Move files

great_ai/__init__.py

@@ -1,5 +1,5 @@
-"""GreatAI"""
+"""GreatAI."""
-__version__ = "0.1.0"
+__version__ = "0.1.1"
 
 
 from .context import configure
@@ -10,15 +10,17 @@ from .errors import (
     RemoteCallError,
     WrongDecoratorOrderError,
 )
-from .models import save_model, use_model
+from .models.save_model import save_model
-from .output_views import (
+from .models.use_model import use_model
-    ClassificationOutput,
-    MultiLabelClassificationOutput,
-    RegressionOutput,
-)
 from .parameters.log_metric import log_metric
 from .parameters.parameter import parameter
 from .persistence import MongodbDriver, ParallelTinyDbDriver, TracingDatabaseDriver
 from .remote import call_remote_great_ai, call_remote_great_ai_async
 from .tracing import add_ground_truth, delete_ground_truth, query_ground_truth
-from .views import RouteConfig, Trace
+from .views import (
+    ClassificationOutput,
+    MultiLabelClassificationOutput,
+    RegressionOutput,
+    RouteConfig,
+    Trace,
+)

great_ai/deploy/great_ai.py

@@ -23,7 +23,7 @@ from tqdm.cli import tqdm
 from ..constants import DASHBOARD_PATH
 from ..context import get_context
 from ..helper import freeze_arguments, get_function_metadata_store, snake_case_to_text
-from ..models import model_versions
+from ..models.use_model import model_versions
 from ..parameters.automatically_decorate_parameters import (
     automatically_decorate_parameters,
 )
@@ -58,7 +58,10 @@ class GreatAI(Generic[T, V]):
         self._wrapped_func = wraps(func)(freeze_arguments(self._cached_func))
 
         wraps(func)(self)
-        self.__doc__ = f"GreatAI wrapper for interacting with the `{self.__name__}` function.\n\n{dedent(self.__doc__ or '')}"
+        self.__doc__ = (
+            f"GreatAI wrapper for interacting with the `{self.__name__}` "
+            + f"function.\n\n{dedent(self.__doc__ or '')}"
+        )
 
         self.version = str(get_context().version)
         flat_model_versions = ".".join(f"{k}-v{v}" for k, v in model_versions)
@@ -79,7 +82,7 @@ class GreatAI(Generic[T, V]):
     @overload
     @staticmethod
     def create(  # type: ignore
-        # "Overloaded function signatures 1 and 2 overlap with incompatible return types"
+        # Overloaded function signatures 1 and 2 overlap with incompatible return types
         # https://github.com/python/mypy/issues/12759
         func: Callable[..., Awaitable[V]],
     ) -> "GreatAI[Awaitable[Trace[V]], V]":
@@ -131,8 +134,8 @@ class GreatAI(Generic[T, V]):
 
         Returns:
             A GreatAI instance wrapping `func`.
-
         """
+
         return GreatAI[Trace[V], V](
             func,
         )

great_ai/deploy/routes/dashboard/assets/index.css

@@ -206,10 +206,6 @@ main > header .placeholder {
   flex-grow: 1;
 }
 
-main > footer {
-  margin: 0;
-}
-
 main > footer {
   display: flex;
   justify-content: space-between;

great_ai/helper/__init__.py

@@ -1,7 +1,6 @@
 from .freeze_arguments import freeze, freeze_arguments
 from .get_arguments import get_arguments
 from .get_function_metadata_store import get_function_metadata_store
-from .hashable_base_model import HashableBaseModel
 from .snake_case_to_text import snake_case_to_text
 from .strip_lines import strip_lines
 from .text_to_hex_color import text_to_hex_color

great_ai/helper/get_arguments.py

@@ -5,7 +5,7 @@ from typing import Any, Callable, Dict, Mapping, Sequence
 def get_arguments(
     func: Callable, args: Sequence[Any], kwargs: Mapping[str, Any]
 ) -> Dict[str, Any]:
-    """Return mapping from parameter names to actual argument values"""
+    """Return mapping from parameter names to actual argument values."""
 
     signature = inspect.signature(func)
 

great_ai/models/__init__.py

@@ -1,2 +0,0 @@
-from .save_model import save_model
-from .use_model import model_versions, use_model

great_ai/models/save_model.py

@@ -19,7 +19,7 @@ def save_model(
             >>> from great_ai import use_model
             >>> save_model(3, 'my_number')
             'my_number:...'
-            
+
             >>> @use_model('my_number')
             ... def my_function(a, model):
             ...     return a + model

great_ai/models/use_model.py

@@ -32,17 +32,13 @@ def use_model(
 ) -> Callable[[F], F]:
     """Inject a model into a function.
 
-    Load a model specified by `key` and `version` using the
+    Load a model specified by `key` and `version` using the currently active `LargeFile`
-    currently active `LargeFile` implementation. If it's a
+    implementation. If it's a single object, it is deserialised using `dill`. If it's a
-    single object, it is deserialised using `dill`. If it's
+    directory of files, a `pathlib.Path` instance is given.
-    a directory of files, a `pathlib.Path` instance is given.
 
-    By default, the function's `model` parameter is replaced
+    By default, the function's `model` parameter is replaced by the loaded model. This
-    by the loaded model. This can be customised by changing
+    can be customised by changing `model_kwarg_name`. Multiple models can be loaded by
-    `model_kwarg_name`.
+    decorating the same function with `use_model` multiple times.
-
-    Multiple models can be loaded by decorating the same
-    function with `use_model` multiple times.
 
     Examples:
             >>> from great_ai import save_model

great_ai/views/__init__.py

@@ -6,6 +6,11 @@ from .function_metadata import FunctionMetadata
 from .health_check_response import HealthCheckResponse
 from .model import Model
 from .operators import operators
+from .outputs import (
+    ClassificationOutput,
+    MultiLabelClassificationOutput,
+    RegressionOutput,
+)
 from .query import Query
 from .route_config import RouteConfig
 from .sort_by import SortBy

great_ai/views/outputs/classification_output.py

@@ -1,6 +1,6 @@
 from typing import Any, Optional, Union
 
-from ..helper import HashableBaseModel
+from ..hashable_base_model import HashableBaseModel
 
 
 class ClassificationOutput(HashableBaseModel):

great_ai/views/outputs/multi_label_classification_output.py

@@ -1,6 +1,6 @@
 from typing import List
 
-from ..helper import HashableBaseModel
+from ..hashable_base_model import HashableBaseModel
 from .classification_output import ClassificationOutput
 
 

great_ai/views/outputs/regression_output.py

@@ -1,6 +1,6 @@
 from typing import Any, Optional, Union
 
-from ..helper import HashableBaseModel
+from ..hashable_base_model import HashableBaseModel
 
 
 class RegressionOutput(HashableBaseModel):

great_ai/views/trace.py

@@ -3,7 +3,7 @@ from typing import Any, Dict, Generic, List, Optional, TypeVar
 
 from pydantic import Extra
 
-from ..helper import HashableBaseModel
+from .hashable_base_model import HashableBaseModel
 from .model import Model
 
 T = TypeVar("T")