# coding: utf-8

"""
    goose-server

    An AI agent

    The version of the OpenAPI document: 1.9.0
    Contact: ai-oss-tools@block.xyz
    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 datetime import datetime
from pydantic import BaseModel, ConfigDict, Field, StrictInt, StrictStr
from typing import Any, ClassVar, Dict, List, Optional
from typing_extensions import Annotated
from goose_api.models.message import Message
from goose_api.models.recipe import Recipe
from typing import Optional, Set
from typing_extensions import Self

class Session(BaseModel):
    """
    Session
    """ # noqa: E501
    accumulated_input_tokens: Optional[StrictInt] = None
    accumulated_output_tokens: Optional[StrictInt] = None
    accumulated_total_tokens: Optional[StrictInt] = None
    conversation: Optional[List[Message]] = None
    created_at: datetime
    description: StrictStr
    extension_data: Dict[str, Any] = Field(description="Extension data containing all extension states Keys are in format \"extension_name.version\" (e.g., \"todo.v0\")")
    id: StrictStr
    input_tokens: Optional[StrictInt] = None
    message_count: Annotated[int, Field(strict=True, ge=0)]
    output_tokens: Optional[StrictInt] = None
    recipe: Optional[Recipe] = None
    schedule_id: Optional[StrictStr] = None
    total_tokens: Optional[StrictInt] = None
    updated_at: datetime
    working_dir: StrictStr
    __properties: ClassVar[List[str]] = ["accumulated_input_tokens", "accumulated_output_tokens", "accumulated_total_tokens", "conversation", "created_at", "description", "extension_data", "id", "input_tokens", "message_count", "output_tokens", "recipe", "schedule_id", "total_tokens", "updated_at", "working_dir"]

    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 Session 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 conversation (list)
        _items = []
        if self.conversation:
            for _item_conversation in self.conversation:
                if _item_conversation:
                    _items.append(_item_conversation.to_dict())
            _dict['conversation'] = _items
        # override the default output from pydantic by calling `to_dict()` of recipe
        if self.recipe:
            _dict['recipe'] = self.recipe.to_dict()
        # set to None if accumulated_input_tokens (nullable) is None
        # and model_fields_set contains the field
        if self.accumulated_input_tokens is None and "accumulated_input_tokens" in self.model_fields_set:
            _dict['accumulated_input_tokens'] = None

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

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

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

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

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

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

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

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

        return _dict

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

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

        _obj = cls.model_validate({
            "accumulated_input_tokens": obj.get("accumulated_input_tokens"),
            "accumulated_output_tokens": obj.get("accumulated_output_tokens"),
            "accumulated_total_tokens": obj.get("accumulated_total_tokens"),
            "conversation": [Message.from_dict(_item) for _item in obj["conversation"]] if obj.get("conversation") is not None else None,
            "created_at": obj.get("created_at"),
            "description": obj.get("description"),
            "extension_data": obj.get("extension_data"),
            "id": obj.get("id"),
            "input_tokens": obj.get("input_tokens"),
            "message_count": obj.get("message_count"),
            "output_tokens": obj.get("output_tokens"),
            "recipe": Recipe.from_dict(obj["recipe"]) if obj.get("recipe") is not None else None,
            "schedule_id": obj.get("schedule_id"),
            "total_tokens": obj.get("total_tokens"),
            "updated_at": obj.get("updated_at"),
            "working_dir": obj.get("working_dir")
        })
        return _obj