resolve conversation issues

bootcamp/tutorials/integration/rag_with_langflow.ipynb

@@ -66,19 +66,18 @@
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    "source": [
     "### Steps to replace astraDB with Milvus:\n",
-    "1. Click on these two astraDB module, which I marked red in the above image, and press *backspace* to delete them.\n",
-    "2. Click on the **Vector Store** option in the sidebar, there will be many vector stores as options.\n",
-    "3. Among these, we drag 2 Milvus module to the canvas.\n",
-    "4. Correctly Connect the Milvus Module to the rest of the components. See the image below for reference:\n",
-    "5. Change the default **Connection URI** field of both Milvus module to `milvus_demo.db`\n",
+    "1. Remove existing cards of Vector Store. Click on two AstraDB cards marked red in the above image, and press **backspace** to delete them.\n",
+    "2. Click on the **Vector Store** option in the sidebar, chose Milvus and drag it into the canvas. Do this twice as we need 2 Milvus cards, one for storing the file processing workflow and one for search workflow.\n",
+    "3. Link the Milvus Modules to the rest of the components. See the image below for reference.\n",
+    "4. Configure the Milvus credentials for both Milvus modules. The simplest way is to use Milvus Lite by setting Connection URI to milvus_demo.db. If you have a Milvus server self-deployed or on Zilliz Cloud, set the Connection URI to server endpoint and Connection Password to token (for Milvus that's concatenated \"<username>:<password>\", for Zilliz Cloud it's API Key). See below image for reference:\n",
     "![Milvus Structure demo](../../../images/langflow_milvus_structure.png)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Embedd knowledge into the RAG system\n",
+    "### Embed knowledge into the RAG system\n",
     "1. Upload a file as LLM's knowledge base through the file module on the bottom left. Here we uploaded a file containing a brief introduction to Milvus\n",
     "2. Run the inserting workflow by pressing the run botton on the Milvus module on the bottom right. This will insert the knowledge to the Milvus vector store\n",
     "3. Test whether the knowledge is in memory. Open playground and ask anything related to the file you uploaded.\n",
@@ -94,7 +93,7 @@
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-   "display_name": "zilliz",
+   "display_name": "compute",
    "language": "python",
    "name": "python3"
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