diff --git a/examples/rag_langchain.ipynb b/examples/rag_langchain.ipynb
index d99ab976..874d3e4e 100644
--- a/examples/rag_langchain.ipynb
+++ b/examples/rag_langchain.ipynb
@@ -74,7 +74,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Loader and splitter"
+    "### Helpers"
    ]
   },
   {
@@ -225,6 +225,13 @@
     "FILE_PATH = \"https://arxiv.org/pdf/2206.01062\"  # DocLayNet paper"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Loader and splitter"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -420,10 +427,10 @@
      "output_type": "stream",
      "text": [
       "Question:\n",
-      "How many pages were human annotated for DocLayNet?\n",
+      "How many pages were human annotated by humans for DocLayNet?\n",
       "\n",
       "Answer:\n",
-      "\"80863 pages were human annotated for DocLayNet.\\nExplanation:\\nFrom the context, it is clear that DocL...\"\n",
+      "\"80863 pages were annotated by humans in DocLayNet.\"\n",
       "\n",
       "Source 1:\n",
       "  text: \"DocLayNet contains 80863 PDF pages. Among these, 7059 carry two instances of human annotations, and ...\"\n",
@@ -442,29 +449,36 @@
       "  path: $.main-text[23]\n",
       "\n",
       "Source 3:\n",
-      "  text: \"Phase 4: Production annotation. The previously selected 80K pages were annotated with the defined 11...\"\n",
-      "  bbox: [317.3695373535156, 82.78482818603516, 559.7149047851562, 244.83221435546875]\n",
-      "  dl_doc_hash: 5dfbd8c115a15fd3396b68409124cfee29fc8efac7b5c846634ff924e635e0dc\n",
-      "  heading: 4 ANNOTATION CAMPAIGN\n",
-      "  page: 5\n",
-      "  path: $.main-text[80]\n",
-      "\n",
-      "Source 4:\n",
       "  text: \"DocLayNet: A Large Human-Annotated Dataset for Document-Layout Analysis\"\n",
       "  bbox: [53.60108947753906, 723.3781127929688, 347.139892578125, 731.6909790039062]\n",
       "  dl_doc_hash: 5dfbd8c115a15fd3396b68409124cfee29fc8efac7b5c846634ff924e635e0dc\n",
       "  heading: REFERENCES\n",
       "  page: 9\n",
-      "  path: $.main-text[133]\n"
+      "  path: $.main-text[133]\n",
+      "\n",
+      "Source 4:\n",
+      "  text: \"DocLayNet: A Large Human-Annotated Dataset for Document-Layout Analysis\"\n",
+      "  bbox: [53.542964935302734, 723.3500366210938, 347.0172424316406, 731.6931762695312]\n",
+      "  dl_doc_hash: 5dfbd8c115a15fd3396b68409124cfee29fc8efac7b5c846634ff924e635e0dc\n",
+      "  heading: 4 ANNOTATION CAMPAIGN\n",
+      "  page: 5\n",
+      "  path: $.main-text[64]\n"
      ]
     }
    ],
    "source": [
     "resp_dict = rag_chain.invoke(\n",
-    "    {\"input\": \"How many pages were human annotated for DocLayNet?\"}\n",
+    "    {\"input\": \"How many pages were human annotated by humans for DocLayNet?\"}\n",
     ")\n",
     "print_qa(resp_dict=resp_dict)"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
diff --git a/examples/rag_llamaindex.ipynb b/examples/rag_llamaindex.ipynb
index 3a3381a6..fb3a9c43 100644
--- a/examples/rag_llamaindex.ipynb
+++ b/examples/rag_llamaindex.ipynb
@@ -43,11 +43,8 @@
    ],
    "source": [
     "import os\n",
-    "from tempfile import TemporaryDirectory\n",
     "\n",
     "from dotenv import load_dotenv\n",
-    "from pydantic import TypeAdapter\n",
-    "from rich.pretty import pprint\n",
     "\n",
     "load_dotenv()"
    ]
@@ -386,6 +383,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from tempfile import TemporaryDirectory\n",
     "from llama_index.vector_stores.milvus import MilvusVectorStore\n",
     "\n",
     "MILVUS_URI = os.environ.get(\n",