"""
Configuration for Audience Segmentation System
"""

import os
from pydantic_settings import BaseSettings


class Settings(BaseSettings):
    """Application settings"""
    
    # MongoDB Configuration
    MONGODB_URI: str = os.getenv("MONGODB_URI", "mongodb://localhost:27017")
    DB_NAME: str = os.getenv("DB_NAME", "audience_segmentation")
    
    # Hugging Face Token (optional, not required for our models)
    HF_TOKEN: str = os.getenv("HF_TOKEN", "")
    
    # Collection Names
    COLLECTION_USERS: str = "User"
    COLLECTION_PAYMENTS: str = "Payment"
    COLLECTION_EVENT_VERSIONS: str = "EventVersion"
    COLLECTION_USER_FOLLOWS: str = "UserFollow"
    COLLECTION_USER_COMMENT_POST: str = "UserCommentPost"
    COLLECTION_POST_SOCIAL_MEDIA: str = "PostSocialMedia"
    
    # AI Result Collections
    COLLECTION_AUDIENCE_SEGMENTS: str = "AudienceSegment"
    COLLECTION_USER_SEGMENT_ASSIGNMENTS: str = "UserSegmentAssignment"
    COLLECTION_SENTIMENT_RESULTS: str = "SentimentAnalysisResult"
    COLLECTION_EVENT_INSIGHTS: str = "EventInsightReport"
    
    # AI Model Configuration
    SENTIMENT_MODEL: str = "wonrax/phobert-base-vietnamese-sentiment"
    LLM_MODEL: str = "Vistral-7B-Chat"
    LLM_LOCAL_PATH: str = os.getenv("LLM_LOCAL_PATH", "./models/vistral-7b-chat")
    
    # Clustering Configuration
    N_CLUSTERS: int = 5  # Number of audience segments
    RANDOM_STATE: int = 42
    
    # Batch Processing
    BATCH_SIZE: int = 32
    
    class Config:
        env_file = ".env"
        case_sensitive = True


settings = Settings()