Update the temp patch

app.py

@@ -231,44 +231,45 @@ st.write(
 )
 # Generate predictions when the user uploads a file
 # if submit_job_button:
-print(st.session_state)
-if "job_button" in st.session_state:
-    # when new file is uploaded
-    # update_uploader_session_info()
-    st.write(
-        f"the state of uploaded file changed after checking: {st.session_state.uploaded_file_changed}"
-    )
-    # if st.session_state.uploaded_file_changed:
-    #     temp_dir = tempfile.mkdtemp()
-    #     # Create a temporary file path for the uploaded file
-    #     temp_file_path = os.path.join(temp_dir, uploaded_file.name)
-    #     # Save the uploaded file to the temporary file path
-    #     with open(temp_file_path, "wb") as temp_file:
-    #         temp_file.write(uploaded_file.read())
-
-    #     mol_features, info_df, results = generate_predictions(
-    #         input_fname=temp_file_path,
-    #         sep="\s+|\t+",
-    #         clf=classifiers_dict[classifier],
-    #         _models_dict=all_models,
-    #         sampling=resample_methods_dict[resampler],
-    #         time_per_mol=120,
-    #         mol_features=None,
-    #         info_df=None,
-    #     )
-    #     st.session_state.mol_features = mol_features
-    #     st.session_state.info_df = info_df
-    # else:
-    #     mol_features, info_df, results = generate_predictions(
-    #         input_fname=None,
-    #         sep="\s+|\t+",
-    #         clf=classifiers_dict[classifier],
-    #         _models_dict=all_models,
-    #         sampling=resample_methods_dict[resampler],
-    #         time_per_mol=120,
-    #         mol_features=st.session_state.mol_features,
-    #         info_df=st.session_state.info_df,
-    #     )
+
+# if "job_button" in st.session_state:
+#     when new file is uploaded
+#     update_uploader_session_info()
+#     st.write(
+#         f"the state of uploaded file changed after checking: {st.session_state.uploaded_file_changed}"
+#     )
+#     if st.session_state.uploaded_file_changed:
+#         temp_dir = tempfile.mkdtemp()
+#         # Create a temporary file path for the uploaded file
+#         temp_file_path = os.path.join(temp_dir, uploaded_file.name)
+#         # Save the uploaded file to the temporary file path
+#         with open(temp_file_path, "wb") as temp_file:
+#             temp_file.write(uploaded_file.read())
+
+#         mol_features, info_df, results = generate_predictions(
+#             input_fname=temp_file_path,
+#             sep="\s+|\t+",
+#             clf=classifiers_dict[classifier],
+#             _models_dict=all_models,
+#             sampling=resample_methods_dict[resampler],
+#             time_per_mol=120,
+#             mol_features=None,
+#             info_df=None,
+#         )
+#         st.session_state.mol_features = mol_features
+#         st.session_state.info_df = info_df
+#     else:
+#         mol_features, info_df, results = generate_predictions(
+#             input_fname=None,
+#             sep="\s+|\t+",
+#             clf=classifiers_dict[classifier],
+#             _models_dict=all_models,
+#             sampling=resample_methods_dict[resampler],
+#             time_per_mol=120,
+#             mol_features=st.session_state.mol_features,
+#             info_df=st.session_state.info_df,
+#         )
+if submit_job_button and uploaded_file:
     temp_dir = tempfile.mkdtemp()
     # Create a temporary file path for the uploaded file
     temp_file_path = os.path.join(temp_dir, uploaded_file.name)