from __future__ import annotations

import os
from dataclasses import dataclass


@dataclass(slots=True)
class Settings:
    app_name: str = "Gorich RAG API"
    site_url: str = os.getenv("GORICH_SITE_URL", "https://gorych34.ru/")
    chroma_path: str = os.getenv("CHROMA_PATH", "/data/chroma")
    huggingface_cache_dir: str = os.getenv("HUGGINGFACE_CACHE_DIR", "/data/huggingface")
    knowledge_collection: str = os.getenv("KNOWLEDGE_COLLECTION", "gorich_knowledge")
    menu_collection: str = os.getenv("MENU_COLLECTION", "gorich_menu")
    menu_snapshot_path: str = os.getenv("MENU_SNAPSHOT_PATH", "/data/menu/gorich_menu.json")
    openrouter_api_key: str = os.getenv("OPENROUTER_API_KEY", "")
    openrouter_model: str = os.getenv("OPENROUTER_MODEL", "mistralai/mistral-medium-3-5")
    openrouter_base_url: str = os.getenv("OPENROUTER_BASE_URL", "https://openrouter.ai/api/v1")
    public_app_url: str = os.getenv("PUBLIC_APP_URL", "http://localhost:8000")
    public_app_name: str = os.getenv("PUBLIC_APP_NAME", "Gorich Bot RAG")
    embedding_model: str = os.getenv(
        "EMBEDDING_MODEL",
        "sergeyzh/rubert-mini-frida",
    )
    embedding_query_prefix: str = os.getenv("EMBEDDING_QUERY_PREFIX", "search_query: ")
    embedding_document_prefix: str = os.getenv(
        "EMBEDDING_DOCUMENT_PREFIX",
        "search_document: ",
    )
    embedding_max_length: int = int(os.getenv("EMBEDDING_MAX_LENGTH", "512"))
    embedding_batch_size: int = int(os.getenv("EMBEDDING_BATCH_SIZE", "32"))
    request_timeout: float = float(os.getenv("REQUEST_TIMEOUT_SECONDS", "60"))
    top_k: int = int(os.getenv("RAG_TOP_K", "5"))
    index_on_startup: bool = os.getenv("INDEX_ON_STARTUP", "true").lower() == "true"


settings = Settings()