from typing import Optional, List, Union
from pydantic import BaseModel, ConfigDict, field_validator, Field
from config import settings

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):
    hasMultipleEscalations: bool = Field(description="Is there evidence of multiple escalation attempts?")
    customerSentiment: Optional[str] = Field(description="Overall customer sentiment (e.g., 'neutral', 'frustrated', 'calm').")
    
    def __init__(self, **data):
        super().__init__(**data)
        
        # Track model usage if Langfuse is enabled
        if settings.langfuse.enabled:
            try:
                settings.langfuse_client.trace(
                    name="LLM Model Usage",
                    input=data,
                    metadata={
                        "model": settings.llm.model if settings.llm.mode == 'openai' else settings.llm.ollama_model,
                        "analysis_flags": {
                            "hasMultipleEscalations": self.hasMultipleEscalations,
                            "customerSentiment": self.customerSentiment
                        }
                    }
                )
            except Exception as e:
                logger.error(f"Failed to track model usage: {e}")