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- 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
139 lines
5.6 KiB
Python
Generated
139 lines
5.6 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, StrictFloat, StrictInt, StrictStr
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from typing import Any, ClassVar, Dict, List, Optional, Union
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from runtime_api_client.models.runner_region import RunnerRegion
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from runtime_api_client.models.runner_state import RunnerState
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from runtime_api_client.models.sandbox_class import SandboxClass
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from typing import Optional, Set
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from typing_extensions import Self
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class Runner(BaseModel):
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"""
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Runner
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""" # noqa: E501
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id: StrictStr = Field(description="The ID of the runner")
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domain: StrictStr = Field(description="The domain of the runner")
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api_url: StrictStr = Field(description="The API URL of the runner", alias="apiUrl")
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api_key: StrictStr = Field(description="The API key for the runner", alias="apiKey")
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cpu: Union[StrictFloat, StrictInt] = Field(description="The CPU capacity of the runner")
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memory: Union[StrictFloat, StrictInt] = Field(description="The memory capacity of the runner in GB")
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disk: Union[StrictFloat, StrictInt] = Field(description="The disk capacity of the runner in GB")
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gpu: Union[StrictFloat, StrictInt] = Field(description="The GPU capacity of the runner")
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gpu_type: StrictStr = Field(description="The type of GPU", alias="gpuType")
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var_class: SandboxClass = Field(description="The class of the runner", alias="class")
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used: Union[StrictFloat, StrictInt] = Field(description="The current usage of the runner")
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capacity: Union[StrictFloat, StrictInt] = Field(description="The capacity of the runner")
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region: RunnerRegion = Field(description="The region of the runner")
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state: RunnerState = Field(description="The state of the runner")
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last_checked: Optional[StrictStr] = Field(default=None, description="The last time the runner was checked", alias="lastChecked")
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unschedulable: StrictBool = Field(description="Whether the runner is unschedulable")
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created_at: StrictStr = Field(description="The creation timestamp of the runner", alias="createdAt")
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updated_at: StrictStr = Field(description="The last update timestamp of the runner", alias="updatedAt")
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additional_properties: Dict[str, Any] = {}
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__properties: ClassVar[List[str]] = ["id", "domain", "apiUrl", "apiKey", "cpu", "memory", "disk", "gpu", "gpuType", "class", "used", "capacity", "region", "state", "lastChecked", "unschedulable", "createdAt", "updatedAt"]
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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 Runner 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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# 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 Runner 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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"id": obj.get("id"),
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"domain": obj.get("domain"),
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"apiUrl": obj.get("apiUrl"),
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"apiKey": obj.get("apiKey"),
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"cpu": obj.get("cpu"),
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"memory": obj.get("memory"),
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"disk": obj.get("disk"),
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"gpu": obj.get("gpu"),
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"gpuType": obj.get("gpuType"),
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"class": obj.get("class"),
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"used": obj.get("used"),
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"capacity": obj.get("capacity"),
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"region": obj.get("region"),
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"state": obj.get("state"),
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"lastChecked": obj.get("lastChecked"),
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"unschedulable": obj.get("unschedulable"),
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"createdAt": obj.get("createdAt"),
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"updatedAt": obj.get("updatedAt")
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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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