Add OpenAI client access OPEA microservice UT cases (#653)

* Add OpeanAI access microservice UT cases

Signed-off-by: lvliang-intel <liang1.lv@intel.com>

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* add the absolute path

Signed-off-by: lvliang-intel <liang1.lv@intel.com>

* refactor code

Signed-off-by: lvliang-intel <liang1.lv@intel.com>

* add openai denpendency

Signed-off-by: lvliang-intel <liang1.lv@intel.com>

* install openai in scripts

Signed-off-by: lvliang-intel <liang1.lv@intel.com>

* fix ci issue

Signed-off-by: lvliang-intel <liang1.lv@intel.com>

---------

Signed-off-by: lvliang-intel <liang1.lv@intel.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

tests/embeddings/test_embeddings_tei_langchain.sh

@@ -46,6 +46,16 @@ function validate_microservice() {
     fi
 }
 
+function validate_microservice_with_openai() {
+    tei_service_port=5001
+    python3 ${WORKPATH}/tests/utils/validate_svc_with_openai.py $ip_address $tei_service_port "embedding"
+    if [ $? -ne 0 ]; then
+        docker logs test-comps-embedding-tei-endpoint
+        docker logs test-comps-embedding-tei-server
+        exit 1
+    fi
+}
+
 function stop_docker() {
     cid=$(docker ps -aq --filter "name=test-comps-embedding-*")
     if [[ ! -z "$cid" ]]; then docker stop $cid && docker rm $cid && sleep 1s; fi
@@ -59,6 +69,8 @@ function main() {
     start_service
 
     validate_microservice
+    pip install openai
+    validate_microservice_with_openai
 
     stop_docker
     echo y | docker system prune

tests/llms/test_llms_text-generation_tgi.sh

@@ -60,6 +60,16 @@ function validate_microservice() {
     fi
 }
 
+function validate_microservice_with_openai() {
+    llm_service_port=5005
+    python3 ${WORKPATH}/tests/utils/validate_svc_with_openai.py "$ip_address" "$llm_service_port" "llm"
+    if [ $? -ne 0 ]; then
+        docker logs test-comps-llm-tgi-endpoint >> ${LOG_PATH}/llm-tgi.log
+        docker logs test-comps-llm-tgi-server >> ${LOG_PATH}/llm-tgi-server.log
+        exit 1
+    fi
+}
+
 function stop_docker() {
     cid=$(docker ps -aq --filter "name=test-comps-llm-tgi*")
     if [[ ! -z "$cid" ]]; then docker stop $cid && docker rm $cid && sleep 1s; fi
@@ -70,15 +80,18 @@ function main() {
     stop_docker
     build_docker_images
 
+    pip install openai
+
     llm_models=(
     Intel/neural-chat-7b-v3-3
-    meta-llama/Llama-2-7b-chat-hf
-    meta-llama/Meta-Llama-3-8B-Instruct
-    microsoft/Phi-3-mini-4k-instruct
+    # meta-llama/Llama-2-7b-chat-hf
+    # meta-llama/Meta-Llama-3-8B-Instruct
+    # microsoft/Phi-3-mini-4k-instruct
     )
     for model in "${llm_models[@]}"; do
       start_service "${model}"
       validate_microservice
+      validate_microservice_with_openai
       stop_docker
     done
 

tests/utils/validate_svc_with_openai.py

@@ -0,0 +1,42 @@
+#!/bin/bash
+# Copyright (C) 2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+import os
+import sys
+
+import openai
+
+
+def validate_svc(ip_address, service_port, service_type):
+    openai.api_key = os.getenv("OPENAI_API_KEY", "empty")
+
+    endpoint = f"http://{ip_address}:{service_port}"
+    client = openai.OpenAI(
+        api_key=openai.api_key,
+        base_url=endpoint + "/v1",
+    )
+
+    if service_type == "llm":
+        response = client.chat.completions.create(model="tgi", messages="What is Deep Learning?", max_tokens=128)
+    elif service_type == "embedding":
+        response = client.embeddings.create(model="tei", input="What is Deep Learning?")
+    else:
+        print(f"Unknown service type: {service_type}")
+        exit(1)
+    result = response.choices[0].text.strip() if service_type == "llm" else response.data[0].embedding
+    if "Deep Learning is" in result if service_type == "llm" else result:
+        print("Result correct.")
+    else:
+        print(f"Result wrong. Received was {result}")
+        exit(1)
+
+
+if __name__ == "__main__":
+    if len(sys.argv) != 4:
+        print("Usage: python3 validate_svc_with_openai.py <ip_address> <service_port> <service_type>")
+        exit(1)
+    ip_address = sys.argv[1]
+    service_port = sys.argv[2]
+    service_type = sys.argv[3]
+    validate_svc(ip_address, service_port, service_type)