llama-stack/llama_stack/providers/tests
Ashwin Bharambe d9d271a684
Allow specifying resources in StackRunConfig (#425)
# 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.
2024-11-12 10:58:49 -08:00
..
agents Allow specifying resources in StackRunConfig (#425) 2024-11-12 10:58:49 -08:00
datasetio migrate dataset to resource (#420) 2024-11-11 17:14:41 -08:00
eval fix eval task registration (#426) 2024-11-12 11:51:34 -05:00
inference Allow specifying resources in StackRunConfig (#425) 2024-11-12 10:58:49 -08:00
memory Allow specifying resources in StackRunConfig (#425) 2024-11-12 10:58:49 -08:00
safety Allow specifying resources in StackRunConfig (#425) 2024-11-12 10:58:49 -08:00
scoring fix tests after registration migration & rename meta-reference -> basic / llm_as_judge provider (#424) 2024-11-12 10:35:44 -05:00
__init__.py Remove "routing_table" and "routing_key" concepts for the user (#201) 2024-10-10 10:24:13 -07:00
conftest.py [Evals API][10/n] API updates for EvalTaskDef + new test migration (#379) 2024-11-07 21:24:12 -08:00
env.py Significantly simpler and malleable test setup (#360) 2024-11-04 17:36:43 -08:00
README.md rename test_inference -> test_text_inference 2024-11-06 16:12:50 -08:00
resolver.py Allow specifying resources in StackRunConfig (#425) 2024-11-12 10:58:49 -08:00

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 the meta_reference fixtures for the dependent APIs
  • together -- uses Together for inference, and meta_reference for the rest
  • ollama -- uses Ollama for inference, and meta_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.