diff --git a/bootcamp/tutorials/integration/rag_with_milvus_and_haystack.ipynb b/bootcamp/tutorials/integration/rag_with_milvus_and_haystack.ipynb
index 0bd2ef984..f96ccf273 100644
--- a/bootcamp/tutorials/integration/rag_with_milvus_and_haystack.ipynb
+++ b/bootcamp/tutorials/integration/rag_with_milvus_and_haystack.ipynb
@@ -25,7 +25,7 @@
     "\n",
     "This guide demonstrates how to build a Retrieval-Augmented Generation (RAG) system using Haystack and Milvus.\n",
     "\n",
-    "The RAG system combines a retrieval system with a generative model to generate new text based on a given prompt. The system first retrieves relevant documents from a corpus using Milvus, and then uses a generative model to generate new text based on the retrieved documents.\n",
+    "The RAG system combines a retrieval system with a generative model to generate new text based on a given prompt. The system first retrieves relevant documents from a corpus using a vector similarity search engine like Milvus, and then uses a generative model to generate new text based on the retrieved documents.\n",
     "\n",
     "[Haystack](https://haystack.deepset.ai/) is the open source Python framework by deepset for building custom apps with large language models (LLMs). [Milvus](https://milvus.io/) is the world's most advanced open-source vector database, built to power embedding similarity search and AI applications.\n",
     "\n",
@@ -141,6 +141,7 @@
     "from haystack.components.embedders import OpenAIDocumentEmbedder, OpenAITextEmbedder\n",
     "from haystack.components.preprocessors import DocumentSplitter\n",
     "from haystack.components.writers import DocumentWriter\n",
+    "from haystack.utils import Secret\n",
     "\n",
     "from milvus_haystack import MilvusDocumentStore\n",
     "from milvus_haystack.milvus_embedding_retriever import MilvusEmbeddingRetriever\n",
@@ -149,7 +150,7 @@
     "document_store = MilvusDocumentStore(\n",
     "    connection_args={\"uri\": \"./milvus.db\"},\n",
     "    # connection_args={\"uri\": \"http://localhost:19530\"},\n",
-    "    # connection_args={\"uri\": YOUR_ZILLIZ_CLOUD_URI, \"token\": YOUR_ZILLIZ_API_KEY},\n",
+    "    # connection_args={\"uri\": YOUR_ZILLIZ_CLOUD_URI, \"token\": Secret.from_env_var(\"ZILLIZ_CLOUD_API_KEY\")},\n",
     "    drop_old=True,\n",
     ")"
    ],
@@ -368,6 +369,18 @@
     ")\n",
     "print(\"RAG answer:\", results[\"generator\"][\"replies\"][0])"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "source": [
+    "For more information about how to use milvus-haystack, please refer to the [milvus-haystack Readme](https://github.com/milvus-io/milvus-haystack)."
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   }
   }
  ],
  "metadata": {