# coding: utf-8

"""
    Hindsight HTTP API

    HTTP API for Hindsight

    The version of the OpenAPI document: 0.5.3
    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
from typing import Any, ClassVar, Dict, List, Optional
from hindsight_client_api.models.reflect_directive import ReflectDirective
from hindsight_client_api.models.reflect_fact import ReflectFact
from hindsight_client_api.models.reflect_mental_model import ReflectMentalModel
from typing import Optional, Set
from typing_extensions import Self

class ReflectBasedOn(BaseModel):
    """
    Evidence the response is based on: memories, mental models, and directives.
    """ # noqa: E501
    memories: Optional[List[ReflectFact]] = Field(default=None, description="Memory facts used to generate the response")
    mental_models: Optional[List[ReflectMentalModel]] = Field(default=None, description="Mental models used during reflection")
    directives: Optional[List[ReflectDirective]] = Field(default=None, description="Directives applied during reflection")
    __properties: ClassVar[List[str]] = ["memories", "mental_models", "directives"]

    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 ReflectBasedOn 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 memories (list)
        _items = []
        if self.memories:
            for _item_memories in self.memories:
                if _item_memories:
                    _items.append(_item_memories.to_dict())
            _dict['memories'] = _items
        # override the default output from pydantic by calling `to_dict()` of each item in mental_models (list)
        _items = []
        if self.mental_models:
            for _item_mental_models in self.mental_models:
                if _item_mental_models:
                    _items.append(_item_mental_models.to_dict())
            _dict['mental_models'] = _items
        # override the default output from pydantic by calling `to_dict()` of each item in directives (list)
        _items = []
        if self.directives:
            for _item_directives in self.directives:
                if _item_directives:
                    _items.append(_item_directives.to_dict())
            _dict['directives'] = _items
        return _dict

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

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

        _obj = cls.model_validate({
            "memories": [ReflectFact.from_dict(_item) for _item in obj["memories"]] if obj.get("memories") is not None else None,
            "mental_models": [ReflectMentalModel.from_dict(_item) for _item in obj["mental_models"]] if obj.get("mental_models") is not None else None,
            "directives": [ReflectDirective.from_dict(_item) for _item in obj["directives"]] if obj.get("directives") is not None else None
        })
        return _obj


