Set all leaf pages to isLesson: true for multi-vector course

qdrant-landing/content/course/multi-vector-search/module-1/late-interaction-basics.md

@@ -2,6 +2,7 @@
 title: "Late Interaction Basics"
 description: Understand the late interaction paradigm and how it differs from traditional dense embeddings for text search.
 weight: 1
+isLesson: true
 ---
 
 {{< date >}} Module 1 {{< /date >}}

qdrant-landing/content/course/multi-vector-search/module-1/maxsim-distance.md

@@ -2,6 +2,7 @@
 title: "MaxSim Distance Metric"
 description: Learn about the MaxSim distance metric used in multi-vector search and how it computes similarity between multi-vector representations.
 weight: 2
+isLesson: true
 ---
 
 {{< date >}} Module 1 {{< /date >}}

qdrant-landing/content/course/multi-vector-search/module-1/multi-vector-in-qdrant.md

@@ -2,6 +2,7 @@
 title: "Multi-Vector Embeddings in Qdrant"
 description: Configure Qdrant collections for multi-vector embeddings and learn how to index and query multi-vector data.
 weight: 5
+isLesson: true
 ---
 
 {{< date >}} Module 1 {{< /date >}}

qdrant-landing/content/course/multi-vector-search/module-1/problems-multi-vector.md

@@ -2,6 +2,7 @@
 title: "Problems of Multi-Vector Search"
 description: Understand the challenges and limitations of multi-vector search at scale, including memory and performance considerations.
 weight: 4
+isLesson: true
 ---
 
 {{< date >}} Module 1 {{< /date >}}

qdrant-landing/content/course/multi-vector-search/module-1/use-cases-multi-vector.md

@@ -2,6 +2,7 @@
 title: "Use Cases for Multi-Vector Search"
 description: Discover scenarios where multi-vector search outperforms single-vector embeddings and provides better retrieval quality.
 weight: 3
+isLesson: true
 ---
 
 {{< date >}} Module 1 {{< /date >}}