diff --git a/examples/rag/langgraph_adaptive_rag_local.ipynb b/examples/rag/langgraph_adaptive_rag_local.ipynb
index 1f2decad1..879e4e21a 100644
--- a/examples/rag/langgraph_adaptive_rag_local.ipynb
+++ b/examples/rag/langgraph_adaptive_rag_local.ipynb
@@ -123,7 +123,7 @@
     "from langchain.text_splitter import RecursiveCharacterTextSplitter\n",
     "from langchain_community.document_loaders import WebBaseLoader\n",
     "from langchain_community.vectorstores import Chroma\n",
-    "from langchain_community.embeddings import GPT4AllEmbeddings\n",
+    "from langchain_nomic.embeddings import NomicEmbeddings\n",
     "\n",
     "urls = [\n",
     "    \"https://lilianweng.github.io/posts/2023-06-23-agent/\",\n",
@@ -143,7 +143,7 @@
     "vectorstore = Chroma.from_documents(\n",
     "    documents=doc_splits,\n",
     "    collection_name=\"rag-chroma\",\n",
-    "    embedding=GPT4AllEmbeddings(),\n",
+    "    embedding=NomicEmbeddings(model=\"nomic-embed-text-v1.5\"),\n",
     ")\n",
     "retriever = vectorstore.as_retriever()"
    ]
diff --git a/examples/rag/langgraph_crag_local.ipynb b/examples/rag/langgraph_crag_local.ipynb
index bc94e65b9..f76094fe3 100644
--- a/examples/rag/langgraph_crag_local.ipynb
+++ b/examples/rag/langgraph_crag_local.ipynb
@@ -185,7 +185,7 @@
    "source": [
     "from langchain_community.document_loaders import WebBaseLoader\n",
     "from langchain_community.vectorstores import Chroma\n",
-    "from langchain_community.embeddings import GPT4AllEmbeddings\n",
+    "from langchain_nomic.embeddings import NomicEmbeddings\n",
     "from langchain.text_splitter import RecursiveCharacterTextSplitter\n",
     "from langchain_mistralai import MistralAIEmbeddings\n",
     "\n",
@@ -202,7 +202,7 @@
     "\n",
     "# Embed and index\n",
     "if run_local == \"Yes\":\n",
-    "    embedding = GPT4AllEmbeddings()\n",
+    "    embedding=NomicEmbeddings(model=\"nomic-embed-text-v1.5\")\n",
     "else:\n",
     "    embedding = MistralAIEmbeddings(mistral_api_key=mistral_api_key)\n",
     "\n",
diff --git a/examples/rag/langgraph_rag_agent_llama3_local.ipynb b/examples/rag/langgraph_rag_agent_llama3_local.ipynb
index c9e05b08b..23366559f 100644
--- a/examples/rag/langgraph_rag_agent_llama3_local.ipynb
+++ b/examples/rag/langgraph_rag_agent_llama3_local.ipynb
@@ -78,7 +78,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 4,
    "id": "2096d49c-d3dc-4329-ada7-aff56d210198",
    "metadata": {},
    "outputs": [],
@@ -90,16 +90,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 5,
    "id": "267c63e1-4c2f-439d-8d95-4c6aa01f41cf",
    "metadata": {},
    "outputs": [],
    "source": [
     "### Index\n",
     "\n",
+    "from langchain_nomic.embeddings import NomicEmbeddings\n",
     "from langchain_community.document_loaders import WebBaseLoader\n",
     "from langchain_community.vectorstores import Chroma\n",
-    "from langchain_community.embeddings import GPT4AllEmbeddings\n",
     "from langchain_text_splitters import RecursiveCharacterTextSplitter\n",
     "\n",
     "urls = [\n",
@@ -120,7 +120,7 @@
     "vectorstore = Chroma.from_documents(\n",
     "    documents=doc_splits,\n",
     "    collection_name=\"rag-chroma\",\n",
-    "    embedding=GPT4AllEmbeddings(),\n",
+    "    embedding=NomicEmbeddings(model=\"nomic-embed-text-v1.5\"),\n",
     ")\n",
     "retriever = vectorstore.as_retriever()"
    ]
diff --git a/examples/rag/langgraph_self_rag_local.ipynb b/examples/rag/langgraph_self_rag_local.ipynb
index 1f1a920e5..f288c3b86 100644
--- a/examples/rag/langgraph_self_rag_local.ipynb
+++ b/examples/rag/langgraph_self_rag_local.ipynb
@@ -140,7 +140,7 @@
     "from langchain.text_splitter import RecursiveCharacterTextSplitter\n",
     "from langchain_community.document_loaders import WebBaseLoader\n",
     "from langchain_community.vectorstores import Chroma\n",
-    "from langchain_community.embeddings import GPT4AllEmbeddings\n",
+    "from langchain_nomic.embeddings import NomicEmbeddings\n",
     "\n",
     "urls = [\n",
     "    \"https://lilianweng.github.io/posts/2023-06-23-agent/\",\n",
@@ -160,7 +160,7 @@
     "vectorstore = Chroma.from_documents(\n",
     "    documents=doc_splits,\n",
     "    collection_name=\"rag-chroma\",\n",
-    "    embedding=GPT4AllEmbeddings(),\n",
+    "    embedding=NomicEmbeddings(model=\"nomic-embed-text-v1.5\"),\n",
     ")\n",
     "retriever = vectorstore.as_retriever()"
    ]