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-# ⭐ Introduction to PageIndex
+#  📄 Introduction to PageIndex
 
 Are you frustrated with vector database retrieval accuracy for long professional documents? Traditional vector-based RAG relies on semantic *similarity* rather than true *relevance*. But **similarity ≠ relevance** — what we truly need in retrieval is **relevance**, and that requires **reasoning**. When working with professional documents that demand domain expertise and multi-step reasoning, similarity search often falls short.
 
@@ -174,6 +174,10 @@ Check out the [Cookbook](https://docs.pageindex.ai/cookbook/vectorless-rag-pagei
 
 Refer to the [API Documentation](https://docs.pageindex.ai/quickstart) for integration details and options.
 
-<br>  
+
+# ⭐ Support us
+Leave a star if you like our project, Thank you!
+![star](https://github.com/user-attachments/assets/eae4ff38-48ae-4a7c-b19f-eab81201d794)
+
 
 © 2025 [Vectify AI](https://vectify.ai)