnalyzer()
-        results = analyzer.analyze_accent(audio_path)
-
-        labels, values = zip(*results["all_scores"].items())
-        fig, ax = plt.subplots()
-        ax.bar(labels, values)
-        ax.set_ylabel('Confidence (%)')
-        ax.set_title('Accent/Language Confidence')
-        plt.xticks(rotation=45)
-        plt.tight_layout()
+# Streamlit UI
+st.title("English Accent or Language Analyzer")
+url = st.text_input("Enter Public Video URL (YouTube or MP4)")
 
-        return results["explanation"], fig
-    except Exception as e:
-        return f"Error: {e}", plt.figure()
+if st.button("Analyze"):
+    if not url:
+        st.error("Please enter a URL.")
+    else:
+        try:
+            audio_path = download_and_extract_audio(url)
+            analyzer = AccentAnalyzer()
+            results = analyzer.analyze_accent(audio_path)
 
-# --- Gradio Interface ---
-iface = gr.Interface(
-    fn=analyze_from_url_gradio,
-    inputs=gr.Textbox(label="Enter Public Video URL (YouTube or MP4)"),
-    outputs=[gr.Textbox(label="Result"), gr.Plot(label="Confidence Plot")],
-    title="English Accent or Language Analyzer",
-    description="Paste a public video URL. The system will detect the accent or language spoken using SpeechBrain or simulation."
-)
+            st.markdown(results["explanation"])
 
-iface.launch()
+            labels, values = zip(*results["all_scores"].items())
+            fig, ax = plt.subplots()
+            ax.bar(labels, values)
+            ax.set_ylabel('Confidence (%)')
+            ax.set_title('Accent/Language Confidence')
+            plt.xticks(rotation=45)
+            st.pyplot(fig)
+        except Exception as e:
+            st.error(f"Error: {e}")