Minor details

app.py

@@ -195,10 +195,17 @@ def generate_cells(dataset_id, cells, notebook_type="eda"):
     )
 
 
+css = """
+#box {
+  height: 650px;
+  overflow-y: scroll !important;
+}
+"""
+
 with gr.Blocks(
     fill_height=True,
     fill_width=True,
-    css="#box { height: 650px; overflow-y: scroll !important}",
+    css=css,
 ) as demo:
     gr.Markdown("# 🤖 Dataset notebook creator 🕵️")
     with gr.Row(equal_height=True):
@@ -236,13 +243,13 @@ with gr.Blocks(
                 if not name:
                     return gr.Markdown("### No dataset provided")
                 html_code = f"""
-                <iframe
-                src="https://huggingface.co/datasets/{name}/embed/viewer/default/train"
-                frameborder="0"
-                width="100%"
-                height="350px"
-                ></iframe>
-                """
+                    <iframe
+                    src="https://huggingface.co/datasets/{name}/embed/viewer/default/train"
+                    frameborder="0"
+                    width="100%"
+                    height="350px"
+                    ></iframe>
+                    """
                 return gr.HTML(value=html_code, elem_classes="viewer")
 
             with gr.Row():

utils/notebook_utils.py

@@ -365,7 +365,7 @@ index.add(vectors)
         "cell_type": "code",
         "source": """
 # Specify the text you want to search for in the list
-query = "How to prepare a cake?"
+query = "How to cook sushi?"
 
 # Generate the embedding for the search query
 query_embedding = model.encode([query])