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fix: Fix KVBM Guide #2539

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Aug 19, 2025
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fix: Fix KVBM Guide #2539

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9 changes: 3 additions & 6 deletions docs/guides/run_kvbm_in_vllm.md
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Expand Up @@ -30,13 +30,10 @@ To use KVBM in vLLM, you can follow the steps below:
docker compose -f deploy/metrics/docker-compose.yml up -d

# build a container containing vllm and kvbm
./container/build.sh --framework kvbm
./container/build.sh --framework vllm --enable-kvbm

# launch the container
./container/run.sh --framework kvbm -it --mount-workspace --use-nixl-gds

# enable using kvbm instead of vllm's own kv cache manager
export DYN_KVBM_MANAGER=kvbm
./container/run.sh --framework vllm -it --mount-workspace --use-nixl-gds

# enable kv offloading to CPU memory
# 4 means 4GB of CPU memory would be used
Expand All @@ -47,7 +44,7 @@ export DYN_KVBM_CPU_CACHE_GB=4
export DYN_KVBM_DISK_CACHE_GB=8

# serve an example LLM model
vllm serve deepseek-ai/DeepSeek-R1-Distill-Llama-8B
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

# make a call to LLM
curl localhost:8000/v1/chat/completions -H "Content-Type: application/json" -d '{
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