mirror of
https://github.com/hanzoai/runtime.git
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zeekay
ea80dc3638
- Add main Dockerfile for production builds - Add Dockerfile.runtime for secure code execution - Add Dockerfile.runtime.fixed with improved configuration - Include .dockerignore for build optimization - Add integration documentation and publishing guides - Update API and CLI components for better runtime support - Enhance sandbox and container management features
164 lines
7.2 KiB
Python
Generated
164 lines
7.2 KiB
Python
Generated
# coding: utf-8
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"""
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Runtime
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Runtime AI platform API Docs
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The version of the OpenAPI document: 1.0
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Contact: [email protected]
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Generated by OpenAPI Generator (https://openapi-generator.tech)
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Do not edit the class manually.
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""" # noqa: E501
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from __future__ import annotations
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import pprint
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import re # noqa: F401
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import json
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from pydantic import BaseModel, ConfigDict, Field, StrictBool, StrictInt, StrictStr, field_validator
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from typing import Any, ClassVar, Dict, List, Optional
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from runtime_api_client.models.create_build_info import CreateBuildInfo
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from runtime_api_client.models.sandbox_volume import SandboxVolume
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from typing import Optional, Set
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from typing_extensions import Self
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class CreateSandbox(BaseModel):
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"""
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CreateSandbox
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""" # noqa: E501
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snapshot: Optional[StrictStr] = Field(default=None, description="The ID or name of the snapshot used for the sandbox")
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user: Optional[StrictStr] = Field(default=None, description="The user associated with the project")
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env: Optional[Dict[str, StrictStr]] = Field(default=None, description="Environment variables for the sandbox")
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labels: Optional[Dict[str, StrictStr]] = Field(default=None, description="Labels for the sandbox")
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public: Optional[StrictBool] = Field(default=None, description="Whether the sandbox http preview is publicly accessible")
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var_class: Optional[StrictStr] = Field(default=None, description="The sandbox class type", alias="class")
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target: Optional[StrictStr] = Field(default=None, description="The target (region) where the sandbox will be created")
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cpu: Optional[StrictInt] = Field(default=None, description="CPU cores allocated to the sandbox")
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gpu: Optional[StrictInt] = Field(default=None, description="GPU units allocated to the sandbox")
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memory: Optional[StrictInt] = Field(default=None, description="Memory allocated to the sandbox in GB")
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disk: Optional[StrictInt] = Field(default=None, description="Disk space allocated to the sandbox in GB")
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auto_stop_interval: Optional[StrictInt] = Field(default=None, description="Auto-stop interval in minutes (0 means disabled)", alias="autoStopInterval")
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auto_archive_interval: Optional[StrictInt] = Field(default=None, description="Auto-archive interval in minutes (0 means the maximum interval will be used)", alias="autoArchiveInterval")
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auto_delete_interval: Optional[StrictInt] = Field(default=None, description="Auto-delete interval in minutes (negative value means disabled, 0 means delete immediately upon stopping)", alias="autoDeleteInterval")
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volumes: Optional[List[SandboxVolume]] = Field(default=None, description="Array of volumes to attach to the sandbox")
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build_info: Optional[CreateBuildInfo] = Field(default=None, description="Build information for the sandbox", alias="buildInfo")
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additional_properties: Dict[str, Any] = {}
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__properties: ClassVar[List[str]] = ["snapshot", "user", "env", "labels", "public", "class", "target", "cpu", "gpu", "memory", "disk", "autoStopInterval", "autoArchiveInterval", "autoDeleteInterval", "volumes", "buildInfo"]
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@field_validator('var_class')
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def var_class_validate_enum(cls, value):
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"""Validates the enum"""
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if value is None:
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return value
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if value not in set(['small', 'medium', 'large']):
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raise ValueError("must be one of enum values ('small', 'medium', 'large')")
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return value
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@field_validator('target')
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def target_validate_enum(cls, value):
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"""Validates the enum"""
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if value is None:
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return value
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if value not in set(['eu', 'us', 'asia']):
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raise ValueError("must be one of enum values ('eu', 'us', 'asia')")
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return value
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model_config = ConfigDict(
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populate_by_name=True,
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validate_assignment=True,
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protected_namespaces=(),
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)
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def to_str(self) -> str:
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"""Returns the string representation of the model using alias"""
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return pprint.pformat(self.model_dump(by_alias=True))
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def to_json(self) -> str:
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"""Returns the JSON representation of the model using alias"""
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# TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
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return json.dumps(self.to_dict())
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@classmethod
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def from_json(cls, json_str: str) -> Optional[Self]:
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"""Create an instance of CreateSandbox from a JSON string"""
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return cls.from_dict(json.loads(json_str))
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def to_dict(self) -> Dict[str, Any]:
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"""Return the dictionary representation of the model using alias.
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This has the following differences from calling pydantic's
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`self.model_dump(by_alias=True)`:
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* `None` is only added to the output dict for nullable fields that
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were set at model initialization. Other fields with value `None`
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are ignored.
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* Fields in `self.additional_properties` are added to the output dict.
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"""
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excluded_fields: Set[str] = set([
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"additional_properties",
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])
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_dict = self.model_dump(
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by_alias=True,
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exclude=excluded_fields,
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exclude_none=True,
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)
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# override the default output from pydantic by calling `to_dict()` of each item in volumes (list)
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_items = []
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if self.volumes:
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for _item_volumes in self.volumes:
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if _item_volumes:
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_items.append(_item_volumes.to_dict())
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_dict['volumes'] = _items
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# override the default output from pydantic by calling `to_dict()` of build_info
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if self.build_info:
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_dict['buildInfo'] = self.build_info.to_dict()
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# puts key-value pairs in additional_properties in the top level
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if self.additional_properties is not None:
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for _key, _value in self.additional_properties.items():
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_dict[_key] = _value
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return _dict
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@classmethod
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def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
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"""Create an instance of CreateSandbox from a dict"""
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if obj is None:
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return None
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if not isinstance(obj, dict):
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return cls.model_validate(obj)
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_obj = cls.model_validate({
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"snapshot": obj.get("snapshot"),
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"user": obj.get("user"),
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"env": obj.get("env"),
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"labels": obj.get("labels"),
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"public": obj.get("public"),
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"class": obj.get("class"),
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"target": obj.get("target"),
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"cpu": obj.get("cpu"),
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"gpu": obj.get("gpu"),
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"memory": obj.get("memory"),
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"disk": obj.get("disk"),
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"autoStopInterval": obj.get("autoStopInterval"),
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"autoArchiveInterval": obj.get("autoArchiveInterval"),
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"autoDeleteInterval": obj.get("autoDeleteInterval"),
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"volumes": [SandboxVolume.from_dict(_item) for _item in obj["volumes"]] if obj.get("volumes") is not None else None,
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"buildInfo": CreateBuildInfo.from_dict(obj["buildInfo"]) if obj.get("buildInfo") is not None else None
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})
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# store additional fields in additional_properties
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for _key in obj.keys():
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if _key not in cls.__properties:
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_obj.additional_properties[_key] = obj.get(_key)
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return _obj
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