# What does this PR do? This PR brings back the facility to not force registration of resources onto the user. This is not just annoying but actually not feasible sometimes. For example, you may have a Stack which boots up with private providers for inference for models A and B. There is no way for the user to actually know which model is being served by these providers now (to be able to register it.) How will this avoid the users needing to do registration? In a follow-up diff, I will make sure I update the sample run.yaml files so they list the models served by the distributions explicitly. So when users do `llama stack build --template <...>` and run it, their distributions come up with the right set of models they expect. For self-hosted distributions, it also allows us to have a place to explicit list the models that need to be served to make the "complete" stack (including safety, e.g.) ## Test Plan Started ollama locally with two lightweight models: Llama3.2-3B-Instruct and Llama-Guard-3-1B. Updated all the tests including agents. Here's the tests I ran so far: ```bash pytest -s -v -m "fireworks and llama_3b" test_text_inference.py::TestInference \ --env FIREWORKS_API_KEY=... pytest -s -v -m "ollama and llama_3b" test_text_inference.py::TestInference pytest -s -v -m ollama test_safety.py pytest -s -v -m faiss test_memory.py pytest -s -v -m ollama test_agents.py \ --inference-model=Llama3.2-3B-Instruct --safety-model=Llama-Guard-3-1B ``` Found a few bugs here and there pre-existing that these test runs fixed. |
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.. | ||
agents | ||
datasetio | ||
eval | ||
inference | ||
memory | ||
safety | ||
scoring | ||
__init__.py | ||
conftest.py | ||
env.py | ||
README.md | ||
resolver.py |
Testing Llama Stack Providers
The Llama Stack is designed as a collection of Lego blocks -- various APIs -- which are composable and can be used to quickly and reliably build an app. We need a testing setup which is relatively flexible to enable easy combinations of these providers.
We use pytest
and all of its dynamism to enable the features needed. Specifically:
-
We use
pytest_addoption
to add CLI options allowing you to override providers, models, etc. -
We use
pytest_generate_tests
to dynamically parametrize our tests. This allows us to support a default set of (providers, models, etc.) combinations but retain the flexibility to override them via the CLI if needed. -
We use
pytest_configure
to make sure we dynamically add appropriate marks based on the fixtures we make.
Common options
All tests support a --providers
option which can be a string of the form api1=provider_fixture1,api2=provider_fixture2
. So, when testing safety (which need inference and safety APIs) you can use --providers inference=together,safety=meta_reference
to use these fixtures in concert.
Depending on the API, there are custom options enabled. For example, inference
tests allow for an --inference-model
override, etc.
By default, we disable warnings and enable short tracebacks. You can override them using pytest's flags as appropriate.
Some providers need special API keys or other configuration options to work. You can check out the individual fixtures (located in tests/<api>/fixtures.py
) for what these keys are. These can be specified using the --env
CLI option. You can also have it be present in the environment (exporting in your shell) or put it in the .env
file in the directory from which you run the test. For example, to use the Together fixture you can use --env TOGETHER_API_KEY=<...>
Inference
We have the following orthogonal parametrizations (pytest "marks") for inference tests:
- providers: (meta_reference, together, fireworks, ollama)
- models: (llama_8b, llama_3b)
If you want to run a test with the llama_8b model with fireworks, you can use:
pytest -s -v llama_stack/providers/tests/inference/test_text_inference.py \
-m "fireworks and llama_8b" \
--env FIREWORKS_API_KEY=<...>
You can make it more complex to run both llama_8b and llama_3b on Fireworks, but only llama_3b with Ollama:
pytest -s -v llama_stack/providers/tests/inference/test_text_inference.py \
-m "fireworks or (ollama and llama_3b)" \
--env FIREWORKS_API_KEY=<...>
Finally, you can override the model completely by doing:
pytest -s -v llama_stack/providers/tests/inference/test_text_inference.py \
-m fireworks \
--inference-model "Llama3.1-70B-Instruct" \
--env FIREWORKS_API_KEY=<...>
Agents
The Agents API composes three other APIs underneath:
- Inference
- Safety
- Memory
Given that each of these has several fixtures each, the set of combinations is large. We provide a default set of combinations (see tests/agents/conftest.py
) with easy to use "marks":
meta_reference
-- uses all themeta_reference
fixtures for the dependent APIstogether
-- uses Together for inference, andmeta_reference
for the restollama
-- uses Ollama for inference, andmeta_reference
for the rest
An example test with Together:
pytest -s -m together llama_stack/providers/tests/agents/test_agents.py \
--env TOGETHER_API_KEY=<...>
If you want to override the inference model or safety model used, you can use the --inference-model
or --safety-model
CLI options as appropriate.