"""This module includes classes to define configurations."""

from typing import Any, Dict, List, Optional

from pyaml_env import parse_config
from pydantic import BaseModel


class Query(BaseModel):
    query: str
    query_abbreviation: str
    abbreviations_replaced: Optional[List] = None
    userName: Optional[str] = None


class SemanticChunk(BaseModel):
    index_answer: int
    doc_name: str
    title: str
    text_answer: str
    # doc_number: str  # TODO Потом поменять название переменной на doc_id везде с чем это будет связанно
    other_info: List
    start_index_paragraph: int


class FilterChunks(BaseModel):
    id: str
    filename: str
    title: str
    chunks: List[SemanticChunk]


class BusinessProcess(BaseModel):
    production_activities_section: Optional[str]
    processes_name: Optional[str]
    level_process: Optional[str]


class Lead(BaseModel):
    person: Optional[str]
    leads: Optional[str]


class Subordinate(BaseModel):
    person_name: Optional[str]
    position: Optional[str]


class OrganizationalStructure(BaseModel):
    position: Optional[str] = None
    leads: Optional[List[Lead]] = None
    subordinates: Optional[Subordinate] = None


class RocksNN(BaseModel):
    division: Optional[str]
    company_name: Optional[str]


class RocksNNSearch(BaseModel):
    division: Optional[str]
    company_name: Optional[List]


class SegmentationSearch(BaseModel):
    segmentation_model: Optional[str]
    company_name: Optional[List]


class Group(BaseModel):
    group_name: Optional[str]
    position_in_group: Optional[str]
    block: Optional[str]


class GroupComposition(BaseModel):
    person_name: Optional[str]
    position_in_group: Optional[str]


class SearchGroupComposition(BaseModel):
    group_name: Optional[str]
    group_composition: Optional[List[GroupComposition]]


class PeopleChunks(BaseModel):
    business_processes: Optional[List[BusinessProcess]] = None
    organizatinal_structure: Optional[List[OrganizationalStructure]] = None
    business_curator: Optional[List[RocksNN]] = None
    groups: Optional[List[Group]] = None
    person_name: str


class SummaryChunks(BaseModel):
    doc_chunks: Optional[List[FilterChunks]] = None
    people_search: Optional[List[PeopleChunks]] = None
    groups_search: Optional[SearchGroupComposition] = None
    rocks_nn_search: Optional[RocksNNSearch] = None
    segmentation_search: Optional[SegmentationSearch] = None
    query_type: str = '[3]'


class ElasticConfiguration:
    def __init__(self, config_data):
        self.es_host = str(config_data['es_host'])
        self.es_port = int(config_data['es_port'])
        self.use_elastic = bool(config_data['use_elastic'])
        self.people_path = str(config_data['people_path'])


class FaissDataConfiguration:
    def __init__(self, config_data):
        self.model_embedding_path = str(config_data['model_embedding_path'])
        self.device = str(config_data['device'])
        self.path_to_metadata = str(config_data['path_to_metadata'])


class ChunksElasticSearchConfiguration:
    def __init__(self, config_data):
        self.use_chunks_search = bool(config_data['use_chunks_search'])
        self.index_name = str(config_data['index_name'])
        self.k_neighbors = int(config_data['k_neighbors'])


class PeopleSearchConfiguration:
    def __init__(self, config_data):
        self.use_people_search = bool(config_data['use_people_search'])
        self.index_name = str(config_data['index_name'])
        self.k_neighbors = int(config_data['k_neighbors'])


class VectorSearchConfiguration:
    def __init__(self, config_data):
        self.use_vector_search = bool(config_data['use_vector_search'])
        self.k_neighbors = int(config_data['k_neighbors'])


class GroupsSearchConfiguration:
    def __init__(self, config_data):
        self.use_groups_search = bool(config_data['use_groups_search'])
        self.index_name = str(config_data['index_name'])
        self.k_neighbors = int(config_data['k_neighbors'])


class RocksNNSearchConfiguration:
    def __init__(self, config_data):
        self.use_rocks_nn_search = bool(config_data['use_rocks_nn_search'])
        self.index_name = str(config_data['index_name'])
        self.k_neighbors = int(config_data['k_neighbors'])


class AbbreviationSearchConfiguration:
    def __init__(self, config_data):
        self.use_abbreviation_search = bool(config_data['use_abbreviation_search'])
        self.index_name = str(config_data['index_name'])
        self.k_neighbors = int(config_data['k_neighbors'])


class SegmentationSearchConfiguration:
    def __init__(self, config_data):
        self.use_segmentation_search = bool(config_data['use_segmentation_search'])
        self.index_name = str(config_data['index_name'])
        self.k_neighbors = int(config_data['k_neighbors'])


class SearchConfiguration:
    def __init__(self, config_data):
        self.vector_search = VectorSearchConfiguration(config_data['vector_search'])
        self.people_elastic_search = PeopleSearchConfiguration(
            config_data['people_elastic_search']
        )
        self.chunks_elastic_search = ChunksElasticSearchConfiguration(
            config_data['chunks_elastic_search']
        )
        self.groups_elastic_search = GroupsSearchConfiguration(
            config_data['groups_elastic_search']
        )
        self.rocks_nn_elastic_search = RocksNNSearchConfiguration(
            config_data['rocks_nn_elastic_search']
        )
        self.segmentation_elastic_search = SegmentationSearchConfiguration(
            config_data['segmentation_elastic_search']
        )
        self.stop_index_names = list(config_data['stop_index_names'])
        self.abbreviation_search = AbbreviationSearchConfiguration(
            config_data['abbreviation_search']
        )


class FilesConfiguration:
    def __init__(self, config_data):
        self.empty_start = bool(config_data['empty_start'])
        self.regulations_path = str(config_data['regulations_path'])
        self.default_regulations_path = str(config_data['default_regulations_path'])
        self.documents_path = str(config_data['documents_path'])


class RankingConfiguration:
    def __init__(self, config_data):
        self.use_ranging = bool(config_data['use_ranging'])
        self.alpha = float(config_data['alpha'])
        self.beta = float(config_data['beta'])
        self.k_neighbors = int(config_data['k_neighbors'])


class DataBaseConfiguration:
    def __init__(self, config_data):
        self.elastic = ElasticConfiguration(config_data['elastic'])
        self.faiss = FaissDataConfiguration(config_data['faiss'])
        self.search = SearchConfiguration(config_data['search'])
        self.files = FilesConfiguration(config_data['files'])
        self.ranker = RankingConfiguration(config_data['ranging'])


class LLMConfiguration:
    def __init__(self, config_data):
        self.base_url = str(config_data['base_url']) if config_data['base_url'] not in ("", "null", "None") else None
        self.api_key_env = (
            str(config_data['api_key_env'])
            if config_data['api_key_env'] not in ("", "null", "None")
            else None
        )
        self.model = str(config_data['model'])
        self.tokenizer = str(config_data['tokenizer_name'])
        self.temperature = float(config_data['temperature'])
        self.top_p = float(config_data['top_p'])
        self.min_p = float(config_data['min_p'])
        self.frequency_penalty = float(config_data['frequency_penalty'])
        self.presence_penalty = float(config_data['presence_penalty'])
        self.seed = int(config_data['seed'])


class CommonConfiguration:
    def __init__(self, config_data):
        self.log_file_path = str(config_data['log_file_path'])
        self.log_sql_path = str(config_data['log_sql_path'])


class Configuration:
    """Encapsulates all configuration parameters."""

    def __init__(self, config_file_path: Optional[str] = None):
        """Creates an instance of the class.

        There is 1 possibility to load configuration data:
            - from configuration file using a path;
        If attribute is not None, the configuration file is used.

        Args:
            config_file_path: A path to config file to load configuration data from.
        """
        if config_file_path is not None:
            self._load_from_config(config_file_path)
        else:
            raise ValueError('At least one of config_path must be not None.')

    def _load_data(self, data: Dict[str, Any]):
        """Loads configuration data from dictionary.

        Args:
            data: A configuration dictionary to load configuration data from.
        """
        self.common_config = CommonConfiguration(data['common'])
        self.db_config = DataBaseConfiguration(data['bd'])
        self.llm_config = LLMConfiguration(data['llm'])

    def _load_from_config(self, config_file_path: str):
        """Reads configuration file and form configuration dictionary.

        Args:
            config_file_path: A configuration dictionary to load configuration data from.
        """
        data = parse_config(config_file_path)
        self._load_data(data)