app/config.py

import os
from typing import Dict, Any
from pydantic import BaseSettings

class Settings(BaseSettings):
    """Application settings with validation"""
    
    # API Settings
    API_V1_PREFIX: str = "/api/v1"
    PROJECT_NAME: str = "Emotion Detection API"
    VERSION: str = "1.0.0"
    
    # Security - Critical: These must be set in environment
    HF_TOKEN: str
    API_SECRET_KEY: str
    ALGORITHM: str = "HS256"
    ACCESS_TOKEN_EXPIRE_MINUTES: int = 30
    
    # Model Configuration
    ENABLED_MODELS: Dict[str, Dict[str, Any]] = {
        "emotion2vec_plus": {
            "url": "https://api-inference.huggingface.co/models/emotion2vec/emotion2vec_plus_base",
            "weight": 0.50,
            "timeout": 30,
            "enabled": True
        },
        "meralion_ser": {
            "url": "https://api-inference.huggingface.co/models/MERaLiON/MERaLiON-SER-v1",
            "weight": 0.25,
            "timeout": 30,
            "enabled": True
        },
        "wav2vec2_english": {
            "url": "https://api-inference.huggingface.co/models/ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition",
            "weight": 0.15,
            "timeout": 25,
            "enabled": True
        },
        "hubert_er": {
            "url": "https://api-inference.huggingface.co/models/superb/hubert-large-superb-er",
            "weight": 0.07,
            "timeout": 25,
            "enabled": True
        },
        "gigam_emo": {
            "url": "https://api-inference.huggingface.co/models/salute-developers/GigaAM-emo",
            "weight": 0.03,
            "timeout": 20,
            "enabled": True
        }
    }
    
    # Audio Processing
    MAX_FILE_SIZE_MB: int = 10
    SUPPORTED_FORMATS: list = ["wav", "mp3", "m4a", "ogg", "flac", "aac"]
    TARGET_SAMPLE_RATE: int = 16000
    
    # Rate Limiting
    RATE_LIMIT_REQUESTS: int = 60
    RATE_LIMIT_PERIOD: int = 60  # seconds
    
    class Config:
        env_file = ".env"
        case_sensitive = True

settings = Settings()