Add Memory Store conceptual doc section (#2624)

On semantic search

docs/docs/cloud/deployment/semantic_search.md

@@ -59,7 +59,7 @@ def search_memory(state: State, *, store: BaseStore):
     results = store.search(
         namespace=("memory", "facts"),  # Organize memories by type
         query="your search query",
-        k=3  # number of results to return
+        limit=3  # number of results to return
     )
     return results
 ```

docs/docs/cloud/reference/cli.md

@@ -81,6 +81,15 @@ The `fields` configuration determines which parts of your documents to embed:
 }
 ```
 
+!!! note "Common model dimensions"
+        - openai:text-embedding-3-large: 3072
+        - openai:text-embedding-3-small: 1536
+        - openai:text-embedding-ada-002: 1536
+        - cohere:embed-english-v3.0: 1024
+        - cohere:embed-english-light-v3.0: 384
+        - cohere:embed-multilingual-v3.0: 1024
+        - cohere:embed-multilingual-light-v3.0: 384
+
 #### Semantic search with a custom embedding function
 
 If you want to use semantic search with a custom embedding function, you can pass a path to a custom embedding function: