llama-stack-mirror/llama_stack/providers/tests
Aidan Do e1f42eb5a5
[#432] Add Groq Provider - chat completions (#609)
# What does this PR do?

Contributes towards issue (#432)

- Groq text chat completions
- Streaming
- All the sampling params that Groq supports

A lot of inspiration taken from @mattf's good work at
https://github.com/meta-llama/llama-stack/pull/355

**What this PR does not do**

- Tool calls (Future PR)
- Adding llama-guard model
- See if we can add embeddings

### PR Train

- https://github.com/meta-llama/llama-stack/pull/609 👈 
- https://github.com/meta-llama/llama-stack/pull/630


## Test Plan

<details>

<summary>Environment</summary>

```bash
export GROQ_API_KEY=<api_key>

wget https://raw.githubusercontent.com/aidando73/llama-stack/240e6e2a9c20450ffdcfbabd800a6c0291f19288/build.yaml
wget https://raw.githubusercontent.com/aidando73/llama-stack/92c9b5297f9eda6a6e901e1adbd894e169dbb278/run.yaml

# Build and run environment
pip install -e . \
&& llama stack build --config ./build.yaml --image-type conda \
&& llama stack run ./run.yaml \
  --port 5001
```

</details>

<details>

<summary>Manual tests</summary>

Using this jupyter notebook to test manually:
2140976d76/hello.ipynb

Use this code to test passing in the api key from provider_data

```
from llama_stack_client import LlamaStackClient

client = LlamaStackClient(
    base_url="http://localhost:5001",
)

response = client.inference.chat_completion(
    model_id="Llama3.2-3B-Instruct",
    messages=[
        {"role": "user", "content": "Hello, world client!"},
    ],
    # Test passing in groq_api_key from the client
    # Need to comment out the groq_api_key in the run.yaml file
    x_llama_stack_provider_data='{"groq_api_key": "<api-key>"}',
    # stream=True,
)
response
```

</details>

<details>
<summary>Integration</summary>

`pytest llama_stack/providers/tests/inference/test_text_inference.py -v
-k groq`

(run in same environment)

```
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_model_list[llama_3b-groq] PASSED                 [  6%]
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_completion[llama_3b-groq] SKIPPED (Other inf...) [ 12%]
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_completion_structured_output[llama_3b-groq] SKIPPED [ 18%]
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_chat_completion_non_streaming[llama_3b-groq] PASSED [ 25%]
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_structured_output[llama_3b-groq] SKIPPED (Ot...) [ 31%]
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_chat_completion_streaming[llama_3b-groq] PASSED  [ 37%]
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_chat_completion_with_tool_calling[llama_3b-groq] SKIPPED [ 43%]
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_chat_completion_with_tool_calling_streaming[llama_3b-groq] SKIPPED [ 50%]
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_model_list[llama_8b-groq] PASSED                 [ 56%]
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_completion[llama_8b-groq] SKIPPED (Other inf...) [ 62%]
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_completion_structured_output[llama_8b-groq] SKIPPED [ 68%]
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_chat_completion_non_streaming[llama_8b-groq] PASSED [ 75%]
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_structured_output[llama_8b-groq] SKIPPED (Ot...) [ 81%]
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_chat_completion_streaming[llama_8b-groq] PASSED  [ 87%]
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_chat_completion_with_tool_calling[llama_8b-groq] SKIPPED [ 93%]
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_chat_completion_with_tool_calling_streaming[llama_8b-groq] SKIPPED [100%]

======================================= 6 passed, 10 skipped, 160 deselected, 7 warnings in 2.05s ========================================
```
</details>

<details>
<summary>Unit tests</summary>

`pytest llama_stack/providers/tests/inference/groq/ -v`

```
llama_stack/providers/tests/inference/groq/test_groq_utils.py::TestConvertChatCompletionRequest::test_sets_model PASSED            [  5%]
llama_stack/providers/tests/inference/groq/test_groq_utils.py::TestConvertChatCompletionRequest::test_converts_user_message PASSED [ 10%]
llama_stack/providers/tests/inference/groq/test_groq_utils.py::TestConvertChatCompletionRequest::test_converts_system_message PASSED [ 15%]
llama_stack/providers/tests/inference/groq/test_groq_utils.py::TestConvertChatCompletionRequest::test_converts_completion_message PASSED [ 20%]
llama_stack/providers/tests/inference/groq/test_groq_utils.py::TestConvertChatCompletionRequest::test_does_not_include_logprobs PASSED [ 25%]
llama_stack/providers/tests/inference/groq/test_groq_utils.py::TestConvertChatCompletionRequest::test_does_not_include_response_format PASSED [ 30%]
llama_stack/providers/tests/inference/groq/test_groq_utils.py::TestConvertChatCompletionRequest::test_does_not_include_repetition_penalty PASSED [ 35%]
llama_stack/providers/tests/inference/groq/test_groq_utils.py::TestConvertChatCompletionRequest::test_includes_stream PASSED       [ 40%]
llama_stack/providers/tests/inference/groq/test_groq_utils.py::TestConvertChatCompletionRequest::test_n_is_1 PASSED                [ 45%]
llama_stack/providers/tests/inference/groq/test_groq_utils.py::TestConvertChatCompletionRequest::test_if_max_tokens_is_0_then_it_is_not_included PASSED [ 50%]
llama_stack/providers/tests/inference/groq/test_groq_utils.py::TestConvertChatCompletionRequest::test_includes_max_tokens_if_set PASSED [ 55%]
llama_stack/providers/tests/inference/groq/test_groq_utils.py::TestConvertChatCompletionRequest::test_includes_temperature PASSED  [ 60%]
llama_stack/providers/tests/inference/groq/test_groq_utils.py::TestConvertChatCompletionRequest::test_includes_top_p PASSED        [ 65%]
llama_stack/providers/tests/inference/groq/test_groq_utils.py::TestConvertNonStreamChatCompletionResponse::test_returns_response PASSED [ 70%]
llama_stack/providers/tests/inference/groq/test_groq_utils.py::TestConvertNonStreamChatCompletionResponse::test_maps_stop_to_end_of_message PASSED [ 75%]
llama_stack/providers/tests/inference/groq/test_groq_utils.py::TestConvertNonStreamChatCompletionResponse::test_maps_length_to_end_of_message PASSED [ 80%]
llama_stack/providers/tests/inference/groq/test_groq_utils.py::TestConvertStreamChatCompletionResponse::test_returns_stream PASSED [ 85%]
llama_stack/providers/tests/inference/groq/test_init.py::TestGroqInit::test_raises_runtime_error_if_config_is_not_groq_config PASSED [ 90%]
llama_stack/providers/tests/inference/groq/test_init.py::TestGroqInit::test_returns_groq_adapter PASSED                            [ 95%]
llama_stack/providers/tests/inference/groq/test_init.py::TestGroqConfig::test_api_key_defaults_to_env_var PASSED                   [100%]

==================================================== 20 passed, 11 warnings in 0.08s =====================================================
```

</details>

## Before submitting

- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [x] Ran pre-commit to handle lint / formatting issues.
- [x] Read the [contributor
guideline](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md),
      Pull Request section?
- [x] Updated relevant documentation
- [x] Wrote necessary unit or integration tests.
2025-01-03 08:27:49 -08:00
..
agents [bugfix] fix meta-reference agents w/ safety multiple model loading pytest (#694) 2024-12-30 16:25:46 -08:00
datasetio [rag evals] refactor & add ability to eval retrieval + generation in agentic eval pipeline (#664) 2025-01-02 11:21:33 -08:00
eval [remove import *] clean up import *'s (#689) 2024-12-27 15:45:44 -08:00
inference [#432] Add Groq Provider - chat completions (#609) 2025-01-03 08:27:49 -08:00
memory [remove import *] clean up import *'s (#689) 2024-12-27 15:45:44 -08:00
post_training [remove import *] clean up import *'s (#689) 2024-12-27 15:45:44 -08:00
safety [remove import *] clean up import *'s (#689) 2024-12-27 15:45:44 -08:00
scoring [rag evals] refactor & add ability to eval retrieval + generation in agentic eval pipeline (#664) 2025-01-02 11:21:33 -08:00
__init__.py Remove "routing_table" and "routing_key" concepts for the user (#201) 2024-10-10 10:24:13 -07:00
conftest.py [1/n] torchtune <> llama-stack integration skeleton (#540) 2024-12-13 11:05:35 -08:00
env.py Significantly simpler and malleable test setup (#360) 2024-11-04 17:36:43 -08:00
README.md update tests --inference-model to hf id 2024-11-18 17:36:58 -08:00
resolver.py [remove import *] clean up import *'s (#689) 2024-12-27 15:45:44 -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 "meta-llama/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-shield CLI options as appropriate.

If you wanted to test a remotely hosted stack, you can use -m remote as follows:

pytest -s -m remote llama_stack/providers/tests/agents/test_agents.py \
  --env REMOTE_STACK_URL=<...>