docs: update KVBM diagram from PNG to SVG (#7277)

Signed-off-by: akshatha-k <akshutk@gmail.com>
Signed-off-by: Dan Gil <dagil@nvidia.com>
Co-authored-by: akshatha-k <akshutk@gmail.com>

docs/components/kvbm/README.md

@@ -40,7 +40,7 @@ Offloading KV cache to CPU or storage is most effective when KV Cache exceeds GP
 
 ## Architecture
 
-![KVBM Architecture](../../assets/img/kvbm-architecture.png)
+![KVBM Architecture](../../assets/img/kvbm-components.svg)
 *High-level layered architecture view of Dynamo KV Block Manager and how it interfaces with different components of the LLM inference ecosystem*
 
 KVBM has three primary logical layers:

docs/design-docs/kvbm-design.md

@@ -8,7 +8,7 @@ This document provides an in-depth look at the architecture, components, framewo
 
 ## KVBM Components
 
-![Internal Components of Dynamo KVBM](../assets/img/kvbm-components.png)
+![Internal Components of Dynamo KVBM](../assets/img/kvbm-components.svg)
 
 
 *Internal Components of Dynamo KVBM*

lib/bindings/kvbm/README.md

@@ -19,7 +19,7 @@ limitations under the License.
 
 The Dynamo KVBM is a distributed KV-cache block management system designed for scalable LLM inference. It cleanly separates memory management from inference runtimes (vLLM, TensorRT-LLM, and SGLang), enabling GPU↔CPU↔Disk/Remote tiering, asynchronous block offload/onboard, and efficient block reuse.
 
-![A block diagram showing a layered architecture view of Dynamo KV Block manager.](../../../docs/assets/img/kvbm-architecture.png)
+![A block diagram showing a layered architecture view of Dynamo KV Block manager.](../../../docs/assets/img/kvbm-components.svg)
 
 
 ## Feature Highlights