SearchQnA App - Adding files to deploy SearchQnA application on AMD GPU

DocSum/docker_compose/amd/gpu/rocm/compose.yaml

@@ -27,8 +27,7 @@ services:
     security_opt:
       - seccomp:unconfined
     ipc: host
-    command: --model-id ${DOCSUM_LLM_MODEL_ID} --max-input-length ${MAX_INPUT_TOKENS} --max-total-tokens ${MAX_TOTAL_TOKENS}
-
+    command: --model-id ${DOCSUM_LLM_MODEL_ID}
   docsum-llm-server:
     image: ${REGISTRY:-opea}/llm-docsum-tgi:${TAG:-latest}
     container_name: docsum-llm-server
@@ -70,6 +69,18 @@ services:
       https_proxy: ${https_proxy}
     restart: unless-stopped
 
+  whisper:
+    image: ${REGISTRY:-opea}/whisper:${TAG:-latest}
+    container_name: whisper-service
+    ports:
+      - "7066:7066"
+    ipc: host
+    environment:
+      no_proxy: ${no_proxy}
+      http_proxy: ${http_proxy}
+      https_proxy: ${https_proxy}
+    restart: unless-stopped
+
   dataprep-audio2text:
     image: ${REGISTRY:-opea}/dataprep-audio2text:${TAG:-latest}
     container_name: dataprep-audio2text-service

DocSum/docsum.py

@@ -108,9 +108,11 @@ async def handle_request(self, request: Request, files: List[UploadFile] = File(
         if "application/json" in request.headers.get("content-type"):
             data = await request.json()
             stream_opt = data.get("stream", True)
+
             summary_type = data.get("summary_type", "auto")
             chunk_size = data.get("chunk_size", -1)
             chunk_overlap = data.get("chunk_overlap", -1)
+
             chat_request = ChatCompletionRequest.model_validate(data)
             prompt = handle_message(chat_request.messages)
 
@@ -119,9 +121,11 @@ async def handle_request(self, request: Request, files: List[UploadFile] = File(
         elif "multipart/form-data" in request.headers.get("content-type"):
             data = await request.form()
             stream_opt = data.get("stream", True)
+
             summary_type = data.get("summary_type", "auto")
             chunk_size = data.get("chunk_size", -1)
             chunk_overlap = data.get("chunk_overlap", -1)
+
             chat_request = ChatCompletionRequest.model_validate(data)
 
             data_type = data.get("type")

DocSum/tests/test_compose_on_xeon.sh

@@ -210,14 +210,17 @@ function validate_microservices() {
         "${host_ip}:7079/v1/multimedia2text" \
         "well" \
         "dataprep-multimedia2text" \
+
         "dataprep-multimedia2text" \
         "{\"video\": \"$(input_data_for_test "video")\"}"
 
     # Docsum Data service - audio
     validate_services_json \
         "${host_ip}:7079/v1/multimedia2text" \
         "well" \
+
         "dataprep-multimedia2text" \
+
         "dataprep-multimedia2text" \
         "{\"audio\": \"$(input_data_for_test "audio")\"}"
 

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

@@ -0,0 +1,179 @@
+# Build and deploy SearchQnA Application on AMD GPU (ROCm)
+
+## Build images
+
+### Build Embedding Image
+
+```bash
+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/tei/langchain/Dockerfile .
+```
+
+### Build Retriever Image
+
+```bash
+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/chroma/langchain/Dockerfile .
+```
+
+### Build Rerank Image
+
+```bash
+docker build --no-cache -t opea/reranking-tei:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/reranks/tei/Dockerfile .
+```
+
+### Build the LLM Docker Image
+
+```bash
+docker build -t opea/llm-tgi:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/text-generation/tgi/Dockerfile .
+```
+
+### Build the MegaService Docker Image
+
+```bash
+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
+
+```bash
+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:
+
+```yaml
+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:
+
+```yaml
+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
+
+```bash
+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
+
+```bash
+chmod +x set_env.sh
+. set_env.sh
+```
+
+### Run services
+
+```
+docker compose up -d
+```
+
+# Validate the MicroServices and MegaService
+
+## Validate TEI service
+
+```bash
+curl http://${SEARCH_HOST_IP}:3001/embed \
+    -X POST \
+    -d '{"inputs":"What is Deep Learning?"}' \
+    -H 'Content-Type: application/json'
+```
+
+## Validate Embedding service
+
+```bash
+curl http://${SEARCH_HOST_IP}:3002/v1/embeddings\
+  -X POST \
+  -d '{"text":"hello"}' \
+  -H 'Content-Type: application/json'
+```
+
+## Validate Web Retriever service
+
+```bash
+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\":${your_embedding}}" \
+  -H 'Content-Type: application/json'
+```
+
+## Validate TEI Reranking service
+
+```bash
+curl http://${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
+
+```bash
+curl http://${SEARCH_HOST_IP}:3005/v1/reranking\
+  -X POST \
+  -d '{"initial_query":"What is Deep Learning?", "retrieved_docs": [{"text":"Deep Learning is not..."}, {"text":"Deep learning is..."}]}' \
+  -H 'Content-Type: application/json'
+```
+
+## Validate TGI service
+
+```bash
+curl http://${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
+
+```bash
+curl http://${SEARCH_HOST_IP}:3007/v1/chat/completions\
+  -X POST \
+  -d '{"query":"What is Deep Learning?","max_tokens":17,"top_k":10,"top_p":0.95,"typical_p":0.95,"temperature":0.01,"repetition_penalty":1.03,"streaming":true}' \
+  -H 'Content-Type: application/json'
+```
+
+## Validate MegaService
+
+```bash
+curl http://${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"
+     }'
+```