Update app.py

app.py

@@ -279,10 +279,11 @@ def generate_rationale(risks, amount, sectors, markets, style, recs):
     try:
         sents = _generate_sentences(prompts)
     except Exception as e:
-        # A GPU failure must not take the whole recommendation down; the table
-        # above is still valid and useful on its own.
+        # A GPU failure must not take the whole recommendation down: the table
+        # above is still valid. The exception message is surfaced so the cause
+        # is diagnosable rather than hidden behind a generic "Error".
         return (f"_Recommendations above are complete. The written explanation "
-                f"could not be generated: {type(e).__name__}._")
+                f"could not be generated._\n\n`{type(e).__name__}: {e}`")
 
     amt = parse_amount(amount)
     rl  = "/".join(_as_list(risks)).lower() or "flexible"
@@ -309,13 +310,14 @@ DISPLAY_COLS = ["ticker", "sector", "market_region", "cluster_name", "risk_level
 
 def run_custom(risks, amount, sectors, markets, style, caps):
     """Plain function, not a generator: @spaces.GPU does not compose well with
-    Gradio generator callbacks, and on GPU the whole round trip is ~2 seconds."""
-    recs, note, query = recommend(risks, amount, sectors, markets, style, caps)
+    Gradio generator callbacks. The semantic query is computed but not shown —
+    it is an internal representation, not something a user needs to read."""
+    recs, note, _query = recommend(risks, amount, sectors, markets, style, caps)
     if recs.empty:
-        return pd.DataFrame(), note, ""
+        return pd.DataFrame(), note
     cols = [c for c in DISPLAY_COLS if c in recs.columns]
     text = generate_rationale(risks, amount, sectors, markets, style, recs)
-    return recs[cols], (note + "\n\n" + text).strip(), f"*Semantic query:* `{query}`"
+    return recs[cols], (note + "\n\n" + text).strip()
 
 def run_quickstart(name):
     """Served from the pre-generated cache — instant, uses no GPU quota."""
@@ -325,12 +327,7 @@ def run_quickstart(name):
               "market_cap_millions_usd"]:
         if c in tbl.columns:
             tbl[c] = pd.to_numeric(tbl[c], errors="coerce")
-    a = entry["answers"]
-    return (tbl[[c for c in DISPLAY_COLS if c in tbl.columns]],
-            entry["rationale"],
-            f"*Preset profile:* {a['risk_level']} risk · ${a['investment_amount']:,} · "
-            f"{a['sector']} · {a['target_market']} · {a['stock_type']} · "
-            f"{a['market_cap_pref']} cap")
+    return tbl[[c for c in DISPLAY_COLS if c in tbl.columns]], entry["rationale"]
 
 # ---------------------------------------------------------------------------
 # UI
@@ -363,8 +360,13 @@ with gr.Blocks(title="StockMatch AI", theme=gr.themes.Soft()) as demo:
             q3 = gr.Dropdown(SECTORS, value=["Utilities"], multiselect=True,
                              label="3. Sector (select one or more, or none for all)")
         with gr.Column():
+            # The dataset covers four regions built from seven exchanges, so
+            # country choices map upward: Japan and China -> Asia, Switzerland
+            # and the UK -> Europe. The label states this rather than silently
+            # substituting a different market.
             q4 = gr.Dropdown(MARKETS, value=["USA"], multiselect=True,
-                             label="4. Target market (select one or more, or none for all)")
+                             label="4. Target market — grouped into US / Europe / "
+                                   "Israel / Asia (select one or more, or none for all)")
             q5 = gr.Radio(["Dividend", "Growth"], value="Dividend",
                           label="5. Stock type preference")
             q6 = gr.CheckboxGroup(["Small", "Medium", "Large"], value=["Large"],
@@ -372,13 +374,12 @@ with gr.Blocks(title="StockMatch AI", theme=gr.themes.Soft()) as demo:
     go = gr.Button("🔍 Find my stocks", variant="primary", size="lg")
 
     gr.Markdown("### Results")
-    info  = gr.Markdown()
     table = gr.Dataframe(label="Matched stocks", interactive=False, wrap=True)
     text  = gr.Markdown()
 
-    go.click(run_custom, [q1, q2, q3, q4, q5, q6], [table, text, info])
-    b1.click(lambda: run_quickstart("Cautious Retiree"),      None, [table, text, info])
-    b2.click(lambda: run_quickstart("Balanced Professional"), None, [table, text, info])
-    b3.click(lambda: run_quickstart("Young Growth Seeker"),   None, [table, text, info])
+    go.click(run_custom, [q1, q2, q3, q4, q5, q6], [table, text])
+    b1.click(lambda: run_quickstart("Cautious Retiree"),      None, [table, text])
+    b2.click(lambda: run_quickstart("Balanced Professional"), None, [table, text])
+    b3.click(lambda: run_quickstart("Young Growth Seeker"),   None, [table, text])
 
 demo.launch()