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Use official tei gaudi image and update tgi gaudi version (#810)

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Signed-off-by: lvliang-intel <liang1.lv@intel.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
This commit is contained in:
lvliang-intel
2024-09-23 17:52:56 +08:00
committed by GitHub
parent c35fe0b429
commit 3fb60608b3
72 changed files with 8024 additions and 154 deletions
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9
DocSum/docker_compose/intel/hpu/gaudi/compose.yaml
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@@ -3,7 +3,7 @@
services:
tgi-service:
image: ghcr.io/huggingface/tgi-gaudi:2.0.1
image: ghcr.io/huggingface/tgi-gaudi:2.0.5
container_name: tgi-gaudi-server
ports:
- "8008:80"
@@ -11,8 +11,11 @@ services:
no_proxy: ${no_proxy}
http_proxy: ${http_proxy}
https_proxy: ${https_proxy}
TGI_LLM_ENDPOINT: ${TGI_LLM_ENDPOINT}
HUGGINGFACEHUB_API_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
HUGGING_FACE_HUB_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
ENABLE_HPU_GRAPH: true
LIMIT_HPU_GRAPH: true
USE_FLASH_ATTENTION: true
FLASH_ATTENTION_RECOMPUTE: true
volumes:
- "./data:/data"
runtime: habana

8
DocSum/docsum.yaml
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@@ -6,7 +6,7 @@ opea_micro_services:
tgi-service:
host: ${TGI_SERVICE_IP}
ports: ${TGI_SERVICE_PORT}
image: ghcr.io/huggingface/tgi-gaudi:2.0.1
image: ghcr.io/huggingface/tgi-gaudi:2.0.5
volumes:
- "./data:/data"
runtime: habana
@@ -17,7 +17,11 @@ opea_micro_services:
HUGGINGFACEHUB_API_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
HABANA_VISIBLE_DEVICES: all
OMPI_MCA_btl_vader_single_copy_mechanism: none
HF_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
HUGGING_FACE_HUB_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
ENABLE_HPU_GRAPH: true
LIMIT_HPU_GRAPH: true
USE_FLASH_ATTENTION: true
FLASH_ATTENTION_RECOMPUTE: true
model-id: ${LLM_MODEL_ID}
llm:
host: ${LLM_SERVICE_HOST_IP}

2
DocSum/kubernetes/intel/README_gmc.md
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@@ -9,7 +9,7 @@ The DocSum application is defined as a Custom Resource (CR) file that the above
The DocSum pipeline uses prebuilt images. The Xeon version uses the prebuilt image llm-docsum-tgi:latest which internally leverages the
the image ghcr.io/huggingface/text-generation-inference:sha-e4201f4-intel-cpu. The service is called tgi-svc. Meanwhile, the Gaudi version launches the
service tgi-gaudi-svc, which uses the image ghcr.io/huggingface/tgi-gaudi:1.2.1. Both TGI model services serve the model specified in the LLM_MODEL_ID variable that is exported by you. In the below example we use Intel/neural-chat-7b-v3-3.
service tgi-gaudi-svc, which uses the image `ghcr.io/huggingface/tgi-gaudi:2.0.5`. Both TGI model services serve the model specified in the LLM_MODEL_ID variable that is exported by you. In the below example we use Intel/neural-chat-7b-v3-3.
[NOTE]
Refer to [Docker Xeon README](https://github.com/opea-project/GenAIExamples/blob/main/DocSum/docker_compose/intel/cpu/xeon/README.md) or

2
DocSum/kubernetes/intel/hpu/gaudi/manifest/docsum.yaml
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@@ -405,7 +405,7 @@ spec:
runAsUser: 1000
seccompProfile:
type: RuntimeDefault
image: "ghcr.io/huggingface/tgi-gaudi:2.0.1"
image: "ghcr.io/huggingface/tgi-gaudi:2.0.5"
imagePullPolicy: IfNotPresent
volumeMounts:
- mountPath: /data

2
DocSum/tests/test_compose_on_gaudi.sh
View File

@@ -22,7 +22,7 @@ function build_docker_images() {
service_list="docsum docsum-ui llm-docsum-tgi"
docker compose -f build.yaml build ${service_list} --no-cache > ${LOG_PATH}/docker_image_build.log
docker pull ghcr.io/huggingface/tgi-gaudi:2.0.1
docker pull ghcr.io/huggingface/tgi-gaudi:2.0.5
docker images && sleep 1s
}