Update app.py

app.py

@@ -35,16 +35,52 @@ st.caption(
     "Predict reaction products, reactants, or yields from your inputs using a pretrained ReactionT5 model."
 )
 
+# ------------------------------
+# Sidebar: configuration
+# ------------------------------
+with st.sidebar:
+    st.header("Configuration")
+
+    task = st.selectbox(
+        "Task",
+        options=["product prediction", "retrosynthesis prediction", "yield prediction"],
+        index=0,
+        help="Choose the task to run.",
+    )
+
 with st.expander("How to format your CSV", expanded=False):
-    st.markdown(
-        """
-- Include a required `REACTANT` column.  
+    if task == "product prediction":
+        st.markdown(
+            """
+- `REACTANT` column is required.  
 - Optional columns: `REAGENT`, `SOLVENT`, `CATALYST`.  
 - If a field lists multiple compounds, separate them with a dot (`.`).  
-- For details, download **demo_reaction_data.csv** and check its contents.
-- Output contains predicted product SMILES and the sum of log-likelihoods for each prediction, sorted by log-likelihood (index 0 is most probable).
+- For details, download **demo_reaction_data.csv** and check its contents.  
+- Output contains predicted product **SMILES** and the sum of log-likelihoods for each prediction,  
+  sorted by log-likelihood (index 0 is most probable).
 """
-    )
+        )
+    elif task == "retrosynthesis prediction":
+        st.markdown(
+            """
+- `PRODUCT` column is required.  
+- No optional columns are used.  
+- If a field lists multiple compounds, separate them with a dot (`.`).  
+- For details, download **demo_retro_data.csv** and check its contents.  
+- Output contains predicted **sets of reactant SMILES** and their log-likelihoods,  
+  sorted by log-likelihood (index 0 is most probable).
+"""
+        )
+    else:  # yield prediction
+        st.markdown(
+            """
+- `REACTANT` and `PRODUCT` columns are required.  
+- Optional columns: `REAGENT`, `SOLVENT`, `CATALYST`.  
+- If a field lists multiple compounds, separate them with a dot (`.`).  
+- For details, download **demo_yield_data.csv** and check its contents.  
+- Output contains predicted **reaction yield** on a **0–100% scale**.
+"""
+        )
 
 # ------------------------------
 # Demo data download
@@ -81,14 +117,6 @@ st.divider()
 # ------------------------------
 with st.sidebar:
     st.header("Configuration")
-
-    task = st.selectbox(
-        "Task",
-        options=["product prediction", "retrosynthesis prediction", "yield prediction"],
-        index=0,
-        help="Choose the task to run.",
-    )
-
     # Model options tied to task
     if task == "product prediction":
         model_options = [