Enhance readme

app.py

@@ -39,17 +39,12 @@ readme_md = """
 Multi-vector search has shown very strong performance compared to single dense vector search in numerous domain, including out-of-domain, [long-context](https://x.com/antoine_chaffin/status/1919396926736257521) and [reasoning-intensive](https://x.com/antoine_chaffin/status/1925555110521798925) retrieval.
 
 They are thus particularly well suited for modern retrieval use cases, including agentic workflows.
-
 [PyLate](https://lightonai.github.io/pylate/) is library built on top of sentence-transformers that allows to easily train and use multi-vector models.
 
 This MCP server is a demonstration of the use of PyLate models alongside its index optimized for multi-vector search, PLAID.
 
-This repository propose to search among the [leetcode split of the BRIGHT dataset](https://huggingface.co/datasets/xlangai/BRIGHT/viewer/documents/leetcode) using [Reason-ModernColBERT](https://huggingface.co/lightonai/Reason-ModernColBERT).
-
-This 150M parameters model outperforms 7B models on this reasoning-intensive retrieval benchmark, which requires reasoning to find relevant documents.
-
+This repository propose to search among the [leetcode split of the BRIGHT dataset](https://huggingface.co/datasets/xlangai/BRIGHT/viewer/documents/leetcode) using [Reason-ModernColBERT](https://huggingface.co/lightonai/Reason-ModernColBERT). This 150M parameters model outperforms 7B models on this reasoning-intensive retrieval benchmark, which requires reasoning to find relevant documents.
 Although it can perform reasoning on its own, [it benefits from LLM reformulation](https://x.com/antoine_chaffin/status/1930625989643587598) and is thus particularly suited as a MCP to collaborate with an LLM.
-
 Effectively, this demo allows to build a tool that can solve any leetcode problem by searching for problems that require similar algorithms and feed it to the LLM.
 
 You can see it working in this example, where the agent find relevant leetcode solution, propose solutions with different complexity level as well as associated tests to validate them and even vizualisation tool.
@@ -72,12 +67,14 @@ iframe2 = """
 """
 
 with gr.Blocks() as demo:
-    gr.Markdown("# LeetCode Search")
-    gr.Markdown("Search in leetcode database index using PyLate")
     gr.Markdown(readme_md)
     gr.HTML(iframe1)
     gr.Markdown(readme_md2)
     gr.HTML(iframe2)
+    gr.Markdown("# LeetCode Search")
+    gr.Markdown(
+        "Search in leetcode database index using PyLate and Reason-ModernColBERT"
+    )
     gr.Interface(
         fn=pylate_search_leetcode,
         inputs=["text"],