from typing import Optional, List, Union
from enum import Enum
from loguru import logger
from pydantic import BaseModel, ConfigDict, field_validator, Field
from datetime import datetime
from config import settings

class LLMResponse(BaseModel):
    status: str
    message: str

class CustomerSentiment(str, Enum):
    NEUTRAL = "neutral"
    FRUSTRATED = "frustrated"
    CALM = "calm"

class IssueCategory(str, Enum):
    TECHNICAL_ISSUE = "technical_issue"
    DATA_REQUEST = "data_request"
    ACCESS_PROBLEM = "access_problem"
    GENERAL_QUESTION = "general_question"
    OTHER = "other"

# New: Add an Enum for technical areas based on Confluence doc
class Area(str, Enum):
    DIRECT_CHANNEL = "Direct Channel"
    STREAMING_CHANNEL = "Streaming Channel"
    JAVA_BATCH_CHANNEL = "Java Batch Channel"
    ETL_BATCH_CHANNEL = "ETL Batch Channel"
    DCR_SERVICE = "DCR Service"
    API_GATEWAY = "API Gateway"
    CALLBACK_SERVICE = "Callback Service"
    PUBLISHER = "Publisher"
    RECONCILIATION = "Reconciliation"
    SNOWFLAKE = "Snowflake"
    AUTHENTICATION = "Authentication"
    OTHER = "Other"

class JiraWebhookPayload(BaseModel):
    model_config = ConfigDict(alias_generator=lambda x: ''.join(word.capitalize() if i > 0 else word for i, word in enumerate(x.split('_'))), populate_by_name=True)
    
    issueKey: str
    summary: str
    description: Optional[str] = None
    comment: Optional[str] = None
    labels: Optional[Union[List[str], str]] = []
    
    @field_validator('labels', mode='before')
    @classmethod
    def convert_labels_to_list(cls, v):
        if isinstance(v, str):
            return [v]
        return v or []
    
    status: Optional[str] = None
    assignee: Optional[str] = None
    updated: Optional[str] = None

class AnalysisFlags(BaseModel):
    model_config = ConfigDict(alias_generator=lambda x: ''.join(word.capitalize() if i > 0 else word for i, word in enumerate(x.split('_'))), populate_by_name=True)
    
    issueCategory: IssueCategory = Field(..., description="The primary category of the Jira ticket.")
    area: Area = Field(..., description="The technical area of the MDM HUB related to the issue.")
    customerSentiment: Optional[CustomerSentiment] = Field(..., description="Overall customer sentiment (e.g., 'neutral', 'frustrated', 'calm').")
    isEscalated: bool = Field(..., description="Is there evidence of multiple escalation attempts?")
    oneSentenceSummary: str = Field(..., description="A single paragraph in concise English that summarizes the discussion.")


class JiraAnalysisResponse(BaseModel):
    model_config = ConfigDict(from_attributes=True)
    id: int
    issue_key: str
    status: str
    issue_summary: str
    request_payload: dict
    analysis_result: Optional[dict] = None
    created_at: datetime
    updated_at: datetime
    error_message: Optional[str] = None
    raw_response: Optional[dict] = None