Update app.py

app.py

@@ -40,13 +40,15 @@ def CTXGen(X0, X1, X2, τ, g_num, model_name):
     msa_data = pd.read_csv('conoData_C0.csv') 
     msa = msa_data['Sequences'].tolist()
     msa = [x for x in msa if x.startswith(f"{X1}|{X2}")]
-    msa = random.choice(msa)
-    X4 = msa.split("|")[3]
-    X5 = msa.split("|")[4]
-    X6 = msa.split("|")[5]
-    print(X4)
-    print(X5)
-    print(X6)
+    if not msa:
+        X4 = ""
+        X5 = ""
+        X6 = ""
+    else:
+        msa = random.choice(msa)
+        X4 = msa.split("|")[3]
+        X5 = msa.split("|")[4]
+        X6 = msa.split("|")[5]
     model.eval()
     with torch.no_grad():
         new_seq = None
@@ -74,7 +76,7 @@ def CTXGen(X0, X1, X2, τ, g_num, model_name):
         logits_parent = model(torch.tensor([input_ids_parent]).to(device), idx_msaseq_parent)
 
         cls_mask_logits_parent = logits_parent[0, 1, :]
-        cls_probability_parent, cls_mask_probs_parent = torch.topk((torch.softmax(cls_mask_logits_parent, dim=-1)), k=10)
+        cls_probability_parent, cls_mask_probs_parent = torch.topk((torch.softmax(cls_mask_logits_parent, dim=-1)), k=53)
 
         seqseq_parent[2] = "[MASK]"
         input_ids_parent = vocab_mlm.__getitem__(seqseq_parent)