"""Application settings.

Every setting can be overridden with an environment variable prefixed
``BOR_`` (or a local gitignored ``.env`` file — see ``.env.example``).
"""
from __future__ import annotations

import os
from functools import lru_cache

from pydantic_settings import BaseSettings, SettingsConfigDict


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

    # --- App ---
    app_name: str = "Brain of Reese"
    app_version: str = "0.1.0"
    environment: str = "development"
    log_level: str = "INFO"
    static_dir: str = "frontend"

    # --- Database (PostgreSQL 17 + pgvector) ---
    database_url: str = "postgresql+psycopg://reese:reese@localhost:5432/brain_of_reese"

    # --- LLM (self-hosted, OpenAI-compatible "aipi" endpoint) ---
    llm_base_url: str = "https://aipi.reeseapps.com/v1"
    llm_api_key: str = ""
    llm_chat_model: str = "turbo"
    llm_embed_model: str = "embed"

    # --- RAG tuning ---
    embedding_dim: int = 768  # verified against aipi /v1 (embed model)
    top_k_chunks: int = 4
    top_n_docs: int = 2
    relevance_threshold: float = 0.30
    max_context_chars: int = 24_000
    chunk_target_chars: int = 2_000
    chunk_overlap_chars: int = 200
    embed_batch_size: int = 16

    # Suggested questions (onboarding + empty state).
    suggestions: list[str] = [
        "How is my Kubernetes cluster set up?",
        "What's my backup strategy?",
        "How do I deploy a new service?",
        "What's currently running in the homelab?",
    ]

    @property
    def effective_api_key(self) -> str:
        """API key for aipi: explicit setting, then $AIPI_KEY, then a placeholder."""
        return self.llm_api_key or os.environ.get("AIPI_KEY", "") or "not-needed"


@lru_cache
def get_settings() -> Settings:
    return Settings()