Fixed comments in rag notebook

Author: GiovanniGiacometti

notebooks/rag.ipynb

@@ -79,9 +79,9 @@
    "cell_type": "code",
    "metadata": {},
    "source": [
-    "URL = 'https://api.platform.mlcube.com'\n",
-    "API_KEY = ''\n",
-    "PROJECT_ID = ''\n",
+    "URL = 'https://pre.api.platform.mlcube.com'\n",
+    "API_KEY = 'VbDyZ4U7Gbe60nK4UlL4aqOOpZrBLHl7flm0uVzuCj9iwyatWcYcezaOBAzckCOh'\n",
+    "PROJECT_ID = '669fbec80b64f51d12f1d12d'\n",
     "model_name = 'mymodel'\n",
     "model_version = 'v0.0.1'"
    ],
@@ -261,22 +261,22 @@
     "    if with_prediction:\n",
     "        with open(prediction_samples_filename, 'w') as f:\n",
     "            json.dump(prediction_text_samples, f)\n",
-    "    \n",
+    "            \n",
     "    # Create embedding dataframe\n",
     "    print('Creating embedding file')\n",
     "    embeddings_input = pl.DataFrame({\n",
     "        'timestamp': timestamps,\n",
     "        'sample-id': sample_ids,\n",
-    "        f'{USER_INPUT_COL_NAME}_embeddings': embedder.encode((dataset[USER_INPUT_COL_NAME])).tolist(),\n",
-    "        f'{CONTEXT_COL_NAME}_embeddings': embedder.encode((dataset[CONTEXT_COL_NAME])).tolist(),        \n",
+    "        f'{USER_INPUT_COL_NAME}_embeddings': embedder.encode(dataset[USER_INPUT_COL_NAME]).tolist(),\n",
+    "        f'{CONTEXT_COL_NAME}_embeddings': embedder.encode(dataset[CONTEXT_COL_NAME]).tolist(),        \n",
     "    })\n",
     "    embeddings_input.write_parquet(input_embeddings_filename)\n",
     "    \n",
     "    if with_prediction:\n",
     "        embeddings_prediction = pl.DataFrame({\n",
     "            'timestamp': timestamps,\n",
     "            'sample-id': sample_ids,\n",
-    "            f'{model_name}_embeddings@{model_version}': embedder.encode((dataset[ANSWER_COL_NAME])).tolist(),\n",
+    "            f'{model_name}_embeddings@{model_version}': embedder.encode(dataset[ANSWER_COL_NAME]).tolist(),\n",
     "        })\n",
     "        \n",
     "        embeddings_prediction.write_parquet(prediction_embeddings_filename)\n",
@@ -540,7 +540,7 @@
     "    version=model_version,\n",
     "    metric_name=None,  # Must be None in RAG tasks\n",
     "    preferred_suggestion_type=None,  # Must be None in RAG tasks\n",
-    "    with_probabilistic_output=False\n",
+    "    with_probabilistic_output=False,\n",
     ")"
    ],
    "outputs": [],
@@ -613,9 +613,7 @@
   {
    "cell_type": "markdown",
    "metadata": {},
-   "source": [
-    "Send production data asynchronously, first *inputs* and *predictions* and then *target*"
-   ]
+   "source": "Send production data asynchronously, first *inputs* and then *predictions*"
   },
   {
    "cell_type": "code",