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chore(package): migrate to src/ layout (#3920)

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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
uv run llama stack list-deps nvidia | xargs -L1 uv pip install
```
### 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.core.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")
```