Exclude dockerfile under tests and exclude check Dockerfile under tests. (#1354)

Signed-off-by: ZePan110 <ze.pan@intel.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

.github/workflows/pr-dockerfile-path-and-build-yaml-scan.yml

@@ -60,7 +60,7 @@ jobs:
           shopt -s globstar
           no_add="FALSE"
           cd ${{github.workspace}}
-          Dockerfiles=$(realpath $(find ./ -name '*Dockerfile*'))
+          Dockerfiles=$(realpath $(find ./ -name '*Dockerfile*' ! -path './tests/*'))
           if [ -n "$Dockerfiles" ]; then
             for dockerfile in $Dockerfiles; do
               service=$(echo "$dockerfile" | awk -F '/GenAIExamples/' '{print $2}' | awk -F '/' '{print $2}')

AgentQnA/tests/step1_build_images.sh

@@ -21,7 +21,7 @@ function build_docker_images_for_retrieval_tool(){
     # git clone https://github.com/opea-project/GenAIComps.git && cd GenAIComps && git checkout "${opea_branch:-"main"}" && cd ../
     get_genai_comps
     echo "Build all the images with --no-cache..."
-    service_list="doc-index-retriever dataprep-redis embedding-tei retriever-redis reranking-tei"
+    service_list="doc-index-retriever dataprep-redis embedding retriever-redis reranking-tei"
     docker compose -f build.yaml build ${service_list} --no-cache
     docker pull ghcr.io/huggingface/text-embeddings-inference:cpu-1.5
 

ChatQnA/docker_compose/intel/hpu/gaudi/how_to_validate_service.md

@@ -43,7 +43,7 @@ Here is the output:
 CONTAINER ID   IMAGE                                                   COMMAND                  CREATED         STATUS                          PORTS                                                                                  NAMES
 28d9a5570246   opea/chatqna-ui:latest                                  "docker-entrypoint.s…"   2 minutes ago   Up 2 minutes                    0.0.0.0:5173->5173/tcp, :::5173->5173/tcp                                              chatqna-gaudi-ui-server
 bee1132464cd   opea/chatqna:latest                                     "python chatqna.py"      2 minutes ago   Up 2 minutes                    0.0.0.0:8888->8888/tcp, :::8888->8888/tcp                                              chatqna-gaudi-backend-server
-f810f3b4d329   opea/embedding-tei:latest                               "python embedding_te…"   2 minutes ago   Up 2 minutes                    0.0.0.0:6000->6000/tcp, :::6000->6000/tcp                                              embedding-tei-server
+f810f3b4d329   opea/embedding:latest                               "python embedding_te…"   2 minutes ago   Up 2 minutes                    0.0.0.0:6000->6000/tcp, :::6000->6000/tcp                                              embedding-server
 325236a01f9b   opea/llm-textgen:latest                                     "python llm.py"          2 minutes ago   Up 2 minutes                    0.0.0.0:9000->9000/tcp, :::9000->9000/tcp                                              llm-textgen-gaudi-server
 2fa17d84605f   opea/dataprep-redis:latest                              "python prepare_doc_…"   2 minutes ago   Up 2 minutes                    0.0.0.0:6007->6007/tcp, :::6007->6007/tcp                                              dataprep-redis-server
 69e1fb59e92c   opea/retriever-redis:latest                             "/home/user/comps/re…"   2 minutes ago   Up 2 minutes                    0.0.0.0:7000->7000/tcp, :::7000->7000/tcp                                              retriever-redis-server

ChatQnA/docker_image_build/build.yaml

@@ -41,12 +41,12 @@ services:
       dockerfile: ./docker/Dockerfile.react
     extends: chatqna
     image: ${REGISTRY:-opea}/chatqna-conversation-ui:${TAG:-latest}
-  embedding-tei:
+  embedding:
     build:
       context: GenAIComps
       dockerfile: comps/embeddings/src/Dockerfile
     extends: chatqna
-    image: ${REGISTRY:-opea}/embedding-tei:${TAG:-latest}
+    image: ${REGISTRY:-opea}/embedding:${TAG:-latest}
   retriever-redis:
     build:
       context: GenAIComps

DocIndexRetriever/docker_compose/intel/cpu/xeon/README.md

@@ -9,7 +9,7 @@ DocRetriever are the most widely adopted use case for leveraging the different m
   ```bash
   git clone https://github.com/opea-project/GenAIComps.git
   cd GenAIComps
-  docker build -t opea/embedding-tei:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/embeddings/src/Dockerfile .
+  docker build -t opea/embedding:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/embeddings/src/Dockerfile .
   ```
 
 - Retriever Vector store Image
@@ -125,7 +125,7 @@ curl http://${host_ip}:8889/v1/retrievaltool -X POST -H "Content-Type: applicati
      -X POST \
      -d '{"text":"Explain the OPEA project"}' \
      -H 'Content-Type: application/json' > query
-   docker container logs embedding-tei-server
+   docker container logs embedding-server
 
    # if you used tei-gaudi
    docker container logs tei-embedding-gaudi-server

DocIndexRetriever/docker_compose/intel/cpu/xeon/compose.yaml

@@ -50,8 +50,8 @@ services:
       timeout: 10s
       retries: 60
   embedding:
-    image: ${REGISTRY:-opea}/embedding-tei:${TAG:-latest}
-    container_name: embedding-tei-server
+    image: ${REGISTRY:-opea}/embedding:${TAG:-latest}
+    container_name: embedding-server
     ports:
       - "6000:6000"
     ipc: host

DocIndexRetriever/docker_compose/intel/cpu/xeon/compose_without_rerank.yaml

@@ -50,8 +50,8 @@ services:
       timeout: 10s
       retries: 60
   embedding:
-    image: ${REGISTRY:-opea}/embedding-tei:${TAG:-latest}
-    container_name: embedding-tei-server
+    image: ${REGISTRY:-opea}/embedding:${TAG:-latest}
+    container_name: embedding-server
     ports:
       - "6000:6000"
     ipc: host

DocIndexRetriever/docker_compose/intel/hpu/gaudi/README.md

@@ -9,7 +9,7 @@ DocRetriever are the most widely adopted use case for leveraging the different m
   ```bash
   git clone https://github.com/opea-project/GenAIComps.git
   cd GenAIComps
-  docker build -t opea/embedding-tei:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/embeddings/src/Dockerfile .
+  docker build -t opea/embedding:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/embeddings/src/Dockerfile .
   ```
 
 - Retriever Vector store Image
@@ -115,7 +115,7 @@ curl http://${host_ip}:8889/v1/retrievaltool -X POST -H "Content-Type: applicati
      -X POST \
      -d '{"text":"Explain the OPEA project"}' \
      -H 'Content-Type: application/json' > query
-   docker container logs embedding-tei-server
+   docker container logs embedding-server
 
    # if you used tei-gaudi
    docker container logs tei-embedding-gaudi-server

DocIndexRetriever/docker_compose/intel/hpu/gaudi/compose.yaml

@@ -55,8 +55,8 @@ services:
       timeout: 10s
       retries: 60
   embedding:
-    image: ${REGISTRY:-opea}/embedding-tei:${TAG:-latest}
-    container_name: embedding-tei-server
+    image: ${REGISTRY:-opea}/embedding:${TAG:-latest}
+    container_name: embedding-server
     ports:
       - "6000:6000"
     ipc: host

DocIndexRetriever/docker_image_build/build.yaml

@@ -11,12 +11,12 @@ services:
       context: ../
       dockerfile: ./Dockerfile
     image: ${REGISTRY:-opea}/doc-index-retriever:${TAG:-latest}
-  embedding-tei:
+  embedding:
     build:
       context: GenAIComps
       dockerfile: comps/embeddings/src/Dockerfile
     extends: doc-index-retriever
-    image: ${REGISTRY:-opea}/embedding-tei:${TAG:-latest}
+    image: ${REGISTRY:-opea}/embedding:${TAG:-latest}
   retriever-redis:
     build:
       context: GenAIComps

DocIndexRetriever/tests/test_compose_on_xeon.sh

@@ -21,7 +21,7 @@ function build_docker_images() {
         echo "Cloning GenAIComps repository"
         git clone https://github.com/opea-project/GenAIComps.git && cd GenAIComps && git checkout "${opea_branch:-"main"}" && cd ../
     fi
-    service_list="dataprep-redis embedding-tei retriever-redis reranking-tei doc-index-retriever"
+    service_list="dataprep-redis embedding retriever-redis reranking-tei doc-index-retriever"
     docker compose -f build.yaml build ${service_list} --no-cache > ${LOG_PATH}/docker_image_build.log
 
     docker pull ghcr.io/huggingface/text-embeddings-inference:cpu-1.5
@@ -98,7 +98,7 @@ function validate_megaservice() {
     echo "return value is $EXIT_CODE"
     if [ "$EXIT_CODE" == "1" ]; then
         echo "=============Embedding container log=================="
-        docker logs embedding-tei-server | tee -a ${LOG_PATH}/doc-index-retriever-service-xeon.log
+        docker logs embedding-server | tee -a ${LOG_PATH}/doc-index-retriever-service-xeon.log
         echo "=============Retriever container log=================="
         docker logs retriever-redis-server | tee -a ${LOG_PATH}/doc-index-retriever-service-xeon.log
         echo "=============TEI Reranking log=================="

DocIndexRetriever/tests/test_compose_without_rerank_on_xeon.sh

@@ -21,7 +21,7 @@ function build_docker_images() {
         echo "Cloning GenAIComps repository"
         git clone https://github.com/opea-project/GenAIComps.git && cd GenAIComps && git checkout "${opea_branch:-"main"}" && cd ../
     fi
-    service_list="dataprep-redis embedding-tei retriever-redis doc-index-retriever"
+    service_list="dataprep-redis embedding retriever-redis doc-index-retriever"
     docker compose -f build.yaml build ${service_list} --no-cache > ${LOG_PATH}/docker_image_build.log
 
     docker pull ghcr.io/huggingface/text-embeddings-inference:cpu-1.5
@@ -92,7 +92,7 @@ function validate_megaservice() {
     echo "return value is $EXIT_CODE"
     if [ "$EXIT_CODE" == "1" ]; then
         echo "=============Embedding container log=================="
-        docker logs embedding-tei-server | tee -a ${LOG_PATH}/doc-index-retriever-service-xeon.log
+        docker logs embedding-server | tee -a ${LOG_PATH}/doc-index-retriever-service-xeon.log
         echo "=============Retriever container log=================="
         docker logs retriever-redis-server | tee -a ${LOG_PATH}/doc-index-retriever-service-xeon.log
         echo "=============Doc-index-retriever container log=================="

MultimodalQnA/README.md

@@ -100,12 +100,12 @@ In the below, we provide a table that describes for each microservice component
 
 By default, the embedding and LVM models are set to a default value as listed below:
 
-| Service       | HW    | Model                                     |
-| ------------- | ----- | ----------------------------------------- |
-| embedding-tei | Xeon  | BridgeTower/bridgetower-large-itm-mlm-itc |
-| LVM           | Xeon  | llava-hf/llava-1.5-7b-hf                  |
-| embedding-tei | Gaudi | BridgeTower/bridgetower-large-itm-mlm-itc |
-| LVM           | Gaudi | llava-hf/llava-v1.6-vicuna-13b-hf         |
+| Service   | HW    | Model                                     |
+| --------- | ----- | ----------------------------------------- |
+| embedding | Xeon  | BridgeTower/bridgetower-large-itm-mlm-itc |
+| LVM       | Xeon  | llava-hf/llava-1.5-7b-hf                  |
+| embedding | Gaudi | BridgeTower/bridgetower-large-itm-mlm-itc |
+| LVM       | Gaudi | llava-hf/llava-v1.6-vicuna-13b-hf         |
 
 You can choose other LVM models, such as `llava-hf/llava-1.5-7b-hf ` and `llava-hf/llava-1.5-13b-hf`, as needed.
 

MultimodalQnA/docker_compose/amd/gpu/rocm/README.md

@@ -28,10 +28,10 @@ cd GenAIComps
 docker build --no-cache -t opea/embedding-multimodal-bridgetower:latest --build-arg EMBEDDER_PORT=$EMBEDDER_PORT --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/embeddings/src/integrations/dependency/bridgetower/Dockerfile .
 ```
 
-Build embedding-tei microservice image
+Build embedding microservice image
 
 ```bash
-docker build --no-cache -t opea/embedding-tei:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/embeddings/src/Dockerfile .
+docker build --no-cache -t opea/embedding:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/embeddings/src/Dockerfile .
 ```
 
 ### 2. Build LVM Images
@@ -87,7 +87,7 @@ Then run the command `docker images`, you will have the following 8 Docker Image
 2. `ghcr.io/huggingface/text-generation-inference:2.4.1-rocm`
 3. `opea/lvm-tgi:latest`
 4. `opea/retriever-multimodal-redis:latest`
-5. `opea/embedding-tei:latest`
+5. `opea/embedding:latest`
 6. `opea/embedding-multimodal-bridgetower:latest`
 7. `opea/multimodalqna:latest`
 8. `opea/multimodalqna-ui:latest`
@@ -98,11 +98,11 @@ Then run the command `docker images`, you will have the following 8 Docker Image
 
 By default, the multimodal-embedding and LVM models are set to a default value as listed below:
 
-| Service       | Model                                       |
-| ------------- | ------------------------------------------- |
-| embedding-tei | BridgeTower/bridgetower-large-itm-mlm-gaudi |
-| LVM           | llava-hf/llava-1.5-7b-hf                    |
-| LVM           | Xkev/Llama-3.2V-11B-cot                     |
+| Service   | Model                                       |
+| --------- | ------------------------------------------- |
+| embedding | BridgeTower/bridgetower-large-itm-mlm-gaudi |
+| LVM       | llava-hf/llava-1.5-7b-hf                    |
+| LVM       | Xkev/Llama-3.2V-11B-cot                     |
 
 Note:
 
@@ -158,7 +158,7 @@ curl http://${host_ip}:${EMBEDDER_PORT}/v1/encode \
      -d '{"text":"This is example", "img_b64_str": "iVBORw0KGgoAAAANSUhEUgAAAAoAAAAKCAYAAACNMs+9AAAAFUlEQVR42mP8/5+hnoEIwDiqkL4KAcT9GO0U4BxoAAAAAElFTkSuQmCC"}'
 ```
 
-2. embedding-tei
+2. embedding
 
 ```bash
 curl http://${host_ip}:$MM_EMBEDDING_PORT_MICROSERVICE/v1/embeddings \

MultimodalQnA/docker_compose/amd/gpu/rocm/compose.yaml

@@ -55,9 +55,9 @@ services:
       start_period: 30s
     entrypoint: ["python", "bridgetower_server.py", "--device", "cpu", "--model_name_or_path", $EMBEDDING_MODEL_ID]
     restart: unless-stopped
-  embedding-tei:
-    image: ${REGISTRY:-opea}/embedding-tei:${TAG:-latest}
-    container_name: embedding-tei
+  embedding:
+    image: ${REGISTRY:-opea}/embedding:${TAG:-latest}
+    container_name: embedding
     depends_on:
       embedding-multimodal-bridgetower:
         condition: service_healthy
@@ -138,7 +138,7 @@ services:
     depends_on:
       - redis-vector-db
       - dataprep-multimodal-redis
-      - embedding-tei
+      - embedding
       - retriever-redis
       - lvm-tgi
     ports:

MultimodalQnA/docker_compose/intel/cpu/xeon/README.md

@@ -24,7 +24,7 @@ embedding-multimodal-bridgetower
 =====================
 Port 6006 - Open to 0.0.0.0/0
 
-embedding-tei
+embedding
 =========
 Port 6000 - Open to 0.0.0.0/0
 
@@ -115,10 +115,10 @@ cd GenAIComps
 docker build --no-cache -t opea/embedding-multimodal-bridgetower:latest --build-arg EMBEDDER_PORT=$EMBEDDER_PORT --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/embeddings/src/integrations/dependency/bridgetower/Dockerfile .
 ```
 
-Build embedding-tei microservice image
+Build embedding microservice image
 
 ```bash
-docker build --no-cache -t opea/embedding-tei:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/embeddings/src/Dockerfile .
+docker build --no-cache -t opea/embedding:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/embeddings/src/Dockerfile .
 ```
 
 ### 2. Build retriever-multimodal-redis Image
@@ -184,7 +184,7 @@ Then run the command `docker images`, you will have the following 11 Docker Imag
 4. `opea/retriever-multimodal-redis:latest`
 5. `opea/whisper:latest`
 6. `opea/redis-vector-db`
-7. `opea/embedding-tei:latest`
+7. `opea/embedding:latest`
 8. `opea/embedding-multimodal-bridgetower:latest`
 9. `opea/multimodalqna:latest`
 10. `opea/multimodalqna-ui:latest`
@@ -195,10 +195,10 @@ Then run the command `docker images`, you will have the following 11 Docker Imag
 
 By default, the multimodal-embedding and LVM models are set to a default value as listed below:
 
-| Service       | Model                                       |
-| ------------- | ------------------------------------------- |
-| embedding-tei | BridgeTower/bridgetower-large-itm-mlm-gaudi |
-| LVM           | llava-hf/llava-1.5-7b-hf                    |
+| Service   | Model                                       |
+| --------- | ------------------------------------------- |
+| embedding | BridgeTower/bridgetower-large-itm-mlm-gaudi |
+| LVM       | llava-hf/llava-1.5-7b-hf                    |
 
 ### Start all the services Docker Containers
 
@@ -227,7 +227,7 @@ curl http://${host_ip}:${EMBEDDER_PORT}/v1/encode \
      -d '{"text":"This is example", "img_b64_str": "iVBORw0KGgoAAAANSUhEUgAAAAoAAAAKCAYAAACNMs+9AAAAFUlEQVR42mP8/5+hnoEIwDiqkL4KAcT9GO0U4BxoAAAAAElFTkSuQmCC"}'
 ```
 
-2. embedding-tei
+2. embedding
 
 ```bash
 curl http://${host_ip}:$MM_EMBEDDING_PORT_MICROSERVICE/v1/embeddings \

MultimodalQnA/docker_compose/intel/cpu/xeon/compose.yaml

@@ -55,9 +55,9 @@ services:
       start_period: 30s
     entrypoint: ["python", "bridgetower_server.py", "--device", "cpu", "--model_name_or_path", $EMBEDDING_MODEL_ID]
     restart: unless-stopped
-  embedding-tei:
-    image: ${REGISTRY:-opea}/embedding-tei:${TAG:-latest}
-    container_name: embedding-tei
+  embedding:
+    image: ${REGISTRY:-opea}/embedding:${TAG:-latest}
+    container_name: embedding
     depends_on:
       embedding-multimodal-bridgetower:
         condition: service_healthy
@@ -120,7 +120,7 @@ services:
     depends_on:
       - redis-vector-db
       - dataprep-multimodal-redis
-      - embedding-tei
+      - embedding
       - retriever-redis
       - lvm-llava-svc
     ports:

MultimodalQnA/docker_compose/intel/hpu/gaudi/README.md

@@ -66,10 +66,10 @@ cd GenAIComps
 docker build --no-cache -t opea/embedding-multimodal-bridgetower:latest --build-arg EMBEDDER_PORT=$EMBEDDER_PORT --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/embeddings/src/integrations/dependency/bridgetower/Dockerfile .
 ```
 
-Build embedding-tei microservice image
+Build embedding microservice image
 
 ```bash
-docker build --no-cache -t opea/embedding-tei:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/embeddings/src/Dockerfile .
+docker build --no-cache -t opea/embedding:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/embeddings/src/Dockerfile .
 ```
 
 ### 2. Build retriever-multimodal-redis Image
@@ -133,7 +133,7 @@ Then run the command `docker images`, you will have the following 11 Docker Imag
 4. `opea/retriever-multimodal-redis:latest`
 5. `opea/whisper:latest`
 6. `opea/redis-vector-db`
-7. `opea/embedding-tei:latest`
+7. `opea/embedding:latest`
 8. `opea/embedding-multimodal-bridgetower:latest`
 9. `opea/multimodalqna:latest`
 10. `opea/multimodalqna-ui:latest`
@@ -144,10 +144,10 @@ Then run the command `docker images`, you will have the following 11 Docker Imag
 
 By default, the multimodal-embedding and LVM models are set to a default value as listed below:
 
-| Service       | Model                                       |
-| ------------- | ------------------------------------------- |
-| embedding-tei | BridgeTower/bridgetower-large-itm-mlm-gaudi |
-| LVM           | llava-hf/llava-v1.6-vicuna-13b-hf           |
+| Service   | Model                                       |
+| --------- | ------------------------------------------- |
+| embedding | BridgeTower/bridgetower-large-itm-mlm-gaudi |
+| LVM       | llava-hf/llava-v1.6-vicuna-13b-hf           |
 
 ### Start all the services Docker Containers
 
@@ -176,7 +176,7 @@ curl http://${host_ip}:${EMBEDDER_PORT}/v1/encode \
      -d '{"text":"This is example", "img_b64_str": "iVBORw0KGgoAAAANSUhEUgAAAAoAAAAKCAYAAACNMs+9AAAAFUlEQVR42mP8/5+hnoEIwDiqkL4KAcT9GO0U4BxoAAAAAElFTkSuQmCC"}'
 ```
 
-2. embedding-tei
+2. embedding
 
 ```bash
 curl http://${host_ip}:$MM_EMBEDDING_PORT_MICROSERVICE/v1/embeddings \

MultimodalQnA/docker_compose/intel/hpu/gaudi/compose.yaml

@@ -55,9 +55,9 @@ services:
       start_period: 30s
     entrypoint: ["python", "bridgetower_server.py", "--device", "hpu", "--model_name_or_path", $EMBEDDING_MODEL_ID]
     restart: unless-stopped
-  embedding-tei:
-    image: ${REGISTRY:-opea}/embedding-tei:${TAG:-latest}
-    container_name: embedding-tei
+  embedding:
+    image: ${REGISTRY:-opea}/embedding:${TAG:-latest}
+    container_name: embedding
     depends_on:
       embedding-multimodal-bridgetower:
         condition: service_healthy
@@ -137,7 +137,7 @@ services:
     depends_on:
       - redis-vector-db
       - dataprep-multimodal-redis
-      - embedding-tei
+      - embedding
       - retriever-redis
       - lvm-tgi
     ports:

MultimodalQnA/docker_image_build/build.yaml

@@ -23,12 +23,12 @@ services:
       dockerfile: comps/embeddings/src/integrations/dependency/bridgetower/Dockerfile
     extends: multimodalqna
     image: ${REGISTRY:-opea}/embedding-multimodal-bridgetower:${TAG:-latest}
-  embedding-tei:
+  embedding:
     build:
       context: GenAIComps
       dockerfile: comps/embeddings/src/Dockerfile
     extends: multimodalqna
-    image: ${REGISTRY:-opea}/embedding-tei:${TAG:-latest}
+    image: ${REGISTRY:-opea}/embedding:${TAG:-latest}
   retriever-redis:
     build:
       context: GenAIComps

MultimodalQnA/tests/test_compose_on_gaudi.sh

@@ -22,7 +22,7 @@ function build_docker_images() {
     cd $WORKPATH/docker_image_build
     git clone https://github.com/opea-project/GenAIComps.git && cd GenAIComps && git checkout "${opea_branch:-"main"}" && cd ../
     echo "Build all the images with --no-cache, check docker_image_build.log for details..."
-    service_list="multimodalqna multimodalqna-ui embedding-multimodal-bridgetower embedding-tei retriever-redis lvm-tgi dataprep-multimodal-redis whisper"
+    service_list="multimodalqna multimodalqna-ui embedding-multimodal-bridgetower embedding retriever-redis lvm-tgi dataprep-multimodal-redis whisper"
     docker compose -f build.yaml build ${service_list} --no-cache > ${LOG_PATH}/docker_image_build.log
 
     docker pull ghcr.io/huggingface/tgi-gaudi:2.0.6
@@ -144,19 +144,19 @@ function validate_microservices() {
         '{"text":"This is example", "img_b64_str": "iVBORw0KGgoAAAANSUhEUgAAAAoAAAAKCAYAAACNMs+9AAAAFUlEQVR42mP8/5+hnoEIwDiqkL4KAcT9GO0U4BxoAAAAAElFTkSuQmCC"}'
 
     # embedding microservice
-    echo "Validating embedding-tei"
+    echo "Validating embedding"
     validate_service \
         "http://${host_ip}:$MM_EMBEDDING_PORT_MICROSERVICE/v1/embeddings" \
         '"embedding":[' \
-        "embedding-tei" \
-        "embedding-tei" \
+        "embedding" \
+        "embedding" \
         '{"text" : "This is some sample text."}'
 
     validate_service \
         "http://${host_ip}:$MM_EMBEDDING_PORT_MICROSERVICE/v1/embeddings" \
         '"embedding":[' \
-        "embedding-tei" \
-        "embedding-tei" \
+        "embedding" \
+        "embedding" \
         '{"text": {"text" : "This is some sample text."}, "image" : {"url": "https://github.com/docarray/docarray/blob/main/tests/toydata/image-data/apple.png?raw=true"}}'
 
     sleep 1m # retrieval can't curl as expected, try to wait for more time

MultimodalQnA/tests/test_compose_on_rocm.sh

@@ -23,7 +23,7 @@ function build_docker_images() {
     git clone https://github.com/opea-project/GenAIComps.git && cd GenAIComps && git checkout "${opea_branch:-"main"}" && cd ../
 
     echo "Build all the images with --no-cache, check docker_image_build.log for details..."
-    service_list="multimodalqna multimodalqna-ui embedding-multimodal-bridgetower embedding-tei retriever-redis lvm-tgi lvm-llava-svc dataprep-multimodal-redis whisper"
+    service_list="multimodalqna multimodalqna-ui embedding-multimodal-bridgetower embedding retriever-redis lvm-tgi lvm-llava-svc dataprep-multimodal-redis whisper"
     docker compose -f build.yaml build ${service_list} --no-cache > ${LOG_PATH}/docker_image_build.log
 
     docker images && sleep 1m
@@ -150,19 +150,19 @@ function validate_microservices() {
         '{"text":"This is example", "img_b64_str": "iVBORw0KGgoAAAANSUhEUgAAAAoAAAAKCAYAAACNMs+9AAAAFUlEQVR42mP8/5+hnoEIwDiqkL4KAcT9GO0U4BxoAAAAAElFTkSuQmCC"}'
 
     # embedding microservice
-    echo "Validating embedding-tei"
+    echo "Validating embedding"
     validate_service \
         "http://${host_ip}:$MM_EMBEDDING_PORT_MICROSERVICE/v1/embeddings" \
         '"embedding":[' \
-        "embedding-tei" \
-        "embedding-tei" \
+        "embedding" \
+        "embedding" \
         '{"text" : "This is some sample text."}'
 
     validate_service \
         "http://${host_ip}:$MM_EMBEDDING_PORT_MICROSERVICE/v1/embeddings" \
         '"embedding":[' \
-        "embedding-tei" \
-        "embedding-tei" \
+        "embedding" \
+        "embedding" \
         '{"text": {"text" : "This is some sample text."}, "image" : {"url": "https://github.com/docarray/docarray/blob/main/tests/toydata/image-data/apple.png?raw=true"}}'
 
     sleep 1m # retrieval can't curl as expected, try to wait for more time

MultimodalQnA/tests/test_compose_on_xeon.sh

@@ -22,7 +22,7 @@ function build_docker_images() {
     cd $WORKPATH/docker_image_build
     git clone https://github.com/opea-project/GenAIComps.git && cd GenAIComps && git checkout "${opea_branch:-"main"}" && cd ../
     echo "Build all the images with --no-cache, check docker_image_build.log for details..."
-    service_list="multimodalqna multimodalqna-ui embedding-multimodal-bridgetower embedding-tei retriever-redis lvm-llava lvm-llava-svc dataprep-multimodal-redis whisper"
+    service_list="multimodalqna multimodalqna-ui embedding-multimodal-bridgetower embedding retriever-redis lvm-llava lvm-llava-svc dataprep-multimodal-redis whisper"
     docker compose -f build.yaml build ${service_list} --no-cache > ${LOG_PATH}/docker_image_build.log
 
     docker images && sleep 1m
@@ -142,19 +142,19 @@ function validate_microservices() {
         '{"text":"This is example", "img_b64_str": "iVBORw0KGgoAAAANSUhEUgAAAAoAAAAKCAYAAACNMs+9AAAAFUlEQVR42mP8/5+hnoEIwDiqkL4KAcT9GO0U4BxoAAAAAElFTkSuQmCC"}'
 
     # embedding microservice
-    echo "Validating embedding-tei"
+    echo "Validating embedding"
     validate_service \
         "http://${host_ip}:$MM_EMBEDDING_PORT_MICROSERVICE/v1/embeddings" \
         '"embedding":[' \
-        "embedding-tei" \
-        "embedding-tei" \
+        "embedding" \
+        "embedding" \
         '{"text" : "This is some sample text."}'
 
     validate_service \
         "http://${host_ip}:$MM_EMBEDDING_PORT_MICROSERVICE/v1/embeddings" \
         '"embedding":[' \
-        "embedding-tei" \
-        "embedding-tei" \
+        "embedding" \
+        "embedding" \
         '{"text": {"text" : "This is some sample text."}, "image" : {"url": "https://github.com/docarray/docarray/blob/main/tests/toydata/image-data/apple.png?raw=true"}}'
 
     sleep 1m # retrieval can't curl as expected, try to wait for more time

ProductivitySuite/docker_compose/intel/cpu/xeon/README.md

@@ -13,7 +13,7 @@ First of all, you need to build Docker Images locally and install the python pac
 ```bash
 git clone https://github.com/opea-project/GenAIComps.git
 cd GenAIComps
-docker build --no-cache -t opea/embedding-tei:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/embeddings/src/Dockerfile .
+docker build --no-cache -t opea/embedding:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/embeddings/src/Dockerfile .
 ```
 
 ### 2. Build Retriever Image

ProductivitySuite/docker_compose/intel/cpu/xeon/compose.yaml

@@ -52,8 +52,8 @@ services:
       timeout: 10s
       retries: 60
   embedding:
-    image: ${REGISTRY:-opea}/embedding-tei:${TAG:-latest}
-    container_name: embedding-tei-server
+    image: ${REGISTRY:-opea}/embedding:${TAG:-latest}
+    container_name: embedding-server
     depends_on:
       tei-embedding-service:
         condition: service_healthy

ProductivitySuite/docker_image_build/build.yaml

@@ -11,12 +11,12 @@ services:
       context: ../../ChatQnA/
       dockerfile: ./Dockerfile
     image: ${REGISTRY:-opea}/chatqna:${TAG:-latest}
-  embedding-tei:
+  embedding:
     build:
       context: GenAIComps
       dockerfile: comps/embeddings/src/Dockerfile
     extends: chatqna
-    image: ${REGISTRY:-opea}/embedding-tei:${TAG:-latest}
+    image: ${REGISTRY:-opea}/embedding:${TAG:-latest}
   retriever-redis:
     build:
       context: GenAIComps

ProductivitySuite/tests/test_compose_on_xeon.sh

@@ -169,7 +169,7 @@ function validate_microservices() {
         "${ip_address}:6000/v1/embeddings" \
         '"embedding":[' \
         "embedding-microservice" \
-        "embedding-tei-server" \
+        "embedding-server" \
         '{"input":"What is Deep Learning?"}'
 
     sleep 1m # retrieval can't curl as expected, try to wait for more time

SearchQnA/docker_compose/intel/cpu/xeon/README.md

@@ -9,7 +9,7 @@ This document outlines the deployment process for a SearchQnA application utiliz
 ```bash
 git clone https://github.com/opea-project/GenAIComps.git
 cd GenAIComps
-docker build --no-cache -t opea/embedding-tei:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/embeddings/src/Dockerfile .
+docker build --no-cache -t opea/embedding:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/embeddings/src/Dockerfile .
 ```
 
 ### 2. Build Retriever Image
@@ -51,7 +51,7 @@ docker build --no-cache -t opea/opea/searchqna-ui:latest --build-arg https_proxy
 
 Then run the command `docker images`, you will have following images ready:
 
-1. `opea/embedding-tei:latest`
+1. `opea/embedding:latest`
 2. `opea/web-retriever-chroma:latest`
 3. `opea/reranking-tei:latest`
 4. `opea/llm-textgen:latest`

SearchQnA/docker_compose/intel/cpu/xeon/compose.yaml

@@ -22,8 +22,8 @@ services:
       timeout: 10s
       retries: 60
   embedding:
-    image: ${REGISTRY:-opea}/embedding-tei:${TAG:-latest}
-    container_name: embedding-tei-server
+    image: ${REGISTRY:-opea}/embedding:${TAG:-latest}
+    container_name: embedding-server
     depends_on:
       tei-embedding-service:
         condition: service_healthy

SearchQnA/docker_compose/intel/hpu/gaudi/README.md

@@ -11,7 +11,7 @@ First of all, you need to build Docker Images locally. This step can be ignored
 ```bash
 git clone https://github.com/opea-project/GenAIComps.git
 cd GenAIComps
-docker build --no-cache -t opea/embedding-tei:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/embeddings/src/Dockerfile .
+docker build --no-cache -t opea/embedding:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/embeddings/src/Dockerfile .
 ```
 
 ### 2. Build Retriever Image
@@ -51,7 +51,7 @@ docker build --no-cache -t opea/searchqna:latest --build-arg https_proxy=$https_
 
 Then run the command `docker images`, you will have
 
-1. `opea/embedding-tei:latest`
+1. `opea/embedding:latest`
 2. `opea/web-retriever-chroma:latest`
 3. `opea/reranking-tei:latest`
 4. `opea/llm-textgen:latest`

SearchQnA/docker_compose/intel/hpu/gaudi/compose.yaml

@@ -30,8 +30,8 @@ services:
       timeout: 10s
       retries: 60
   embedding:
-    image: ${REGISTRY:-opea}/embedding-tei:${TAG:-latest}
-    container_name: embedding-tei-gaudi-server
+    image: ${REGISTRY:-opea}/embedding:${TAG:-latest}
+    container_name: embedding-gaudi-server
     depends_on:
       tei-embedding-service:
         condition: service_healthy

SearchQnA/docker_image_build/build.yaml

@@ -17,12 +17,12 @@ services:
       dockerfile: ./docker/Dockerfile
     extends: searchqna
     image: ${REGISTRY:-opea}/searchqna-ui:${TAG:-latest}
-  embedding-tei:
+  embedding:
     build:
       context: GenAIComps
       dockerfile: comps/embeddings/src/Dockerfile
     extends: searchqna
-    image: ${REGISTRY:-opea}/embedding-tei:${TAG:-latest}
+    image: ${REGISTRY:-opea}/embedding:${TAG:-latest}
   web-retriever-chroma:
     build:
       context: GenAIComps

SearchQnA/tests/test_compose_on_gaudi.sh

@@ -19,7 +19,7 @@ function build_docker_images() {
     git clone https://github.com/opea-project/GenAIComps.git && cd GenAIComps && git checkout "${opea_branch:-"main"}" && cd ../
 
     echo "Build all the images with --no-cache, check docker_image_build.log for details..."
-    service_list="searchqna searchqna-ui embedding-tei web-retriever-chroma reranking-tei llm-textgen"
+    service_list="searchqna searchqna-ui embedding web-retriever-chroma reranking-tei llm-textgen"
     docker compose -f build.yaml build ${service_list} --no-cache > ${LOG_PATH}/docker_image_build.log
 
     docker pull ghcr.io/huggingface/text-embeddings-inference:cpu-1.5
@@ -75,7 +75,7 @@ function validate_megaservice() {
     docker logs web-retriever-chroma-server > ${LOG_PATH}/web-retriever-chroma-server.log
     docker logs searchqna-gaudi-backend-server > ${LOG_PATH}/searchqna-gaudi-backend-server.log
     docker logs tei-embedding-gaudi-server > ${LOG_PATH}/tei-embedding-gaudi-server.log
-    docker logs embedding-tei-gaudi-server > ${LOG_PATH}/embedding-tei-gaudi-server.log
+    docker logs embedding-gaudi-server > ${LOG_PATH}/embedding-gaudi-server.log
 
     if [[ $result == *"capital"* ]]; then
         echo "Result correct."

SearchQnA/tests/test_compose_on_xeon.sh

@@ -19,7 +19,7 @@ function build_docker_images() {
     git clone https://github.com/opea-project/GenAIComps.git && cd GenAIComps && git checkout "${opea_branch:-"main"}" && cd ../
 
     echo "Build all the images with --no-cache, check docker_image_build.log for details..."
-    service_list="searchqna searchqna-ui embedding-tei web-retriever-chroma reranking-tei llm-textgen"
+    service_list="searchqna searchqna-ui embedding web-retriever-chroma reranking-tei llm-textgen"
     docker compose -f build.yaml build ${service_list} --no-cache > ${LOG_PATH}/docker_image_build.log
 
     docker pull ghcr.io/huggingface/text-embeddings-inference:cpu-1.5

docker_images_list.md

@@ -2,7 +2,7 @@
 
 A list of released OPEA docker images in https://hub.docker.com/, contains all relevant images from the GenAIExamples, GenAIComps and GenAIInfra projects. Please expect more public available images in the future release.
 
-Take ChatQnA for example. ChatQnA is a chatbot application service based on the Retrieval Augmented Generation (RAG) architecture. It consists of [opea/embedding-tei](https://hub.docker.com/r/opea/embedding-tei), [opea/retriever-redis](https://hub.docker.com/r/opea/retriever-redis), [opea/reranking-tei](https://hub.docker.com/r/opea/reranking-tei), [opea/llm-textgen](https://hub.docker.com/r/opea/llm-textgen), [opea/dataprep-redis](https://hub.docker.com/r/opea/dataprep-redis), [opea/chatqna](https://hub.docker.com/r/opea/chatqna), [opea/chatqna-ui](https://hub.docker.com/r/opea/chatqna-ui) and [opea/chatqna-conversation-ui](https://hub.docker.com/r/opea/chatqna-conversation-ui) (Optional) multiple microservices. Other services are similar, see the corresponding README for details.
+Take ChatQnA for example. ChatQnA is a chatbot application service based on the Retrieval Augmented Generation (RAG) architecture. It consists of [opea/embedding](https://hub.docker.com/r/opea/embedding), [opea/retriever-redis](https://hub.docker.com/r/opea/retriever-redis), [opea/reranking-tei](https://hub.docker.com/r/opea/reranking-tei), [opea/llm-textgen](https://hub.docker.com/r/opea/llm-textgen), [opea/dataprep-redis](https://hub.docker.com/r/opea/dataprep-redis), [opea/chatqna](https://hub.docker.com/r/opea/chatqna), [opea/chatqna-ui](https://hub.docker.com/r/opea/chatqna-ui) and [opea/chatqna-conversation-ui](https://hub.docker.com/r/opea/chatqna-conversation-ui) (Optional) multiple microservices. Other services are similar, see the corresponding README for details.
 
 ## Example images
 
@@ -57,10 +57,9 @@ Take ChatQnA for example. ChatQnA is a chatbot application service based on the
 | [opea/dataprep-vdms](https://hub.docker.com/r/opea/dataprep-vdms)                                                   | [Link](https://github.com/opea-project/GenAIComps/blob/main/comps/dataprep/vdms/langchain/Dockerfile)                                      | This docker image exposes an OPEA dataprep microservice based on VDMS vectordb for use by GenAI applications.                                                                                                              |
 | [opea/embedding-langchain-mosec](https://hub.docker.com/r/opea/embedding-langchain-mosec)                           | [Link](https://github.com/opea-project/GenAIComps/blob/main/comps/3rd_parties/nginx/src/Dockerfile)                                        | The docker image exposed the OPEA mosec embedding microservice base on Langchain framework for GenAI application use                                                                                                       |
 | [opea/embedding-multimodal-clip](https://hub.docker.com/r/opea/embedding-multimodal-clip)                           | [Link](https://github.com/opea-project/GenAIComps/blob/main/comps/embeddings/src/integrations/dependency/clip/Dockerfile)                  | The docker image exposes OPEA multimodal CLIP-based embedded microservices for use by GenAI applications                                                                                                                   |
-| [opea/embedding-tei](https://hub.docker.com/r/opea/embedding-tei)                                                   | [Link](https://github.com/opea-project/GenAIComps/blob/main/comps/embeddings/src/Dockerfile)                                               | The docker image exposes OPEA multimodal embedded microservices for use by GenAI applications                                                                                                                              |
+| [opea/embedding](https://hub.docker.com/r/opea/embedding)                                                           | [Link](https://github.com/opea-project/GenAIComps/blob/main/comps/embeddings/src/Dockerfile)                                               | The docker image exposes OPEA multimodal embedded microservices for use by GenAI applications                                                                                                                              |
 | [opea/embedding-multimodal-bridgetower](https://hub.docker.com/r/opea/embedding-multimodal-bridgetower)             | [Link](https://github.com/opea-project/GenAIComps/blob/main/comps/embeddings/src/integrations/dependency/bridgetower/Dockerfile)           | The docker image exposes OPEA multimodal embedded microservices based on bridgetower for use by GenAI applications                                                                                                         |
 | [opea/embedding-multimodal-bridgetower-gaudi](https://hub.docker.com/r/opea/embedding-multimodal-bridgetower-gaudi) | [Link](https://github.com/opea-project/GenAIComps/blob/main/comps/embeddings/src/integrations/dependency/bridgetower/Dockerfile.intel_hpu) | The docker image exposes OPEA multimodal embedded microservices based on bridgetower for use by GenAI applications on the Gaudi                                                                                            |
-| [opea/embedding-tei](https://hub.docker.com/r/opea/embedding-tei)                                                   | [Link](https://github.com/opea-project/GenAIComps/blob/main/comps/embeddings/src/Dockerfile)                                               | The docker image exposed the OPEA embedding microservice upon tei docker image for GenAI application use                                                                                                                   |
 | [opea/feedbackmanagement](https://hub.docker.com/r/opea/feedbackmanagement)                                         | [Link](https://github.com/opea-project/GenAIComps/blob/main/comps/feedback_management/mongo/Dockerfile)                                    | The docker image exposes that the OPEA feedback management microservice uses a MongoDB database for GenAI applications.                                                                                                    |
 | [opea/finetuning](https://hub.docker.com/r/opea/finetuning)                                                         | [Link](https://github.com/opea-project/GenAIComps/blob/main/comps/finetuning/Dockerfile)                                                   | The docker image exposed the OPEA Fine-tuning microservice for GenAI application use                                                                                                                                       |
 | [opea/finetuning-gaudi](https://hub.docker.com/r/opea/finetuning-gaudi)                                             | [Link](https://github.com/opea-project/GenAIComps/blob/main/comps/finetuning/Dockerfile.intel_hpu)                                         | The docker image exposed the OPEA Fine-tuning microservice for GenAI application use on the Gaudi                                                                                                                          |