diff --git a/DocSum/docker_compose/intel/cpu/xeon/README.md b/DocSum/docker_compose/intel/cpu/xeon/README.md
index 9465c0c976..2aacacafbb 100644
--- a/DocSum/docker_compose/intel/cpu/xeon/README.md
+++ b/DocSum/docker_compose/intel/cpu/xeon/README.md
@@ -2,6 +2,8 @@
 
 This document outlines the deployment process for a Document Summarization application utilizing the [GenAIComps](https://github.com/opea-project/GenAIComps.git) microservice pipeline on an Intel Xeon server. The steps include Docker image creation, container deployment via Docker Compose, and service execution to integrate microservices such as `llm`. We will publish the Docker images to Docker Hub soon, which will simplify the deployment process for this service.
 
+The default pipeline deploys with vLLM as the LLM serving component. It also provides options of using TGI backend for LLM microservice, please refer to [start-microservice-docker-containers](#start-microservice-docker-containers) section in this page.
+
 ## 🚀 Apply Intel Xeon Server on AWS
 
 To apply a Intel Xeon server on AWS, start by creating an AWS account if you don't have one already. Then, head to the [EC2 Console](https://console.aws.amazon.com/ec2/v2/home) to begin the process. Within the EC2 service, select the Amazon EC2 M7i or M7i-flex instance type to leverage 4th Generation Intel Xeon Scalable processors. These instances are optimized for high-performance computing and demanding workloads.
@@ -116,9 +118,20 @@ To set up environment variables for deploying Document Summarization services, f
 
 ```bash
 cd GenAIExamples/DocSum/docker_compose/intel/cpu/xeon
+```
+
+If use vLLM as the LLM serving backend.
+
+```bash
 docker compose -f compose.yaml up -d
 ```
 
+If use TGI as the LLM serving backend.
+
+```bash
+docker compose -f compose_tgi.yaml up -d
+```
+
 You will have the following Docker Images:
 
 1. `opea/docsum-ui:latest`
@@ -128,10 +141,30 @@ You will have the following Docker Images:
 
 ### Validate Microservices
 
-1. TGI Service
+1. LLM backend Service
+
+   In the first startup, this service will take more time to download, load and warm up the model. After it's finished, the service will be ready.
+   Try the command below to check whether the LLM serving is ready.
+
+   ```bash
+   # vLLM service
+   docker logs docsum-xeon-vllm-service 2>&1 | grep complete
+   # If the service is ready, you will get the response like below.
+   INFO:     Application startup complete.
+   ```
+
+   ```bash
+   # TGI service
+   docker logs docsum-xeon-tgi-service | grep Connected
+   # If the service is ready, you will get the response like below.
+   2024-09-03T02:47:53.402023Z  INFO text_generation_router::server: router/src/server.rs:2311: Connected
+   ```
+
+   Then try the `cURL` command below to validate services.
 
    ```bash
-   curl http://${host_ip}:8008/generate \
+   # either vLLM or TGI service
+   curl http://${host_ip}:8008/v1/chat/completions \
      -X POST \
      -d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":17, "do_sample": true}}' \
      -H 'Content-Type: application/json'
diff --git a/DocSum/docker_compose/intel/cpu/xeon/compose.yaml b/DocSum/docker_compose/intel/cpu/xeon/compose.yaml
index 8d91db5e73..8eb3bb28b6 100644
--- a/DocSum/docker_compose/intel/cpu/xeon/compose.yaml
+++ b/DocSum/docker_compose/intel/cpu/xeon/compose.yaml
@@ -2,54 +2,53 @@
 # SPDX-License-Identifier: Apache-2.0
 
 services:
-  tgi-server:
-    image: ghcr.io/huggingface/text-generation-inference:2.4.0-intel-cpu
-    container_name: tgi-server
+  vllm-service:
+    image: ${REGISTRY:-opea}/vllm:${TAG:-latest}
+    container_name: docsum-xeon-vllm-service
     ports:
-      - ${LLM_ENDPOINT_PORT:-8008}:80
+      - "8008:80"
+    volumes:
+      - "${MODEL_CACHE:-./data}:/root/.cache/huggingface/hub"
+    shm_size: 1g
     environment:
       no_proxy: ${no_proxy}
       http_proxy: ${http_proxy}
       https_proxy: ${https_proxy}
-      TGI_LLM_ENDPOINT: ${TGI_LLM_ENDPOINT}
-      HUGGINGFACEHUB_API_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
-      host_ip: ${host_ip}
-      LLM_ENDPOINT_PORT: ${LLM_ENDPOINT_PORT}
+      HF_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
+      LLM_MODEL_ID: ${LLM_MODEL_ID}
+      VLLM_TORCH_PROFILER_DIR: "/mnt"
     healthcheck:
-      test: ["CMD-SHELL", "curl -f http://${host_ip}:${LLM_ENDPOINT_PORT}/health || exit 1"]
+      test: ["CMD-SHELL", "curl -f http://localhost:80/health || exit 1"]
       interval: 10s
       timeout: 10s
       retries: 100
-    volumes:
-      - "${MODEL_CACHE:-./data}:/data"
-    shm_size: 1g
-    command: --model-id ${LLM_MODEL_ID} --cuda-graphs 0  --max-input-length ${MAX_INPUT_TOKENS} --max-total-tokens ${MAX_TOTAL_TOKENS}
+    command: --model $LLM_MODEL_ID --host 0.0.0.0 --port 80
 
-  llm-docsum-tgi:
+  llm-docsum-vllm:
     image: ${REGISTRY:-opea}/llm-docsum:${TAG:-latest}
-    container_name: llm-docsum-server
+    container_name: docsum-xeon-llm-server
     depends_on:
-      tgi-server:
+      vllm-service:
         condition: service_healthy
     ports:
-      - ${DOCSUM_PORT:-9000}:9000
+      - ${LLM_PORT:-9000}:9000
     ipc: host
     environment:
       no_proxy: ${no_proxy}
       http_proxy: ${http_proxy}
       https_proxy: ${https_proxy}
       LLM_ENDPOINT: ${LLM_ENDPOINT}
+      LLM_MODEL_ID: ${LLM_MODEL_ID}
       HUGGINGFACEHUB_API_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
       MAX_INPUT_TOKENS: ${MAX_INPUT_TOKENS}
       MAX_TOTAL_TOKENS: ${MAX_TOTAL_TOKENS}
-      LLM_MODEL_ID: ${LLM_MODEL_ID}
       DocSum_COMPONENT_NAME: ${DocSum_COMPONENT_NAME}
       LOGFLAG: ${LOGFLAG:-False}
     restart: unless-stopped
 
   whisper:
     image: ${REGISTRY:-opea}/whisper:${TAG:-latest}
-    container_name: whisper-server
+    container_name: docsum-xeon-whisper-server
     ports:
       - "7066:7066"
     ipc: host
@@ -63,10 +62,10 @@ services:
     image: ${REGISTRY:-opea}/docsum:${TAG:-latest}
     container_name: docsum-xeon-backend-server
     depends_on:
-      - tgi-server
-      - llm-docsum-tgi
+      - vllm-service
+      - llm-docsum-vllm
     ports:
-      - "8888:8888"
+      - "${BACKEND_SERVICE_PORT:-8888}:8888"
     environment:
       - no_proxy=${no_proxy}
       - https_proxy=${https_proxy}
@@ -83,7 +82,7 @@ services:
     depends_on:
       - docsum-xeon-backend-server
     ports:
-      - "5173:5173"
+      - "${FRONTEND_SERVICE_PORT:-5173}:5173"
     environment:
       - no_proxy=${no_proxy}
       - https_proxy=${https_proxy}
diff --git a/DocSum/docker_compose/intel/cpu/xeon/compose_tgi.yaml b/DocSum/docker_compose/intel/cpu/xeon/compose_tgi.yaml
new file mode 100644
index 0000000000..4b0362bd09
--- /dev/null
+++ b/DocSum/docker_compose/intel/cpu/xeon/compose_tgi.yaml
@@ -0,0 +1,97 @@
+# Copyright (C) 2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+services:
+  tgi-server:
+    image: ghcr.io/huggingface/text-generation-inference:2.4.0-intel-cpu
+    container_name: docsum-xeon-tgi-server
+    ports:
+      - ${LLM_ENDPOINT_PORT:-8008}:80
+    volumes:
+      - "${MODEL_CACHE:-./data}:/data"
+    environment:
+      no_proxy: ${no_proxy}
+      http_proxy: ${http_proxy}
+      https_proxy: ${https_proxy}
+      TGI_LLM_ENDPOINT: ${TGI_LLM_ENDPOINT}
+      HUGGINGFACEHUB_API_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
+      host_ip: ${host_ip}
+    healthcheck:
+      test: ["CMD-SHELL", "curl -f http://localhost:80/health || exit 1"]
+      interval: 10s
+      timeout: 10s
+      retries: 100
+    shm_size: 1g
+    command: --model-id ${LLM_MODEL_ID} --cuda-graphs 0  --max-input-length ${MAX_INPUT_TOKENS} --max-total-tokens ${MAX_TOTAL_TOKENS}
+
+  llm-docsum-tgi:
+    image: ${REGISTRY:-opea}/llm-docsum:${TAG:-latest}
+    container_name: docsum-xeon-llm-server
+    depends_on:
+      tgi-server:
+        condition: service_healthy
+    ports:
+      - ${LLM_PORT:-9000}:9000
+    ipc: host
+    environment:
+      no_proxy: ${no_proxy}
+      http_proxy: ${http_proxy}
+      https_proxy: ${https_proxy}
+      LLM_ENDPOINT: ${LLM_ENDPOINT}
+      LLM_MODEL_ID: ${LLM_MODEL_ID}
+      HUGGINGFACEHUB_API_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
+      MAX_INPUT_TOKENS: ${MAX_INPUT_TOKENS}
+      MAX_TOTAL_TOKENS: ${MAX_TOTAL_TOKENS}
+      DocSum_COMPONENT_NAME: ${DocSum_COMPONENT_NAME}
+      LOGFLAG: ${LOGFLAG:-False}
+    restart: unless-stopped
+
+  whisper:
+    image: ${REGISTRY:-opea}/whisper:${TAG:-latest}
+    container_name: docsum-xeon-whisper-server
+    ports:
+      - "7066:7066"
+    ipc: host
+    environment:
+      no_proxy: ${no_proxy}
+      http_proxy: ${http_proxy}
+      https_proxy: ${https_proxy}
+    restart: unless-stopped
+
+  docsum-xeon-backend-server:
+    image: ${REGISTRY:-opea}/docsum:${TAG:-latest}
+    container_name: docsum-xeon-backend-server
+    depends_on:
+      - tgi-server
+      - llm-docsum-tgi
+    ports:
+      - "${BACKEND_SERVICE_PORT:-8888}:8888"
+    environment:
+      - no_proxy=${no_proxy}
+      - https_proxy=${https_proxy}
+      - http_proxy=${http_proxy}
+      - MEGA_SERVICE_HOST_IP=${MEGA_SERVICE_HOST_IP}
+      - LLM_SERVICE_HOST_IP=${LLM_SERVICE_HOST_IP}
+      - ASR_SERVICE_HOST_IP=${ASR_SERVICE_HOST_IP}
+    ipc: host
+    restart: always
+
+  docsum-gradio-ui:
+    image: ${REGISTRY:-opea}/docsum-gradio-ui:${TAG:-latest}
+    container_name: docsum-xeon-ui-server
+    depends_on:
+      - docsum-xeon-backend-server
+    ports:
+      - "${FRONTEND_SERVICE_PORT:-5173}:5173"
+    environment:
+      - no_proxy=${no_proxy}
+      - https_proxy=${https_proxy}
+      - http_proxy=${http_proxy}
+      - BACKEND_SERVICE_ENDPOINT=${BACKEND_SERVICE_ENDPOINT}
+      - DOC_BASE_URL=${BACKEND_SERVICE_ENDPOINT}
+    ipc: host
+    restart: always
+
+networks:
+  default:
+    driver: bridge
diff --git a/DocSum/docker_compose/intel/hpu/gaudi/README.md b/DocSum/docker_compose/intel/hpu/gaudi/README.md
index d150b3f28e..8d947554fd 100644
--- a/DocSum/docker_compose/intel/hpu/gaudi/README.md
+++ b/DocSum/docker_compose/intel/hpu/gaudi/README.md
@@ -2,6 +2,8 @@
 
 This document outlines the deployment process for a Document Summarization application utilizing the [GenAIComps](https://github.com/opea-project/GenAIComps.git) microservice pipeline on Intel Gaudi server. The steps include Docker image creation, container deployment via Docker Compose, and service execution to integrate microservices such as `llm`. We will publish the Docker images to Docker Hub soon, which will simplify the deployment process for this service.
 
+The default pipeline deploys with vLLM as the LLM serving component. It also provides options of using TGI backend for LLM microservice, please refer to [start-microservice-docker-containers](#start-microservice-docker-containers) section in this page.
+
 ## 🚀 Build Docker Images
 
 ### 1. Build MicroService Docker Image
@@ -108,9 +110,20 @@ To set up environment variables for deploying Document Summarization services, f
 
 ```bash
 cd GenAIExamples/DocSum/docker_compose/intel/hpu/gaudi
+```
+
+If use vLLM as the LLM serving backend.
+
+```bash
 docker compose -f compose.yaml up -d
 ```
 
+If use TGI as the LLM serving backend.
+
+```bash
+docker compose -f compose_tgi.yaml up -d
+```
+
 You will have the following Docker Images:
 
 1. `opea/docsum-ui:latest`
@@ -120,10 +133,30 @@ You will have the following Docker Images:
 
 ### Validate Microservices
 
-1. TGI Service
+1. LLM backend Service
+
+   In the first startup, this service will take more time to download, load and warm up the model. After it's finished, the service will be ready.
+   Try the command below to check whether the LLM serving is ready.
+
+   ```bash
+   # vLLM service
+   docker logs docsum-xeon-vllm-service 2>&1 | grep complete
+   # If the service is ready, you will get the response like below.
+   INFO:     Application startup complete.
+   ```
+
+   ```bash
+   # TGI service
+   docker logs docsum-xeon-tgi-service | grep Connected
+   # If the service is ready, you will get the response like below.
+   2024-09-03T02:47:53.402023Z  INFO text_generation_router::server: router/src/server.rs:2311: Connected
+   ```
+
+   Then try the `cURL` command below to validate services.
 
    ```bash
-   curl http://${host_ip}:8008/generate \
+   # either vLLM or TGI service
+   curl http://${host_ip}:8008/v1/chat/completions \
      -X POST \
      -d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":17, "do_sample": true}}' \
      -H 'Content-Type: application/json'
diff --git a/DocSum/docker_compose/intel/hpu/gaudi/compose.yaml b/DocSum/docker_compose/intel/hpu/gaudi/compose.yaml
index 9ae96e3d7d..681c3e7dd9 100644
--- a/DocSum/docker_compose/intel/hpu/gaudi/compose.yaml
+++ b/DocSum/docker_compose/intel/hpu/gaudi/compose.yaml
@@ -2,47 +2,42 @@
 # SPDX-License-Identifier: Apache-2.0
 
 services:
-  tgi-gaudi-server:
-    image: ghcr.io/huggingface/tgi-gaudi:2.3.1
-    container_name: tgi-gaudi-server
+  vllm-service:
+    image: ${REGISTRY:-opea}/vllm-gaudi:${TAG:-latest}
+    container_name: docsum-gaudi-vllm-service
     ports:
-      - ${LLM_ENDPOINT_PORT:-8008}:80
+      - "8008:80"
     volumes:
-      - "${DATA_PATH:-./data}:/data"
+      - "${MODEL_CACHE:-./data}:/root/.cache/huggingface/hub"
     environment:
       no_proxy: ${no_proxy}
       http_proxy: ${http_proxy}
       https_proxy: ${https_proxy}
-      HUGGING_FACE_HUB_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
-      HF_HUB_DISABLE_PROGRESS_BARS: 1
-      HF_HUB_ENABLE_HF_TRANSFER: 0
+      HF_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
       HABANA_VISIBLE_DEVICES: all
       OMPI_MCA_btl_vader_single_copy_mechanism: none
-      ENABLE_HPU_GRAPH: true
-      LIMIT_HPU_GRAPH: true
-      USE_FLASH_ATTENTION: true
-      FLASH_ATTENTION_RECOMPUTE: true
-      host_ip: ${host_ip}
-      LLM_ENDPOINT_PORT: ${LLM_ENDPOINT_PORT}
-    runtime: habana
-    cap_add:
-      - SYS_NICE
-    ipc: host
+      LLM_MODEL_ID: ${LLM_MODEL_ID}
+      NUM_CARDS: ${NUM_CARDS}
+      VLLM_TORCH_PROFILER_DIR: "/mnt"
     healthcheck:
-      test: ["CMD-SHELL", "curl -f http://${host_ip}:${LLM_ENDPOINT_PORT}/health || exit 1"]
+      test: ["CMD-SHELL", "curl -f http://localhost:80/health || exit 1"]
       interval: 10s
       timeout: 10s
       retries: 100
-    command: --model-id ${LLM_MODEL_ID} --max-input-length ${MAX_INPUT_TOKENS} --max-total-tokens ${MAX_TOTAL_TOKENS}
+    runtime: habana
+    cap_add:
+      - SYS_NICE
+    ipc: host
+    command: --model $LLM_MODEL_ID --tensor-parallel-size ${NUM_CARDS} --host 0.0.0.0 --port 80 --block-size ${BLOCK_SIZE} --max-num-seqs ${MAX_NUM_SEQS} --max-seq_len-to-capture ${MAX_SEQ_LEN_TO_CAPTURE}
 
-  llm-docsum-tgi:
+  llm-docsum-vllm:
     image: ${REGISTRY:-opea}/llm-docsum:${TAG:-latest}
-    container_name: llm-docsum-gaudi-server
+    container_name: docsum-gaudi-llm-server
     depends_on:
-      tgi-gaudi-server:
+      vllm-service:
         condition: service_healthy
     ports:
-      - ${DOCSUM_PORT:-9000}:9000
+      - ${LLM_PORT:-9000}:9000
     ipc: host
     environment:
       no_proxy: ${no_proxy}
@@ -59,7 +54,7 @@ services:
 
   whisper:
     image: ${REGISTRY:-opea}/whisper:${TAG:-latest}
-    container_name: whisper-server
+    container_name: docsum-gaudi-whisper-server
     ports:
       - "7066:7066"
     ipc: host
@@ -78,10 +73,10 @@ services:
     image: ${REGISTRY:-opea}/docsum:${TAG:-latest}
     container_name: docsum-gaudi-backend-server
     depends_on:
-      - tgi-gaudi-server
-      - llm-docsum-tgi
+      - vllm-service
+      - llm-docsum-vllm
     ports:
-      - "8888:8888"
+      - "${BACKEND_SERVICE_PORT:-8888}:8888"
     environment:
       - no_proxy=${no_proxy}
       - https_proxy=${https_proxy}
@@ -99,7 +94,7 @@ services:
     depends_on:
       - docsum-gaudi-backend-server
     ports:
-      - "5173:5173"
+      - "${FRONTEND_SERVICE_PORT:-5173}:5173"
     environment:
       - no_proxy=${no_proxy}
       - https_proxy=${https_proxy}
diff --git a/DocSum/docker_compose/intel/hpu/gaudi/compose_tgi.yaml b/DocSum/docker_compose/intel/hpu/gaudi/compose_tgi.yaml
new file mode 100644
index 0000000000..01008de27a
--- /dev/null
+++ b/DocSum/docker_compose/intel/hpu/gaudi/compose_tgi.yaml
@@ -0,0 +1,114 @@
+# Copyright (C) 2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+services:
+  tgi-gaudi-server:
+    image: ghcr.io/huggingface/tgi-gaudi:2.3.1
+    container_name: docsum-gaudi-tgi-server
+    ports:
+      - ${LLM_ENDPOINT_PORT:-8008}:80
+    volumes:
+      - "${MODEL_CACHE}:/data"
+    environment:
+      no_proxy: ${no_proxy}
+      http_proxy: ${http_proxy}
+      https_proxy: ${https_proxy}
+      HUGGING_FACE_HUB_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
+      HF_HUB_DISABLE_PROGRESS_BARS: 1
+      HF_HUB_ENABLE_HF_TRANSFER: 0
+      HABANA_VISIBLE_DEVICES: all
+      OMPI_MCA_btl_vader_single_copy_mechanism: none
+      ENABLE_HPU_GRAPH: true
+      LIMIT_HPU_GRAPH: true
+      USE_FLASH_ATTENTION: true
+      FLASH_ATTENTION_RECOMPUTE: true
+      host_ip: ${host_ip}
+      LLM_ENDPOINT_PORT: ${LLM_ENDPOINT_PORT}
+    runtime: habana
+    cap_add:
+      - SYS_NICE
+    ipc: host
+    healthcheck:
+      test: ["CMD-SHELL", "curl -f http://localhost:80/health || exit 1"]
+      interval: 10s
+      timeout: 10s
+      retries: 100
+    command: --model-id ${LLM_MODEL_ID} --max-input-length ${MAX_INPUT_TOKENS} --max-total-tokens ${MAX_TOTAL_TOKENS}
+
+  llm-docsum-tgi:
+    image: ${REGISTRY:-opea}/llm-docsum:${TAG:-latest}
+    container_name: docsum-gaudi-llm-server
+    depends_on:
+      tgi-gaudi-server:
+        condition: service_healthy
+    ports:
+      - ${LLM_PORT:-9000}:9000
+    ipc: host
+    environment:
+      no_proxy: ${no_proxy}
+      http_proxy: ${http_proxy}
+      https_proxy: ${https_proxy}
+      HUGGINGFACEHUB_API_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
+      MAX_INPUT_TOKENS: ${MAX_INPUT_TOKENS}
+      MAX_TOTAL_TOKENS: ${MAX_TOTAL_TOKENS}
+      LLM_ENDPOINT: ${LLM_ENDPOINT}
+      LLM_MODEL_ID: ${LLM_MODEL_ID}
+      DocSum_COMPONENT_NAME: ${DocSum_COMPONENT_NAME}
+      LOGFLAG: ${LOGFLAG:-False}
+    restart: unless-stopped
+
+  whisper:
+    image: ${REGISTRY:-opea}/whisper:${TAG:-latest}
+    container_name: docsum-gaudi-whisper-server
+    ports:
+      - "7066:7066"
+    ipc: host
+    environment:
+      no_proxy: ${no_proxy}
+      http_proxy: ${http_proxy}
+      https_proxy: ${https_proxy}
+      HABANA_VISIBLE_DEVICES: all
+      OMPI_MCA_btl_vader_single_copy_mechanism: none
+    runtime: habana
+    cap_add:
+      - SYS_NICE
+    restart: unless-stopped
+
+  docsum-gaudi-backend-server:
+    image: ${REGISTRY:-opea}/docsum:${TAG:-latest}
+    container_name: docsum-gaudi-backend-server
+    depends_on:
+      - tgi-gaudi-server
+      - llm-docsum-tgi
+    ports:
+      - "${BACKEND_SERVICE_PORT:-8888}:8888"
+    environment:
+      - no_proxy=${no_proxy}
+      - https_proxy=${https_proxy}
+      - http_proxy=${http_proxy}
+      - MEGA_SERVICE_HOST_IP=${MEGA_SERVICE_HOST_IP}
+      - LLM_SERVICE_HOST_IP=${LLM_SERVICE_HOST_IP}
+      - ASR_SERVICE_HOST_IP=${ASR_SERVICE_HOST_IP}
+
+    ipc: host
+    restart: always
+
+  docsum-gradio-ui:
+    image: ${REGISTRY:-opea}/docsum-gradio-ui:${TAG:-latest}
+    container_name: docsum-gaudi-ui-server
+    depends_on:
+      - docsum-gaudi-backend-server
+    ports:
+      - "${FRONTEND_SERVICE_PORT:-5173}:5173"
+    environment:
+      - no_proxy=${no_proxy}
+      - https_proxy=${https_proxy}
+      - http_proxy=${http_proxy}
+      - BACKEND_SERVICE_ENDPOINT=${BACKEND_SERVICE_ENDPOINT}
+      - DOC_BASE_URL=${BACKEND_SERVICE_ENDPOINT}
+    ipc: host
+    restart: always
+
+networks:
+  default:
+    driver: bridge
diff --git a/DocSum/docker_compose/set_env.sh b/DocSum/docker_compose/set_env.sh
index f116a99c3a..25afc30b3a 100644
--- a/DocSum/docker_compose/set_env.sh
+++ b/DocSum/docker_compose/set_env.sh
@@ -6,18 +6,21 @@ pushd "../../" > /dev/null
 source .set_env.sh
 popd > /dev/null
 
+
+export no_proxy="${no_proxy},${host_ip}"
+
+export LLM_ENDPOINT_PORT=8008
+export LLM_MODEL_ID="Intel/neural-chat-7b-v3-3"
 export MAX_INPUT_TOKENS=1024
 export MAX_TOTAL_TOKENS=2048
 
-export no_proxy="${no_proxy},${host_ip}"
+export LLM_PORT=9000
+export LLM_ENDPOINT="http://${host_ip}:${LLM_ENDPOINT_PORT}"
+export DocSum_COMPONENT_NAME="OpeaDocSumTgi"
+
 export MEGA_SERVICE_HOST_IP=${host_ip}
 export LLM_SERVICE_HOST_IP=${host_ip}
 export ASR_SERVICE_HOST_IP=${host_ip}
-export LLM_MODEL_ID="Intel/neural-chat-7b-v3-3"
-
-export BACKEND_SERVICE_ENDPOINT="http://${host_ip}:8888/v1/docsum"
 
-export LLM_ENDPOINT_PORT=8008
-export DOCSUM_PORT=9000
-export LLM_ENDPOINT="http://${host_ip}:${LLM_ENDPOINT_PORT}"
-export DocSum_COMPONENT_NAME="OpeaDocSumTgi"
+export BACKEND_SERVICE_PORT=8888
+export BACKEND_SERVICE_ENDPOINT="http://${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum"
diff --git a/DocSum/docker_image_build/build.yaml b/DocSum/docker_image_build/build.yaml
index 7eabbfc6aa..6d09a07aa9 100644
--- a/DocSum/docker_image_build/build.yaml
+++ b/DocSum/docker_image_build/build.yaml
@@ -49,3 +49,15 @@ services:
       dockerfile: comps/llms/src/doc-summarization/Dockerfile
     extends: docsum
     image: ${REGISTRY:-opea}/llm-docsum:${TAG:-latest}
+  vllm:
+    build:
+      context: vllm
+      dockerfile: Dockerfile.cpu
+    extends: docsum
+    image: ${REGISTRY:-opea}/vllm:${TAG:-latest}
+  vllm-gaudi:
+    build:
+      context: vllm-fork
+      dockerfile: Dockerfile.hpu
+    extends: docsum
+    image: ${REGISTRY:-opea}/vllm-gaudi:${TAG:-latest}
diff --git a/DocSum/tests/test_compose_on_gaudi.sh b/DocSum/tests/test_compose_on_gaudi.sh
index 1c8632b76d..d3653d0e93 100644
--- a/DocSum/tests/test_compose_on_gaudi.sh
+++ b/DocSum/tests/test_compose_on_gaudi.sh
@@ -12,23 +12,29 @@ export host_ip=$(hostname -I | awk '{print $1}')
 
 echo "REGISTRY=IMAGE_REPO=${IMAGE_REPO}"
 echo "TAG=IMAGE_TAG=${IMAGE_TAG}"
+export no_proxy="${no_proxy},${host_ip}"
+export MODEL_CACHE=${model_cache:-"./data"}
 export REGISTRY=${IMAGE_REPO}
 export TAG=${IMAGE_TAG}
+export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
+export LLM_ENDPOINT_PORT=8008
+export LLM_MODEL_ID="Intel/neural-chat-7b-v3-3"
+export NUM_CARDS=1
+export BLOCK_SIZE=128
+export MAX_NUM_SEQS=256
+export MAX_SEQ_LEN_TO_CAPTURE=2048
 export MAX_INPUT_TOKENS=2048
 export MAX_TOTAL_TOKENS=4096
-export LLM_MODEL_ID="Intel/neural-chat-7b-v3-3"
-export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
+export LLM_PORT=9000
+export LLM_ENDPOINT="http://${host_ip}:${LLM_ENDPOINT_PORT}"
+export DocSum_COMPONENT_NAME="OpeaDocSumvLLM"
 export MEGA_SERVICE_HOST_IP=${host_ip}
 export LLM_SERVICE_HOST_IP=${host_ip}
 export ASR_SERVICE_HOST_IP=${host_ip}
-export BACKEND_SERVICE_ENDPOINT="http://${host_ip}:8888/v1/docsum"
-export no_proxy="${no_proxy},${host_ip}"
-export LLM_ENDPOINT_PORT=8008
-export DOCSUM_PORT=9000
-export LLM_ENDPOINT="http://${host_ip}:${LLM_ENDPOINT_PORT}"
-export DocSum_COMPONENT_NAME="OpeaDocSumTgi"
+export FRONTEND_SERVICE_PORT=5173
+export BACKEND_SERVICE_PORT=8888
+export BACKEND_SERVICE_ENDPOINT="http://${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum"
 export LOGFLAG=True
-export DATA_PATH=${model_cache:-"/data/cache"}
 
 WORKPATH=$(dirname "$PWD")
 LOG_PATH="$WORKPATH/tests"
@@ -39,17 +45,31 @@ ROOT_FOLDER=$(dirname "$(readlink -f "$0")")
 
 function build_docker_images() {
     opea_branch=${opea_branch:-"main"}
+    # If the opea_branch isn't main, replace the git clone branch in Dockerfile.
+    if [[ "${opea_branch}" != "main" ]]; then
+        cd $WORKPATH
+        OLD_STRING="RUN git clone --depth 1 https://github.com/opea-project/GenAIComps.git"
+        NEW_STRING="RUN git clone --depth 1 --branch ${opea_branch} https://github.com/opea-project/GenAIComps.git"
+        find . -type f -name "Dockerfile*" | while read -r file; do
+            echo "Processing file: $file"
+            sed -i "s|$OLD_STRING|$NEW_STRING|g" "$file"
+        done
+    fi
+
     cd $WORKPATH/docker_image_build
     git clone --depth 1 --branch ${opea_branch} https://github.com/opea-project/GenAIComps.git
     pushd GenAIComps
     docker build --no-cache -t ${REGISTRY}/comps-base:${TAG} --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile .
     popd && sleep 1s
 
+    git clone https://github.com/HabanaAI/vllm-fork.git && cd vllm-fork
+    VLLM_VER=$(git describe --tags "$(git rev-list --tags --max-count=1)")
+    git checkout ${VLLM_VER} &> /dev/null && cd ../
+
     echo "Build all the images with --no-cache, check docker_image_build.log for details..."
-    service_list="docsum docsum-gradio-ui whisper llm-docsum"
+    service_list="docsum docsum-gradio-ui whisper llm-docsum vllm-gaudi"
     docker compose -f build.yaml build ${service_list} --no-cache > ${LOG_PATH}/docker_image_build.log
 
-    docker pull ghcr.io/huggingface/tgi-gaudi:2.3.1
     docker images && sleep 1s
 }
 
@@ -84,115 +104,95 @@ input_data_for_test() {
     esac
 }
 
-function validate_services_json() {
+function validate_service() {
     local URL="$1"
     local EXPECTED_RESULT="$2"
     local SERVICE_NAME="$3"
     local DOCKER_NAME="$4"
-    local INPUT_DATA="$5"
-
-    local HTTP_STATUS=$(curl -s -o /dev/null -w "%{http_code}" -X POST -d "$INPUT_DATA" -H 'Content-Type: application/json' "$URL")
-
-    echo "==========================================="
-
-    if [ "$HTTP_STATUS" -eq 200 ]; then
-        echo "[ $SERVICE_NAME ] HTTP status is 200. Checking content..."
-
-        local CONTENT=$(curl -s -X POST -d "$INPUT_DATA" -H 'Content-Type: application/json' "$URL" | tee ${LOG_PATH}/${SERVICE_NAME}.log)
-
-        if echo "$CONTENT" | grep -q "$EXPECTED_RESULT"; then
-            echo "[ $SERVICE_NAME ] Content is as expected."
-        else
-            echo "[ $SERVICE_NAME ] Content does not match the expected result: $CONTENT"
-            docker logs ${DOCKER_NAME} >> ${LOG_PATH}/${SERVICE_NAME}.log
-            exit 1
-        fi
+    local VALIDATE_TYPE="$5"
+    local INPUT_DATA="$6"
+    local FORM_DATA1="$7"
+    local FORM_DATA2="$8"
+    local FORM_DATA3="$9"
+    local FORM_DATA4="${10}"
+    local FORM_DATA5="${11}"
+    local FORM_DATA6="${12}"
+
+    if [[ $VALIDATE_TYPE == *"json"* ]]; then
+        HTTP_RESPONSE=$(curl --silent --write-out "HTTPSTATUS:%{http_code}" -X POST -d "$INPUT_DATA" -H 'Content-Type: application/json' "$URL")
     else
-        echo "[ $SERVICE_NAME ] HTTP status is not 200. Received status was $HTTP_STATUS"
-        docker logs ${DOCKER_NAME} >> ${LOG_PATH}/${SERVICE_NAME}.log
-        exit 1
+        CURL_CMD=(curl --silent --write-out "HTTPSTATUS:%{http_code}" -X POST -F "$FORM_DATA1" -F "$FORM_DATA2" -F "$FORM_DATA3" -F "$FORM_DATA4" -F "$FORM_DATA5" -H 'Content-Type: multipart/form-data' "$URL")
+        if [[ -n "$FORM_DATA6" ]]; then
+            CURL_CMD+=(-F "$FORM_DATA6")
+        fi
+        HTTP_RESPONSE=$("${CURL_CMD[@]}")
     fi
-    sleep 1s
-}
-
-function validate_services_form() {
-    local URL="$1"
-    local EXPECTED_RESULT="$2"
-    local SERVICE_NAME="$3"
-    local DOCKER_NAME="$4"
-    local FORM_DATA1="$5"
-    local FORM_DATA2="$6"
-    local FORM_DATA3="$7"
-    local FORM_DATA4="$8"
-    local FORM_DATA5="$9"
-
-    local HTTP_STATUS=$(curl -s -o /dev/null -w "%{http_code}" -X POST -F "$FORM_DATA1" -F "$FORM_DATA2" -F "$FORM_DATA3" -F "$FORM_DATA4" -F "$FORM_DATA5" -H 'Content-Type: multipart/form-data' "$URL")
-
-    if [ "$HTTP_STATUS" -eq 200 ]; then
-        echo "[ $SERVICE_NAME ] HTTP status is 200. Checking content..."
+    HTTP_STATUS=$(echo $HTTP_RESPONSE | tr -d '\n' | sed -e 's/.*HTTPSTATUS://')
+    RESPONSE_BODY=$(echo $HTTP_RESPONSE | sed -e 's/HTTPSTATUS\:.*//g')
 
-        local CONTENT=$(curl -s -X POST -F "$FORM_DATA1" -F "$FORM_DATA2" -F "$FORM_DATA3" -F "$FORM_DATA4" -F "$FORM_DATA5" -H 'Content-Type: multipart/form-data' "$URL" | tee ${LOG_PATH}/${SERVICE_NAME}.log)
+    docker logs ${DOCKER_NAME} >> ${LOG_PATH}/${SERVICE_NAME}.log
 
-        if echo "$CONTENT" | grep -q "$EXPECTED_RESULT"; then
-            echo "[ $SERVICE_NAME ] Content is as expected."
-        else
-            echo "[ $SERVICE_NAME ] Content does not match the expected result: $CONTENT"
-            docker logs ${DOCKER_NAME} >> ${LOG_PATH}/${SERVICE_NAME}.log
-            exit 1
-        fi
-    else
+    # check response status
+    if [ "$HTTP_STATUS" -ne "200" ]; then
         echo "[ $SERVICE_NAME ] HTTP status is not 200. Received status was $HTTP_STATUS"
-        docker logs ${DOCKER_NAME} >> ${LOG_PATH}/${SERVICE_NAME}.log
         exit 1
+    else
+        echo "[ $SERVICE_NAME ] HTTP status is 200. Checking content..."
     fi
+    # check response body
+    if [[ "$RESPONSE_BODY" != *"$EXPECTED_RESULT"* ]]; then
+        echo "EXPECTED_RESULT==> $EXPECTED_RESULT"
+        echo "RESPONSE_BODY==> $RESPONSE_BODY"
+        echo "[ $SERVICE_NAME ] Content does not match the expected result: $RESPONSE_BODY"
+        exit 1
+    else
+        echo "[ $SERVICE_NAME ] Content is as expected."
+    fi
+
     sleep 1s
 }
 
 function validate_microservices() {
     # Check if the microservices are running correctly.
 
-    # tgi for llm service
-    validate_services_json \
-        "${host_ip}:8008/generate" \
-        "generated_text" \
-        "tgi-gaudi-server" \
-        "tgi-gaudi-server" \
-        '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":17, "do_sample": true}}'
-
     # llm microservice
-    validate_services_json \
-        "${host_ip}:9000/v1/docsum" \
+    validate_service \
+        "${host_ip}:${LLM_PORT}/v1/docsum" \
         "text" \
-        "llm-docsum-tgi" \
-        "llm-docsum-gaudi-server" \
+        "llm-docsum-vllm" \
+        "docsum-gaudi-llm-server" \
+        "json" \
         '{"messages":"Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for the most popular models, including FlagEmbedding, Ember, GTE and E5."}'
 
     # whisper microservice
     ulimit -s 65536
-    validate_services_json \
+    validate_service \
         "${host_ip}:7066/v1/asr" \
         '{"asr_result":"well"}' \
         "whisper" \
-        "whisper-server" \
+        "docsum-gaudi-whisper-server" \
+        "json" \
         "{\"audio\": \"$(input_data_for_test "audio")\"}"
 
 }
 
 function validate_megaservice_text() {
     echo ">>> Checking text data in json format"
-    validate_services_json \
-        "${host_ip}:8888/v1/docsum" \
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
         "[DONE]" \
         "docsum-gaudi-backend-server" \
         "docsum-gaudi-backend-server" \
+        "json" \
         '{"type": "text", "messages": "Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for the most popular models, including FlagEmbedding, Ember, GTE and E5."}'
 
     echo ">>> Checking text data in form format, set language=en"
-    validate_services_form \
-        "${host_ip}:8888/v1/docsum" \
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
         "[DONE]" \
         "docsum-gaudi-backend-server" \
         "docsum-gaudi-backend-server" \
+        "media" "" \
         "type=text" \
         "messages=Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for the most popular models, including FlagEmbedding, Ember, GTE and E5." \
         "max_tokens=32" \
@@ -200,11 +200,12 @@ function validate_megaservice_text() {
         "stream=True"
 
     echo ">>> Checking text data in form format, set language=zh"
-    validate_services_form \
-        "${host_ip}:8888/v1/docsum" \
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
         "[DONE]" \
         "docsum-gaudi-backend-server" \
         "docsum-gaudi-backend-server" \
+        "media" "" \
         "type=text" \
         "messages=2024年9月26日，北京——今日，英特尔正式发布英特尔® 至强® 6性能核处理器（代号Granite Rapids），为AI、数据分析、科学计算等计算密集型业务提供卓越性能。" \
         "max_tokens=32" \
@@ -212,125 +213,141 @@ function validate_megaservice_text() {
         "stream=True"
 
     echo ">>> Checking text data in form format, upload file"
-    validate_services_form \
-        "${host_ip}:8888/v1/docsum" \
-        "[DONE]" \
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "TEI" \
         "docsum-gaudi-backend-server" \
         "docsum-gaudi-backend-server" \
+        "media" "" \
         "type=text" \
         "messages=" \
         "files=@$ROOT_FOLDER/data/short.txt" \
         "max_tokens=32" \
-        "language=en"
+        "language=en" \
+        "stream=False"
 }
 
 function validate_megaservice_multimedia() {
     echo ">>> Checking audio data in json format"
-    validate_services_json \
-        "${host_ip}:8888/v1/docsum" \
-        "[DONE]" \
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "well" \
         "docsum-gaudi-backend-server" \
         "docsum-gaudi-backend-server" \
-        "{\"type\": \"audio\",  \"messages\": \"$(input_data_for_test "audio")\"}"
+        "json" \
+        "{\"type\": \"audio\",  \"messages\": \"$(input_data_for_test "audio")\", \"stream\": \"False\"}"
 
     echo ">>> Checking audio data in form format"
-    validate_services_form \
-        "${host_ip}:8888/v1/docsum" \
-        "[DONE]" \
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "you" \
         "docsum-gaudi-backend-server" \
         "docsum-gaudi-backend-server" \
+        "media" "" \
         "type=audio" \
         "messages=UklGRigAAABXQVZFZm10IBIAAAABAAEARKwAAIhYAQACABAAAABkYXRhAgAAAAEA" \
         "max_tokens=32" \
         "language=en" \
-        "stream=True"
+        "stream=False"
 
     echo ">>> Checking video data in json format"
-    validate_services_json \
-        "${host_ip}:8888/v1/docsum" \
-        "[DONE]" \
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "bye" \
         "docsum-gaudi-backend-server" \
         "docsum-gaudi-backend-server" \
-        "{\"type\": \"video\",  \"messages\": \"$(input_data_for_test "video")\"}"
+        "json" \
+        "{\"type\": \"video\",  \"messages\": \"$(input_data_for_test "video")\", \"stream\": \"False\"}"
 
     echo ">>> Checking video data in form format"
-    validate_services_form \
-        "${host_ip}:8888/v1/docsum" \
-        "[DONE]" \
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "bye" \
         "docsum-gaudi-backend-server" \
         "docsum-gaudi-backend-server" \
+        "media" "" \
         "type=video" \
         "messages=\"$(input_data_for_test "video")\"" \
         "max_tokens=32" \
         "language=en" \
-        "stream=True"
+        "stream=False"
 }
 
 function validate_megaservice_long_text() {
     echo ">>> Checking long text data in form format, set summary_type=auto"
-    validate_services_form \
-        "${host_ip}:8888/v1/docsum" \
-        "[DONE]" \
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "Intel" \
         "docsum-gaudi-backend-server" \
         "docsum-gaudi-backend-server" \
+        "media" "" \
         "type=text" \
         "messages=" \
         "files=@$ROOT_FOLDER/data/long.txt" \
         "max_tokens=128" \
-        "summary_type=auto"
+        "summary_type=auto" \
+        "stream=False"
 
     echo ">>> Checking long text data in form format, set summary_type=stuff"
-    validate_services_form \
-        "${host_ip}:8888/v1/docsum" \
-        "[DONE]" \
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "TEI" \
         "docsum-gaudi-backend-server" \
         "docsum-gaudi-backend-server" \
+        "media" "" \
         "type=text" \
         "messages=" \
-        "files=@$ROOT_FOLDER/data/long.txt" \
+        "files=@$ROOT_FOLDER/data/short.txt" \
         "max_tokens=128" \
-        "summary_type=stuff"
+        "summary_type=stuff" \
+        "stream=False"
 
     echo ">>> Checking long text data in form format, set summary_type=truncate"
-    validate_services_form \
-        "${host_ip}:8888/v1/docsum" \
-        "[DONE]" \
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "Intel" \
         "docsum-gaudi-backend-server" \
         "docsum-gaudi-backend-server" \
+        "media" "" \
         "type=text" \
         "messages=" \
         "files=@$ROOT_FOLDER/data/long.txt" \
         "max_tokens=128" \
-        "summary_type=truncate"
+        "summary_type=truncate" \
+        "stream=False"
 
     echo ">>> Checking long text data in form format, set summary_type=map_reduce"
-    validate_services_form \
-        "${host_ip}:8888/v1/docsum" \
-        "[DONE]" \
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "Intel" \
         "docsum-gaudi-backend-server" \
         "docsum-gaudi-backend-server" \
+        "media" "" \
         "type=text" \
         "messages=" \
         "files=@$ROOT_FOLDER/data/long.txt" \
         "max_tokens=128" \
-        "summary_type=map_reduce"
+        "summary_type=map_reduce" \
+        "stream=False"
 
     echo ">>> Checking long text data in form format, set summary_type=refine"
-    validate_services_form \
-        "${host_ip}:8888/v1/docsum" \
-        "[DONE]" \
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "Intel" \
         "docsum-gaudi-backend-server" \
         "docsum-gaudi-backend-server" \
+        "media" "" \
         "type=text" \
         "messages=" \
         "files=@$ROOT_FOLDER/data/long.txt" \
         "max_tokens=128" \
-        "summary_type=refine"
+        "summary_type=refine" \
+        "stream=False"
 }
 
 function stop_docker() {
     cd $WORKPATH/docker_compose/intel/hpu/gaudi
-    docker compose stop && docker compose rm -f
+    docker compose -f compose.yaml stop && docker compose rm -f
 }
 
 function main() {
diff --git a/DocSum/tests/test_compose_on_xeon.sh b/DocSum/tests/test_compose_on_xeon.sh
index c813da75d4..090084047e 100644
--- a/DocSum/tests/test_compose_on_xeon.sh
+++ b/DocSum/tests/test_compose_on_xeon.sh
@@ -12,22 +12,24 @@ export host_ip=$(hostname -I | awk '{print $1}')
 
 echo "REGISTRY=IMAGE_REPO=${IMAGE_REPO}"
 echo "TAG=IMAGE_TAG=${IMAGE_TAG}"
+export no_proxy="${no_proxy},${host_ip}"
 export MODEL_CACHE=${model_cache:-"./data"}
 export REGISTRY=${IMAGE_REPO}
 export TAG=${IMAGE_TAG}
+export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
+export LLM_ENDPOINT_PORT=8008
+export LLM_MODEL_ID="Intel/neural-chat-7b-v3-3"
 export MAX_INPUT_TOKENS=2048
 export MAX_TOTAL_TOKENS=4096
-export LLM_MODEL_ID="Intel/neural-chat-7b-v3-3"
-export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
+export LLM_PORT=9000
+export LLM_ENDPOINT="http://${host_ip}:${LLM_ENDPOINT_PORT}"
+export DocSum_COMPONENT_NAME="OpeaDocSumvLLM"
 export MEGA_SERVICE_HOST_IP=${host_ip}
 export LLM_SERVICE_HOST_IP=${host_ip}
 export ASR_SERVICE_HOST_IP=${host_ip}
-export BACKEND_SERVICE_ENDPOINT="http://${host_ip}:8888/v1/docsum"
-export no_proxy="${no_proxy},${host_ip}"
-export LLM_ENDPOINT_PORT=8008
-export DOCSUM_PORT=9000
-export LLM_ENDPOINT="http://${host_ip}:${LLM_ENDPOINT_PORT}"
-export DocSum_COMPONENT_NAME="OpeaDocSumTgi"
+export FRONTEND_SERVICE_PORT=5173
+export BACKEND_SERVICE_PORT=8888
+export BACKEND_SERVICE_ENDPOINT="http://${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum"
 export LOGFLAG=True
 
 WORKPATH=$(dirname "$PWD")
@@ -38,17 +40,33 @@ ROOT_FOLDER=$(dirname "$(readlink -f "$0")")
 
 function build_docker_images() {
     opea_branch=${opea_branch:-"main"}
+    # If the opea_branch isn't main, replace the git clone branch in Dockerfile.
+    if [[ "${opea_branch}" != "main" ]]; then
+        cd $WORKPATH
+        OLD_STRING="RUN git clone --depth 1 https://github.com/opea-project/GenAIComps.git"
+        NEW_STRING="RUN git clone --depth 1 --branch ${opea_branch} https://github.com/opea-project/GenAIComps.git"
+        find . -type f -name "Dockerfile*" | while read -r file; do
+            echo "Processing file: $file"
+            sed -i "s|$OLD_STRING|$NEW_STRING|g" "$file"
+        done
+    fi
+
     cd $WORKPATH/docker_image_build
     git clone --depth 1 --branch ${opea_branch} https://github.com/opea-project/GenAIComps.git
     pushd GenAIComps
     docker build --no-cache -t ${REGISTRY}/comps-base:${TAG} --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile .
     popd && sleep 1s
 
+    git clone https://github.com/vllm-project/vllm.git && cd vllm
+    VLLM_VER="$(git describe --tags "$(git rev-list --tags --max-count=1)" )"
+    echo "Check out vLLM tag ${VLLM_VER}"
+    git checkout ${VLLM_VER} &> /dev/null
+    cd ../
+
     echo "Build all the images with --no-cache, check docker_image_build.log for details..."
-    service_list="docsum docsum-gradio-ui whisper llm-docsum"
+    service_list="docsum docsum-gradio-ui whisper llm-docsum vllm"
     docker compose -f build.yaml build ${service_list} --no-cache > ${LOG_PATH}/docker_image_build.log
 
-    docker pull ghcr.io/huggingface/text-generation-inference:1.4
     docker images && sleep 1s
 }
 
@@ -83,118 +101,95 @@ input_data_for_test() {
     esac
 }
 
-function validate_services_json() {
+function validate_service() {
     local URL="$1"
     local EXPECTED_RESULT="$2"
     local SERVICE_NAME="$3"
     local DOCKER_NAME="$4"
-    local INPUT_DATA="$5"
-
-    local HTTP_STATUS=$(curl -s -o /dev/null -w "%{http_code}" -X POST -d "$INPUT_DATA" -H 'Content-Type: application/json' "$URL")
-
-    echo "==========================================="
-
-    if [ "$HTTP_STATUS" -eq 200 ]; then
-        echo "[ $SERVICE_NAME ] HTTP status is 200. Checking content..."
-
-        local CONTENT=$(curl -s -X POST -d "$INPUT_DATA" -H 'Content-Type: application/json' "$URL" | tee ${LOG_PATH}/${SERVICE_NAME}.log)
-
-        if echo "$CONTENT" | grep -q "$EXPECTED_RESULT"; then
-            echo "[ $SERVICE_NAME ] Content is as expected."
-        else
-            echo "EXPECTED_RESULT==> $EXPECTED_RESULT"
-            echo "CONTENT==> $CONTENT"
-            echo "[ $SERVICE_NAME ] Content does not match the expected result: $CONTENT"
-            docker logs ${DOCKER_NAME} >> ${LOG_PATH}/${SERVICE_NAME}.log
-            exit 1
-
-        fi
+    local VALIDATE_TYPE="$5"
+    local INPUT_DATA="$6"
+    local FORM_DATA1="$7"
+    local FORM_DATA2="$8"
+    local FORM_DATA3="$9"
+    local FORM_DATA4="${10}"
+    local FORM_DATA5="${11}"
+    local FORM_DATA6="${12}"
+
+    if [[ $VALIDATE_TYPE == *"json"* ]]; then
+        HTTP_RESPONSE=$(curl --silent --write-out "HTTPSTATUS:%{http_code}" -X POST -d "$INPUT_DATA" -H 'Content-Type: application/json' "$URL")
     else
-        echo "[ $SERVICE_NAME ] HTTP status is not 200. Received status was $HTTP_STATUS"
-        docker logs ${DOCKER_NAME} >> ${LOG_PATH}/${SERVICE_NAME}.log
-        exit 1
+        CURL_CMD=(curl --silent --write-out "HTTPSTATUS:%{http_code}" -X POST -F "$FORM_DATA1" -F "$FORM_DATA2" -F "$FORM_DATA3" -F "$FORM_DATA4" -F "$FORM_DATA5" -H 'Content-Type: multipart/form-data' "$URL")
+        if [[ -n "$FORM_DATA6" ]]; then
+            CURL_CMD+=(-F "$FORM_DATA6")
+        fi
+        HTTP_RESPONSE=$("${CURL_CMD[@]}")
     fi
-    sleep 1s
-}
+    HTTP_STATUS=$(echo $HTTP_RESPONSE | tr -d '\n' | sed -e 's/.*HTTPSTATUS://')
+    RESPONSE_BODY=$(echo $HTTP_RESPONSE | sed -e 's/HTTPSTATUS\:.*//g')
 
-function validate_services_form() {
-    local URL="$1"
-    local EXPECTED_RESULT="$2"
-    local SERVICE_NAME="$3"
-    local DOCKER_NAME="$4"
-    local FORM_DATA1="$5"
-    local FORM_DATA2="$6"
-    local FORM_DATA3="$7"
-    local FORM_DATA4="$8"
-    local FORM_DATA5="$9"
-
-    local HTTP_STATUS=$(curl -s -o /dev/null -w "%{http_code}" -X POST -F "$FORM_DATA1" -F "$FORM_DATA2" -F "$FORM_DATA3" -F "$FORM_DATA4" -F "$FORM_DATA5" -H 'Content-Type: multipart/form-data' "$URL")
-
-    if [ "$HTTP_STATUS" -eq 200 ]; then
-        echo "[ $SERVICE_NAME ] HTTP status is 200. Checking content..."
+    docker logs ${DOCKER_NAME} >> ${LOG_PATH}/${SERVICE_NAME}.log
 
-        local CONTENT=$(curl -s -X POST -F "$FORM_DATA1" -F "$FORM_DATA2" -F "$FORM_DATA3" -F "$FORM_DATA4" -F "$FORM_DATA5" -H 'Content-Type: multipart/form-data' "$URL" | tee ${LOG_PATH}/${SERVICE_NAME}.log)
-
-        if echo "$CONTENT" | grep -q "$EXPECTED_RESULT"; then
-            echo "[ $SERVICE_NAME ] Content is as expected."
-        else
-            echo "[ $SERVICE_NAME ] Content does not match the expected result: $CONTENT"
-            docker logs ${DOCKER_NAME} >> ${LOG_PATH}/${SERVICE_NAME}.log
-            exit 1
-        fi
-    else
+    # check response status
+    if [ "$HTTP_STATUS" -ne "200" ]; then
         echo "[ $SERVICE_NAME ] HTTP status is not 200. Received status was $HTTP_STATUS"
-        docker logs ${DOCKER_NAME} >> ${LOG_PATH}/${SERVICE_NAME}.log
         exit 1
+    else
+        echo "[ $SERVICE_NAME ] HTTP status is 200. Checking content..."
     fi
+    # check response body
+    if [[ "$RESPONSE_BODY" != *"$EXPECTED_RESULT"* ]]; then
+        echo "EXPECTED_RESULT==> $EXPECTED_RESULT"
+        echo "RESPONSE_BODY==> $RESPONSE_BODY"
+        echo "[ $SERVICE_NAME ] Content does not match the expected result: $RESPONSE_BODY"
+        exit 1
+    else
+        echo "[ $SERVICE_NAME ] Content is as expected."
+    fi
+
     sleep 1s
 }
 
 function validate_microservices() {
     # Check if the microservices are running correctly.
 
-    # tgi for llm service
-    validate_services_json \
-        "${host_ip}:8008/generate" \
-        "generated_text" \
-        "tgi-server" \
-        "tgi-server" \
-        '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":17, "do_sample": true}}'
-
     # llm microservice
-    validate_services_json \
-        "${host_ip}:9000/v1/docsum" \
+    validate_service \
+        "${host_ip}:${LLM_PORT}/v1/docsum" \
         "text" \
-        "llm-docsum-tgi" \
-        "llm-docsum-server" \
+        "llm-docsum-vllm" \
+        "docsum-xeon-llm-server" \
+        "json" \
         '{"messages":"Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for the most popular models, including FlagEmbedding, Ember, GTE and E5."}'
 
     # whisper microservice
     ulimit -s 65536
-    validate_services_json \
+    validate_service \
         "${host_ip}:7066/v1/asr" \
         '{"asr_result":"well"}' \
         "whisper" \
-        "whisper-server" \
+        "docsum-xeon-whisper-server" \
+        "json" \
         "{\"audio\": \"$(input_data_for_test "audio")\"}"
 
 }
 
 function validate_megaservice_text() {
     echo ">>> Checking text data in json format"
-    validate_services_json \
-        "${host_ip}:8888/v1/docsum" \
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
         "[DONE]" \
         "docsum-xeon-backend-server" \
         "docsum-xeon-backend-server" \
+        "json" \
         '{"type": "text", "messages": "Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for the most popular models, including FlagEmbedding, Ember, GTE and E5."}'
 
     echo ">>> Checking text data in form format, set language=en"
-    validate_services_form \
-        "${host_ip}:8888/v1/docsum" \
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
         "[DONE]" \
         "docsum-xeon-backend-server" \
         "docsum-xeon-backend-server" \
+        "media" "" \
         "type=text" \
         "messages=Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for the most popular models, including FlagEmbedding, Ember, GTE and E5." \
         "max_tokens=32" \
@@ -202,11 +197,12 @@ function validate_megaservice_text() {
         "stream=True"
 
     echo ">>> Checking text data in form format, set language=zh"
-    validate_services_form \
-        "${host_ip}:8888/v1/docsum" \
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
         "[DONE]" \
         "docsum-xeon-backend-server" \
         "docsum-xeon-backend-server" \
+        "media" "" \
         "type=text" \
         "messages=2024年9月26日，北京——今日，英特尔正式发布英特尔® 至强® 6性能核处理器（代号Granite Rapids），为AI、数据分析、科学计算等计算密集型业务提供卓越性能。" \
         "max_tokens=32" \
@@ -214,120 +210,136 @@ function validate_megaservice_text() {
         "stream=True"
 
     echo ">>> Checking text data in form format, upload file"
-    validate_services_form \
-        "${host_ip}:8888/v1/docsum" \
-        "[DONE]" \
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "TEI" \
         "docsum-xeon-backend-server" \
         "docsum-xeon-backend-server" \
+        "media" "" \
         "type=text" \
         "messages=" \
         "files=@$ROOT_FOLDER/data/short.txt" \
         "max_tokens=32" \
-        "language=en"
+        "language=en" \
+        "stream=False"
 }
 
 function validate_megaservice_multimedia() {
     echo ">>> Checking audio data in json format"
-    validate_services_json \
-        "${host_ip}:8888/v1/docsum" \
-        "[DONE]" \
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "well" \
         "docsum-xeon-backend-server" \
         "docsum-xeon-backend-server" \
-        "{\"type\": \"audio\",  \"messages\": \"$(input_data_for_test "audio")\"}"
+        "json" \
+        "{\"type\": \"audio\",  \"messages\": \"$(input_data_for_test "audio")\", \"stream\": \"False\"}"
 
     echo ">>> Checking audio data in form format"
-    validate_services_form \
-        "${host_ip}:8888/v1/docsum" \
-        "[DONE]" \
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "you" \
         "docsum-xeon-backend-server" \
         "docsum-xeon-backend-server" \
+        "media" "" \
         "type=audio" \
         "messages=UklGRigAAABXQVZFZm10IBIAAAABAAEARKwAAIhYAQACABAAAABkYXRhAgAAAAEA" \
         "max_tokens=32" \
         "language=en" \
-        "stream=True"
+        "stream=False"
 
     echo ">>> Checking video data in json format"
-    validate_services_json \
-        "${host_ip}:8888/v1/docsum" \
-        "[DONE]" \
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "bye" \
         "docsum-xeon-backend-server" \
         "docsum-xeon-backend-server" \
-        "{\"type\": \"video\",  \"messages\": \"$(input_data_for_test "video")\"}"
+        "json" \
+        "{\"type\": \"video\",  \"messages\": \"$(input_data_for_test "video")\", \"stream\": \"False\"}"
 
     echo ">>> Checking video data in form format"
-    validate_services_form \
-        "${host_ip}:8888/v1/docsum" \
-        "[DONE]" \
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "bye" \
         "docsum-xeon-backend-server" \
         "docsum-xeon-backend-server" \
+        "media" "" \
         "type=video" \
         "messages=\"$(input_data_for_test "video")\"" \
         "max_tokens=32" \
         "language=en" \
-        "stream=True"
+        "stream=False"
 }
 
 function validate_megaservice_long_text() {
     echo ">>> Checking long text data in form format, set summary_type=auto"
-    validate_services_form \
-        "${host_ip}:8888/v1/docsum" \
-        "[DONE]" \
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "Intel" \
         "docsum-xeon-backend-server" \
         "docsum-xeon-backend-server" \
+        "media" "" \
         "type=text" \
         "messages=" \
         "files=@$ROOT_FOLDER/data/long.txt" \
         "max_tokens=128" \
-        "summary_type=auto"
+        "summary_type=auto" \
+        "stream=False"
 
     echo ">>> Checking long text data in form format, set summary_type=stuff"
-    validate_services_form \
-        "${host_ip}:8888/v1/docsum" \
-        "[DONE]" \
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "TEI" \
         "docsum-xeon-backend-server" \
         "docsum-xeon-backend-server" \
+        "media" "" \
         "type=text" \
         "messages=" \
-        "files=@$ROOT_FOLDER/data/long.txt" \
+        "files=@$ROOT_FOLDER/data/short.txt" \
         "max_tokens=128" \
-        "summary_type=stuff"
+        "summary_type=stuff" \
+        "stream=False"
 
     echo ">>> Checking long text data in form format, set summary_type=truncate"
-    validate_services_form \
-        "${host_ip}:8888/v1/docsum" \
-        "[DONE]" \
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "Intel" \
         "docsum-xeon-backend-server" \
         "docsum-xeon-backend-server" \
+        "media" "" \
         "type=text" \
         "messages=" \
         "files=@$ROOT_FOLDER/data/long.txt" \
         "max_tokens=128" \
-        "summary_type=truncate"
+        "summary_type=truncate" \
+        "stream=False"
 
     echo ">>> Checking long text data in form format, set summary_type=map_reduce"
-    validate_services_form \
-        "${host_ip}:8888/v1/docsum" \
-        "[DONE]" \
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "Intel" \
         "docsum-xeon-backend-server" \
         "docsum-xeon-backend-server" \
+        "media" "" \
         "type=text" \
         "messages=" \
         "files=@$ROOT_FOLDER/data/long.txt" \
         "max_tokens=128" \
-        "summary_type=map_reduce"
+        "summary_type=map_reduce" \
+        "stream=False"
 
     echo ">>> Checking long text data in form format, set summary_type=refine"
-    validate_services_form \
-        "${host_ip}:8888/v1/docsum" \
-        "[DONE]" \
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "Intel" \
         "docsum-xeon-backend-server" \
         "docsum-xeon-backend-server" \
+        "media" "" \
         "type=text" \
         "messages=" \
         "files=@$ROOT_FOLDER/data/long.txt" \
         "max_tokens=128" \
-        "summary_type=refine"
+        "summary_type=refine" \
+        "stream=False"
 }
 
 function stop_docker() {
diff --git a/DocSum/tests/test_compose_tgi_on_gaudi.sh b/DocSum/tests/test_compose_tgi_on_gaudi.sh
new file mode 100644
index 0000000000..3f21cdee82
--- /dev/null
+++ b/DocSum/tests/test_compose_tgi_on_gaudi.sh
@@ -0,0 +1,386 @@
+#!/bin/bash
+# Copyright (C) 2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+set -xe
+
+IMAGE_REPO=${IMAGE_REPO:-"opea"}
+IMAGE_TAG=${IMAGE_TAG:-"latest"}
+export http_proxy=$http_proxy
+export https_proxy=$https_proxy
+export host_ip=$(hostname -I | awk '{print $1}')
+
+echo "REGISTRY=IMAGE_REPO=${IMAGE_REPO}"
+echo "TAG=IMAGE_TAG=${IMAGE_TAG}"
+export no_proxy="${no_proxy},${host_ip}"
+export MODEL_CACHE=${model_cache:-"./data"}
+export REGISTRY=${IMAGE_REPO}
+export TAG=${IMAGE_TAG}
+export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
+export LLM_ENDPOINT_PORT=8008
+export LLM_MODEL_ID="Intel/neural-chat-7b-v3-3"
+export MAX_INPUT_TOKENS=2048
+export MAX_TOTAL_TOKENS=4096
+export LLM_PORT=9000
+export LLM_ENDPOINT="http://${host_ip}:${LLM_ENDPOINT_PORT}"
+export DocSum_COMPONENT_NAME="OpeaDocSumTgi"
+export MEGA_SERVICE_HOST_IP=${host_ip}
+export LLM_SERVICE_HOST_IP=${host_ip}
+export ASR_SERVICE_HOST_IP=${host_ip}
+export FRONTEND_SERVICE_PORT=5173
+export BACKEND_SERVICE_PORT=8888
+export BACKEND_SERVICE_ENDPOINT="http://${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum"
+export LOGFLAG=True
+
+WORKPATH=$(dirname "$PWD")
+LOG_PATH="$WORKPATH/tests"
+
+
+# Get the root folder of the current script
+ROOT_FOLDER=$(dirname "$(readlink -f "$0")")
+
+function build_docker_images() {
+    opea_branch=${opea_branch:-"main"}
+    cd $WORKPATH/docker_image_build
+    git clone --depth 1 --branch ${opea_branch} https://github.com/opea-project/GenAIComps.git
+    pushd GenAIComps
+    docker build --no-cache -t ${REGISTRY}/comps-base:${TAG} --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile .
+    popd && sleep 1s
+
+    echo "Build all the images with --no-cache, check docker_image_build.log for details..."
+    service_list="docsum docsum-gradio-ui whisper llm-docsum"
+    docker compose -f build.yaml build ${service_list} --no-cache > ${LOG_PATH}/docker_image_build.log
+
+    docker pull ghcr.io/huggingface/tgi-gaudi:2.3.1
+    docker images && sleep 1s
+}
+
+function start_services() {
+    cd $WORKPATH/docker_compose/intel/hpu/gaudi
+    docker compose -f compose_tgi.yaml up -d > ${LOG_PATH}/start_services_with_compose.log
+    sleep 1m
+}
+
+get_base64_str() {
+    local file_name=$1
+    base64 -w 0 "$file_name"
+}
+
+# Function to generate input data for testing based on the document type
+input_data_for_test() {
+    local document_type=$1
+    case $document_type in
+        ("text")
+            echo "THIS IS A TEST >>>> and a number of states are starting to adopt them voluntarily special correspondent john delenco of education week reports it takes just 10 minutes to cross through gillette wyoming this small city sits in the northeast corner of the state surrounded by 100s of miles of prairie but schools here in campbell county are on the edge of something big the next generation science standards you are going to build a strand of dna and you are going to decode it and figure out what that dna actually says for christy mathis at sage valley junior high school the new standards are about learning to think like a scientist there is a lot of really good stuff in them every standard is a performance task it is not you know the child needs to memorize these things it is the student needs to be able to do some pretty intense stuff we are analyzing we are critiquing we are."
+            ;;
+        ("audio")
+            get_base64_str "$ROOT_FOLDER/data/test.wav"
+            ;;
+        ("video")
+            get_base64_str "$ROOT_FOLDER/data/test.mp4"
+            ;;
+        (*)
+            echo "Invalid document type" >&2
+            exit 1
+            ;;
+    esac
+}
+
+function validate_service() {
+    local URL="$1"
+    local EXPECTED_RESULT="$2"
+    local SERVICE_NAME="$3"
+    local DOCKER_NAME="$4"
+    local VALIDATE_TYPE="$5"
+    local INPUT_DATA="$6"
+    local FORM_DATA1="$7"
+    local FORM_DATA2="$8"
+    local FORM_DATA3="$9"
+    local FORM_DATA4="${10}"
+    local FORM_DATA5="${11}"
+    local FORM_DATA6="${12}"
+
+    if [[ $VALIDATE_TYPE == *"json"* ]]; then
+        HTTP_RESPONSE=$(curl --silent --write-out "HTTPSTATUS:%{http_code}" -X POST -d "$INPUT_DATA" -H 'Content-Type: application/json' "$URL")
+    else
+        CURL_CMD=(curl --silent --write-out "HTTPSTATUS:%{http_code}" -X POST -F "$FORM_DATA1" -F "$FORM_DATA2" -F "$FORM_DATA3" -F "$FORM_DATA4" -F "$FORM_DATA5" -H 'Content-Type: multipart/form-data' "$URL")
+        if [[ -n "$FORM_DATA6" ]]; then
+            CURL_CMD+=(-F "$FORM_DATA6")
+        fi
+        HTTP_RESPONSE=$("${CURL_CMD[@]}")
+    fi
+    HTTP_STATUS=$(echo $HTTP_RESPONSE | tr -d '\n' | sed -e 's/.*HTTPSTATUS://')
+    RESPONSE_BODY=$(echo $HTTP_RESPONSE | sed -e 's/HTTPSTATUS\:.*//g')
+
+    docker logs ${DOCKER_NAME} >> ${LOG_PATH}/${SERVICE_NAME}.log
+
+    # check response status
+    if [ "$HTTP_STATUS" -ne "200" ]; then
+        echo "[ $SERVICE_NAME ] HTTP status is not 200. Received status was $HTTP_STATUS"
+        exit 1
+    else
+        echo "[ $SERVICE_NAME ] HTTP status is 200. Checking content..."
+    fi
+    # check response body
+    if [[ "$RESPONSE_BODY" != *"$EXPECTED_RESULT"* ]]; then
+        echo "EXPECTED_RESULT==> $EXPECTED_RESULT"
+        echo "RESPONSE_BODY==> $RESPONSE_BODY"
+        echo "[ $SERVICE_NAME ] Content does not match the expected result: $RESPONSE_BODY"
+        exit 1
+    else
+        echo "[ $SERVICE_NAME ] Content is as expected."
+    fi
+
+    sleep 1s
+}
+
+function validate_microservices() {
+    # Check if the microservices are running correctly.
+
+    # tgi for llm service
+    validate_service \
+        "${host_ip}:${LLM_ENDPOINT_PORT}/generate" \
+        "generated_text" \
+        "tgi-server" \
+        "docsum-gaudi-tgi-server" \
+        "json" \
+        '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":17, "do_sample": true}}'
+
+    # llm microservice
+    validate_service \
+        "${host_ip}:${LLM_PORT}/v1/docsum" \
+        "text" \
+        "llm-docsum-tgi" \
+        "docsum-gaudi-llm-server" \
+        "json" \
+        '{"messages":"Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for the most popular models, including FlagEmbedding, Ember, GTE and E5."}'
+
+    # whisper microservice
+    ulimit -s 65536
+    validate_service \
+        "${host_ip}:7066/v1/asr" \
+        '{"asr_result":"well"}' \
+        "whisper" \
+        "docsum-gaudi-whisper-server" \
+        "json" \
+        "{\"audio\": \"$(input_data_for_test "audio")\"}"
+
+}
+
+function validate_megaservice_text() {
+    echo ">>> Checking text data in json format"
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "[DONE]" \
+        "docsum-gaudi-backend-server" \
+        "docsum-gaudi-backend-server" \
+        "json" \
+        '{"type": "text", "messages": "Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for the most popular models, including FlagEmbedding, Ember, GTE and E5."}'
+
+    echo ">>> Checking text data in form format, set language=en"
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "[DONE]" \
+        "docsum-gaudi-backend-server" \
+        "docsum-gaudi-backend-server" \
+        "media" "" \
+        "type=text" \
+        "messages=Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for the most popular models, including FlagEmbedding, Ember, GTE and E5." \
+        "max_tokens=32" \
+        "language=en" \
+        "stream=True"
+
+    echo ">>> Checking text data in form format, set language=zh"
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "[DONE]" \
+        "docsum-gaudi-backend-server" \
+        "docsum-gaudi-backend-server" \
+        "media" "" \
+        "type=text" \
+        "messages=2024年9月26日，北京——今日，英特尔正式发布英特尔® 至强® 6性能核处理器（代号Granite Rapids），为AI、数据分析、科学计算等计算密集型业务提供卓越性能。" \
+        "max_tokens=32" \
+        "language=zh" \
+        "stream=True"
+
+    echo ">>> Checking text data in form format, upload file"
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "TEI" \
+        "docsum-gaudi-backend-server" \
+        "docsum-gaudi-backend-server" \
+        "media" "" \
+        "type=text" \
+        "messages=" \
+        "files=@$ROOT_FOLDER/data/short.txt" \
+        "max_tokens=32" \
+        "language=en" \
+        "stream=False"
+}
+
+function validate_megaservice_multimedia() {
+    echo ">>> Checking audio data in json format"
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "well" \
+        "docsum-gaudi-backend-server" \
+        "docsum-gaudi-backend-server" \
+        "json" \
+        "{\"type\": \"audio\",  \"messages\": \"$(input_data_for_test "audio")\", \"stream\": \"False\"}"
+
+    echo ">>> Checking audio data in form format"
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "you" \
+        "docsum-gaudi-backend-server" \
+        "docsum-gaudi-backend-server" \
+        "media" "" \
+        "type=audio" \
+        "messages=UklGRigAAABXQVZFZm10IBIAAAABAAEARKwAAIhYAQACABAAAABkYXRhAgAAAAEA" \
+        "max_tokens=32" \
+        "language=en" \
+        "stream=False"
+
+    echo ">>> Checking video data in json format"
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "bye" \
+        "docsum-gaudi-backend-server" \
+        "docsum-gaudi-backend-server" \
+        "json" \
+        "{\"type\": \"video\",  \"messages\": \"$(input_data_for_test "video")\", \"stream\": \"False\"}"
+
+    echo ">>> Checking video data in form format"
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "bye" \
+        "docsum-gaudi-backend-server" \
+        "docsum-gaudi-backend-server" \
+        "media" "" \
+        "type=video" \
+        "messages=\"$(input_data_for_test "video")\"" \
+        "max_tokens=32" \
+        "language=en" \
+        "stream=False"
+}
+
+function validate_megaservice_long_text() {
+    echo ">>> Checking long text data in form format, set summary_type=auto"
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "Intel" \
+        "docsum-gaudi-backend-server" \
+        "docsum-gaudi-backend-server" \
+        "media" "" \
+        "type=text" \
+        "messages=" \
+        "files=@$ROOT_FOLDER/data/long.txt" \
+        "max_tokens=128" \
+        "summary_type=auto" \
+        "stream=False"
+
+    echo ">>> Checking long text data in form format, set summary_type=stuff"
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "TEI" \
+        "docsum-gaudi-backend-server" \
+        "docsum-gaudi-backend-server" \
+        "media" "" \
+        "type=text" \
+        "messages=" \
+        "files=@$ROOT_FOLDER/data/short.txt" \
+        "max_tokens=128" \
+        "summary_type=stuff" \
+        "stream=False"
+
+    echo ">>> Checking long text data in form format, set summary_type=truncate"
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "Intel" \
+        "docsum-gaudi-backend-server" \
+        "docsum-gaudi-backend-server" \
+        "media" "" \
+        "type=text" \
+        "messages=" \
+        "files=@$ROOT_FOLDER/data/long.txt" \
+        "max_tokens=128" \
+        "summary_type=truncate" \
+        "stream=False"
+
+    echo ">>> Checking long text data in form format, set summary_type=map_reduce"
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "Intel" \
+        "docsum-gaudi-backend-server" \
+        "docsum-gaudi-backend-server" \
+        "media" "" \
+        "type=text" \
+        "messages=" \
+        "files=@$ROOT_FOLDER/data/long.txt" \
+        "max_tokens=128" \
+        "summary_type=map_reduce" \
+        "stream=False"
+
+    echo ">>> Checking long text data in form format, set summary_type=refine"
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "Intel" \
+        "docsum-gaudi-backend-server" \
+        "docsum-gaudi-backend-server" \
+        "media" "" \
+        "type=text" \
+        "messages=" \
+        "files=@$ROOT_FOLDER/data/long.txt" \
+        "max_tokens=128" \
+        "summary_type=refine" \
+        "stream=False"
+}
+
+function stop_docker() {
+    cd $WORKPATH/docker_compose/intel/hpu/gaudi
+    docker compose -f compose_tgi.yaml stop && docker compose rm -f
+}
+
+function main() {
+    echo "==========================================="
+    echo ">>>> Stopping any running Docker containers..."
+    stop_docker
+
+    echo "==========================================="
+    if [[ "$IMAGE_REPO" == "opea" ]]; then
+        echo ">>>> Building Docker images..."
+        build_docker_images
+    fi
+
+    echo "==========================================="
+    echo ">>>> Starting Docker services..."
+    start_services
+
+    echo "==========================================="
+    echo ">>>> Validating microservices..."
+    validate_microservices
+
+    echo "==========================================="
+    echo ">>>> Validating megaservice for text..."
+    validate_megaservice_text
+
+    echo "==========================================="
+    echo ">>>> Validating megaservice for multimedia..."
+    validate_megaservice_multimedia
+
+    echo "==========================================="
+    echo ">>>> Validating megaservice for long text..."
+    validate_megaservice_long_text
+
+    echo "==========================================="
+    echo ">>>> Stopping Docker containers..."
+    stop_docker
+
+    echo "==========================================="
+    echo ">>>> Pruning Docker system..."
+    echo y | docker system prune
+    echo ">>>> Docker system pruned successfully."
+    echo "==========================================="
+}
+
+main
diff --git a/DocSum/tests/test_compose_tgi_on_xeon.sh b/DocSum/tests/test_compose_tgi_on_xeon.sh
new file mode 100644
index 0000000000..3d7b3f1b22
--- /dev/null
+++ b/DocSum/tests/test_compose_tgi_on_xeon.sh
@@ -0,0 +1,385 @@
+#!/bin/bash
+# Copyright (C) 2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+set -xe
+
+IMAGE_REPO=${IMAGE_REPO:-"opea"}
+IMAGE_TAG=${IMAGE_TAG:-"latest"}
+export http_proxy=$http_proxy
+export https_proxy=$https_proxy
+export host_ip=$(hostname -I | awk '{print $1}')
+
+echo "REGISTRY=IMAGE_REPO=${IMAGE_REPO}"
+echo "TAG=IMAGE_TAG=${IMAGE_TAG}"
+export no_proxy="${no_proxy},${host_ip}"
+export MODEL_CACHE=${model_cache:-"./data"}
+export REGISTRY=${IMAGE_REPO}
+export TAG=${IMAGE_TAG}
+export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
+export LLM_ENDPOINT_PORT=8008
+export LLM_MODEL_ID="Intel/neural-chat-7b-v3-3"
+export MAX_INPUT_TOKENS=2048
+export MAX_TOTAL_TOKENS=4096
+export LLM_PORT=9000
+export LLM_ENDPOINT="http://${host_ip}:${LLM_ENDPOINT_PORT}"
+export DocSum_COMPONENT_NAME="OpeaDocSumTgi"
+export MEGA_SERVICE_HOST_IP=${host_ip}
+export LLM_SERVICE_HOST_IP=${host_ip}
+export ASR_SERVICE_HOST_IP=${host_ip}
+export FRONTEND_SERVICE_PORT=5173
+export BACKEND_SERVICE_PORT=8888
+export BACKEND_SERVICE_ENDPOINT="http://${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum"
+export LOGFLAG=True
+
+WORKPATH=$(dirname "$PWD")
+LOG_PATH="$WORKPATH/tests"
+
+# Get the root folder of the current script
+ROOT_FOLDER=$(dirname "$(readlink -f "$0")")
+
+function build_docker_images() {
+    opea_branch=${opea_branch:-"main"}
+    cd $WORKPATH/docker_image_build
+    git clone --depth 1 --branch ${opea_branch} https://github.com/opea-project/GenAIComps.git
+    pushd GenAIComps
+    docker build --no-cache -t ${REGISTRY}/comps-base:${TAG} --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile .
+    popd && sleep 1s
+
+    echo "Build all the images with --no-cache, check docker_image_build.log for details..."
+    service_list="docsum docsum-gradio-ui whisper llm-docsum"
+    docker compose -f build.yaml build ${service_list} --no-cache > ${LOG_PATH}/docker_image_build.log
+
+    docker pull ghcr.io/huggingface/text-generation-inference:1.4
+    docker images && sleep 1s
+}
+
+function start_services() {
+    cd $WORKPATH/docker_compose/intel/cpu/xeon/
+    docker compose -f compose_tgi.yaml up -d > ${LOG_PATH}/start_services_with_compose.log
+    sleep 1m
+}
+
+get_base64_str() {
+    local file_name=$1
+    base64 -w 0 "$file_name"
+}
+
+# Function to generate input data for testing based on the document type
+input_data_for_test() {
+    local document_type=$1
+    case $document_type in
+        ("text")
+            echo "THIS IS A TEST >>>> and a number of states are starting to adopt them voluntarily special correspondent john delenco of education week reports it takes just 10 minutes to cross through gillette wyoming this small city sits in the northeast corner of the state surrounded by 100s of miles of prairie but schools here in campbell county are on the edge of something big the next generation science standards you are going to build a strand of dna and you are going to decode it and figure out what that dna actually says for christy mathis at sage valley junior high school the new standards are about learning to think like a scientist there is a lot of really good stuff in them every standard is a performance task it is not you know the child needs to memorize these things it is the student needs to be able to do some pretty intense stuff we are analyzing we are critiquing we are."
+            ;;
+        ("audio")
+            get_base64_str "$ROOT_FOLDER/data/test.wav"
+            ;;
+        ("video")
+            get_base64_str "$ROOT_FOLDER/data/test.mp4"
+            ;;
+        (*)
+            echo "Invalid document type" >&2
+            exit 1
+            ;;
+    esac
+}
+
+function validate_service() {
+    local URL="$1"
+    local EXPECTED_RESULT="$2"
+    local SERVICE_NAME="$3"
+    local DOCKER_NAME="$4"
+    local VALIDATE_TYPE="$5"
+    local INPUT_DATA="$6"
+    local FORM_DATA1="$7"
+    local FORM_DATA2="$8"
+    local FORM_DATA3="$9"
+    local FORM_DATA4="${10}"
+    local FORM_DATA5="${11}"
+    local FORM_DATA6="${12}"
+
+    if [[ $VALIDATE_TYPE == *"json"* ]]; then
+        HTTP_RESPONSE=$(curl --silent --write-out "HTTPSTATUS:%{http_code}" -X POST -d "$INPUT_DATA" -H 'Content-Type: application/json' "$URL")
+    else
+        CURL_CMD=(curl --silent --write-out "HTTPSTATUS:%{http_code}" -X POST -F "$FORM_DATA1" -F "$FORM_DATA2" -F "$FORM_DATA3" -F "$FORM_DATA4" -F "$FORM_DATA5" -H 'Content-Type: multipart/form-data' "$URL")
+        if [[ -n "$FORM_DATA6" ]]; then
+            CURL_CMD+=(-F "$FORM_DATA6")
+        fi
+        HTTP_RESPONSE=$("${CURL_CMD[@]}")
+    fi
+    HTTP_STATUS=$(echo $HTTP_RESPONSE | tr -d '\n' | sed -e 's/.*HTTPSTATUS://')
+    RESPONSE_BODY=$(echo $HTTP_RESPONSE | sed -e 's/HTTPSTATUS\:.*//g')
+
+    docker logs ${DOCKER_NAME} >> ${LOG_PATH}/${SERVICE_NAME}.log
+
+    # check response status
+    if [ "$HTTP_STATUS" -ne "200" ]; then
+        echo "[ $SERVICE_NAME ] HTTP status is not 200. Received status was $HTTP_STATUS"
+        exit 1
+    else
+        echo "[ $SERVICE_NAME ] HTTP status is 200. Checking content..."
+    fi
+    # check response body
+    if [[ "$RESPONSE_BODY" != *"$EXPECTED_RESULT"* ]]; then
+        echo "EXPECTED_RESULT==> $EXPECTED_RESULT"
+        echo "RESPONSE_BODY==> $RESPONSE_BODY"
+        echo "[ $SERVICE_NAME ] Content does not match the expected result: $RESPONSE_BODY"
+        exit 1
+    else
+        echo "[ $SERVICE_NAME ] Content is as expected."
+    fi
+
+    sleep 1s
+}
+
+function validate_microservices() {
+    # Check if the microservices are running correctly.
+
+    # tgi for llm service
+    validate_service \
+        "${host_ip}:${LLM_ENDPOINT_PORT}/generate" \
+        "generated_text" \
+        "tgi-server" \
+        "docsum-xeon-tgi-server" \
+        "json" \
+        '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":17, "do_sample": true}}'
+
+    # llm microservice
+    validate_service \
+        "${host_ip}:${LLM_PORT}/v1/docsum" \
+        "text" \
+        "llm-docsum-tgi" \
+        "docsum-xeon-llm-server" \
+        "json" \
+        '{"messages":"Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for the most popular models, including FlagEmbedding, Ember, GTE and E5."}'
+
+    # whisper microservice
+    ulimit -s 65536
+    validate_service \
+        "${host_ip}:7066/v1/asr" \
+        '{"asr_result":"well"}' \
+        "whisper" \
+        "docsum-xeon-whisper-server" \
+        "json" \
+        "{\"audio\": \"$(input_data_for_test "audio")\"}"
+
+}
+
+function validate_megaservice_text() {
+    echo ">>> Checking text data in json format"
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "[DONE]" \
+        "docsum-xeon-backend-server" \
+        "docsum-xeon-backend-server" \
+        "json" \
+        '{"type": "text", "messages": "Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for the most popular models, including FlagEmbedding, Ember, GTE and E5."}'
+
+    echo ">>> Checking text data in form format, set language=en"
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "[DONE]" \
+        "docsum-xeon-backend-server" \
+        "docsum-xeon-backend-server" \
+        "media" "" \
+        "type=text" \
+        "messages=Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for the most popular models, including FlagEmbedding, Ember, GTE and E5." \
+        "max_tokens=32" \
+        "language=en" \
+        "stream=True"
+
+    echo ">>> Checking text data in form format, set language=zh"
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "[DONE]" \
+        "docsum-xeon-backend-server" \
+        "docsum-xeon-backend-server" \
+        "media" "" \
+        "type=text" \
+        "messages=2024年9月26日，北京——今日，英特尔正式发布英特尔® 至强® 6性能核处理器（代号Granite Rapids），为AI、数据分析、科学计算等计算密集型业务提供卓越性能。" \
+        "max_tokens=32" \
+        "language=zh" \
+        "stream=True"
+
+    echo ">>> Checking text data in form format, upload file"
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "TEI" \
+        "docsum-xeon-backend-server" \
+        "docsum-xeon-backend-server" \
+        "media" "" \
+        "type=text" \
+        "messages=" \
+        "files=@$ROOT_FOLDER/data/short.txt" \
+        "max_tokens=32" \
+        "language=en" \
+        "stream=False"
+}
+
+function validate_megaservice_multimedia() {
+    echo ">>> Checking audio data in json format"
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "well" \
+        "docsum-xeon-backend-server" \
+        "docsum-xeon-backend-server" \
+        "json" \
+        "{\"type\": \"audio\",  \"messages\": \"$(input_data_for_test "audio")\", \"stream\": \"False\"}"
+
+    echo ">>> Checking audio data in form format"
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "you" \
+        "docsum-xeon-backend-server" \
+        "docsum-xeon-backend-server" \
+        "media" "" \
+        "type=audio" \
+        "messages=UklGRigAAABXQVZFZm10IBIAAAABAAEARKwAAIhYAQACABAAAABkYXRhAgAAAAEA" \
+        "max_tokens=32" \
+        "language=en" \
+        "stream=False"
+
+    echo ">>> Checking video data in json format"
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "bye" \
+        "docsum-xeon-backend-server" \
+        "docsum-xeon-backend-server" \
+        "json" \
+        "{\"type\": \"video\",  \"messages\": \"$(input_data_for_test "video")\", \"stream\": \"False\"}"
+
+    echo ">>> Checking video data in form format"
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "bye" \
+        "docsum-xeon-backend-server" \
+        "docsum-xeon-backend-server" \
+        "media" "" \
+        "type=video" \
+        "messages=\"$(input_data_for_test "video")\"" \
+        "max_tokens=32" \
+        "language=en" \
+        "stream=False"
+}
+
+function validate_megaservice_long_text() {
+    echo ">>> Checking long text data in form format, set summary_type=auto"
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "Intel" \
+        "docsum-xeon-backend-server" \
+        "docsum-xeon-backend-server" \
+        "media" "" \
+        "type=text" \
+        "messages=" \
+        "files=@$ROOT_FOLDER/data/long.txt" \
+        "max_tokens=128" \
+        "summary_type=auto" \
+        "stream=False"
+
+    echo ">>> Checking long text data in form format, set summary_type=stuff"
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "TEI" \
+        "docsum-xeon-backend-server" \
+        "docsum-xeon-backend-server" \
+        "media" "" \
+        "type=text" \
+        "messages=" \
+        "files=@$ROOT_FOLDER/data/short.txt" \
+        "max_tokens=128" \
+        "summary_type=stuff" \
+        "stream=False"
+
+    echo ">>> Checking long text data in form format, set summary_type=truncate"
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "Intel" \
+        "docsum-xeon-backend-server" \
+        "docsum-xeon-backend-server" \
+        "media" "" \
+        "type=text" \
+        "messages=" \
+        "files=@$ROOT_FOLDER/data/long.txt" \
+        "max_tokens=128" \
+        "summary_type=truncate" \
+        "stream=False"
+
+    echo ">>> Checking long text data in form format, set summary_type=map_reduce"
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "Intel" \
+        "docsum-xeon-backend-server" \
+        "docsum-xeon-backend-server" \
+        "media" "" \
+        "type=text" \
+        "messages=" \
+        "files=@$ROOT_FOLDER/data/long.txt" \
+        "max_tokens=128" \
+        "summary_type=map_reduce" \
+        "stream=False"
+
+    echo ">>> Checking long text data in form format, set summary_type=refine"
+    validate_service \
+        "${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" \
+        "Intel" \
+        "docsum-xeon-backend-server" \
+        "docsum-xeon-backend-server" \
+        "media" "" \
+        "type=text" \
+        "messages=" \
+        "files=@$ROOT_FOLDER/data/long.txt" \
+        "max_tokens=128" \
+        "summary_type=refine" \
+        "stream=False"
+}
+
+function stop_docker() {
+    cd $WORKPATH/docker_compose/intel/cpu/xeon/
+    docker compose -f compose_tgi.yaml stop && docker compose rm -f
+}
+
+function main() {
+    echo "==========================================="
+    echo ">>>> Stopping any running Docker containers..."
+    stop_docker
+
+    echo "==========================================="
+    if [[ "$IMAGE_REPO" == "opea" ]]; then
+        echo ">>>> Building Docker images..."
+        build_docker_images
+    fi
+
+    echo "==========================================="
+    echo ">>>> Starting Docker services..."
+    start_services
+
+    echo "==========================================="
+    echo ">>>> Validating microservices..."
+    validate_microservices
+
+    echo "==========================================="
+    echo ">>>> Validating megaservice for text..."
+    validate_megaservice_text
+
+    echo "==========================================="
+    echo ">>>> Validating megaservice for multimedia..."
+    validate_megaservice_multimedia
+
+    echo "==========================================="
+    echo ">>>> Validating megaservice for long text..."
+    validate_megaservice_long_text
+
+    echo "==========================================="
+    echo ">>>> Stopping Docker containers..."
+    stop_docker
+
+    echo "==========================================="
+    echo ">>>> Pruning Docker system..."
+    echo y | docker system prune
+    echo ">>>> Docker system pruned successfully."
+    echo "==========================================="
+}
+
+main