from functools import lru_cache
import os
from typing import Optional

from pydantic import Field
from pydantic_settings import BaseSettings, SettingsConfigDict

from app.model_catalog import resolve_model_profile


class Settings(BaseSettings):
    model_config = SettingsConfigDict(env_file=".env", env_file_encoding="utf-8")

    config_file: str = Field(default="config.json", alias="MODEL_CONFIG_FILE")
    model_key: Optional[str] = Field(default=None, alias="MODEL_KEY")
    selected_model: Optional[str] = None
    model_name: str = Field(default="", alias="MODEL_NAME")
    served_model_name: Optional[str] = None
    host: str = Field(default="0.0.0.0", alias="HOST")
    port: int = Field(default=8000, alias="PORT")
    max_model_len: int = Field(default=8192, alias="MAX_MODEL_LEN")
    gpu_memory_utilization: float = Field(default=0.92, alias="GPU_MEMORY_UTILIZATION")
    tensor_parallel_size: int = Field(default=2, alias="TENSOR_PARALLEL_SIZE")
    max_num_seqs: int = Field(default=64, alias="MAX_NUM_SEQS")
    max_tokens: int = Field(default=4096, alias="MAX_TOKENS")
    dtype: str = Field(default="bfloat16", alias="DTYPE")
    enforce_eager: bool = Field(default=False, alias="ENFORCE_EAGER")
    trust_remote_code: bool = Field(default=False, alias="TRUST_REMOTE_CODE")
    tool_call_parser: Optional[str] = Field(default=None, alias="TOOL_CALL_PARSER")
    enable_auto_tool_choice: bool = Field(default=False, alias="ENABLE_AUTO_TOOL_CHOICE")
    revision: Optional[str] = Field(default=None, alias="REVISION")
    api_key: Optional[str] = Field(default=None, alias="API_KEY")


@lru_cache(maxsize=1)
def get_settings() -> Settings:
    settings = Settings()
    _, updates, env_vars = resolve_model_profile(
        catalog_path=settings.config_file,
        requested_model=settings.model_key,
        requested_tp=settings.tensor_parallel_size,
    )
    for key, value in env_vars.items():
        os.environ[key] = value
    return settings.model_copy(update=updates)