forked from phoenix-oss/llama-stack-mirror
eab550f7d2
# What does this PR do?
When running a Llama Stack server and invoking the
`/v1/safety/run-shield` endpoint, the NVIDIA Guardrails endpoint in some
cases errors with a `422: Unprocessable Entity` due to malformed input.
For example, given an request body like:
```
{
"model": "test",
"messages": [
{ "role": "user", "content": "You are stupid." }
]
}
```
`convert_pydantic_to_json_value` converts the message to:
```
{ "role": "user", "content": "You are stupid.", "context": null }
```
Which causes NVIDIA Guardrails to return an error `HTTPError: 422 Client
Error: Unprocessable Entity for url:
http://nemo.test/v1/guardrail/checks`, because `context` shouldn't be
included in the body.
[//]: # (If resolving an issue, uncomment and update the line below)
[//]: # (Closes #[issue-number])
## Test Plan
I ran the Llama Stack server locally and manually verified that the
endpoint now succeeds.
```
message = {"role": "user", "content": "You are stupid."}
response = client.safety.run_shield(messages=[message], shield_id=shield_id, params={})
```
Server logs:
```
14:29:09.656 [START] /v1/safety/run-shield
INFO: 127.0.0.1:54616 - "POST /v1/safety/run-shield HTTP/1.1" 200 OK
14:29:09.918 [END] /v1/safety/run-shield [StatusCode.OK] (262.26ms
```
[//]: # (## Documentation)
Co-authored-by: Jash Gulabrai <jgulabrai@nvidia.com>
|
||
|---|---|---|
| .. | ||
| __init__.py | ||
| config.py | ||
| nvidia.py | ||
| README.md | ||
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:
llama stack build --template nvidia --image-type conda
Basic Usage using the LlamaStack Python Client
Initialize the client
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
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
# 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")