forked from phoenix-oss/llama-stack-mirror
chore(lint): update Ruff ignores for project conventions and maintainability (#1184)
- Added new ignores from flake8-bugbear (`B007`, `B008`) - Ignored `C901` (high function complexity) for now, pending review - Maintained PyTorch conventions (`N812`, `N817`) - Allowed `E731` (lambda assignments) for flexibility - Consolidated existing ignores (`E402`, `E501`, `F405`, `C408`, `N812`) - Documented rationale for each ignored rule This keeps our linting aligned with project needs while tracking potential fixes. Signed-off-by: Sébastien Han <seb@redhat.com> Signed-off-by: Sébastien Han <seb@redhat.com>
This commit is contained in:
Sébastien Han
GitHub
parent
3b57d8ee88
commit
6fa257b475
33 changed files with 113 additions and 145 deletions
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@ -39,12 +39,11 @@ class Testeval:
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@pytest.mark.asyncio
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async def test_eval_evaluate_rows(self, eval_stack, inference_model, judge_model):
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eval_impl, benchmarks_impl, datasetio_impl, datasets_impl, models_impl = (
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eval_impl, benchmarks_impl, datasetio_impl, datasets_impl = (
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eval_stack[Api.eval],
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eval_stack[Api.benchmarks],
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eval_stack[Api.datasetio],
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eval_stack[Api.datasets],
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eval_stack[Api.models],
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)
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await register_dataset(datasets_impl, for_generation=True, dataset_id="test_dataset_for_eval")
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@ -92,11 +91,10 @@ class Testeval:
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@pytest.mark.asyncio
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async def test_eval_run_eval(self, eval_stack, inference_model, judge_model):
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eval_impl, benchmarks_impl, datasets_impl, models_impl = (
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eval_impl, benchmarks_impl, datasets_impl = (
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eval_stack[Api.eval],
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eval_stack[Api.benchmarks],
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eval_stack[Api.datasets],
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eval_stack[Api.models],
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)
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await register_dataset(datasets_impl, for_generation=True, dataset_id="test_dataset_for_eval")
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@ -131,11 +129,10 @@ class Testeval:
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@pytest.mark.asyncio
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async def test_eval_run_benchmark_eval(self, eval_stack, inference_model):
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eval_impl, benchmarks_impl, datasets_impl, models_impl = (
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eval_impl, benchmarks_impl, datasets_impl = (
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eval_stack[Api.eval],
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eval_stack[Api.benchmarks],
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eval_stack[Api.datasets],
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eval_stack[Api.models],
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)
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response = await datasets_impl.list_datasets()
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@ -18,54 +18,48 @@ from llama_stack.models.llama.sku_list import all_registered_models
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INFERENCE_APIS = ["chat_completion"]
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FUNCTIONALITIES = ["streaming", "structured_output", "tool_calling"]
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SUPPORTED_MODELS = {
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"ollama": set(
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[
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CoreModelId.llama3_1_8b_instruct.value,
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CoreModelId.llama3_1_8b_instruct.value,
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CoreModelId.llama3_1_70b_instruct.value,
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CoreModelId.llama3_1_70b_instruct.value,
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CoreModelId.llama3_1_405b_instruct.value,
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CoreModelId.llama3_1_405b_instruct.value,
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CoreModelId.llama3_2_1b_instruct.value,
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CoreModelId.llama3_2_1b_instruct.value,
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CoreModelId.llama3_2_3b_instruct.value,
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CoreModelId.llama3_2_3b_instruct.value,
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CoreModelId.llama3_2_11b_vision_instruct.value,
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CoreModelId.llama3_2_11b_vision_instruct.value,
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CoreModelId.llama3_2_90b_vision_instruct.value,
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CoreModelId.llama3_2_90b_vision_instruct.value,
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CoreModelId.llama3_3_70b_instruct.value,
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CoreModelId.llama_guard_3_8b.value,
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CoreModelId.llama_guard_3_1b.value,
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]
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),
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"fireworks": set(
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[
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CoreModelId.llama3_1_8b_instruct.value,
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CoreModelId.llama3_1_70b_instruct.value,
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CoreModelId.llama3_1_405b_instruct.value,
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CoreModelId.llama3_2_1b_instruct.value,
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CoreModelId.llama3_2_3b_instruct.value,
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CoreModelId.llama3_2_11b_vision_instruct.value,
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CoreModelId.llama3_2_90b_vision_instruct.value,
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CoreModelId.llama3_3_70b_instruct.value,
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CoreModelId.llama_guard_3_8b.value,
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CoreModelId.llama_guard_3_11b_vision.value,
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]
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),
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"together": set(
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[
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CoreModelId.llama3_1_8b_instruct.value,
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CoreModelId.llama3_1_70b_instruct.value,
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CoreModelId.llama3_1_405b_instruct.value,
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CoreModelId.llama3_2_3b_instruct.value,
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CoreModelId.llama3_2_11b_vision_instruct.value,
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CoreModelId.llama3_2_90b_vision_instruct.value,
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CoreModelId.llama3_3_70b_instruct.value,
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CoreModelId.llama_guard_3_8b.value,
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CoreModelId.llama_guard_3_11b_vision.value,
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]
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),
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"ollama": {
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CoreModelId.llama3_1_8b_instruct.value,
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CoreModelId.llama3_1_8b_instruct.value,
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CoreModelId.llama3_1_70b_instruct.value,
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CoreModelId.llama3_1_70b_instruct.value,
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CoreModelId.llama3_1_405b_instruct.value,
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CoreModelId.llama3_1_405b_instruct.value,
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CoreModelId.llama3_2_1b_instruct.value,
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CoreModelId.llama3_2_1b_instruct.value,
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CoreModelId.llama3_2_3b_instruct.value,
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CoreModelId.llama3_2_3b_instruct.value,
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CoreModelId.llama3_2_11b_vision_instruct.value,
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CoreModelId.llama3_2_11b_vision_instruct.value,
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CoreModelId.llama3_2_90b_vision_instruct.value,
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CoreModelId.llama3_2_90b_vision_instruct.value,
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CoreModelId.llama3_3_70b_instruct.value,
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CoreModelId.llama_guard_3_8b.value,
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CoreModelId.llama_guard_3_1b.value,
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},
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"fireworks": {
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CoreModelId.llama3_1_8b_instruct.value,
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CoreModelId.llama3_1_70b_instruct.value,
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CoreModelId.llama3_1_405b_instruct.value,
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CoreModelId.llama3_2_1b_instruct.value,
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CoreModelId.llama3_2_3b_instruct.value,
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CoreModelId.llama3_2_11b_vision_instruct.value,
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CoreModelId.llama3_2_90b_vision_instruct.value,
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CoreModelId.llama3_3_70b_instruct.value,
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CoreModelId.llama_guard_3_8b.value,
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CoreModelId.llama_guard_3_11b_vision.value,
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},
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"together": {
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CoreModelId.llama3_1_8b_instruct.value,
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CoreModelId.llama3_1_70b_instruct.value,
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CoreModelId.llama3_1_405b_instruct.value,
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CoreModelId.llama3_2_3b_instruct.value,
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CoreModelId.llama3_2_11b_vision_instruct.value,
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CoreModelId.llama3_2_90b_vision_instruct.value,
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CoreModelId.llama3_3_70b_instruct.value,
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CoreModelId.llama_guard_3_8b.value,
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CoreModelId.llama_guard_3_11b_vision.value,
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},
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}
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@ -45,13 +45,11 @@ class TestScoring:
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scoring_functions_impl,
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datasetio_impl,
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datasets_impl,
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models_impl,
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) = (
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scoring_stack[Api.scoring],
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scoring_stack[Api.scoring_functions],
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scoring_stack[Api.datasetio],
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scoring_stack[Api.datasets],
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scoring_stack[Api.models],
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)
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scoring_fns_list = await scoring_functions_impl.list_scoring_functions()
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provider_id = scoring_fns_list[0].provider_id
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@ -102,13 +100,11 @@ class TestScoring:
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scoring_functions_impl,
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datasetio_impl,
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datasets_impl,
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models_impl,
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) = (
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scoring_stack[Api.scoring],
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scoring_stack[Api.scoring_functions],
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scoring_stack[Api.datasetio],
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scoring_stack[Api.datasets],
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scoring_stack[Api.models],
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)
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await register_dataset(datasets_impl, for_rag=True)
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response = await datasets_impl.list_datasets()
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@ -163,13 +159,11 @@ class TestScoring:
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scoring_functions_impl,
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datasetio_impl,
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datasets_impl,
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models_impl,
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) = (
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scoring_stack[Api.scoring],
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scoring_stack[Api.scoring_functions],
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scoring_stack[Api.datasetio],
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scoring_stack[Api.datasets],
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scoring_stack[Api.models],
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)
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await register_dataset(datasets_impl, for_rag=True)
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rows = await datasetio_impl.get_rows_paginated(
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