Update TEI docker image to 1.6 (opea-project#1453)

xiguiw · web-flow · commit 0672112936d4 · 2025-03-27T13:24:56.000+08:00
update TEI docker image to ghcr.io/huggingface/text-embeddings-inference:cpu-1.6

Signed-off-by: Wang, Xigui &lt;xigui.wang@intel.com&gt;
diff --git a/comps/dataprep/src/README_finance.md b/comps/dataprep/src/README_finance.md
@@ -29,7 +29,7 @@ First, you need to start a TEI service.
 ```bash
 your_port=6006
 model="BAAI/bge-base-en-v1.5"
-docker run -p $your_port:80 -v ./data:/data --name tei_server -e http_proxy=$http_proxy -e https_proxy=$https_proxy --pull always ghcr.io/huggingface/text-embeddings-inference:cpu-1.5 --model-id $model
+docker run -p $your_port:80 -v ./data:/data --name tei_server -e http_proxy=$http_proxy -e https_proxy=$https_proxy --pull always ghcr.io/huggingface/text-embeddings-inference:cpu-1.6 --model-id $model
 ```
 
 Then you need to test your TEI service using the following commands:
diff --git a/comps/dataprep/src/README_milvus.md b/comps/dataprep/src/README_milvus.md
@@ -26,7 +26,7 @@ First, start the TEI embedding server.
 ```bash
 your_port=6010
 model="BAAI/bge-base-en-v1.5"
-docker run -p $your_port:80 -v ./data:/data --name tei_server -e http_proxy=$http_proxy -e https_proxy=$https_proxy --pull always ghcr.io/huggingface/text-embeddings-inference:cpu-1.5 --model-id $model
+docker run -p $your_port:80 -v ./data:/data --name tei_server -e http_proxy=$http_proxy -e https_proxy=$https_proxy --pull always ghcr.io/huggingface/text-embeddings-inference:cpu-1.6 --model-id $model
 export TEI_EMBEDDING_ENDPOINT="http://localhost:$your_port"
 ```
 
diff --git a/comps/dataprep/src/README_opensearch.md b/comps/dataprep/src/README_opensearch.md
@@ -26,7 +26,7 @@ First, you need to start a TEI service.
 ```bash
 your_port=6006
 model="BAAI/bge-base-en-v1.5"
-docker run -p $your_port:80 -v ./data:/data --name tei_server -e http_proxy=$http_proxy -e https_proxy=$https_proxy --pull always ghcr.io/huggingface/text-embeddings-inference:cpu-1.5 --model-id $model
+docker run -p $your_port:80 -v ./data:/data --name tei_server -e http_proxy=$http_proxy -e https_proxy=$https_proxy --pull always ghcr.io/huggingface/text-embeddings-inference:cpu-1.6 --model-id $model
 ```
 
 Then you need to test your TEI service using the following commands:
diff --git a/comps/dataprep/src/README_redis.md b/comps/dataprep/src/README_redis.md
@@ -23,7 +23,7 @@ First, you need to start a TEI service.
 ```bash
 your_port=6006
 model="BAAI/bge-base-en-v1.5"
-docker run -p $your_port:80 -v ./data:/data --name tei_server -e http_proxy=$http_proxy -e https_proxy=$https_proxy --pull always ghcr.io/huggingface/text-embeddings-inference:cpu-1.5 --model-id $model
+docker run -p $your_port:80 -v ./data:/data --name tei_server -e http_proxy=$http_proxy -e https_proxy=$https_proxy --pull always ghcr.io/huggingface/text-embeddings-inference:cpu-1.6 --model-id $model
 ```
 
 Then you need to test your TEI service using the following commands:
diff --git a/comps/embeddings/src/README_tei.md b/comps/embeddings/src/README_tei.md
@@ -16,7 +16,7 @@ This guide walks you through starting, deploying, and consuming the **TEI-based
    model="BAAI/bge-large-en-v1.5"
    docker run -p $your_port:80 -v ./data:/data --name tei-embedding-serving \
    -e http_proxy=$http_proxy -e https_proxy=$https_proxy --pull always \
-   ghcr.io/huggingface/text-embeddings-inference:cpu-1.5 --model-id $model
+   ghcr.io/huggingface/text-embeddings-inference:cpu-1.6 --model-id $model
    ```
 
 2. **Test the TEI service**:
diff --git a/comps/rerankings/src/README_tei.md b/comps/rerankings/src/README_tei.md
@@ -31,7 +31,7 @@ This README provides set-up instructions and comprehensive details regarding the
     export RERANK_MODEL_ID="BAAI/bge-reranker-base"
     export volume=$PWD/data
 
-    docker run -d -p 12005:80 -v $volume:/data -e http_proxy=$http_proxy -e https_proxy=$https_proxy --pull always ghcr.io/huggingface/text-embeddings-inference:cpu-1.5 --model-id $RERANK_MODEL_ID --hf-api-token $HF_TOKEN --auto-truncate
+    docker run -d -p 12005:80 -v $volume:/data -e http_proxy=$http_proxy -e https_proxy=$https_proxy --pull always ghcr.io/huggingface/text-embeddings-inference:cpu-1.6 --model-id $RERANK_MODEL_ID --hf-api-token $HF_TOKEN --auto-truncate
   ```
 
 2. **Verify the TEI Service**:
diff --git a/comps/retrievers/src/README_elasticsearch.md b/comps/retrievers/src/README_elasticsearch.md
@@ -28,7 +28,7 @@ pip install -r requirements.txt
 ```bash
 model=BAAI/bge-base-en-v1.5
 volume=$PWD/data
-docker run -d -p 6060:80 -v $volume:/data -e http_proxy=$http_proxy -e https_proxy=$https_proxy --pull always ghcr.io/huggingface/text-embeddings-inference:cpu-1.5 --model-id $model
+docker run -d -p 6060:80 -v $volume:/data -e http_proxy=$http_proxy -e https_proxy=$https_proxy --pull always ghcr.io/huggingface/text-embeddings-inference:cpu-1.6 --model-id $model
 ```
 
 ### 1.3 Verify the TEI Service
diff --git a/comps/retrievers/src/README_opensearch.md b/comps/retrievers/src/README_opensearch.md
@@ -21,7 +21,7 @@ pip install -r requirements.txt
 ```bash
 model=BAAI/bge-base-en-v1.5
 volume=$PWD/data
-docker run -d -p 6060:80 -v $volume:/data -e http_proxy=$http_proxy -e https_proxy=$https_proxy --pull always ghcr.io/huggingface/text-embeddings-inference:cpu-1.5 --model-id $model
+docker run -d -p 6060:80 -v $volume:/data -e http_proxy=$http_proxy -e https_proxy=$https_proxy --pull always ghcr.io/huggingface/text-embeddings-inference:cpu-1.6 --model-id $model
 ```
 
 ### 1.3 Verify the TEI Service
diff --git a/comps/retrievers/src/README_pathway.md b/comps/retrievers/src/README_pathway.md
@@ -17,7 +17,7 @@ model=BAAI/bge-base-en-v1.5
 export TEI_EMBEDDING_ENDPOINT="http://${your_ip}:6060"  # if you want to use the hosted embedding service, example: "http://127.0.0.1:6060"
 
 # then run:
-docker run -p 6060:80 -e http_proxy=$http_proxy -e https_proxy=$https_proxy --pull always ghcr.io/huggingface/text-embeddings-inference:cpu-1.5 --model-id $model
+docker run -p 6060:80 -e http_proxy=$http_proxy -e https_proxy=$https_proxy --pull always ghcr.io/huggingface/text-embeddings-inference:cpu-1.6 --model-id $model
 ```
 
 Health check the embedding service with:
diff --git a/comps/retrievers/src/README_pgvector.md b/comps/retrievers/src/README_pgvector.md
@@ -21,7 +21,7 @@ pip install -r requirements.txt
 ```bash
 model=BAAI/bge-base-en-v1.5
 volume=$PWD/data
-docker run -d -p 6060:80 -v $volume:/data -e http_proxy=$http_proxy -e https_proxy=$https_proxy --pull always ghcr.io/huggingface/text-embeddings-inference:cpu-1.5 --model-id $model
+docker run -d -p 6060:80 -v $volume:/data -e http_proxy=$http_proxy -e https_proxy=$https_proxy --pull always ghcr.io/huggingface/text-embeddings-inference:cpu-1.6 --model-id $model
 ```
 
 ### 1.3 Verify the TEI Service
diff --git a/comps/retrievers/src/README_redis.md b/comps/retrievers/src/README_redis.md
@@ -21,7 +21,7 @@ pip install -r requirements.txt
 ```bash
 model=BAAI/bge-base-en-v1.5
 volume=$PWD/data
-docker run -d -p 6060:80 -v $volume:/data -e http_proxy=$http_proxy -e https_proxy=$https_proxy --pull always ghcr.io/huggingface/text-embeddings-inference:cpu-1.5 --model-id $model
+docker run -d -p 6060:80 -v $volume:/data -e http_proxy=$http_proxy -e https_proxy=$https_proxy --pull always ghcr.io/huggingface/text-embeddings-inference:cpu-1.6 --model-id $model
 ```
 
 ### 1.3 Verify the TEI Service
diff --git a/comps/retrievers/src/README_vdms.md b/comps/retrievers/src/README_vdms.md
@@ -38,7 +38,7 @@ pip install -r requirements.txt
 ```bash
 model=BAAI/bge-base-en-v1.5
 volume=$PWD/data
-docker run -d -p 6060:80 -v $volume:/data -e http_proxy=$http_proxy -e https_proxy=$https_proxy --pull always ghcr.io/huggingface/text-embeddings-inference:cpu-1.5 --model-id $model
+docker run -d -p 6060:80 -v $volume:/data -e http_proxy=$http_proxy -e https_proxy=$https_proxy --pull always ghcr.io/huggingface/text-embeddings-inference:cpu-1.6 --model-id $model
 ```
 
 ### 1.3 Verify the TEI Service
diff --git a/comps/third_parties/tei/deployment/docker_compose/compose.yaml b/comps/third_parties/tei/deployment/docker_compose/compose.yaml
@@ -3,7 +3,7 @@
 
 services:
   tei-embedding-serving:
-    image: ghcr.io/huggingface/text-embeddings-inference:cpu-1.5
+    image: ghcr.io/huggingface/text-embeddings-inference:cpu-1.6
     container_name: tei-embedding-serving
     entrypoint: /bin/sh -c "apt-get update && apt-get install -y curl && text-embeddings-router --json-output --model-id ${EMBEDDING_MODEL_ID} --auto-truncate"
     ports:
@@ -24,7 +24,7 @@ services:
       retries: 48
 
   tei-reranking-serving:
-    image: ghcr.io/huggingface/text-embeddings-inference:cpu-1.5
+    image: ghcr.io/huggingface/text-embeddings-inference:cpu-1.6
     container_name: tei-reranking-serving
     entrypoint: /bin/sh -c "apt-get update && apt-get install -y curl && text-embeddings-router --json-output --model-id ${RERANK_MODEL_ID} --auto-truncate"
     ports:
diff --git a/comps/web_retrievers/deployment/docker_compose/compose.yaml b/comps/web_retrievers/deployment/docker_compose/compose.yaml
@@ -21,7 +21,7 @@ services:
       tei-embedding-service:
         condition: service_healthy
   tei-embedding-service:
-    image: ghcr.io/huggingface/text-embeddings-inference:cpu-1.5
+    image: ghcr.io/huggingface/text-embeddings-inference:cpu-1.6
     container_name: tei-embedding-server
     entrypoint: /bin/sh -c "apt-get update && apt-get install -y curl && text-embeddings-router --json-output --model-id ${EMBEDDING_MODEL_ID} --auto-truncate"
     ports:
diff --git a/comps/web_retrievers/src/README.md b/comps/web_retrievers/src/README.md
@@ -16,7 +16,7 @@ docker build -t opea/web-retriever:latest --build-arg https_proxy=$https_proxy -
 ```bash
 model=BAAI/bge-base-en-v1.5
 volume=$PWD/data
-docker run -d -p 6060:80 -v $volume:/data -e http_proxy=$http_proxy -e https_proxy=$https_proxy --pull always ghcr.io/huggingface/text-embeddings-inference:cpu-1.5 --model-id $model --auto-truncate
+docker run -d -p 6060:80 -v $volume:/data -e http_proxy=$http_proxy -e https_proxy=$https_proxy --pull always ghcr.io/huggingface/text-embeddings-inference:cpu-1.6 --model-id $model --auto-truncate
 ```
 
 ### 1.3 Start Web Retriever Service
diff --git a/tests/cores/mega/ChatQnA_E2E_manifests_base.yaml b/tests/cores/mega/ChatQnA_E2E_manifests_base.yaml
@@ -131,7 +131,7 @@ spec:
         envFrom:
         - configMapRef:
             name: qna-config
-        image: ghcr.io/huggingface/text-embeddings-inference:cpu-1.5
+        image: ghcr.io/huggingface/text-embeddings-inference:cpu-1.6
         imagePullPolicy: IfNotPresent
         name: embedding-server-deploy
         ports:
diff --git a/tests/cores/mega/mega.yaml b/tests/cores/mega/mega.yaml
@@ -19,7 +19,7 @@ micro_services:
     dependencies:
       - redis-vector-db
   - service_name: embedding-server
-    image: ghcr.io/huggingface/text-embeddings-inference:cpu-1.5
+    image: ghcr.io/huggingface/text-embeddings-inference:cpu-1.6
     ports:
       - "8090:80"
     volumes:
diff --git a/tests/dataprep/test_dataprep_neo4j_on_intel_hpu.sh b/tests/dataprep/test_dataprep_neo4j_on_intel_hpu.sh
@@ -22,7 +22,7 @@ function build_docker_images() {
         echo "opea/dataprep built successful"
     fi
     docker pull ghcr.io/huggingface/tgi-gaudi:2.3.1
-    docker pull ghcr.io/huggingface/text-embeddings-inference:cpu-1.5
+    docker pull ghcr.io/huggingface/text-embeddings-inference:cpu-1.6
 }
 
 function start_service() {
diff --git a/tests/retrievers/test_retrievers_neo4j_on_intel_hpu.sh b/tests/retrievers/test_retrievers_neo4j_on_intel_hpu.sh
@@ -36,7 +36,7 @@ function build_docker_images() {
     fi
 
     docker pull ghcr.io/huggingface/tgi-gaudi:2.3.1
-    docker pull ghcr.io/huggingface/text-embeddings-inference:cpu-1.5
+    docker pull ghcr.io/huggingface/text-embeddings-inference:cpu-1.6
 }
 
 function start_service() {
diff --git a/tests/third_parties/test_third_parties_pathway.sh b/tests/third_parties/test_third_parties_pathway.sh
@@ -29,7 +29,7 @@ function start_service() {
     # tei endpoint
     tei_endpoint=5436
     model="BAAI/bge-base-en-v1.5"
-    docker run -d --name="test-comps-vectorstore-pathway-tei-endpoint" -e http_proxy=$http_proxy -e https_proxy=$https_proxy -p $tei_endpoint:80 -v $DATA_PATH:/data --pull always ghcr.io/huggingface/text-embeddings-inference:cpu-1.5 --model-id $model
+    docker run -d --name="test-comps-vectorstore-pathway-tei-endpoint" -e http_proxy=$http_proxy -e https_proxy=$https_proxy -p $tei_endpoint:80 -v $DATA_PATH:/data --pull always ghcr.io/huggingface/text-embeddings-inference:cpu-1.6 --model-id $model
 
     sleep 30s
     export TEI_EMBEDDING_ENDPOINT="http://${ip_address}:${tei_endpoint}"
