Update app.py

app.py

@@ -12,6 +12,7 @@ def train(data: str, message: str):
     if "→" not in data and "\n" not in data:
         return "Dataset should be like:\nquestion→answer\nquestion→answer\netc."
     dset, responses = todset(data)
+    resps_len = len(responses)
     tokenizer = Tokenizer()
     tokenizer.fit_on_texts(list(dset.keys()))
     
@@ -26,7 +27,7 @@ def train(data: str, message: str):
     model.add(Dense(512, activation="relu"))
     model.add(Dense(512, activation="relu"))
     model.add(Dense(256, activation="relu"))
-    model.add(Dense(dset_size, activation="softmax"))
+    model.add(Dense(resps_len, activation="softmax"))
     
     X = []
     y = []
@@ -34,7 +35,7 @@ def train(data: str, message: str):
     for key in dset:
         tokens = tokenizer.texts_to_sequences([key,])[0]
         X.append(np.array((list(tokens)+[0,]*inp_len)[:inp_len]))
-        output_array = np.zeros(dset_size)
+        output_array = np.zeros(resps_len)
         output_array[dset[key]] = 1
         y.append(output_array)