hostname

.env.example

@@ -1,6 +1,6 @@
 OPENAI_WHISPER_IMAGE=registry.lan/openai-whisper-stt:latest
 STT_PORT=9000
-STT_NODE_HOSTNAME=tpi-n1
+STT_NODE_HOSTNAME=tpi-n2
 MODEL_NAME=whisper-base-onnx
 STT_API_KEY=
 MAX_DECODE_TOKENS=128

README.md

@@ -53,10 +53,10 @@ VLM_ENABLED=true
 Then copy RKLLM assets into the `rkllm-root` volume (one-time):
 
 ```bash
-docker volume create rk-whisper-stt-api_rkllm-root
+docker volume create rkllm-root
 
 docker run --rm \
-  -v rk-whisper-stt-api_rkllm-root:/dst \
+  -v rkllm-root:/dst \
   -v /home/ubuntu/rkllm-demo:/src:ro \
   alpine:3.20 \
   sh -c 'cp -r /src/models /dst/ && mkdir -p /dst/quickstart && cp -r /src/quickstart/demo_Linux_aarch64 /dst/quickstart/'
@@ -89,7 +89,7 @@ docker push registry.lan/openai-whisper-stt:latest
 
 ```bash
 cp .env.example .env
-# edit STT_NODE_HOSTNAME to the target node
+# edit STT_NODE_HOSTNAME to match your target node (e.g. tpi-n2)
 docker stack deploy -c stack.yml whisper-stt
 ```
 

docker-compose.yml

@@ -43,4 +43,6 @@ services:
 
 volumes:
   whisper-models:
+    name: whisper-models
   rkllm-root:
+    name: rkllm-root

stack.yml

@@ -31,7 +31,7 @@ services:
       replicas: 1
       placement:
         constraints:
-          - node.hostname == ${STT_NODE_HOSTNAME:-tpi-n1}
+          - node.hostname == ${STT_NODE_HOSTNAME:-tpi-n2}
       restart_policy:
         condition: on-failure
     networks:
@@ -39,7 +39,9 @@ services:
 
 volumes:
   whisper-models:
+    name: whisper-models
   rkllm-root:
+    name: rkllm-root
 
 networks:
   dokploy-network: