"""Configuration settings for the API"""

import os
from pathlib import Path
from dotenv import load_dotenv
import logging

# Configure logging
logger = logging.getLogger(__name__)

# Load environment variables from .env file
load_dotenv()

# Get project root directory
API_DIR = Path(__file__).parent
PROJECT_ROOT = API_DIR.parent

# Hugging Face configuration
HUGGINGFACE_API_KEY = os.getenv("HUGGINGFACE_API_KEY", "")

HUGGINGFACE_STANCE_MODEL_ID = os.getenv("HUGGINGFACE_STANCE_MODEL_ID")
HUGGINGFACE_LABEL_MODEL_ID = os.getenv("HUGGINGFACE_LABEL_MODEL_ID")
HUGGINGFACE_STT_MODEL_ID = os.getenv("HUGGINGFACE_STT_MODEL_ID")

# Use Hugging Face model ID instead of local path
STANCE_MODEL_ID = HUGGINGFACE_STANCE_MODEL_ID
LABEL_MODEL_ID = HUGGINGFACE_LABEL_MODEL_ID

# API configuration
API_TITLE = "NLP Project API"
API_DESCRIPTION = "API for various NLP models including stance detection and more"
API_VERSION = "1.0.0"

# Server configuration
HOST = os.getenv("HOST", "0.0.0.0")  # Use 0.0.0.0 for Docker/Spaces
PORT = int(os.getenv("PORT", "7860"))  # Default 7860 for Hugging Face Spaces
RELOAD = os.getenv("RELOAD", "False").lower() == "true"  # Set to False in production

# CORS configuration
CORS_ORIGINS = ["*"]  # In production, specify exact origins
CORS_CREDENTIALS = True
CORS_METHODS = ["*"]
CORS_HEADERS = ["*"]

# Free model configurations
STT_MODEL_ID = "openai/whisper-small"  # Free Whisper model for STT
CHATBOT_MODEL_ID = "microsoft/DialoGPT-medium"  # Free chatbot model
TTS_USE_GTTS = True  # Use gTTS (Google Text-to-Speech) free tier

# Audio settings
ALLOWED_AUDIO_TYPES = {
    "audio/wav",
    "audio/x-wav",
    "audio/mpeg",
    "audio/mp3",
    "audio/mp4",
    "audio/m4a"
}

MAX_TEXT_LENGTH = 500
MIN_TEXT_LENGTH = 1
MAX_AUDIO_SIZE = 10 * 1024 * 1024  # 10MB

# Validate configuration
def validate_config():
    """Validate that we can use free models"""
    logger.info("✓ Using free models for STT, TTS, and Chatbot")
    return True

validate_config()