Merge-related changes.

llama_stack/templates/sambanova/doc_template.md

@@ -49,9 +49,10 @@ You can do this via Conda (build code) or Docker which has a pre-built image.
 This method allows you to get started quickly without having to build the distribution code.
 
 ```bash
-LLAMA_STACK_PORT=5001
+LLAMA_STACK_PORT=8321
 docker run \
   -it \
+  --pull always \
   -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
   llamastack/distribution-{{ name }} \
   --port $LLAMA_STACK_PORT \

llama_stack/templates/sambanova/run.yaml

@@ -38,7 +38,8 @@ providers:
   safety:
   - provider_id: llama-guard
     provider_type: inline::llama-guard
-    config: {}
+    config:
+      excluded_categories: []
   agents:
   - provider_id: meta-reference
     provider_type: inline::meta-reference
@@ -51,7 +52,7 @@ providers:
   - provider_id: meta-reference
     provider_type: inline::meta-reference
     config:
-      service_name: ${env.OTEL_SERVICE_NAME:llama-stack}
+      service_name: "${env.OTEL_SERVICE_NAME:\u200B}"
       sinks: ${env.TELEMETRY_SINKS:console,sqlite}
       sqlite_db_path: ${env.SQLITE_DB_PATH:~/.llama/distributions/sambanova/trace_store.db}
   tool_runtime:

llama_stack/templates/sambanova/sambanova.py

@@ -7,17 +7,19 @@
 from pathlib import Path
 
 from llama_stack.apis.preprocessing.preprocessors import PreprocessorInput
-from llama_stack.distribution.datatypes import (
-    Provider,
-    ShieldInput,
-    ToolGroupInput,
-)
+from llama_stack.distribution.datatypes import Provider, ShieldInput, ToolGroupInput
 from llama_stack.providers.inline.vector_io.faiss.config import FaissVectorIOConfig
 from llama_stack.providers.remote.inference.sambanova import SambaNovaImplConfig
 from llama_stack.providers.remote.inference.sambanova.models import MODEL_ENTRIES
 from llama_stack.providers.remote.vector_io.chroma.config import ChromaVectorIOConfig
-from llama_stack.providers.remote.vector_io.pgvector.config import PGVectorVectorIOConfig
-from llama_stack.templates.template import DistributionTemplate, RunConfigSettings, get_model_registry
+from llama_stack.providers.remote.vector_io.pgvector.config import (
+    PGVectorVectorIOConfig,
+)
+from llama_stack.templates.template import (
+    DistributionTemplate,
+    RunConfigSettings,
+    get_model_registry,
+)
 
 
 def get_distribution_template() -> DistributionTemplate:
@@ -118,7 +120,7 @@ def get_distribution_template() -> DistributionTemplate:
         },
         run_config_env_vars={
             "LLAMASTACK_PORT": (
-                "5001",
+                "8321",
                 "Port for the Llama Stack distribution server",
             ),
             "SAMBANOVA_API_KEY": (