update app.py

app.py

@@ -42,35 +42,38 @@ def pick_unique(idxs, goal, energy, max_minutes, ignore_goal=False, ignore_energ
     return out, used
 
 def fill_random(need, used, goal, energy, max_minutes):
-    pool = [a for a in actions if a["title"] not in used and a["title"] not in recent
-            and (not goal or a["goal"]==goal)
-            and (not energy or a["energy"]==energy)
-            and (not max_minutes or a["duration_min"]<=int(max_minutes))]
+    pool = [a for a in actions if a["title"] not in used and a["title"] not in recent and (not goal or a["goal"]==goal) and (not energy or a["energy"]==energy) and (not max_minutes or a["duration_min"]<=int(max_minutes))]
     if len(pool) < need:
         pool = [a for a in actions if a["title"] not in used and a["title"] not in recent]
     random.shuffle(pool)
     return pool[:need]
 
 def search(query, goal, energy, max_minutes):
-    q = (query or "").strip()
-    qx = f"{q} Goal:{goal or 'any'} Energy:{energy or 'any'} Max:{int(max_minutes) if max_minutes else ''} minutes"
-    v = model.encode([qx], normalize_embeddings=True)
-    D, I = index.search(np.asarray(v, dtype="float32"), 800)
-    idxs = list(I[0]); random.shuffle(idxs)
-
-    res, used = [], set()
-    step, used = pick_unique(idxs, goal, energy, max_minutes, False, False, False, 3, used); res += step
-    if len(res) < 3:
-        step, used = pick_unique(idxs, goal, energy, max_minutes, False, True, False, 3-len(res), used); res += step
-    if len(res) < 3:
-        step, used = pick_unique(idxs, goal, energy, max_minutes, False, True, True, 3-len(res), used); res += step
-    if len(res) < 3:
-        step, used = pick_unique(idxs, goal, energy, max_minutes, True, True, True, 3-len(res), used); res += step
-    if len(res) < 3:
-        res += fill_random(3-len(res), used, goal, energy, max_minutes)
-
-    recent.extend([a["title"] for a in res[:3]])
-    return "\n\n---\n\n".join(render(a) for a in res[:3])
+    try:
+        q = (query or "").strip()
+        qx = f"{q} Goal:{goal or 'any'} Energy:{energy or 'any'} Max:{int(max_minutes) if max_minutes else ''} minutes"
+        v = model.encode([qx], normalize_embeddings=True)
+        D, I = index.search(np.asarray(v, dtype="float32"), 800)
+        idxs = list(I[0])
+        random.shuffle(idxs)
+        res, used = [], set()
+        step, used = pick_unique(idxs, goal, energy, max_minutes, False, False, False, 3, used); res += step
+        if len(res) < 3:
+            step, used = pick_unique(idxs, goal, energy, max_minutes, False, True, False, 3-len(res), used); res += step
+        if len(res) < 3:
+            step, used = pick_unique(idxs, goal, energy, max_minutes, False, True, True, 3-len(res), used); res += step
+        if len(res) < 3:
+            step, used = pick_unique(idxs, goal, energy, max_minutes, True, True, True, 3-len(res), used); res += step
+        if len(res) < 3:
+            res += fill_random(3-len(res), used, goal, energy, max_minutes)
+        recent.extend([a["title"] for a in res[:3]])
+        return "\n\n---\n\n".join(render(a) for a in res[:3])
+    except Exception:
+        pool = [a for a in actions if (not goal or a["goal"]==goal) and (not energy or a["energy"]==energy) and (not max_minutes or a["duration_min"]<=int(max_minutes))]
+        if len(pool) < 3:
+            pool = actions[:]
+        random.shuffle(pool)
+        return "\n\n---\n\n".join(render(a) for a in pool[:3])
 
 goals = ["","calm","focus","productivity","wellbeing"]
 energies = ["","low","medium","high"]
@@ -86,4 +89,17 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="indigo", neutral_hue="slate"))
             e = gr.Radio(energies, label="Energy")
             m = gr.Slider(1, 15, step=1, value=5, label="Max minutes")
     out = gr.Markdown()
-    btn.click(search,
+    btn.click(search, [q, g, e, m], out)
+    gr.Examples(
+        [["Stressed before exam","calm","low",5],
+         ["No energy but need to start studying","focus","low",7],
+         ["Keep switching tabs while writing essay","focus","medium",10]],
+        inputs=[q, g, e, m],
+        outputs=out,
+        fn=search,
+        label="One-click examples",
+        cache_examples=False
+    )
+
+demo.queue(concurrency_count=4, max_size=32)
+demo.launch()