# coding: utf-8

"""
Root Signals API

Root Signals JSON API provides a way to access Root Signals using provisioned API token

The version of the OpenAPI document: 1.0.0 (latest)
Generated by OpenAPI Generator (https://openapi-generator.tech)

Do not edit the class manually.
"""  # noqa: E501

from __future__ import annotations

import json
import pprint
import re  # noqa: F401
from typing import Any, ClassVar, Dict, List, Optional, Set

from pydantic import BaseModel, ConfigDict, Field, StrictBool
from typing_extensions import Annotated, Self

from root.generated.openapi_aclient.models.input_output_pair_input_request import InputOutputPairInputRequest


class EvaluationJobRequestRequest(BaseModel):
    """
    EvaluationJobRequestRequest
    """  # noqa: E501

    id: Optional[Annotated[str, Field(min_length=1, strict=True)]] = Field(
        default=None, description="Will be set automatically"
    )
    created_at: Optional[Annotated[str, Field(min_length=1, strict=True)]] = Field(
        default=None, description="Will be set automatically"
    )
    updated_at: Optional[Annotated[str, Field(min_length=1, strict=True)]] = Field(
        default=None, description="Will be set automatically"
    )
    samples: List[InputOutputPairInputRequest] = Field(description="List of content to evaluate in batch")
    job_name: Optional[Annotated[str, Field(min_length=1, strict=True)]] = Field(
        default=None, description="Optional name for this batch job"
    )
    drop_hints: Optional[StrictBool] = Field(
        default=False, description="Whether to drop existing preference hints during evaluation"
    )
    dataset_name: Optional[Annotated[str, Field(min_length=1, strict=True)]] = Field(
        default=None, description="Optional dataset name to set for the samples. Should be unique"
    )
    fast_mode: Optional[StrictBool] = Field(default=False, description="Use fast agents for evaluation")
    __properties: ClassVar[List[str]] = [
        "id",
        "created_at",
        "updated_at",
        "samples",
        "job_name",
        "drop_hints",
        "dataset_name",
        "fast_mode",
    ]

    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 EvaluationJobRequestRequest 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,
        )
        # override the default output from pydantic by calling `to_dict()` of each item in samples (list)
        _items = []
        if self.samples:
            for _item in self.samples:
                if _item:
                    _items.append(_item.to_dict())
            _dict["samples"] = _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 created_at (nullable) is None
        # and model_fields_set contains the field
        if self.created_at is None and "created_at" in self.model_fields_set:
            _dict["created_at"] = None

        # set to None if updated_at (nullable) is None
        # and model_fields_set contains the field
        if self.updated_at is None and "updated_at" in self.model_fields_set:
            _dict["updated_at"] = None

        # set to None if job_name (nullable) is None
        # and model_fields_set contains the field
        if self.job_name is None and "job_name" in self.model_fields_set:
            _dict["job_name"] = None

        # set to None if drop_hints (nullable) is None
        # and model_fields_set contains the field
        if self.drop_hints is None and "drop_hints" in self.model_fields_set:
            _dict["drop_hints"] = None

        # set to None if dataset_name (nullable) is None
        # and model_fields_set contains the field
        if self.dataset_name is None and "dataset_name" in self.model_fields_set:
            _dict["dataset_name"] = None

        # set to None if fast_mode (nullable) is None
        # and model_fields_set contains the field
        if self.fast_mode is None and "fast_mode" in self.model_fields_set:
            _dict["fast_mode"] = None

        return _dict

    @classmethod
    def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
        """Create an instance of EvaluationJobRequestRequest from a dict"""
        if obj is None:
            return None

        if not isinstance(obj, dict):
            return cls.model_validate(obj)

        _obj = cls.model_validate(
            {
                "id": obj.get("id"),
                "created_at": obj.get("created_at"),
                "updated_at": obj.get("updated_at"),
                "samples": [InputOutputPairInputRequest.from_dict(_item) for _item in obj["samples"]]
                if obj.get("samples") is not None
                else None,
                "job_name": obj.get("job_name"),
                "drop_hints": obj.get("drop_hints") if obj.get("drop_hints") is not None else False,
                "dataset_name": obj.get("dataset_name"),
                "fast_mode": obj.get("fast_mode") if obj.get("fast_mode") is not None else False,
            }
        )
        return _obj
