fixing errors

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

@@ -22,7 +22,7 @@ class NVIDIASafetyConfig(BaseModel):
      Configuration for the NVIDIA Guardrail microservice endpoint.
 
     Attributes:
-        url (str): A base url for accessing the NVIDIA guardrail endpoint, e.g. http://localhost:8000
+        guardrails_service_url (str): A base url for accessing the NVIDIA guardrail endpoint, e.g. http://localhost:8000
         api_key (str): The access key for the hosted NIM endpoints
 
     There are two ways to access NVIDIA NIMs -

llama_stack/providers/remote/safety/nvidia/nvidia.py

@@ -8,7 +8,7 @@ import json
 import logging
 from typing import Any, Dict, List
 
-from llama_stack.apis.inference import Message
+from llama_stack.apis.inference import Message, UserMessage
 from llama_stack.apis.safety import (
     RunShieldResponse,
     Safety,
@@ -16,6 +16,8 @@ from llama_stack.apis.safety import (
     ViolationLevel,
 )
 from llama_stack.apis.shields import Shield
+from llama_stack.distribution.library_client import convert_pydantic_to_json_value
+from llama_stack.models.llama.datatypes import CoreModelId
 from llama_stack.providers.datatypes import ShieldsProtocolPrivate
 import requests
 
@@ -23,10 +25,21 @@ from .config import NVIDIASafetyConfig
 
 logger = logging.getLogger(__name__)
 
+SHIELD_IDS_TO_MODEL_MAPPING = {
+    CoreModelId.llama3_8b_instruct.value: "meta/llama3-8b-instruct",
+    CoreModelId.llama3_70b_instruct.value:  "meta/llama3-70b-instruct",
+    CoreModelId.llama3_1_8b_instruct.value: "meta/llama-3.1-8b-instruct",
+    CoreModelId.llama3_1_70b_instruct.value: "meta/llama-3.1-70b-instruct",
+    CoreModelId.llama3_1_405b_instruct.value: "meta/llama-3.1-405b-instruct",
+    CoreModelId.llama3_2_1b_instruct.value: "meta/llama-3.2-1b-instruct",
+    CoreModelId.llama3_2_3b_instruct.value: "meta/llama-3.2-3b-instruct",
+    CoreModelId.llama3_2_11b_vision_instruct.value: "meta/llama-3.2-11b-vision-instruct",
+    CoreModelId.llama3_2_90b_vision_instruct.value: "meta/llama-3.2-90b-vision-instruct"
+}
 
 class NVIDIASafetyAdapter(Safety, ShieldsProtocolPrivate):
     def __init__(self, config: NVIDIASafetyConfig) -> None:
-        print(f"Initializing NVIDIASafetyAdapter({config.url})...")
+        print(f"Initializing NVIDIASafetyAdapter({config.guardrails_service_url})...")
         self.config = config
         self.registered_shields = []
 
@@ -46,7 +59,7 @@ class NVIDIASafetyAdapter(Safety, ShieldsProtocolPrivate):
         shield = await self.shield_store.get_shield(shield_id)
         if not shield:
             raise ValueError(f"Shield {shield_id} not found")
-        self.shield = NeMoGuardrails(self.config, shield.provider_resource_id)
+        self.shield = NeMoGuardrails(self.config, SHIELD_IDS_TO_MODEL_MAPPING[shield.shield_id])
         return await self.shield.run(messages)
         
     
@@ -58,24 +71,25 @@ class NeMoGuardrails:
         threshold: float = 0.9,
         temperature: float = 1.0,
     ):
-        config_id = config["config_id"]
+        self.config_id = config.config_id
-        config_store_path = config["config_store_path"]
+        self.config_store_path = config.config_store_path
-        assert  config_id is not None or config_store_path is not None, "Must provide one of config id or config store path"
+        self.model = model
+        assert  self.config_id is not None or self.config_store_path is not None, "Must provide one of config id or config store path"
         if temperature <= 0:
             raise ValueError("Temperature must be greater than 0")
 
         self.config = config
         self.temperature = temperature
         self.threshold = threshold
-        self.guardrails_service_url = config["guardrails_service_url"]
+        self.guardrails_service_url = config.guardrails_service_url
 
     async def run(self, messages: List[Message]) -> RunShieldResponse:
         headers = {
             "Accept": "application/json",
         }
         request_data = {
-            "model": "meta/llama-3.1-8b-instruct",
+            "model": self.model,
-            "messages": messages,
+            "messages": convert_pydantic_to_json_value(messages),
             "temperature": self.temperature,
             "top_p": 1,
             "frequency_penalty": 0,
@@ -83,7 +97,7 @@ class NeMoGuardrails:
             "max_tokens": 160,
             "stream": False,
             "guardrails": {
-                "config_id": self.config["config_id"],
+                "config_id": self.config_id,
             }
         }
         response = requests.post(
@@ -91,6 +105,7 @@ class NeMoGuardrails:
             headers=headers,
             json=request_data
         )
+        print(response)
         response.raise_for_status()
         if 'Content-Type' in response.headers and response.headers['Content-Type'].startswith('application/json'):
             response_json = response.json()

llama_stack/templates/nvidia/run-with-safety.yaml

@@ -30,7 +30,7 @@ providers:
     provider_type: remote::nvidia
     config:
       url: ${env.GUARDRAILS_SERVICE_URL:http://localhost:7331}
-      config_id: 
+      config_id: self-check
   agents:
   - provider_id: meta-reference
     provider_type: inline::meta-reference
@@ -139,6 +139,7 @@ models:
   model_type: llm
 shields:
 - shield_id: ${env.SAFETY_MODEL}
+  provider_id: nvidia
 vector_dbs: []
 datasets: []
 scoring_fns: []