fix run out of data error

app.py

@@ -87,12 +87,8 @@ with open("intents.json") as file:
     data = json.load(file)
 
 with open("data.pickle", "rb") as f:
-  data = pd.read_pickle(f)
   words, labels, training, output = pickle.load(f)
 
-df = pd.DataFrame(data)
-df.to_csv('data_train.csv', index=False)
-
 net = tflearn.input_data(shape=[None, len(training[0])])
 net = tflearn.fully_connected(net, 8)
 net = tflearn.fully_connected(net, 8)

model.ipynb

@@ -5,89 +5,7 @@
    "execution_count": 2,
    "id": "ace57031",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>Question_ID</th>\n",
-       "      <th>Questions</th>\n",
-       "      <th>Answers</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>1590140</td>\n",
-       "      <td>What does it mean to have a mental illness?</td>\n",
-       "      <td>Mental illnesses are health conditions that di...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>2110618</td>\n",
-       "      <td>Who does mental illness affect?</td>\n",
-       "      <td>It is estimated that mental illness affects 1 ...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>6361820</td>\n",
-       "      <td>What causes mental illness?</td>\n",
-       "      <td>It is estimated that mental illness affects 1 ...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>9434130</td>\n",
-       "      <td>What are some of the warning signs of mental i...</td>\n",
-       "      <td>Symptoms of mental health disorders vary depen...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>7657263</td>\n",
-       "      <td>Can people with mental illness recover?</td>\n",
-       "      <td>When healing from mental illness, early identi...</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "  Question_ID                                          Questions  \\\n",
-       "0     1590140        What does it mean to have a mental illness?   \n",
-       "1     2110618                    Who does mental illness affect?   \n",
-       "2     6361820                        What causes mental illness?   \n",
-       "3     9434130  What are some of the warning signs of mental i...   \n",
-       "4     7657263            Can people with mental illness recover?   \n",
-       "\n",
-       "                                             Answers  \n",
-       "0  Mental illnesses are health conditions that di...  \n",
-       "1  It is estimated that mental illness affects 1 ...  \n",
-       "2  It is estimated that mental illness affects 1 ...  \n",
-       "3  Symptoms of mental health disorders vary depen...  \n",
-       "4  When healing from mental illness, early identi...  "
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "from sklearn.feature_extraction.text import TfidfVectorizer\n",
     "from sklearn.model_selection import train_test_split\n",
@@ -127,7 +45,14 @@
     "            pass\n",
     "\n",
     "data = pd.read_csv(\"data.csv\")\n",
-    "data.head()"
+    "data.head()\n",
+    "\n",
+    "with open(\"data.pickle\", \"rb\") as f:\n",
+    "  data = pd.read_pickle(f)\n",
+    "#   words, labels, training, output = pickle.load(f)\n",
+    "\n",
+    "df = pd.DataFrame(data)\n",
+    "df.to_csv('data_train.csv', index=False)"
    ]
   },
   {