Sec fixes as raised by bandit (#917)

minor fixes to hashlib and jinja

llama_stack/templates/sambanova/sambanova.py

@@ -8,7 +8,12 @@ from pathlib import Path
 
 from llama_models.sku_list import all_registered_models
 
-from llama_stack.distribution.datatypes import ModelInput, Provider, ShieldInput
+from llama_stack.distribution.datatypes import (
+    ModelInput,
+    Provider,
+    ShieldInput,
+    ToolGroupInput,
+)
 from llama_stack.providers.remote.inference.sambanova import SambaNovaImplConfig
 from llama_stack.providers.remote.inference.sambanova.sambanova import MODEL_ALIASES
 
@@ -29,10 +34,11 @@ def get_distribution_template() -> DistributionTemplate:
             "inline::rag-runtime",
         ],
     }
+    name = "sambanova"
 
     inference_provider = Provider(
-        provider_id="sambanova",
-        provider_type="remote::sambanova",
+        provider_id=name,
+        provider_type=f"remote::{name}",
         config=SambaNovaImplConfig.sample_run_config(),
     )
 
@@ -43,12 +49,28 @@ def get_distribution_template() -> DistributionTemplate:
         ModelInput(
             model_id=core_model_to_hf_repo[m.llama_model],
             provider_model_id=m.provider_model_id,
+            provider_id=name,
         )
         for m in MODEL_ALIASES
     ]
 
+    default_tool_groups = [
+        ToolGroupInput(
+            toolgroup_id="builtin::websearch",
+            provider_id="tavily-search",
+        ),
+        ToolGroupInput(
+            toolgroup_id="builtin::rag",
+            provider_id="rag-runtime",
+        ),
+        ToolGroupInput(
+            toolgroup_id="builtin::code_interpreter",
+            provider_id="code-interpreter",
+        ),
+    ]
+
     return DistributionTemplate(
-        name="sambanova",
+        name=name,
         distro_type="self_hosted",
         description="Use SambaNova.AI for running LLM inference",
         docker_image=None,
@@ -62,6 +84,7 @@ def get_distribution_template() -> DistributionTemplate:
                 },
                 default_models=default_models,
                 default_shields=[ShieldInput(shield_id="meta-llama/Llama-Guard-3-8B")],
+                default_tool_groups=default_tool_groups,
             ),
         },
         run_config_env_vars={