Set vLLM as default model for VisualQnA (#1644)
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@@ -2,32 +2,31 @@
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# SPDX-License-Identifier: Apache-2.0
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services:
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llava-tgi-service:
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image: ghcr.io/huggingface/text-generation-inference:2.4.0-intel-cpu
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container_name: tgi-llava-xeon-server
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vllm-service:
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image: ${REGISTRY:-opea}/vllm:${TAG:-latest}
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container_name: vllm-service
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ports:
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- "8399:80"
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- ${VLLM_PORT:-8399}:80
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volumes:
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- "${MODEL_CACHE:-./data}:/data"
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shm_size: 1g
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- "${MODEL_CACHE:-./data}:/root/.cache/huggingface/hub"
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environment:
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no_proxy: ${no_proxy}
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http_proxy: ${http_proxy}
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https_proxy: ${https_proxy}
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HF_HUB_DISABLE_PROGRESS_BARS: 1
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HF_HUB_ENABLE_HF_TRANSFER: 0
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host_ip: ${host_ip}
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HF_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
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VLLM_TORCH_PROFILER_DIR: "/mnt"
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healthcheck:
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test: ["CMD-SHELL", "curl -f http://$host_ip:8399/health || exit 1"]
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test: ["CMD-SHELL", "curl -f http://localhost:80/health || exit 1"]
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interval: 10s
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timeout: 10s
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retries: 60
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command: --model-id ${LVM_MODEL_ID} --max-input-length 4096 --max-total-tokens 8192 --cuda-graphs 0
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retries: 100
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command: --model $LVM_MODEL_ID --host 0.0.0.0 --port 80 --chat-template examples/template_llava.jinja # https://docs.vllm.ai/en/v0.5.0/models/vlm.html
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lvm:
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image: ${REGISTRY:-opea}/lvm:${TAG:-latest}
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container_name: lvm-xeon-server
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depends_on:
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llava-tgi-service:
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vllm-service:
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condition: service_healthy
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ports:
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- "9399:9399"
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@@ -37,7 +36,8 @@ services:
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http_proxy: ${http_proxy}
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https_proxy: ${https_proxy}
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LVM_ENDPOINT: ${LVM_ENDPOINT}
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LVM_COMPONENT_NAME: "OPEA_TGI_LLAVA_LVM"
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LVM_COMPONENT_NAME: "OPEA_VLLM_LVM"
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LLM_MODEL_ID: ${LVM_MODEL_ID}
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HF_HUB_DISABLE_PROGRESS_BARS: 1
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HF_HUB_ENABLE_HF_TRANSFER: 0
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restart: unless-stopped
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@@ -45,7 +45,7 @@ services:
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image: ${REGISTRY:-opea}/visualqna:${TAG:-latest}
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container_name: visualqna-xeon-backend-server
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depends_on:
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- llava-tgi-service
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- vllm-service
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- lvm
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ports:
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- "8888:8888"
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