Addressed API version conflicts

Author: HeidiSteen

Quickstart-RAG/Quickstart-rag.ipynb

@@ -83,7 +83,9 @@
     "\n",
     "Create a virtual environment so that you can install the dependencies in isolation.\n",
     "\n",
-    "1. In Visual Studio Code, press Ctrl-shift-P to open the command palette, search for \"Python: Create Environment\", and then select `Venv` to create a virtual environment in the current workspace.\n",
+    "1. In Visual Studio Code, open the folder containing quickstart-rag.ipynb.\n",
+    "\n",
+    "1. Press Ctrl-shift-P to open the command palette, search for \"Python: Create Environment\", and then select `Venv` to create a virtual environment in the current workspace.\n",
     "\n",
     "1. Select Quickstart-RAG\\requirements.txt for the dependencies.\n",
     "\n",

Tutorial-RAG/Tutorial-rag.ipynb

@@ -72,6 +72,23 @@
     "# \"ResourceId=/subscriptions/FAKE-SUBCRIPTION=ID/resourceGroups/FAKE-RESOURCE-GROUP/providers/Microsoft.Storage/storageAccounts/FAKE-ACCOUNT;\""
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Create a virtual environment\n",
+    "\n",
+    "Create a virtual environment so that you can install the dependencies in isolation.\n",
+    "\n",
+    "1. In Visual Studio Code, open the folder containing tutorial-rag.ipynb.\n",
+    "\n",
+    "1. Press Ctrl-shift-P to open the command palette, search for \"Python: Create Environment\", and then select `Venv` to create a virtual environment in the current workspace.\n",
+    "\n",
+    "1. Select Tutorial-RAG\\tutorial-rag-requirements.txt for the dependencies.\n",
+    "\n",
+    "It takes several minutes to create the environment. When the environment is ready, continue to the next step."
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -198,7 +215,7 @@
     "    OutputFieldMappingEntry,\n",
     "    AzureOpenAIEmbeddingSkill,\n",
     "    EntityRecognitionSkill,\n",
-    "    SearchIndexerIndexProjections,\n",
+    "    SearchIndexerIndexProjection,\n",
     "    SearchIndexerIndexProjectionSelector,\n",
     "    SearchIndexerIndexProjectionsParameters,\n",
     "    IndexProjectionMode,\n",
@@ -226,8 +243,8 @@
     "embedding_skill = AzureOpenAIEmbeddingSkill(  \n",
     "    description=\"Skill to generate embeddings via Azure OpenAI\",  \n",
     "    context=\"/document/pages/*\",  \n",
-    "    resource_uri=AZURE_OPENAI_ACCOUNT,  \n",
-    "    deployment_id=\"text-embedding-ada-002\",  \n",
+    "    resource_url=AZURE_OPENAI_ACCOUNT,  \n",
+    "    deployment_name=\"text-embedding-ada-002\",  \n",
     "    model_name=\"text-embedding-ada-002\",\n",
     "    dimensions=1536,\n",
     "    inputs=[  \n",
@@ -251,7 +268,7 @@
     "    ]\n",
     ")\n",
     "  \n",
-    "index_projections = SearchIndexerIndexProjections(  \n",
+    "index_projections = SearchIndexerIndexProjection(  \n",
     "    selectors=[  \n",
     "        SearchIndexerIndexProjectionSelector(  \n",
     "            target_index_name=index_name,  \n",
@@ -278,7 +295,7 @@
     "    name=skillset_name,  \n",
     "    description=\"Skillset to chunk documents and generating embeddings\",  \n",
     "    skills=skills,  \n",
-    "    index_projections=index_projections,\n",
+    "    index_projection=index_projections,\n",
     "    cognitive_services_account=cognitive_services_account\n",
     ")\n",
     "  \n",
@@ -345,7 +362,7 @@
     "from azure.search.documents.models import VectorizableTextQuery\n",
     "\n",
     "# Vector Search using text-to-vector conversion of the querystring\n",
-    "query = \"how much of earth is covered by water\"  \n",
+    "query = \"where are NASA's headquarters located?\"  \n",
     "\n",
     "search_client = SearchClient(endpoint=AZURE_SEARCH_SERVICE, credential=AZURE_SEARCH_CREDENTIAL, index_name=index_name)\n",
     "vector_query = VectorizableTextQuery(text=query, k_nearest_neighbors=1, fields=\"text_vector\", exhaustive=True)\n",