Update app.py

app.py

@@ -1,19 +1,24 @@
-import joblib
+import os
 import librosa
 import numpy as np
+import joblib
 import gradio as gr
+from huggingface_hub import hf_hub_download
+
+# Download the model from Hugging Face Hub
+MODEL_REPO = "sangambhamare/TruthDetection"
+MODEL_FILENAME = "model.joblib"
 
-# --- Load the trained Random Forest model ---
-MODEL_PATH = "model.joblib"
-model = joblib.load(MODEL_PATH)
+model_path = hf_hub_download(repo_id=MODEL_REPO, filename=MODEL_FILENAME)
+model = joblib.load(model_path)
 
-# --- Extract MFCC features from audio ---
+# MFCC extraction
 def extract_mfcc(file_path):
     y, sr = librosa.load(file_path, sr=None)
     mfcc = librosa.feature.mfcc(y=y, sr=sr, n_mfcc=13)
     return np.mean(mfcc, axis=1)
 
-# --- Prediction function ---
+# Prediction
 def predict_audio(audio_file):
     try:
         features = extract_mfcc(audio_file).reshape(1, -1)
@@ -22,14 +27,20 @@ def predict_audio(audio_file):
     except Exception as e:
         return f"Error: {e}"
 
-# --- Gradio Interface ---
-iface = gr.Interface(
-    fn=predict_audio,
-    inputs=gr.Audio(type="filepath", label="Upload Audio File"),
-    outputs=gr.Textbox(label="Prediction"),
-    title="Truth Detection Model",
-    description="Upload an audio clip to detect if the story is true or deceptive."
-)
+# Gradio UI
+with gr.Blocks() as demo:
+    gr.Markdown("<h1 style='text-align: center;'>Truth Detection from Audio Stories</h1>")
+    gr.Markdown(
+        "<p style='text-align: center;'>"
+        "This tool analyzes a 30-second audio story and predicts whether it is true or deceptive "
+        "based on MFCC features and a trained Random Forest classifier."
+        "</p>"
+    )
+    audio_input = gr.Audio(type="filepath", label="Upload WAV Audio File (30 seconds)")
+    output = gr.Textbox(label="Prediction")
+    submit_btn = gr.Button("Predict")
+    submit_btn.click(fn=predict_audio, inputs=audio_input, outputs=output)
+    gr.Markdown("<p style='text-align: center; font-size: 12px; color: gray;'>Developed by Sangam Sanjay Bhamare, 2025.</p>")
 
 if __name__ == "__main__":
-    iface.launch()
+    demo.launch()