add external to apply and default requirement type (#196)

mlem/api/commands.py

@@ -54,7 +54,8 @@ def apply(
     *data: Union[str, DatasetMeta, Any],
     method: str = None,
     output: str = None,
-    link: bool = False,
+    link: bool = None,
+    external: bool = None,
 ) -> Optional[Any]:
     """Apply provided model against provided data
 
@@ -67,6 +68,7 @@ def apply(
         output (str, optional): If value is provided,
             assume it's path and save output there.
         link (bool): Whether to create a link to saved output in MLEM root folder.
+        external (bool): Whether to save result outside mlem dir
 
     Returns:
         If `output=None`, returns results for given data.
@@ -89,7 +91,7 @@ def apply(
             return res[0]
         return res
     if len(res) == 1:
-        return save(res[0], output, link=link)
+        return save(res[0], output, external=external, link=link)
 
     raise NotImplementedError(
         "Saving several input data objects is not implemented yet"

mlem/cli/apply.py

@@ -6,6 +6,7 @@
 from mlem.api import import_object
 from mlem.cli.main import (
     mlem_command,
+    option_external,
     option_json,
     option_link,
     option_repo,
@@ -58,6 +59,7 @@ def apply(
         help="Specify how to read data file for import",  # f"Available types: {list_implementations(ImportHook)}"
     ),
     link: bool = option_link,
+    external: bool = option_external,
     json: bool = option_json,
 ):
     """Apply a model to a dataset. Resulting dataset will be saved as MLEM object to `output` if it is provided, otherwise will be printed
@@ -97,6 +99,7 @@ def apply(
             method=method,
             output=output,
             link=link,
+            external=external,
         )
     if output is None and json:
         print(

mlem/core/requirements.py

@@ -49,6 +49,7 @@ class Requirement(MlemObject):
 
     class Config:
         type_root = True
+        default_type = "installable"
 
     abs_name: ClassVar[str] = "requirement"
     type: ClassVar = ...