#24: Workaround fastapi/fastapi#684 by setting info in models.

py/API_models/exports.py

@@ -57,6 +57,8 @@ class ExportReq(BaseModel):
                                     "Per A(cquisition) or S(ample) or ''")
     out_to_ftp: bool = Field(title="Copy result file to FTP area. Original file is still available.")
 
+    class Config:
+        schema_extra = {"title": "Export request Model"}
 
 class ExportRsp(EMODnetExportRsp):
     """

py/API_models/helpers/TypedDictToModel.py

@@ -13,16 +13,17 @@
 
 # noinspection PyPackageRequirements
 from pydantic import create_model
-
-from API_models.helpers import PydanticModelT
 # noinspection PyPackageRequirements
 from pydantic.fields import ModelField
 
+from API_models.helpers import PydanticModelT
+
 # Generify the def with input type
 T = TypeVar('T')
 
 
-def typed_dict_to_model(typed_dict: T, field_infos:  Optional[Dict[str, Any]] = None):  # TODO -> Type[BaseModel]:
+def typed_dict_to_model(typed_dict: T, field_infos:  Optional[Dict[str, Any]] = None,
+                        config: Any = None):  # TODO -> Type[BaseModel], and type for config:
     annotations = {}
     for name, field in typed_dict.__annotations__.items():
         if field == Optional[str]:
@@ -32,7 +33,7 @@ def typed_dict_to_model(typed_dict: T, field_infos:  Optional[Dict[str, Any]] =
             raise Exception("Not managed yet")  # pragma:nocover
 
     ret: PydanticModelT = create_model(
-        typed_dict.__name__, **annotations  # type: ignore
+        typed_dict.__name__, __config__=config, **annotations  # type: ignore
     )
     # Make the model get-able
     # noinspection PyTypeHints

py/API_models/imports.py

@@ -20,6 +20,9 @@ class ImportReq(BaseModel):
     update_mode: str = Field(title="Update data ('Yes'), including classification ('Cla')",
                              default="")
 
+    class Config:
+        schema_extra = {"title": "Import request Model"}
+
 
 class ImportRsp(BaseModel):
     """ Import response. """
@@ -84,6 +87,9 @@ class SimpleImportReq(BaseModel):
     #                                    default=[v for v in PossibleSimpleImportFields.__members__])
     possible_values: List[str] = [v for v in SimpleImportFields.__members__]
 
+    class Config:
+        schema_extra = {"title": "Simple import request Model"}
+
 
 class SimpleImportRsp(BaseModel):
     """ Simple Import, response. """

py/API_models/login.py

@@ -9,6 +9,9 @@
 
 
 class LoginReq(BaseModel):
-    password: str = Field(title="User's password" , default=None, description="User password", example="test!")
-    username: str = Field(title="User's eamil", default=None, description="User email used during registration", example="[email protected]")
+    password: str = Field(title="User's password", default=None, description="User password", example="test!")
+    username: str = Field(title="User's email", default=None, description="User email used during registration",
+                          example="[email protected]")
 
+    class Config:
+        schema_extra = {"title": "Login request Model"}

py/API_models/prediction.py

@@ -11,20 +11,27 @@ class PredictionReq(BaseModel):
     """
         Prediction, AKA Auto Classification, request.
     """
-    project_id: int = Field(title="Project Id", description="The destination project, of which objects will be predicted.")
-    source_project_ids: List[int] = Field(title="Source project Ids", description="The source projects, objects in them will serve as reference.",
-                                    min_items=1)
-    features: List[str] = Field(title="Features", description="The object features AKA free column, to use in the algorithm. "
-                                "Features must be common to all projects, source ones and destination one",
+    project_id: int = Field(title="Project Id",
+                            description="The destination project, of which objects will be predicted.")
+    source_project_ids: List[int] = Field(title="Source project Ids",
+                                          description="The source projects, objects in them will serve as reference.",
+                                          min_items=1)
+    features: List[str] = Field(title="Features",
+                                description="The object features AKA free column, to use in the algorithm. "
+                                            "Features must be common to all projects, source ones and destination one",
                                 min_items=1)
-    categories: List[int] = Field(title="Categories", description="In source projects, only objects validated with these categories "
-                                  "will be considered.",
+    categories: List[int] = Field(title="Categories",
+                                  description="In source projects, only objects validated with these categories "
+                                              "will be considered.",
                                   min_items=1)
-    use_scn: bool = Field(title="Use scn", description="Use extra features, generated using the image, for improving the prediction.",
+    use_scn: bool = Field(title="Use scn",
+                          description="Use extra features, generated using the image, for improving the prediction.",
                           default=False)
 
     class Config:
         schema_extra = {
+            "title": "Prediction Request",
+            "description": "How to predict, in details.",
             "example": {
                 "project_id": [3426],
                 "source_project_ids": [1040, 1820],
@@ -38,7 +45,8 @@ class PredictionRsp(BaseModel):
     """
         Prediction response.
     """
-    errors: List[str] = Field(title="Errors", description="Showstopper problems found while preparing the prediction.",
+    errors: List[str] = Field(title="Errors",
+                              description="Showstopper problems found while preparing the prediction.",
                               example=[], default=[])
     warnings: List[str] = Field(title="Warnings", description="Problems found while preparing the prediction.",
                                 example=[], default=[])

py/API_models/subset.py

@@ -28,6 +28,9 @@ class SubsetReq(BaseModel):
     limit_value: float = Field(title="Limit value", description="Limit value, e.g. 20% or 5 per copepoda or 5% per sample.", example=10.0)
     do_images: bool = Field(title="Do images", description="If set, also clone images.", example=True)
 
+    class Config:
+        schema_extra = {"title": "Subset request Model"}
+
 
 class SubsetRsp(BaseModel):
     """ Subset response. """