chore: update openapi specs

Author: alarv

src/jaqpot_api_client/__init__.py

@@ -54,6 +54,7 @@
 from jaqpot_api_client.models.dataset_type import DatasetType
 from jaqpot_api_client.models.doa import Doa
 from jaqpot_api_client.models.doa_method import DoaMethod
+from jaqpot_api_client.models.docker_config import DockerConfig
 from jaqpot_api_client.models.error_code import ErrorCode
 from jaqpot_api_client.models.error_response import ErrorResponse
 from jaqpot_api_client.models.feature import Feature

src/jaqpot_api_client/models/__init__.py

@@ -27,6 +27,7 @@
 from jaqpot_api_client.models.dataset_type import DatasetType
 from jaqpot_api_client.models.doa import Doa
 from jaqpot_api_client.models.doa_method import DoaMethod
+from jaqpot_api_client.models.docker_config import DockerConfig
 from jaqpot_api_client.models.error_code import ErrorCode
 from jaqpot_api_client.models.error_response import ErrorResponse
 from jaqpot_api_client.models.feature import Feature

src/jaqpot_api_client/models/docker_config.py

@@ -0,0 +1,98 @@
+# coding: utf-8
+
+"""
+    Jaqpot API
+
+    A modern RESTful API for model management and prediction services, built using Spring Boot and Kotlin. Supports seamless integration with machine learning workflows.
+
+    The version of the OpenAPI document: 1.0.0
+    Contact: upci.ntua@gmail.com
+    Generated by OpenAPI Generator (https://openapi-generator.tech)
+
+    Do not edit the class manually.
+"""  # noqa: E501
+
+
+from __future__ import annotations
+import pprint
+import re  # noqa: F401
+import json
+
+from pydantic import BaseModel, ConfigDict, Field, field_validator
+from typing import Any, ClassVar, Dict, List, Optional
+from typing_extensions import Annotated
+from typing import Optional, Set
+from typing_extensions import Self
+
+class DockerConfig(BaseModel):
+    """
+    DockerConfig
+    """ # noqa: E501
+    app_name: Annotated[str, Field(strict=True, max_length=63)] = Field(description="Unique identifier used for internal service discovery", alias="appName")
+    docker_image: Optional[Annotated[str, Field(strict=True, max_length=255)]] = Field(default=None, description="Reference to the Docker image (for admin documentation)", alias="dockerImage")
+    __properties: ClassVar[List[str]] = ["appName", "dockerImage"]
+
+    @field_validator('app_name')
+    def app_name_validate_regular_expression(cls, value):
+        """Validates the regular expression"""
+        if not re.match(r"^[a-z0-9][a-z0-9-]*[a-z0-9]$", value):
+            raise ValueError(r"must validate the regular expression /^[a-z0-9][a-z0-9-]*[a-z0-9]$/")
+        return value
+
+    model_config = ConfigDict(
+        populate_by_name=True,
+        validate_assignment=True,
+        protected_namespaces=(),
+    )
+
+
+    def to_str(self) -> str:
+        """Returns the string representation of the model using alias"""
+        return pprint.pformat(self.model_dump(by_alias=True))
+
+    def to_json(self) -> str:
+        """Returns the JSON representation of the model using alias"""
+        # TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
+        return json.dumps(self.to_dict())
+
+    @classmethod
+    def from_json(cls, json_str: str) -> Optional[Self]:
+        """Create an instance of DockerConfig from a JSON string"""
+        return cls.from_dict(json.loads(json_str))
+
+    def to_dict(self) -> Dict[str, Any]:
+        """Return the dictionary representation of the model using alias.
+
+        This has the following differences from calling pydantic's
+        `self.model_dump(by_alias=True)`:
+
+        * `None` is only added to the output dict for nullable fields that
+          were set at model initialization. Other fields with value `None`
+          are ignored.
+        """
+        excluded_fields: Set[str] = set([
+        ])
+
+        _dict = self.model_dump(
+            by_alias=True,
+            exclude=excluded_fields,
+            exclude_none=True,
+        )
+        return _dict
+
+    @classmethod
+    def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
+        """Create an instance of DockerConfig from a dict"""
+        if obj is None:
+            return None
+
+        if not isinstance(obj, dict):
+            return cls.model_validate(obj)
+
+        _obj = cls.model_validate({
+            "appName": obj.get("appName"),
+            "dockerImage": obj.get("dockerImage")
+        })
+        return _obj
+
+

src/jaqpot_api_client/models/feature_type.py

@@ -33,6 +33,7 @@ class FeatureType(str, Enum):
     SMILES = 'SMILES'
     STRING = 'STRING'
     TEXT = 'TEXT'
+    BOOLEAN = 'BOOLEAN'
     FLOAT_ARRAY = 'FLOAT_ARRAY'
     STRING_ARRAY = 'STRING_ARRAY'
 

src/jaqpot_api_client/models/model.py

@@ -23,6 +23,7 @@
 from typing import Any, ClassVar, Dict, List, Optional, Union
 from typing_extensions import Annotated
 from jaqpot_api_client.models.doa import Doa
+from jaqpot_api_client.models.docker_config import DockerConfig
 from jaqpot_api_client.models.feature import Feature
 from jaqpot_api_client.models.library import Library
 from jaqpot_api_client.models.model_scores import ModelScores
@@ -67,9 +68,10 @@ class Model(BaseModel):
     legacy_prediction_service: Optional[StrictStr] = Field(default=None, alias="legacyPredictionService")
     scores: Optional[ModelScores] = None
     r_pbpk_config: Optional[RPbpkConfig] = Field(default=None, alias="rPbpkConfig")
+    docker_config: Optional[DockerConfig] = Field(default=None, alias="dockerConfig")
     created_at: Optional[datetime] = Field(default=None, description="The date and time when the feature was created.", alias="createdAt")
     updated_at: Optional[datetime] = Field(default=None, description="The date and time when the model was last updated.", alias="updatedAt")
-    __properties: ClassVar[List[str]] = ["id", "name", "description", "type", "jaqpotpyVersion", "doas", "libraries", "dependentFeatures", "independentFeatures", "sharedWithOrganizations", "visibility", "task", "archived", "archivedAt", "torchConfig", "preprocessors", "featurizers", "rawPreprocessor", "rawModel", "creator", "canEdit", "isAdmin", "selectedFeatures", "tags", "legacyPredictionService", "scores", "rPbpkConfig", "createdAt", "updatedAt"]
+    __properties: ClassVar[List[str]] = ["id", "name", "description", "type", "jaqpotpyVersion", "doas", "libraries", "dependentFeatures", "independentFeatures", "sharedWithOrganizations", "visibility", "task", "archived", "archivedAt", "torchConfig", "preprocessors", "featurizers", "rawPreprocessor", "rawModel", "creator", "canEdit", "isAdmin", "selectedFeatures", "tags", "legacyPredictionService", "scores", "rPbpkConfig", "dockerConfig", "createdAt", "updatedAt"]
 
     model_config = ConfigDict(
         populate_by_name=True,
@@ -168,6 +170,9 @@ def to_dict(self) -> Dict[str, Any]:
         # override the default output from pydantic by calling `to_dict()` of r_pbpk_config
         if self.r_pbpk_config:
             _dict['rPbpkConfig'] = self.r_pbpk_config.to_dict()
+        # override the default output from pydantic by calling `to_dict()` of docker_config
+        if self.docker_config:
+            _dict['dockerConfig'] = self.docker_config.to_dict()
         return _dict
 
     @classmethod
@@ -207,6 +212,7 @@ def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
             "legacyPredictionService": obj.get("legacyPredictionService"),
             "scores": ModelScores.from_dict(obj["scores"]) if obj.get("scores") is not None else None,
             "rPbpkConfig": RPbpkConfig.from_dict(obj["rPbpkConfig"]) if obj.get("rPbpkConfig") is not None else None,
+            "dockerConfig": DockerConfig.from_dict(obj["dockerConfig"]) if obj.get("dockerConfig") is not None else None,
             "createdAt": obj.get("createdAt"),
             "updatedAt": obj.get("updatedAt")
         })

src/jaqpot_api_client/models/model_type.py

@@ -41,6 +41,7 @@ class ModelType(str, Enum):
     R_SVM = 'R_SVM'
     R_TREE_CLASS = 'R_TREE_CLASS'
     R_TREE_REGR = 'R_TREE_REGR'
+    DOCKER = 'DOCKER'
     QSAR_TOOLBOX_CALCULATOR = 'QSAR_TOOLBOX_CALCULATOR'
     QSAR_TOOLBOX_QSAR_MODEL = 'QSAR_TOOLBOX_QSAR_MODEL'
     QSAR_TOOLBOX_PROFILER = 'QSAR_TOOLBOX_PROFILER'

src/jaqpot_api_client/models/prediction_model.py

@@ -32,7 +32,7 @@ class PredictionModel(BaseModel):
     """
     PredictionModel
     """ # noqa: E501
-    id: Optional[StrictInt] = Field(default=None, description="Unique identifier for the prediction model")
+    id: StrictInt = Field(description="Unique identifier for the prediction model")
     dependent_features: List[Feature] = Field(description="List of dependent features for the model", alias="dependentFeatures")
     independent_features: List[Feature] = Field(description="List of independent features for the model", alias="independentFeatures")
     type: ModelType
@@ -123,11 +123,6 @@ def to_dict(self) -> Dict[str, Any]:
                 if _item_preprocessors:
                     _items.append(_item_preprocessors.to_dict())
             _dict['preprocessors'] = _items
-        # set to None if id (nullable) is None
-        # and model_fields_set contains the field
-        if self.id is None and "id" in self.model_fields_set:
-            _dict['id'] = None
-
         # set to None if torch_config (nullable) is None
         # and model_fields_set contains the field
         if self.torch_config is None and "torch_config" in self.model_fields_set: