docs: add start vllm + KVBM using dynamo into runbook (#3213)

Signed-off-by: Ziqi Fan <ziqif@nvidia.com>

docs/guides/run_kvbm_in_vllm.md

@@ -43,8 +43,13 @@ export DYN_KVBM_CPU_CACHE_GB=4
 # 8 means 8GB of disk would be used
 export DYN_KVBM_DISK_CACHE_GB=8
 
-# serve an example LLM model
-vllm serve --kv-transfer-config '{"kv_connector":"DynamoConnector","kv_role":"kv_both", "kv_connector_module_path": "dynamo.llm.vllm_integration.connector"}' deepseek-ai/DeepSeek-R1-Distill-Llama-8B
+# [DYNAMO] start dynamo frontend
+python -m dynamo.frontend --http-port 8000 &
+
+# [DYNAMO] serve an LLM model using KVBM with dynamo
+python -m dynamo.vllm \
+    --model deepseek-ai/DeepSeek-R1-Distill-Llama-8B \
+    --connector kvbm &
 
 # make a call to LLM
 curl localhost:8000/v1/chat/completions   -H "Content-Type: application/json"   -d '{
@@ -60,6 +65,11 @@ curl localhost:8000/v1/chat/completions   -H "Content-Type: application/json"
   }'
 ```
 
+Alternatively, can use "vllm serve" with KVBM by replacing the above two [DYNAMO] cmds with below:
+```bash
+vllm serve --kv-transfer-config '{"kv_connector":"DynamoConnector","kv_role":"kv_both", "kv_connector_module_path": "dynamo.llm.vllm_integration.connector"}' deepseek-ai/DeepSeek-R1-Distill-Llama-8B
+```
+
 ## Enable and View KVBM Metrics
 
 Follow below steps to enable metrics collection and view via Grafana dashboard: