diff --git a/openai_pgvector_helloworld/openai_pgvector_helloworld.ipynb b/openai_pgvector_helloworld/openai_pgvector_helloworld.ipynb
index c6265d4..876a6bf 100644
--- a/openai_pgvector_helloworld/openai_pgvector_helloworld.ipynb
+++ b/openai_pgvector_helloworld/openai_pgvector_helloworld.ipynb
@@ -136,8 +136,14 @@
     "# Helper function: calculate cost of embedding num_tokens\n",
     "# Assumes we're using the text-embedding-ada-002 model\n",
     "# See https://openai.com/pricing\n",
+    "costs = {\n",
+    "    \"text-embedding-3-small\": 0.020/1_000_000,\n",
+    "    \"text-embedding-3-large\": 0.130/1_000_000,\n",
+    "    \"text-embedding-ada-002\": 0.100/1_000_000,\n",
+    "}\n",
+    "    \n",
     "def get_embedding_cost(num_tokens):\n",
-    "    return num_tokens/1000*0.0001\n",
+    "    return num_tokens * costs['text-embedding-ada-002']\n",
     "\n",
     "# Helper function: calculate total cost of embedding all content in the dataframe\n",
     "def get_total_embeddings_cost():\n",
@@ -151,11 +157,11 @@
     "\n",
     "# Helper function: get embeddings for a text\n",
     "def get_embeddings(text):\n",
-    "    response = openai.Embedding.create(\n",
+    "    response = openai.embeddings.create(\n",
     "        model=\"text-embedding-ada-002\",\n",
     "        input = text.replace(\"\\n\",\" \")\n",
     "    )\n",
-    "    embedding = response['data'][0]['embedding']\n",
+    "    embedding = response.data[0].embedding\n",
     "    return embedding"
    ]
   },
@@ -265,7 +271,7 @@
     "# Save the dataframe with embeddings as a CSV file\n",
     "df_new.to_csv('blog_data_and_embeddings.csv', index=False)\n",
     "# It may also be useful to save as a json file, but we won't use this in the tutorial\n",
-    "#df_new.to_json('blog_data_and_embeddings.json')"
+    "df_new.to_json('blog_data_and_embeddings.json')"
    ]
   },
   {
@@ -506,14 +512,14 @@
     "# Helper function: get text completion from OpenAI API\n",
     "# Note max tokens is 4097\n",
     "# Note we're using the latest gpt-3.5-turbo-0613 model\n",
-    "def get_completion_from_messages(messages, model=\"gpt-3.5-turbo-0613\", temperature=0, max_tokens=1000):\n",
-    "    response = openai.ChatCompletion.create(\n",
+    "def get_completion_from_messages(messages, model=\"gpt-4o-mini-2024-07-18\", temperature=0, max_tokens=1000):\n",
+    "    response = openai.chat.completions.create(\n",
     "        model=model,\n",
     "        messages=messages,\n",
     "        temperature=temperature, \n",
     "        max_tokens=max_tokens, \n",
     "    )\n",
-    "    return response.choices[0].message[\"content\"]"
+    "    return response.choices[0].message.content"
    ]
   },
   {
@@ -611,6 +617,15 @@
     "print(input_2)\n",
     "print(response_2)"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# References\n",
+    "- https://docs.timescale.com/self-hosted/latest/install/installation-docker/#install-self-hosted-timescaledb-from-a-pre-built-container\n",
+    "- https://github.com/openai/openai-python/discussions/742 (OpenAI migration guide)"
+   ]
   }
  ],
  "metadata": {
@@ -629,7 +644,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.16"
+   "version": "3.11.6"
   }
  },
  "nbformat": 4,