diff --git a/src/content/docs/workers-ai/tutorials/build-a-retrieval-augmented-generation-ai.mdx b/src/content/docs/workers-ai/tutorials/build-a-retrieval-augmented-generation-ai.mdx
index 711aca436523c39..64d0b6832d40a5a 100644
--- a/src/content/docs/workers-ai/tutorials/build-a-retrieval-augmented-generation-ai.mdx
+++ b/src/content/docs/workers-ai/tutorials/build-a-retrieval-augmented-generation-ai.mdx
@@ -280,40 +280,47 @@ const app = new Hono();
 // Existing post route...
 // app.post('/notes', async (c) => { ... })
 
-app.get('/', async (c) => {
-  const question = c.req.query('text') || "What is the square root of 9?"
-
-  const embeddings = await c.env.AI.run('@cf/baai/bge-base-en-v1.5', { text: question })
-  const vectors = embeddings.data[0]
-
-  const vectorQuery = await c.env.VECTOR_INDEX.query(vectors, { topK: 1 });
-  const vecId = vectorQuery.matches[0].id
-
-  let notes = []
-  if (vecId) {
-    const query = `SELECT * FROM notes WHERE id = ?`
-    const { results } = await c.env.DB.prepare(query).bind(vecId).all()
-    if (results) notes = results.map(vec => vec.text)
-  }
-
-  const contextMessage = notes.length
-    ? `Context:\n${notes.map(note => `- ${note}`).join("\n")}`
-    : ""
-
-  const systemPrompt = `When answering the question or responding, use the context provided, if it is provided and relevant.`
-
-  const { response: answer } = await c.env.AI.run(
-    '@cf/meta/llama-3-8b-instruct',
-    {
-      messages: [
-        ...(notes.length ? [{ role: 'system', content: contextMessage }] : []),
-        { role: 'system', content: systemPrompt },
-        { role: 'user', content: question }
-      ]
-    }
-  )
-
-  return c.text(answer);
+app.get("/", async (c) => {
+	const question = c.req.query("text") || "What is the square root of 9?";
+
+	const embeddings = await c.env.AI.run("@cf/baai/bge-base-en-v1.5", {
+		text: question,
+	});
+	const vectors = embeddings.data[0];
+
+	const vectorQuery = await c.env.VECTOR_INDEX.query(vectors, { topK: 1 });
+	let vecId;
+	if (vectorQuery?.matches?.length) {
+		vecId = vectorQuery.matches[0].id;
+	} else {
+		console.log("No matching vector found or vectorQuery.matches is empty");
+	}
+
+	let notes = [];
+	if (vecId) {
+		const query = `SELECT * FROM notes WHERE id = ?`;
+		const { results } = await c.env.DB.prepare(query).bind(vecId).all();
+		if (results) notes = results.map((vec) => vec.text);
+	}
+
+	const contextMessage = notes.length
+		? `Context:\n${notes.map((note) => `- ${note}`).join("\n")}`
+		: "";
+
+	const systemPrompt = `When answering the question or responding, use the context provided, if it is provided and relevant.`;
+
+	const { response: answer } = await c.env.AI.run(
+		"@cf/meta/llama-3-8b-instruct",
+		{
+			messages: [
+				...(notes.length ? [{ role: "system", content: contextMessage }] : []),
+				{ role: "system", content: systemPrompt },
+				{ role: "user", content: question },
+			],
+		},
+	);
+
+	return c.text(answer);
 });
 
 app.onError((err, c) => {