additional cells and drop old doc

docs/core_docs/docs/integrations/text_embedding/openai.ipynb

@@ -91,6 +91,15 @@
     "});"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "fb4153d3",
+   "metadata": {},
+   "source": [
+    "If you're part of an organization, you can set `process.env.OPENAI_ORGANIZATION` to your OpenAI organization id, or pass it in as `organization` when\n",
+    "initializing the model."
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "77d271b6",
@@ -270,6 +279,111 @@
     "console.log(vectors[1].slice(0, 100));"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "2b1a3527",
+   "metadata": {},
+   "source": [
+    "## Specifying dimensions\n",
+    "\n",
+    "With the `text-embedding-3` class of models, you can specify the size of the embeddings you want returned. For example by default `text-embedding-3-large` returns embeddings of dimension 3072:\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "a611fe1a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "3072\n"
+     ]
+    }
+   ],
+   "source": [
+    "import { OpenAIEmbeddings } from \"@langchain/openai\";\n",
+    "\n",
+    "const embeddingsDefaultDimensions = new OpenAIEmbeddings({\n",
+    "  model: \"text-embedding-3-large\",\n",
+    "});\n",
+    "\n",
+    "const vectorsDefaultDimensions = await embeddingsDefaultDimensions.embedDocuments([\"some text\"]);\n",
+    "console.log(vectorsDefaultDimensions[0].length);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "08efe771",
+   "metadata": {},
+   "source": [
+    "But by passing in `dimensions: 1024` we can reduce the size of our embeddings to 1024:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "19667fdb",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1024\n"
+     ]
+    }
+   ],
+   "source": [
+    "import { OpenAIEmbeddings } from \"@langchain/openai\";\n",
+    "\n",
+    "const embeddings1024 = new OpenAIEmbeddings({\n",
+    "  model: \"text-embedding-3-large\",\n",
+    "  dimensions: 1024,\n",
+    "});\n",
+    "\n",
+    "const vectors1024 = await embeddings1024.embedDocuments([\"some text\"]);\n",
+    "console.log(vectors1024[0].length);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6b84c0df",
+   "metadata": {},
+   "source": [
+    "## Custom URLs\n",
+    "\n",
+    "You can customize the base URL the SDK sends requests to by passing a `configuration` parameter like this:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3bfa20a6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import { OpenAIEmbeddings } from \"@langchain/openai\";\n",
+    "\n",
+    "const model = new OpenAIEmbeddings({\n",
+    "  configuration: {\n",
+    "    baseURL: \"https://your_custom_url.com\",\n",
+    "  },\n",
+    "});"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ac3cac9b",
+   "metadata": {},
+   "source": [
+    "You can also pass other `ClientOptions` parameters accepted by the official SDK.\n",
+    "\n",
+    "If you are hosting on Azure OpenAI, see the [dedicated page instead](/docs/integrations/text_embedding/azure_openai)."
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "8938e581",