app

.ipynb_checkpoints/app-checkpoint.py

@@ -43,7 +43,7 @@ torch.manual_seed(1004)
 np.random.seed(1004)
 
 st.title('Sol-LLaMA')
-smiles_str = st.text_area('Enter SMILE string')
+smiles_str = st.text_area('Enter SMILE string', value='CC(=C=C(C)C)C')
 
 file_path = './smiles_str.txt'
 # # Open the file in write mode ('w') and write the content

Untitled.ipynb

@@ -412,7 +412,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 29,
    "id": "a6d6145b-d5f9-44e4-85ca-f27b8c8a339d",
    "metadata": {},
    "outputs": [],
@@ -426,12 +426,14 @@
     "        v_attention_mask = v_batch['attention_mask'].to(device)\n",
     "        # v_y_labels = v_batch['labels'].to(device)\n",
     "        v_y_logits = local_model_ft(input_ids=v_input_ids, attention_mask=v_attention_mask)\n",
-    "        list_predictions.append(v_y_logits[0].tolist())"
+    "        list_predictions.append(v_y_logits[0].tolist())\n",
+    "\n",
+    "list_predictions[0].insert(0, smiles_str)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 30,
    "id": "7bc3e296-6871-45fb-8459-78eadc36bb61",
    "metadata": {
     "scrolled": true
@@ -458,6 +460,7 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
+       "      <th>SMILES</th>\n",
        "      <th>E</th>\n",
        "      <th>S</th>\n",
        "      <th>A</th>\n",
@@ -468,6 +471,7 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
+       "      <td>COO2</td>\n",
        "      <td>0.352832</td>\n",
        "      <td>-0.380014</td>\n",
        "      <td>-0.954426</td>\n",
@@ -479,17 +483,17 @@
        "</div>"
       ],
       "text/plain": [
-       "          E         S         A         B         V\n",
-       "0  0.352832 -0.380014 -0.954426 -1.511138  1.032684"
+       "  SMILES         E         S         A         B         V\n",
+       "0   COO2  0.352832 -0.380014 -0.954426 -1.511138  1.032684"
       ]
      },
-     "execution_count": 28,
+     "execution_count": 30,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "df = pd.DataFrame(list_predictions, columns=[\"E\", \"S\", \"A\", \"B\", \"V\"])\n",
+    "df = pd.DataFrame(list_predictions, columns=[\"SMILES\", \"E\", \"S\", \"A\", \"B\", \"V\"])\n",
     "df"
    ]
   },

app.py

@@ -43,7 +43,7 @@ torch.manual_seed(1004)
 np.random.seed(1004)
 
 st.title('Sol-LLaMA')
-smiles_str = st.text_area('Enter SMILE string')
+smiles_str = st.text_area('Enter SMILE string', value='CC(=C=C(C)C)C')
 
 file_path = './smiles_str.txt'
 # # Open the file in write mode ('w') and write the content