Merge branch 'main' into nvidia-e2e-notebook

llama_stack/providers/remote/safety/nvidia/README.md

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+# NVIDIA Safety Provider for LlamaStack
+
+This provider enables safety checks and guardrails for LLM interactions using NVIDIA's NeMo Guardrails service.
+
+## Features
+
+- Run safety checks for messages
+
+## Getting Started
+
+### Prerequisites
+
+- LlamaStack with NVIDIA configuration
+- Access to NVIDIA NeMo Guardrails service
+- NIM for model to use for safety check is deployed
+
+### Setup
+
+Build the NVIDIA environment:
+
+```bash
+llama stack build --template nvidia --image-type conda
+```
+
+### Basic Usage using the LlamaStack Python Client
+
+#### Initialize the client
+
+```python
+import os
+
+os.environ["NVIDIA_API_KEY"] = "your-api-key"
+os.environ["NVIDIA_GUARDRAILS_URL"] = "http://guardrails.test"
+
+from llama_stack.distribution.library_client import LlamaStackAsLibraryClient
+
+client = LlamaStackAsLibraryClient("nvidia")
+client.initialize()
+```
+
+#### Create a safety shield
+
+```python
+from llama_stack.apis.safety import Shield
+from llama_stack.apis.inference import Message
+
+# Create a safety shield
+shield = Shield(
+    shield_id="your-shield-id",
+    provider_resource_id="safety-model-id",  # The model to use for safety checks
+    description="Safety checks for content moderation",
+)
+
+# Register the shield
+await client.safety.register_shield(shield)
+```
+
+#### Run safety checks
+
+```python
+# Messages to check
+messages = [Message(role="user", content="Your message to check")]
+
+# Run safety check
+response = await client.safety.run_shield(
+    shield_id="your-shield-id",
+    messages=messages,
+)
+
+# Check for violations
+if response.violation:
+    print(f"Safety violation detected: {response.violation.user_message}")
+    print(f"Violation level: {response.violation.violation_level}")
+    print(f"Metadata: {response.violation.metadata}")
+else:
+    print("No safety violations detected")
+```