feat add sambanova safety adaptor

docs/source/distributions/self_hosted_distro/sambanova.md

@@ -17,7 +17,7 @@ The `llamastack/distribution-sambanova` distribution consists of the following p
 |-----|-------------|
 | agents | `inline::meta-reference` |
 | inference | `remote::sambanova`, `inline::sentence-transformers` |
-| safety | `inline::llama-guard` |
+| safety | `remote::sambanova` |
 | telemetry | `inline::meta-reference` |
 | tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::rag-runtime`, `remote::model-context-protocol`, `remote::wolfram-alpha` |
 | vector_io | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |

llama_stack/providers/registry/safety.py

@@ -64,4 +64,13 @@ def available_providers() -> List[ProviderSpec]:
                 config_class="llama_stack.providers.remote.safety.nvidia.NVIDIASafetyConfig",
             ),
         ),
+        remote_provider_spec(
+            api=Api.safety,
+            adapter=AdapterSpec(
+                adapter_type="sambanova",
+                pip_packages=["litellm"],
+                module="llama_stack.providers.remote.safety.sambanova",
+                config_class="llama_stack.providers.remote.safety.sambanova.SambaNovaSafetyConfig",
+            ),
+        ),
     ]

llama_stack/providers/remote/safety/bedrock/bedrock.py

@@ -28,6 +28,7 @@ class BedrockSafetyAdapter(Safety, ShieldsProtocolPrivate):
     def __init__(self, config: BedrockSafetyConfig) -> None:
         self.config = config
         self.registered_shields = []
+        self.test = 2
 
     async def initialize(self) -> None:
         try:

llama_stack/providers/remote/safety/sambanova/__init__.py

@@ -0,0 +1,18 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+
+from typing import Any
+
+from .config import SambaNovaSafetyConfig
+
+
+async def get_adapter_impl(config: SambaNovaSafetyConfig, _deps) -> Any:
+    from .sambanova import SambaNovaSafetyAdapter
+
+    impl = SambaNovaSafetyAdapter(config)
+    await impl.initialize()
+    return impl

llama_stack/providers/remote/safety/sambanova/config.py

@@ -0,0 +1,30 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from typing import Any, Dict, Optional
+
+from pydantic import BaseModel, Field
+
+from llama_stack.schema_utils import json_schema_type
+
+
+@json_schema_type
+class SambaNovaSafetyConfig(BaseModel):
+    url: str = Field(
+        default="https://api.sambanova.ai/v1",
+        description="The URL for the SambaNova AI server",
+    )
+    api_key: Optional[str] = Field(
+        default=None,
+        description="The SambaNova cloud API Key",
+    )
+
+    @classmethod
+    def sample_run_config(cls, **kwargs) -> Dict[str, Any]:
+        return {
+            "url": "https://api.sambanova.ai/v1",
+            "api_key": "${env.SAMBANOVA_API_KEY}",
+        }

llama_stack/providers/remote/safety/sambanova/sambanova.py

@@ -0,0 +1,85 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+import json
+import logging
+from typing import Any, Dict, List, Optional
+
+import litellm
+import requests
+
+from llama_stack.apis.inference import Message
+from llama_stack.apis.safety import (
+    RunShieldResponse,
+    Safety,
+    SafetyViolation,
+    ViolationLevel,
+)
+from llama_stack.apis.shields import Shield
+from llama_stack.providers.datatypes import ShieldsProtocolPrivate
+from llama_stack.providers.utils.inference.openai_compat import convert_message_to_openai_dict_new
+
+from .config import SambaNovaSafetyConfig
+
+logger = logging.getLogger(__name__)
+
+CANNED_RESPONSE_TEXT = "I can't answer that. Can I help with something else?"
+
+
+class SambaNovaSafetyAdapter(Safety, ShieldsProtocolPrivate):
+    def __init__(self, config: SambaNovaSafetyConfig) -> None:
+        self.config = config
+
+    async def initialize(self) -> None:
+        pass
+
+    async def shutdown(self) -> None:
+        pass
+
+    async def register_shield(self, shield: Shield) -> None:
+        list_models_url = self.config.url + "/models"
+        try:
+            response = requests.get(list_models_url)
+            response.raise_for_status()
+        except requests.exceptions.RequestException as e:
+            raise RuntimeError(f"Request to {list_models_url} failed") from e
+        available_models = [model.get("id") for model in response.json().get("data", {})]
+        if (
+            len(available_models) == 0
+            or "guard" not in shield.provider_resource_id.lower()
+            or shield.provider_resource_id.split("sambanova/")[-1] not in available_models
+        ):
+            raise ValueError(f"Shield {shield.provider_resource_id} not found in SambaNova")
+
+    async def run_shield(
+        self, shield_id: str, messages: List[Message], params: Optional[Dict[str, Any]] = None
+    ) -> RunShieldResponse:
+        shield = await self.shield_store.get_shield(shield_id)
+        if not shield:
+            raise ValueError(f"Shield {shield_id} not found")
+
+        shield_params = shield.params
+        logger.debug(f"run_shield::{shield_params}::messages={messages}")
+        content_messages = [await convert_message_to_openai_dict_new(m) for m in messages]
+        logger.debug(f"run_shield::final:messages::{json.dumps(content_messages, indent=2)}:")
+
+        response = litellm.completion(model=shield.provider_resource_id, messages=content_messages)
+        shield_message = response.choices[0].message.content
+
+        if "unsafe" in shield_message.lower():
+            user_message = CANNED_RESPONSE_TEXT
+            violation_type = shield_message.split("\n")[-1]
+            metadata = {"violation_type": violation_type}
+
+            return RunShieldResponse(
+                violation=SafetyViolation(
+                    user_message=user_message,
+                    violation_level=ViolationLevel.ERROR,
+                    metadata=metadata,
+                )
+            )
+
+        return RunShieldResponse()

llama_stack/templates/sambanova/build.yaml

@@ -1,6 +1,6 @@
 version: '2'
 distribution_spec:
-  description: Use SambaNova for running LLM inference
+  description: Use SambaNova for running LLM inference and safety
   providers:
     inference:
     - remote::sambanova
@@ -10,7 +10,7 @@ distribution_spec:
     - remote::chromadb
     - remote::pgvector
     safety:
-    - inline::llama-guard
+    - remote::sambanova
     agents:
     - inline::meta-reference
     telemetry:

llama_stack/templates/sambanova/run.yaml

@@ -38,10 +38,11 @@ providers:
       user: ${env.PGVECTOR_USER:}
       password: ${env.PGVECTOR_PASSWORD:}
   safety:
-  - provider_id: llama-guard
-    provider_type: inline::llama-guard
+  - provider_id: sambanova
+    provider_type: remote::sambanova
     config:
-      excluded_categories: []
+      url: https://api.sambanova.ai/v1
+      api_key: ${env.SAMBANOVA_API_KEY}
   agents:
   - provider_id: meta-reference
     provider_type: inline::meta-reference
@@ -181,6 +182,9 @@ models:
   model_type: embedding
 shields:
 - shield_id: meta-llama/Llama-Guard-3-8B
+  provider_shield_id: sambanova/Meta-Llama-Guard-3-8B
+- shield_id: sambanova/Meta-Llama-Guard-3-8B
+  provider_shield_id: sambanova/Meta-Llama-Guard-3-8B
 vector_dbs: []
 datasets: []
 scoring_fns: []

llama_stack/templates/sambanova/sambanova.py

@@ -34,7 +34,7 @@ def get_distribution_template() -> DistributionTemplate:
     providers = {
         "inference": ["remote::sambanova", "inline::sentence-transformers"],
         "vector_io": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
-        "safety": ["inline::llama-guard"],
+        "safety": ["remote::sambanova"],
         "agents": ["inline::meta-reference"],
         "telemetry": ["inline::meta-reference"],
         "tool_runtime": [
@@ -115,7 +115,7 @@ def get_distribution_template() -> DistributionTemplate:
     return DistributionTemplate(
         name=name,
         distro_type="self_hosted",
-        description="Use SambaNova for running LLM inference",
+        description="Use SambaNova for running LLM inference and safety",
         container_image=None,
         template_path=Path(__file__).parent / "doc_template.md",
         providers=providers,
@@ -127,7 +127,15 @@ def get_distribution_template() -> DistributionTemplate:
                     "vector_io": vector_io_providers,
                 },
                 default_models=default_models + [embedding_model],
-                default_shields=[ShieldInput(shield_id="meta-llama/Llama-Guard-3-8B")],
+                default_shields=[
+                    ShieldInput(
+                        shield_id="meta-llama/Llama-Guard-3-8B", provider_shield_id="sambanova/Meta-Llama-Guard-3-8B"
+                    ),
+                    ShieldInput(
+                        shield_id="sambanova/Meta-Llama-Guard-3-8B",
+                        provider_shield_id="sambanova/Meta-Llama-Guard-3-8B",
+                    ),
+                ],
                 default_tool_groups=default_tool_groups,
             ),
         },

pyproject.toml

@@ -255,6 +255,7 @@ exclude = [
     "^llama_stack/providers/remote/inference/together/",
     "^llama_stack/providers/remote/inference/vllm/",
     "^llama_stack/providers/remote/safety/bedrock/",
+    "^llama_stack/providers/remote/safety/sambanova/",
     "^llama_stack/providers/remote/safety/nvidia/",
     "^llama_stack/providers/remote/safety/sample/",
     "^llama_stack/providers/remote/tool_runtime/bing_search/",