GenAIExamples/SearchQnA/docker_compose/amd/gpu/rocm/README.md

Build and deploy SearchQnA Application on AMD GPU (ROCm)

Build images

Build Embedding Image

git clone https://github.com/opea-project/GenAIComps.git
cd GenAIComps
docker build --no-cache -t opea/embedding-tei:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/embeddings/src/Dockerfile .

Build Retriever Image

docker build --no-cache -t opea/web-retriever-chroma:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/web_retrievers/src/Dockerfile .

Build Rerank Image

docker build --no-cache -t opea/reranking-tei:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/rerankings/src/Dockerfile .

Build the LLM Docker Image

docker build -t opea/llm-tgi:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/src/text-generation/Dockerfile .

Build the MegaService Docker Image

git clone https://github.com/opea-project/GenAIExamples.git
cd GenAIExamples/SearchQnA
docker build --no-cache -t opea/searchqna:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile .

Build the UI Docker Image

cd GenAIExamples/SearchQnA/ui
docker build --no-cache -t opea/opea/searchqna-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile .

Deploy SearchQnA Application

Features of Docker compose for AMD GPUs

1. Added forwarding of GPU devices to the container TGI service with instructions:

shm_size: 1g
devices:
  - /dev/kfd:/dev/kfd
  - /dev/dri/:/dev/dri/
cap_add:
  - SYS_PTRACE
group_add:
  - video
security_opt:
  - seccomp:unconfined

In this case, all GPUs are thrown. To reset a specific GPU, you need to use specific device names cardN and renderN.

For example:

shm_size: 1g
devices:
  - /dev/kfd:/dev/kfd
  - /dev/dri/card0:/dev/dri/card0
  - /dev/dri/render128:/dev/dri/render128
cap_add:
  - SYS_PTRACE
group_add:
  - video
security_opt:
  - seccomp:unconfined

To find out which GPU device IDs cardN and renderN correspond to the same GPU, use the GPU driver utility

Go to the directory with the Docker compose file

cd GenAIExamples/SearchQnA/docker_compose/amd/gpu/rocm

Set environments

In the file "GenAIExamples/SearchQnA/docker_compose/amd/gpu/rocm/set_env.sh " it is necessary to set the required values. Parameter assignments are specified in the comments for each variable setting command

chmod +x set_env.sh
. set_env.sh

Run services

docker compose up -d

Validate the MicroServices and MegaService

Validate TEI service

curl http://${SEARCH_HOST_IP}:3001/embed \
    -X POST \
    -d '{"inputs":"What is Deep Learning?"}' \
    -H 'Content-Type: application/json'

Validate Embedding service

curl http://${SEARCH_HOST_IP}:3002/v1/embeddings\
  -X POST \
  -d '{"text":"hello"}' \
  -H 'Content-Type: application/json'

Validate Web Retriever service

export your_embedding=$(python3 -c "import random; embedding = [random.uniform(-1, 1) for _ in range(768)]; print(embedding)")
curl http://${SEARCH_HOST_IP}:3003/v1/web_retrieval \
  -X POST \
  -d "{\"text\":\"What is the 2024 holiday schedule?\",\"embedding\":${your_embedding}}" \
  -H 'Content-Type: application/json'

Validate TEI Reranking service

curl http://${SEARCH_HOST_IP}:3004/rerank \
    -X POST \
    -d '{"query":"What is Deep Learning?", "texts": ["Deep Learning is not...", "Deep learning is..."]}' \
    -H 'Content-Type: application/json'

Validate Reranking service

curl http://${SEARCH_HOST_IP}:3005/v1/reranking\
  -X POST \
  -d '{"initial_query":"What is Deep Learning?", "retrieved_docs": [{"text":"Deep Learning is not..."}, {"text":"Deep learning is..."}]}' \
  -H 'Content-Type: application/json'

Validate TGI service

curl http://${SEARCH_HOST_IP}:3006/generate \
  -X POST \
  -d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":17, "do_sample": true}}' \
  -H 'Content-Type: application/json'

Validate LLM service

curl http://${SEARCH_HOST_IP}:3007/v1/chat/completions\
  -X POST \
  -d '{"query":"What is Deep Learning?","max_tokens":17,"top_k":10,"top_p":0.95,"typical_p":0.95,"temperature":0.01,"repetition_penalty":1.03,"streaming":true}' \
  -H 'Content-Type: application/json'

Validate MegaService

curl http://${SEARCH_HOST_IP}:3008/v1/searchqna -H "Content-Type: application/json" -d '{
     "messages": "What is the latest news? Give me also the source link.",
     "stream": "True"
     }'