Merge branch 'reorg' of https://github.com/opea-project/GenAIComps in…

…to reorg

.github/workflows/pr-dockerfile-path-scan.yaml

@@ -71,7 +71,7 @@ jobs:
           if [[ "$is_use" == "TRUE" ]]; then
             echo "Warning: Changed Dockerfile paths:"
             echo "$used_files"
-            echo "Please modify the corresponding README in GenAIComps and ask suyue.chen@intel.com for final confirmation."
+            echo "Please modify the corresponding README in GenAIComps."
             exit 1
           fi
 
@@ -90,6 +90,7 @@ jobs:
         run: |
           cd ..
           git clone https://github.com/opea-project/GenAIExamples
+          cd GenAIExamples && git checkout refactor_folder && cd ../  # for test only
 
       - name: Check for changed Dockerfile paths
         run: |

.github/workflows/pr-examples-test.yml

@@ -4,7 +4,7 @@
 name: Example-test
 
 on:
-  pull_request_target:
+  pull_request:
     branches: [main]
     types: [opened, reopened, ready_for_review, synchronize] # added `ready_for_review` since draft is skipped
     paths:
@@ -44,22 +44,23 @@ jobs:
         run: |
           cd ../ && sudo rm -rf GenAIExamples
           git clone https://github.com/opea-project/GenAIExamples.git
-          cd GenAIExamples/ChatQnA/docker
+          cd GenAIExamples && git checkout refactor_folder && cd ../  # for test only
+          cd GenAIExamples/ChatQnA/docker_image_build
           cp -r ${{ github.workspace }}/../GenAIComps .
 
           cd ../tests
-          sed -i '/GenAIComps.git/d' test_chatqna_on_gaudi.sh
-          cat test_chatqna_on_gaudi.sh
+          sed -i '/GenAIComps.git/d' test_compose_on_gaudi.sh
+          cat test_compose_on_gaudi.sh
 
           echo "Run test..."
           echo "LOG_DIR=$(pwd)" >> $GITHUB_ENV
           export IMAGE_TAG="comps"
-          timeout 50m bash test_chatqna_on_gaudi.sh
+          timeout 50m bash test_compose_on_gaudi.sh
 
       - name: Clean up container
         if: cancelled() || failure()
         run: |
-          cd ${{ github.workspace }}/../GenAIExamples/ChatQnA/docker/gaudi
+          cd ${{ github.workspace }}/../GenAIExamples/ChatQnA/docker_compose/intel/hpu/gaudi
           docker compose stop && docker compose rm -f
           docker system prune -f
 

.github/workflows/pr-microservice-test.yml

@@ -5,7 +5,7 @@ name: MicroService-test
 
 on:
   pull_request:
-    branches: ["main", "*rc"]
+    branches: ["main", "*rc", "reorg"]
     types: [opened, reopened, ready_for_review, synchronize] # added `ready_for_review` since draft is skipped
     paths:
       - comps/**

comps/embeddings/neural-speed/README.md

@@ -9,7 +9,7 @@ docker build --build-arg http_proxy=$http_proxy --build-arg https_proxy=$https_p
 ## build embedding microservice docker image
 
 ```
-docker build --build-arg http_proxy=$http_proxy --build-arg https_proxy=$https_proxy -t opea/embedding-langchain-mosec:neuralspeed -f comps/embeddings/neural-speed/docker/Dockerfile .
+docker build --build-arg http_proxy=$http_proxy --build-arg https_proxy=$https_proxy -t opea/embedding-langchain-mosec:neuralspeed -f comps/embeddings/neural-speed/Dockerfile .
 ```
 
 Note: Please contact us to request model files before building images.

comps/intent_detection/langchain/intent_detection.py

@@ -5,9 +5,9 @@
 
 from langchain import LLMChain, PromptTemplate
 from langchain_community.llms import HuggingFaceEndpoint
+from template import IntentTemplate
 
 from comps import GeneratedDoc, LLMParamsDoc, ServiceType, opea_microservices, register_microservice
-from template import IntentTemplate
 
 
 @register_microservice(
@@ -31,7 +31,8 @@ def llm_generate(input: LLMParamsDoc):
         timeout=600,
     )
 
-    prompt = PromptTemplate(template=IntentTemplate.generate_intent_template, input_variables=["query"])
+    prompt_template = 'Please identify the intent of the user query. You may only respond with "chitchat" or \QA" without explanations or engaging in conversation.### User Query: {query}, ### Response: '
+    prompt = PromptTemplate(template=prompt_template, input_variables=["query"])
 
     llm_chain = LLMChain(prompt=prompt, llm=llm)
 

comps/intent_detection/langchain/requirements.txt

@@ -7,3 +7,4 @@ opentelemetry-exporter-otlp
 opentelemetry-sdk
 prometheus-fastapi-instrumentator
 shortuuid
+uvicorn

comps/reranks/video-rag-qna/README.md

@@ -10,7 +10,7 @@ For the `VideoRAGQnA` usecase, during the data preparation phase, frames are ext
 
 ```bash
 cd GenAIComps
-docker build --no-cache -t opea/reranking-videoragqna:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy  -f comps/reranks/video-rag-qna/docker/Dockerfile .
+docker build --no-cache -t opea/reranking-videoragqna:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy  -f comps/reranks/video-rag-qna/Dockerfile .
 ```
 
 ### 1.2 Start Rerank Service

comps/retrievers/multimodal/redis/langchain/README.md

@@ -51,7 +51,7 @@ export INDEX_NAME=${your_index_name}
 
 ```bash
 cd ../../../../
-docker build -t opea/multimodal-retriever-redis:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/retrievers/langchain/redis_multimodal/docker/Dockerfile .
+docker build -t opea/multimodal-retriever-redis:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/retrievers/multimodal/redis/langchain/Dockerfile .
 ```
 
 To start a docker container, you have two options:

tests/agent/test_agent_langchain_on_intel_hpu.sh

@@ -50,36 +50,36 @@ function start_tgi_service() {
 
 function start_react_langchain_agent_service() {
     echo "Starting react_langchain agent microservice"
-    docker run -d --runtime=runc --name="comps-agent-endpoint" -v $WORKPATH/comps/agent/langchain/tools:/home/user/comps/agent/langchain/tools -p 5042:9090 --ipc=host -e HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN} -e model=${model} -e strategy=react_langchain -e llm_endpoint_url=http://${ip_address}:${tgi_port} -e llm_engine=tgi -e recursion_limit=10 -e require_human_feedback=false -e tools=/home/user/comps/agent/langchain/tools/custom_tools.yaml opea/comps-agent-langchain:comps
+    docker run -d --runtime=runc --name="test-comps-agent-endpoint" -v $WORKPATH/comps/agent/langchain/tools:/home/user/comps/agent/langchain/tools -p 5042:9090 --ipc=host -e HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN} -e model=${model} -e strategy=react_langchain -e llm_endpoint_url=http://${ip_address}:${tgi_port} -e llm_engine=tgi -e recursion_limit=10 -e require_human_feedback=false -e tools=/home/user/comps/agent/langchain/tools/custom_tools.yaml opea/comps-agent-langchain:comps
     sleep 5s
 
-    docker logs comps-agent-endpoint
+    docker logs test-comps-agent-endpoint
     echo "Service started successfully"
 }
 
 
 function start_react_langgraph_agent_service() {
     echo "Starting react_langgraph agent microservice"
-    docker run -d --runtime=runc --name="comps-agent-endpoint" -v $WORKPATH/comps/agent/langchain/tools:/home/user/comps/agent/langchain/tools -p 5042:9090 --ipc=host -e HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN} -e model=${model} -e strategy=react_langgraph -e llm_endpoint_url=http://${ip_address}:${tgi_port} -e llm_engine=tgi -e recursion_limit=10 -e require_human_feedback=false -e tools=/home/user/comps/agent/langchain/tools/custom_tools.yaml opea/comps-agent-langchain:comps
+    docker run -d --runtime=runc --name="test-comps-agent-endpoint" -v $WORKPATH/comps/agent/langchain/tools:/home/user/comps/agent/langchain/tools -p 5042:9090 --ipc=host -e HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN} -e model=${model} -e strategy=react_langgraph -e llm_endpoint_url=http://${ip_address}:${tgi_port} -e llm_engine=tgi -e recursion_limit=10 -e require_human_feedback=false -e tools=/home/user/comps/agent/langchain/tools/custom_tools.yaml opea/comps-agent-langchain:comps
     sleep 5s
-    docker logs comps-agent-endpoint
+    docker logs test-comps-agent-endpoint
     echo "Service started successfully"
 }
 
 function start_react_langgraph_agent_service_openai() {
     echo "Starting react_langgraph agent microservice"
-    docker run -d --runtime=runc --name="comps-agent-endpoint" -v $WORKPATH/comps/agent/langchain/tools:/home/user/comps/agent/langchain/tools -p 5042:9090 --ipc=host -e model=gpt-4o-mini-2024-07-18 -e strategy=react_langgraph -e llm_engine=openai -e OPENAI_API_KEY=${OPENAI_API_KEY} -e recursion_limit=10 -e require_human_feedback=false -e tools=/home/user/comps/agent/langchain/tools/custom_tools.yaml opea/comps-agent-langchain:comps
+    docker run -d --runtime=runc --name="test-comps-agent-endpoint" -v $WORKPATH/comps/agent/langchain/tools:/home/user/comps/agent/langchain/tools -p 5042:9090 --ipc=host -e model=gpt-4o-mini-2024-07-18 -e strategy=react_langgraph -e llm_engine=openai -e OPENAI_API_KEY=${OPENAI_API_KEY} -e recursion_limit=10 -e require_human_feedback=false -e tools=/home/user/comps/agent/langchain/tools/custom_tools.yaml opea/comps-agent-langchain:comps
     sleep 5s
-    docker logs comps-agent-endpoint
+    docker logs test-comps-agent-endpoint
     echo "Service started successfully"
 }
 
 
 function start_ragagent_agent_service() {
     echo "Starting rag agent microservice"
-    docker run -d --runtime=runc --name="comps-agent-endpoint" -v $WORKPATH/comps/agent/langchain/tools:/home/user/comps/agent/langchain/tools -p 5042:9090 --ipc=host -e HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN} -e model=${model} -e strategy=rag_agent -e llm_endpoint_url=http://${ip_address}:${tgi_port} -e llm_engine=tgi -e recursion_limit=10 -e require_human_feedback=false -e tools=/home/user/comps/agent/langchain/tools/custom_tools.yaml opea/comps-agent-langchain:comps
+    docker run -d --runtime=runc --name="test-comps-agent-endpoint" -v $WORKPATH/comps/agent/langchain/tools:/home/user/comps/agent/langchain/tools -p 5042:9090 --ipc=host -e HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN} -e model=${model} -e strategy=rag_agent -e llm_endpoint_url=http://${ip_address}:${tgi_port} -e llm_engine=tgi -e recursion_limit=10 -e require_human_feedback=false -e tools=/home/user/comps/agent/langchain/tools/custom_tools.yaml opea/comps-agent-langchain:comps
     sleep 5s
-    docker logs comps-agent-endpoint
+    docker logs test-comps-agent-endpoint
     echo "Service started successfully"
 }
 
@@ -109,7 +109,7 @@ function validate_microservice() {
     echo "return value is $EXIT_CODE"
     if [ "$EXIT_CODE" == "1" ]; then
         docker logs test-comps-tgi-gaudi-service &> ${LOG_PATH}/test-comps-tgi-gaudi-service.log
-        docker logs comps-agent-endpoint &> ${LOG_PATH}/test-comps-langchain-agent-endpoint.log
+        docker logs test-comps-agent-endpoint &> ${LOG_PATH}/test-comps-langchain-agent-endpoint.log
         exit 1
     fi
 }
@@ -137,7 +137,7 @@ function stop_tgi_docker() {
 }
 
 function stop_agent_docker() {
-    cid=$(docker ps -aq --filter "name=comps-agent-endpoint")
+    cid=$(docker ps -aq --filter "name=test-comps-agent-endpoint")
     echo "Stopping the docker containers "${cid}
     if [[ ! -z "$cid" ]]; then docker rm $cid -f && sleep 1s; fi
     echo "Docker containers stopped successfully"

tests/intent_detection/test_intent_detection_langchain.sh

@@ -7,9 +7,10 @@ set -xe
 WORKPATH=$(dirname "$PWD")
 LOG_PATH="$WORKPATH/tests"
 ip_address=$(hostname -I | awk '{print $1}')
+
 function build_docker_images() {
     cd $WORKPATH
-    docker build --no-cache -t opea/llm-tgi:latest -f comps/intent_detection/langchain/Dockerfile .
+    docker build --no-cache -t opea/intent-detection:comps -f comps/intent_detection/langchain/Dockerfile .
 }
 
 function start_service() {
@@ -22,8 +23,19 @@ function start_service() {
     export TGI_LLM_ENDPOINT="http://${ip_address}:${tgi_endpoint}"
     intent_port=5043
     unset http_proxy
-    docker run -d --name="test-comps-intent-server" -p ${intent_port}:9000 --ipc=host -e http_proxy=$http_proxy -e https_proxy=$https_proxy -e TGI_LLM_ENDPOINT=$TGI_LLM_ENDPOINT -e HUGGINGFACEHUB_API_TOKEN=$HUGGINGFACEHUB_API_TOKEN opea/llm-tgi:latest
-    sleep 5m
+    docker run -d --name="test-comps-intent-server" -p ${intent_port}:9000 --ipc=host -e http_proxy=$http_proxy -e https_proxy=$https_proxy -e TGI_LLM_ENDPOINT=$TGI_LLM_ENDPOINT -e HUGGINGFACEHUB_API_TOKEN=$HUGGINGFACEHUB_API_TOKEN opea/intent-detection:comps
+
+    # check whether tgi is fully ready
+    n=0
+    until [[ "$n" -ge 100 ]] || [[ $ready == true ]]; do
+        docker logs test-comps-intent-tgi-endpoint > ${LOG_PATH}/tgi.log
+        n=$((n+1))
+        if grep -q Connected ${LOG_PATH}/tgi.log; then
+            break
+        fi
+        sleep 5s
+    done
+    sleep 5s
 }
 
 function validate_microservice() {
@@ -33,11 +45,16 @@ function validate_microservice() {
         -d '{"query":"What is Deep Learning?","max_new_tokens":10,"top_k":1,"temperature":0.001,"streaming":false}' \
         -H 'Content-Type: application/json')
 
-    echo "==============="
-    echo $result
+    if [[ $result == *"QA"* ]]; then
+        echo $result
+        echo "Result correct."
+    else
+        echo "Result wrong. Received was $result"
+        docker logs test-comps-intent-server > ${LOG_PATH}/intent_detection.log
+        docker logs test-comps-intent-tgi-endpoint > ${LOG_PATH}/tgi.log
+        exit 1
+    fi
 
-    docker logs test-comps-intent-server >> ${LOG_PATH}/intent_detection.log
-    docker logs test-comps-intent-tgi-endpoint >> ${LOG_PATH}/tgi-endpoint.log
 }
 
 function stop_docker() {