mirror of
https://github.com/meta-llama/llama-stack.git
synced 2025-06-28 02:53:30 +00:00
252a487085
# What does this PR do? Adds nvidia as a safety provider by interfacing with the nemo guardrails microservice. This enables checking user’s input or the LLM’s output against input and output guardrails by using the `/v1/guardrails/checks` endpoint of the[ guardrails API.](https://developer.nvidia.com/docs/nemo-microservices/guardrails/source/guides/checks-guide.html) ## Test Plan Deploy nemo guardrails service following the documentation: https://developer.nvidia.com/docs/nemo-microservices/guardrails/source/getting-started/deploy-docker.html ### Standalone: ```bash (venv) local-cdgamarose@a1u1g-rome-0153:~/llama-stack$ pytest -v -s llama_stack/providers/tests/safety/test_safety.py --providers inference=nvidia,safety=nvidia --safety-shield meta/llama-3.1-8b-instruct =================================================================================== test session starts =================================================================================== platform linux -- Python 3.10.12, pytest-8.3.4, pluggy-1.5.0 -- /localhome/local-cdgamarose/llama-stack/venv/bin/python3 cachedir: .pytest_cache metadata: {'Python': '3.10.12', 'Platform': 'Linux-5.15.0-122-generic-x86_64-with-glibc2.35', 'Packages': {'pytest': '8.3.4', 'pluggy': '1.5.0'}, 'Plugins': {'metadata': '3.1.1', 'asyncio': '0.25.3', 'anyio': '4.8.0', 'html': '4.1.1'}} rootdir: /localhome/local-cdgamarose/llama-stack configfile: pyproject.toml plugins: metadata-3.1.1, asyncio-0.25.3, anyio-4.8.0, html-4.1.1 asyncio: mode=strict, asyncio_default_fixture_loop_scope=None collected 2 items llama_stack/providers/tests/safety/test_safety.py::TestSafety::test_shield_list[--inference=nvidia:safety=nvidia] Initializing NVIDIASafetyAdapter(http://0.0.0.0:7331)... PASSED llama_stack/providers/tests/safety/test_safety.py::TestSafety::test_run_shield[--inference=nvidia:safety=nvidia] PASSED ============================================================================== 2 passed, 2 warnings in 4.78s ============================================================================== ``` ### Distribution: ``` llama stack run llama_stack/templates/nvidia/run-with-safety.yaml curl -v -X 'POST' "http://localhost:8321/v1/safety/run-shield" -H 'accept: application/json' -H 'Content-Type: application/json' -d '{"shield_id": "meta/llama-3.1-8b-instruct", "messages":[{"role": "user", "content": "you are stupid"}]}' {"violation":{"violation_level":"error","user_message":"Sorry I cannot do this.","metadata":{"self check input":{"status":"blocked"}}}} ``` [//]: # (## Documentation) --------- Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com> |
||
|---|---|---|
| .. | ||
| _static | ||
| notebooks | ||
| openapi_generator | ||
| resources | ||
| source | ||
| zero_to_hero_guide | ||
| conftest.py | ||
| contbuild.sh | ||
| dog.jpg | ||
| getting_started.ipynb | ||
| license_header.txt | ||
| make.bat | ||
| Makefile | ||
| readme.md | ||
| requirements.txt | ||
Llama Stack Documentation
Here's a collection of comprehensive guides, examples, and resources for building AI applications with Llama Stack. For the complete documentation, visit our ReadTheDocs page.
Content
Try out Llama Stack's capabilities through our detailed Jupyter notebooks:
- Building AI Applications Notebook - A comprehensive guide to building production-ready AI applications using Llama Stack
- Benchmark Evaluations Notebook - Detailed performance evaluations and benchmarking results
- Zero-to-Hero Guide - Step-by-step guide for getting started with Llama Stack