"""
Global configuration for Core Code API
"""
from pydantic_settings import BaseSettings
from functools import lru_cache


class Settings(BaseSettings):
    """Global application settings"""

    # Application
    app_name: str = "Core Code API"
    app_version: str = "1.0.0"
    debug: bool = False

    # Server
    host: str = "0.0.0.0"
    port: int = 8083

    # CORS
    cors_origins: list[str] = ["*"]
    cors_credentials: bool = True
    cors_methods: list[str] = ["*"]
    cors_headers: list[str] = ["*"]

    # Logging
    log_level: str = "INFO"

    # Ollama Configuration (for AI orchestration)
    ollama_base_url: str = "http://ollama:11434"
    ollama_timeout: int = 300  # 5 minutes

    # Model Configuration
    default_model: str = "gemma:7b"
    lightweight_models: str = "gemma:2b,gemma:7b"
    heavy_models: str = "mistral:7b,gemma2:9b,mixtral:8x7b"
    code_models: str = "codestral:latest,codegemma:latest"

    # Model Aliases (OpenAI → Local)
    alias_gpt35: str = "gemma:7b"
    alias_gpt4: str = "mistral:7b"
    alias_gpt4_turbo: str = "mixtral:8x7b"
    alias_gpt4_code: str = "codestral:latest"

    # Memory Configuration
    memory_tier1_max_turns: int = 10
    memory_consolidation_threshold: int = 10

    # Qdrant Configuration
    qdrant_host: str = "qdrant"
    qdrant_port: int = 6333
    qdrant_collection_conversations: str = "core_api_conversations"
    qdrant_collection_documents: str = "core_api_documents"
    qdrant_collection_user_facts: str = "core_api_user_facts"

    # Embeddings
    embedding_model: str = "sentence-transformers/all-MiniLM-L6-v2"
    embedding_dimension: int = 384
    embedding_batch_size: int = 32

    # Infrastructure Management
    portainer_url: str = "http://localhost:8001"
    portainer_api_key: str = ""

    npm_url: str = "http://localhost:81"
    npm_email: str = ""
    npm_password: str = ""

    kuma_url: str = "http://localhost:3001"
    kuma_username: str = ""
    kuma_password: str = ""

    @property
    def model_aliases(self) -> dict:
        """Computed property for model aliases"""
        return {
            "gpt-3.5-turbo": self.alias_gpt35,
            "gpt-4": self.alias_gpt4,
            "gpt-4-turbo": self.alias_gpt4_turbo,
            "gpt-4-code": self.alias_gpt4_code,
        }

    def get_lightweight_models(self) -> list[str]:
        """Parse comma-separated lightweight models"""
        return [m.strip().strip('"').strip("'") for m in self.lightweight_models.split(",") if m.strip()]

    def get_heavy_models(self) -> list[str]:
        """Parse comma-separated heavy models"""
        return [m.strip().strip('"').strip("'") for m in self.heavy_models.split(",") if m.strip()]

    def get_code_models(self) -> list[str]:
        """Parse comma-separated code models"""
        return [m.strip().strip('"').strip("'") for m in self.code_models.split(",") if m.strip()]

    class Config:
        env_file = ".env"
        case_sensitive = False


@lru_cache()
def get_settings() -> Settings:
    """Cached settings instance"""
    return Settings()