refactor: packages (#249)

openllm-python/tests/_strategies/_configuration.py

@@ -1,12 +1,8 @@
 from __future__ import annotations
-import logging
-import typing as t
-
+import logging, typing as t, openllm
+from openllm_core._configuration import ModelSettings
 from hypothesis import strategies as st
 
-import openllm
-from openllm._configuration import ModelSettings
-
 logger = logging.getLogger(__name__)
 
 env_strats = st.sampled_from([openllm.utils.EnvVarMixin(model_name) for model_name in openllm.CONFIG_MAPPING.keys()])

openllm-python/tests/compiled_test.py

@@ -1,11 +0,0 @@
-from __future__ import annotations
-
-import pytest
-
-import openllm
-
-@pytest.mark.parametrize("name", ["AutoConfig", "AutoLLM", "AutoVLLM", "AutoFlaxLLM", "AutoTFLLM", "LLM", "LLMRunner", "LLMRunnable", "LLMEmbeddings",
-                                  "Runner", "client", "exceptions", "bundle", "build", "ggml", "transformers", "import_model", "infer_auto_class",
-                                  "infer_quantisation_config", "models", "list_models", "start", "start_grpc", "build", "serialisation"])
-def test_compiled_imports(name: str):
-  assert getattr(openllm, name) is not None

openllm-python/tests/configuration_test.py

@@ -1,32 +1,10 @@
 from __future__ import annotations
-import contextlib
-import logging
-import os
-import sys
-import typing as t
+import contextlib, os, sys, typing as t, attr, pytest, transformers, openllm
 from unittest import mock
-
-import attr
-import pytest
-import transformers
-from hypothesis import (
-  assume,
-  given,
-  strategies as st,
-)
-
-import openllm
-from openllm._configuration import GenerationConfig, ModelSettings, field_env_key
-
+from openllm_core._configuration import GenerationConfig, ModelSettings, field_env_key
+from hypothesis import assume, given, strategies as st
 from ._strategies._configuration import make_llm_config, model_settings
 
-logger = logging.getLogger(__name__)
-
-if t.TYPE_CHECKING:
-  DictStrAny = dict[str, t.Any]
-else:
-  DictStrAny = dict
-
 # XXX: @aarnphm fixes TypedDict behaviour in 3.11
 @pytest.mark.skipif(sys.version_info[:2] == (3, 11), reason="TypedDict in 3.11 behaves differently, so we need to fix this")
 def test_missing_default():
@@ -43,7 +21,6 @@ def test_forbidden_access():
   assert pytest.raises(openllm.exceptions.ForbiddenAttributeError, cl_.__getattribute__, cl_(), "__config__",)
   assert pytest.raises(openllm.exceptions.ForbiddenAttributeError, cl_.__getattribute__, cl_(), "GenerationConfig",)
   assert pytest.raises(openllm.exceptions.ForbiddenAttributeError, cl_.__getattribute__, cl_(), "SamplingParams",)
-
   assert openllm.utils.lenient_issubclass(cl_.__openllm_generation_class__, GenerationConfig)
 
 @given(model_settings())
@@ -133,7 +110,7 @@ def test_struct_envvar_with_overwrite_provided_env(monkeypatch: pytest.MonkeyPat
     assert sent.field1 == 20.0
 
 @given(model_settings())
-@pytest.mark.parametrize(("return_dict", "typ"), [(True, DictStrAny), (False, transformers.GenerationConfig)])
+@pytest.mark.parametrize(("return_dict", "typ"), [(True, dict), (False, transformers.GenerationConfig)])
 def test_conversion_to_transformers(return_dict: bool, typ: type[t.Any], gen_settings: ModelSettings):
   cl_ = make_llm_config("ConversionLLM", gen_settings)
   assert isinstance(cl_().to_generation_config(return_as_dict=return_dict), typ)

openllm-python/tests/conftest.py

@@ -1,6 +1,6 @@
 from __future__ import annotations
 import itertools, os, typing as t, pytest, openllm
-if t.TYPE_CHECKING: from openllm._configuration import LiteralRuntime
+if t.TYPE_CHECKING: from openllm_core._typing_compat import LiteralRuntime
 
 _FRAMEWORK_MAPPING = {"flan_t5": "google/flan-t5-small", "opt": "facebook/opt-125m", "baichuan": "baichuan-inc/Baichuan-7B",}
 _PROMPT_MAPPING = {"qa": "Answer the following yes/no question by reasoning step-by-step. Can you write a whole Haiku in a single tweet?",}

openllm-python/tests/models/conftest.py

@@ -4,7 +4,7 @@ from abc import ABC, abstractmethod
 import attr, docker, docker.errors, docker.types, orjson, pytest, openllm
 from syrupy.extensions.json import JSONSnapshotExtension
 from openllm._llm import normalise_model_name
-from openllm._typing_compat import DictStrAny, ListAny
+from openllm_core._typing_compat import DictStrAny, ListAny
 
 logger = logging.getLogger(__name__)
 

openllm-python/tests/models_test.py

@@ -1,11 +1,7 @@
 from __future__ import annotations
-import os
-import typing as t
+import os, typing as t, pytest
 
-import pytest
-
-if t.TYPE_CHECKING:
-  import openllm
+if t.TYPE_CHECKING: import openllm
 
 @pytest.mark.skipif(os.getenv("GITHUB_ACTIONS") is not None, reason="Model is too large for CI")
 def test_flan_t5_implementation(prompt: str, llm: openllm.LLM[t.Any, t.Any]):

openllm-python/tests/package_test.py

@@ -1,15 +1,7 @@
 from __future__ import annotations
-import functools
-import os
-import typing as t
-
-import pytest
-
-import openllm
+import functools, os, typing as t, pytest, openllm
 from bentoml._internal.configuration.containers import BentoMLContainer
-
-if t.TYPE_CHECKING:
-  from pathlib import Path
+if t.TYPE_CHECKING: from pathlib import Path
 
 HF_INTERNAL_T5_TESTING = "hf-internal-testing/tiny-random-t5"
 

openllm-python/tests/strategies_test.py

@@ -1,16 +1,8 @@
 from __future__ import annotations
-import os
-import typing as t
-
-import pytest
-
-if t.TYPE_CHECKING:
-  from _pytest.monkeypatch import MonkeyPatch
-
-import bentoml
-from bentoml._internal.resource import get_resource
-from openllm import _strategies as strategy
-from openllm._strategies import CascadingResourceStrategy, NvidiaGpuResource
+import os, typing as t, pytest, bentoml
+from openllm_core import _strategies as strategy
+from openllm_core._strategies import CascadingResourceStrategy, NvidiaGpuResource, get_resource
+if t.TYPE_CHECKING: from _pytest.monkeypatch import MonkeyPatch
 
 def test_nvidia_gpu_resource_from_env(monkeypatch: pytest.MonkeyPatch):
   with monkeypatch.context() as mcls: