Fix Reorg Issues (#657)

Signed-off-by: letonghan <letong.han@intel.com>

comps/intent_detection/langchain/intent_detection.py

@@ -5,7 +5,6 @@
 
 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
 

comps/llms/text-generation/vllm/langchain/dependency/build_docker_vllm.sh

@@ -30,7 +30,7 @@ fi
 
 # Build the docker image for vLLM based on the hardware mode
 if [ "$hw_mode" = "hpu" ]; then
-    docker build -f docker/Dockerfile.Intel_HPU -t opea/vllm:hpu --shm-size=128g . --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy
+    docker build -f docker/Dockerfile.intel_hpu -t opea/vllm:hpu --shm-size=128g . --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy
 else
     git clone https://github.com/vllm-project/vllm.git
     cd ./vllm/

comps/lvms/tgi-llava/template.py

@@ -0,0 +1,10 @@
+# Copyright (C) 2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+
+class ChatTemplate:
+
+    @staticmethod
+    def generate_multimodal_rag_on_videos_prompt(question: str, context: str):
+        template = """The transcript associated with the image is '{context}'. {question}"""
+        return template.format(context=context, question=question)

tests/embeddings/test_embeddings_tei_langchain.sh

@@ -20,7 +20,7 @@ function build_docker_images() {
 }
 
 function start_service() {
-    tei_endpoint=5001=
+    tei_endpoint=5001
     model="BAAI/bge-base-en-v1.5"
     unset http_proxy
     docker run -d --name="test-comps-embedding-tei-endpoint" -p $tei_endpoint:80 -v ./data:/data --pull always ghcr.io/huggingface/text-embeddings-inference:cpu-1.5 --model-id $model

tests/intent_detection/test_intent_detection_langchain.sh

@@ -40,7 +40,7 @@ function start_service() {
 
 function validate_microservice() {
     intent_port=5043
-    result=$(http_proxy="" curl http://${ip_address}:${intent_port}/v1/chat/intent\
+    result=$(http_proxy="" curl http://localhost:${intent_port}/v1/chat/intent\
         -X POST \
         -d '{"query":"What is Deep Learning?","max_new_tokens":10,"top_k":1,"temperature":0.001,"streaming":false}' \
         -H 'Content-Type: application/json')