From 8c7cf932570a76677161f9d1280496c90525cfc8 Mon Sep 17 00:00:00 2001
From: Robin Lester <30799887+rolester@users.noreply.github.com>
Date: Sat, 27 Jul 2024 00:46:19 +0100
Subject: [PATCH] Update CosmosDB-NoSQL-Vector_AzureOpenAI_Tutorial.ipynb

Fixed SQL query to only return one content field and gave an order so the results most similar are at the top
---
 .../CosmosDB-NoSQL-Vector_AzureOpenAI_Tutorial.ipynb            | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/Python/CosmosDB-NoSQL_VectorSearch/CosmosDB-NoSQL-Vector_AzureOpenAI_Tutorial.ipynb b/Python/CosmosDB-NoSQL_VectorSearch/CosmosDB-NoSQL-Vector_AzureOpenAI_Tutorial.ipynb
index e050c53..73b16ea 100644
--- a/Python/CosmosDB-NoSQL_VectorSearch/CosmosDB-NoSQL-Vector_AzureOpenAI_Tutorial.ipynb
+++ b/Python/CosmosDB-NoSQL_VectorSearch/CosmosDB-NoSQL-Vector_AzureOpenAI_Tutorial.ipynb
@@ -464,7 +464,7 @@
     "def vector_search(query, num_results=5):\n",
     "    query_embedding = generate_embeddings(query)\n",
     "    results = container.query_items(\n",
-    "            query='SELECT TOP @num_results c.content, c.title, c.content, c.category, VectorDistance(c.contentVector,@embedding) AS SimilarityScore  FROM c',\n",
+    "            query='SELECT TOP @num_results c.content, c.title, c.category, VectorDistance(c.contentVector,@embedding) AS SimilarityScore  FROM c ORDER BY VectorDistance(c.contentVector,@embedding)',\n",
     "            parameters=[\n",
     "                {\"name\": \"@embedding\", \"value\": query_embedding} \n",
     "                {\"name\": \"@num_results\", \"value\": num_results} \n",