Update app.py

app.py

@@ -257,8 +257,11 @@ if "explainer" not in st.session_state:
 
 # ---------------- TRAIN ----------------
 with tab_train:
+    st.subheader("Train model")
+
     train_file = st.file_uploader("Upload training Excel (.xlsx)", type=["xlsx"])
-    if train_file:
+
+    if train_file is not None:
         df = pd.read_excel(train_file, engine="openpyxl")
         st.dataframe(df.head())
 
@@ -269,8 +272,10 @@ with tab_train:
 
                 st.session_state.pipe = pipe
                 st.session_state.explainer = explainer
+                st.session_state.meta = meta
 
             st.success("Training complete. model.joblib and meta.json created.")
+
             m = meta["metrics"]
             c1, c2, c3, c4 = st.columns(4)
             c1.metric("ROC AUC", f"{m['roc_auc']:.3f}")
@@ -278,6 +283,31 @@ with tab_train:
             c3.metric("Train N", m["n_train"])
             c4.metric("Test N", m["n_test"])
 
+    # ---------------- PUBLISH (only after training) ----------------
+    if st.session_state.get("pipe") is not None:
+        st.divider()
+        st.subheader("Publish trained model to Hugging Face Hub")
+
+        MODEL_REPO_ID = "Synav/LogiSHAP-Studio-LogReg"
+        default_version = datetime.utcnow().strftime("%Y%m%d-%H%M%S")
+
+        version_tag = st.text_input(
+            "Version tag",
+            value=default_version,
+            help="Used as releases/<version>/ in the model repository",
+        )
+
+        if st.button("Publish model.joblib + meta.json to Model Repo"):
+            try:
+                with st.spinner("Uploading to Hugging Face Model repo..."):
+                    paths = publish_to_hub(MODEL_REPO_ID, version_tag)
+
+                st.success("Uploaded successfully to your model repository.")
+                st.json(paths)
+
+            except Exception as e:
+                st.error(f"Upload failed: {e}")
+
 
 # ---------------- PREDICT ----------------
 with tab_predict: