Update app.py

app.py

@@ -6,12 +6,16 @@ import torch.nn.functional as F
 import torchvision.models as models
 import tempfile
 import os
+import uuid
 
 if "uploaded_file" not in st.session_state:
     st.session_state.uploaded_file = None
+if "uploader_key" not in st.session_state:
+    st.session_state.uploader_key = str(uuid.uuid4())
 
 def reset_state():
     st.session_state.uploaded_file = None
+    st.session_state.uploader_key = str(uuid.uuid4())
     st.rerun()
 
 st.markdown(
@@ -90,11 +94,14 @@ def main():
     st.markdown('<div class="main">', unsafe_allow_html=True)
     st.title("Audio Deepfake Detector")
     st.write("Upload a **.wav** file to check if it's **Real** or **Fake**.")
-    
-    if st.session_state.uploaded_file is None:
-        uploaded_file = st.file_uploader("Choose a .wav file", type=["wav"])
-        if uploaded_file is not None:
-            st.session_state.uploaded_file = uploaded_file
+
+    uploaded_file = st.file_uploader(
+        "Choose a .wav file",
+        type=["wav"],
+        key=st.session_state.uploader_key
+    )
+    if uploaded_file is not None:
+        st.session_state.uploaded_file = uploaded_file
 
     if st.session_state.uploaded_file is not None:
         with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmp_file:
@@ -102,6 +109,7 @@ def main():
             tmp_path = tmp_file.name
 
         st.audio(st.session_state.uploaded_file, format="audio/wav")
+
         device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
         checkpoint_path = "best_model.pth"
         try:
@@ -112,8 +120,10 @@ def main():
             st.error(f"Error during prediction: {e}")
         finally:
             os.remove(tmp_path)
+
         if st.button("Reset"):
             reset_state()
+
     st.markdown("</div>", unsafe_allow_html=True)
 
 if __name__ == "__main__":