add vector database 3d space visualisation

app.py

@@ -592,9 +592,9 @@ st.write("""\
     
     The retrieval of documents based on search terms involves two main steps:
 
-    Vectorization of the search query: The search query is converted into a vector using the same process used to vectorize the documents in the database.
+    - **Vectorization of the search query**: The search query is converted into a vector using the same process used to vectorize the documents in the database.
 
-    Vector similarity search: The vector database then identifies the vectors that are closest to the query vector. 
+    - **Vector similarity search**: The vector database then identifies the vectors that are closest to the query vector. 
     This is typically done using a distance metric like Euclidean distance or cosine similarity. The documents 
     corresponding to these vectors are returned as the search results.