diff --git a/notebook/integrate_openai.ipynb b/notebook/integrate_openai.ipynb
index 563a631a35..b8b5ae7ecb 100644
--- a/notebook/integrate_openai.ipynb
+++ b/notebook/integrate_openai.ipynb
@@ -21,7 +21,7 @@
     "\n",
     "FLAML requires `Python>=3.7`. To run this notebook example, please install flaml with the [openai] option:\n",
     "```bash\n",
-    "pip install flaml[openai]\n",
+    "pip install flaml[openai]==1.1.3\n",
     "```"
    ]
   },
@@ -38,7 +38,7 @@
    },
    "outputs": [],
    "source": [
-    "# %pip install flaml[openai] datasets"
+    "# %pip install flaml[openai]==1.1.3 datasets"
    ]
   },
   {
@@ -447,31 +447,33 @@
     "* `optimization_budget` is the total budget allowed to perform the tuning. For example, 5 means 5 dollars are allowed in total, which translates to 250K tokens for the text Davinci model.\n",
     "* `num_sumples` is the number of different hyperparameter configurations which is allowed to try. The tuning will stop after either num_samples trials or after optimization_budget dollars spent, whichever happens first. -1 means no hard restriction in the number of trials and the actual number is decided by `optimization_budget`.\n",
     "\n",
-    "Users can specify tuning data, optimization metric, optimization mode, evaluation function, search spaces etc.. The default search space is \n",
-    "```python\n",
-    "    price1K = {\n",
-    "        \"text-ada-001\": 0.0004,\n",
-    "        \"text-babbage-001\": 0.0005,\n",
-    "        \"text-curie-001\": 0.002,\n",
-    "        \"code-cushman-001\": 0.024,\n",
-    "        \"code-davinci-002\": 0.1,\n",
-    "        \"text-davinci-002\": 0.02,\n",
-    "        \"text-davinci-003\": 0.02,\n",
-    "    }\n",
+    "Users can specify tuning data, optimization metric, optimization mode, evaluation function, search spaces etc.. The default search space is:\n",
     "\n",
-    "    default_search_space = {\n",
-    "        \"model\": tune.choice(list(price1K.keys())),\n",
-    "        \"temperature_or_top_p\": tune.choice(\n",
-    "            [\n",
-    "                {\"temperature\": tune.uniform(0, 1)},\n",
-    "                {\"top_p\": tune.uniform(0, 1)},\n",
-    "            ]\n",
-    "        ),\n",
-    "        \"max_tokens\": tune.lograndint(50, 1000),\n",
-    "        \"n\": tune.randint(1, 100),\n",
-    "        \"prompt\": \"{prompt}\",\n",
-    "    }\n",
+    "```python\n",
+    "price1K = {\n",
+    "    \"text-ada-001\": 0.0004,\n",
+    "    \"text-babbage-001\": 0.0005,\n",
+    "    \"text-curie-001\": 0.002,\n",
+    "    \"code-cushman-001\": 0.024,\n",
+    "    \"code-davinci-002\": 0.1,\n",
+    "    \"text-davinci-002\": 0.02,\n",
+    "    \"text-davinci-003\": 0.02,\n",
+    "}\n",
+    "\n",
+    "default_search_space = {\n",
+    "    \"model\": tune.choice(list(price1K.keys())),\n",
+    "    \"temperature_or_top_p\": tune.choice(\n",
+    "        [\n",
+    "            {\"temperature\": tune.uniform(0, 1)},\n",
+    "            {\"top_p\": tune.uniform(0, 1)},\n",
+    "        ]\n",
+    "    ),\n",
+    "    \"max_tokens\": tune.lograndint(50, 1000),\n",
+    "    \"n\": tune.randint(1, 100),\n",
+    "    \"prompt\": \"{prompt}\",\n",
+    "}\n",
     "```\n",
+    "\n",
     "The default search space can be overriden by users' input.\n",
     "For example, the following code specifies two choices for the model, four choices for the prompt and a fixed list of stop sequences. For hyperparameters which don't appear in users' input, the default search space will be used."
    ]