updates.

embeddings.py

@@ -27,7 +27,8 @@ logger = logging.getLogger("embeddings-demo")
 # Configuration
 EMBEDDINGS_URL = os.environ.get(
     "EMBEDDINGS_URL", 
-    "http://embeddings-predictor.ai-ml.svc.cluster.local"
+    # Default: Ray Serve Embeddings endpoint
+    "http://ai-inference-serve-svc.ai-ml.svc.cluster.local:8000/embeddings"
 )
 MLFLOW_TRACKING_URI = os.environ.get(
     "MLFLOW_TRACKING_URI",

embeddings.yaml

@@ -29,7 +29,8 @@ spec:
               protocol: TCP
           env:
             - name: EMBEDDINGS_URL
-              value: "http://embeddings-predictor.ai-ml.svc.cluster.local"
+              # Ray Serve endpoint - routes to /embeddings prefix
+              value: "http://ai-inference-serve-svc.ai-ml.svc.cluster.local:8000/embeddings"
             - name: MLFLOW_TRACKING_URI
               value: "http://mlflow.mlflow.svc.cluster.local:80"
           resources:

stt.py

@@ -29,7 +29,8 @@ logger = logging.getLogger("stt-demo")
 # Configuration
 STT_URL = os.environ.get(
     "STT_URL",
-    "http://whisper-predictor.ai-ml.svc.cluster.local"
+    # Default: Ray Serve whisper endpoint
+    "http://ai-inference-serve-svc.ai-ml.svc.cluster.local:8000/whisper"
 )
 MLFLOW_TRACKING_URI = os.environ.get(
     "MLFLOW_TRACKING_URI",

stt.yaml

@@ -29,7 +29,8 @@ spec:
               protocol: TCP
           env:
             - name: WHISPER_URL
-              value: "http://whisper-predictor.ai-ml.svc.cluster.local"
+              # Ray Serve endpoint - routes to /whisper prefix
+              value: "http://ai-inference-serve-svc.ai-ml.svc.cluster.local:8000/whisper"
             - name: MLFLOW_TRACKING_URI
               value: "http://mlflow.mlflow.svc.cluster.local:80"
           resources:

tts.py

@@ -29,7 +29,8 @@ logger = logging.getLogger("tts-demo")
 # Configuration
 TTS_URL = os.environ.get(
     "TTS_URL",
-    "http://tts-predictor.ai-ml.svc.cluster.local"
+    # Default: Ray Serve TTS endpoint
+    "http://ai-inference-serve-svc.ai-ml.svc.cluster.local:8000/tts"
 )
 MLFLOW_TRACKING_URI = os.environ.get(
     "MLFLOW_TRACKING_URI",

tts.yaml

@@ -29,7 +29,8 @@ spec:
               protocol: TCP
           env:
             - name: TTS_URL
-              value: "http://tts-predictor.ai-ml.svc.cluster.local"
+              # Ray Serve endpoint - routes to /tts prefix
+              value: "http://ai-inference-serve-svc.ai-ml.svc.cluster.local:8000/tts"
             - name: MLFLOW_TRACKING_URI
               value: "http://mlflow.mlflow.svc.cluster.local:80"
           resources: