Update Multimodal Docker File Path

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

@@ -124,7 +124,7 @@ docker build --no-cache -t opea/embedding-multimodal:latest --build-arg https_pr
 ### 2. Build retriever-multimodal-redis Image
 
 ```bash
-docker build --no-cache -t opea/retriever-multimodal-redis:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/retrievers/multimodal/redis/langchain/Dockerfile .
+docker build --no-cache -t opea/retriever-redis:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/retrievers/redis/langchain/Dockerfile .
 ```
 
 ### 3. Build LVM Images

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

@@ -74,9 +74,9 @@ services:
       MMEI_EMBEDDING_ENDPOINT: ${MMEI_EMBEDDING_ENDPOINT}
       MM_EMBEDDING_PORT_MICROSERVICE: ${MM_EMBEDDING_PORT_MICROSERVICE}
     restart: unless-stopped
-  retriever-multimodal-redis:
-    image: ${REGISTRY:-opea}/retriever-multimodal-redis:${TAG:-latest}
-    container_name: retriever-multimodal-redis
+  retriever-redis:
+    image: ${REGISTRY:-opea}/retriever-redis:${TAG:-latest}
+    container_name: retriever-redis
     depends_on:
       - redis-vector-db
     ports:
@@ -88,6 +88,7 @@ services:
       https_proxy: ${https_proxy}
       REDIS_URL: ${REDIS_URL}
       INDEX_NAME: ${INDEX_NAME}
+      BRIDGE_TOWER_EMBEDDING: ${BRIDGE_TOWER_EMBEDDING}
     restart: unless-stopped
   lvm-llava:
     image: ${REGISTRY:-opea}/lvm-llava:${TAG:-latest}
@@ -121,7 +122,7 @@ services:
       - redis-vector-db
       - dataprep-multimodal-redis
       - embedding-multimodal
-      - retriever-multimodal-redis
+      - retriever-redis
       - lvm-llava-svc
       - asr
     ports:

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

@@ -75,7 +75,7 @@ docker build --no-cache -t opea/embedding-multimodal:latest --build-arg https_pr
 ### 2. Build retriever-multimodal-redis Image
 
 ```bash
-docker build --no-cache -t opea/retriever-multimodal-redis:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/retrievers/multimodal/redis/langchain/Dockerfile .
+docker build --no-cache -t opea/retriever-redis:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/retrievers/redis/langchain/Dockerfile .
 ```
 
 ### 3. Build LVM Images

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

@@ -74,9 +74,9 @@ services:
       MMEI_EMBEDDING_ENDPOINT: ${MMEI_EMBEDDING_ENDPOINT}
       MM_EMBEDDING_PORT_MICROSERVICE: ${MM_EMBEDDING_PORT_MICROSERVICE}
     restart: unless-stopped
-  retriever-multimodal-redis:
-    image: ${REGISTRY:-opea}/retriever-multimodal-redis:${TAG:-latest}
-    container_name: retriever-multimodal-redis
+  retriever-redis:
+    image: ${REGISTRY:-opea}/retriever-redis:${TAG:-latest}
+    container_name: retriever-redis
     depends_on:
       - redis-vector-db
     ports:
@@ -88,6 +88,7 @@ services:
       https_proxy: ${https_proxy}
       REDIS_URL: ${REDIS_URL}
       INDEX_NAME: ${INDEX_NAME}
+      BRIDGE_TOWER_EMBEDDING: ${BRIDGE_TOWER_EMBEDDING}
     restart: unless-stopped
   tgi-gaudi:
     image: ghcr.io/huggingface/tgi-gaudi:2.0.6
@@ -138,7 +139,7 @@ services:
       - redis-vector-db
       - dataprep-multimodal-redis
       - embedding-multimodal
-      - retriever-multimodal-redis
+      - retriever-redis
       - lvm-tgi
       - asr
     ports:

MultimodalQnA/docker_image_build/build.yaml

@@ -29,12 +29,12 @@ services:
       dockerfile: comps/embeddings/multimodal/multimodal_langchain/Dockerfile
     extends: multimodalqna
     image: ${REGISTRY:-opea}/embedding-multimodal:${TAG:-latest}
-  retriever-multimodal-redis:
+  retriever-redis:
     build:
       context: GenAIComps
-      dockerfile: comps/retrievers/multimodal/redis/langchain/Dockerfile
+      dockerfile: comps/retrievers/redis/langchain/Dockerfile
     extends: multimodalqna
-    image: ${REGISTRY:-opea}/retriever-multimodal-redis:${TAG:-latest}
+    image: ${REGISTRY:-opea}/retriever-redis:${TAG:-latest}
   lvm-llava:
     build:
       context: GenAIComps

MultimodalQnA/multimodalqna.py

@@ -54,7 +54,7 @@ def add_remote_service(self):
             name="retriever",
             host=MM_RETRIEVER_SERVICE_HOST_IP,
             port=MM_RETRIEVER_SERVICE_PORT,
-            endpoint="/v1/multimodal_retrieval",
+            endpoint="/v1/retrieval",
             use_remote_service=True,
             service_type=ServiceType.RETRIEVER,
         )

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-multimodal retriever-multimodal-redis lvm-tgi dataprep-multimodal-redis whisper asr"
+    service_list="multimodalqna multimodalqna-ui embedding-multimodal-bridgetower embedding-multimodal retriever-redis lvm-tgi dataprep-multimodal-redis whisper asr"
     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
@@ -41,6 +41,7 @@ function setup_env() {
     export REDIS_URL="redis://${host_ip}:6379"
     export REDIS_HOST=${host_ip}
     export INDEX_NAME="mm-rag-redis"
+    export BRIDGE_TOWER_EMBEDDING=true
     export LLAVA_SERVER_PORT=8399
     export LVM_ENDPOINT="http://${host_ip}:8399"
     export EMBEDDING_MODEL_ID="BridgeTower/bridgetower-large-itm-mlm-itc"
@@ -192,13 +193,13 @@ function validate_microservices() {
     sleep 1m
 
     # multimodal retrieval microservice
-    echo "Validating retriever-multimodal-redis"
+    echo "Validating retriever-redis"
     your_embedding=$(python3 -c "import random; embedding = [random.uniform(-1, 1) for _ in range(512)]; print(embedding)")
     validate_service \
-        "http://${host_ip}:7000/v1/multimodal_retrieval" \
+        "http://${host_ip}:7000/v1/retrieval" \
         "retrieved_docs" \
-        "retriever-multimodal-redis" \
-        "retriever-multimodal-redis" \
+        "retriever-redis" \
+        "retriever-redis" \
         "{\"text\":\"test\",\"embedding\":${your_embedding}}"
 
     sleep 3m

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-multimodal retriever-multimodal-redis lvm-llava lvm-llava-svc dataprep-multimodal-redis whisper asr"
+    service_list="multimodalqna multimodalqna-ui embedding-multimodal-bridgetower embedding-multimodal retriever-redis lvm-llava lvm-llava-svc dataprep-multimodal-redis whisper asr"
     docker compose -f build.yaml build ${service_list} --no-cache > ${LOG_PATH}/docker_image_build.log
 
     docker images && sleep 1m
@@ -39,6 +39,7 @@ function setup_env() {
     export REDIS_URL="redis://${host_ip}:6379"
     export REDIS_HOST=${host_ip}
     export INDEX_NAME="mm-rag-redis"
+    export BRIDGE_TOWER_EMBEDDING=true
     export LLAVA_SERVER_PORT=8399
     export LVM_ENDPOINT="http://${host_ip}:8399"
     export LVM_MODEL_ID="llava-hf/llava-1.5-7b-hf"
@@ -190,13 +191,13 @@ function validate_microservices() {
     sleep 1m
 
     # multimodal retrieval microservice
-    echo "Validating retriever-multimodal-redis"
+    echo "Validating retriever-redis"
     your_embedding=$(python3 -c "import random; embedding = [random.uniform(-1, 1) for _ in range(512)]; print(embedding)")
     validate_service \
-        "http://${host_ip}:7000/v1/multimodal_retrieval" \
+        "http://${host_ip}:7000/v1/retrieval" \
         "retrieved_docs" \
-        "retriever-multimodal-redis" \
-        "retriever-multimodal-redis" \
+        "retriever-redis" \
+        "retriever-redis" \
         "{\"text\":\"test\",\"embedding\":${your_embedding}}"
 
     sleep 3m

docker_images_list.md

@@ -91,7 +91,6 @@ Take ChatQnA for example. ChatQnA is a chatbot application service based on the
 | [opea/reranking-langchain-mosec-endpoint](https://hub.docker.com/r/opea/reranking-langchain-mosec-endpoint)         | [Link](https://github.com/opea-project/GenAIComps/blob/main/comps/reranks/mosec/langchain/dependency/Dockerfile)          | The docker image exposed the OPEA mosec reranking endpoint microservice base on Langchain framework for GenAI application use                                                                                              |
 | [opea/reranking-tei](https://hub.docker.com/r/opea/reranking-tei)                                                   | [Link](https://github.com/opea-project/GenAIComps/blob/main/comps/reranks/tei/Dockerfile)                                 | The docker image exposed the OPEA reranking microservice based on tei docker image for GenAI application use                                                                                                               |
 | [opea/retriever-milvus](https://hub.docker.com/r/opea/retriever-milvus)                                             | [Link](https://github.com/opea-project/GenAIComps/blob/main/comps/retrievers/milvus/langchain/Dockerfile)                 | The docker image exposed the OPEA retrieval microservice based on milvus vectordb for GenAI application use                                                                                                                |
-| [opea/retriever-multimodal-redis](https://hub.docker.com/r/opea/retriever-multimodal-redis)                         | [Link](https://github.com/opea-project/GenAIComps/blob/main/comps/retrievers/multimodal/redis/langchain/Dockerfile)       | The docker image exposed the OPEA retrieval microservice based on multimodal redis vectordb for GenAI application use                                                                                                      |
 | [opea/retriever-pathway](https://hub.docker.com/r/opea/retriever-pathway)                                           | [Link](https://github.com/opea-project/GenAIComps/blob/main/comps/retrievers/pathway/langchain/Dockerfile)                | The docker image exposed the OPEA retrieval microservice with pathway for GenAI application use                                                                                                                            |
 | [opea/retriever-pgvector](https://hub.docker.com/r/opea/retriever-pgvector)                                         | [Link](https://github.com/opea-project/GenAIComps/blob/main/comps/retrievers/pgvector/langchain/Dockerfile)               | The docker image exposed the OPEA retrieval microservice based on pgvector vectordb for GenAI application use                                                                                                              |
 | [opea/retriever-pinecone](https://hub.docker.com/r/opea/retriever-pinecone)                                         | [Link](https://github.com/opea-project/GenAIComps/blob/main/comps/retrievers/pinecone/langchain/Dockerfile)               | The docker image exposed the OPEA retrieval microservice based on pinecone vectordb for GenAI application use                                                                                                              |