"""
config.py
─────────
Central configuration for the AstroBot RAG application.
All tuneable parameters live here — change once, affects everywhere.
"""

import os
from dataclasses import dataclass, field


@dataclass
class AppConfig:
    # ── Groq LLM ──────────────────────────────────────────────────────────────
    groq_api_key: str         = field(default_factory=lambda: os.environ.get("GROQ_API_KEY", ""))
    groq_model: str           = "llama-3.1-8b-instant"
    groq_temperature: float   = 0.2
    groq_max_tokens: int      = 1024

    # ── Hugging Face Dataset ───────────────────────────────────────────────────
    hf_dataset: str           = field(default_factory=lambda: os.environ.get("HF_DATASET", ""))
    hf_token: str             = field(default_factory=lambda: os.environ.get("HF_TOKEN", ""))
    dataset_split: str        = "train"

    # Ordered list of candidate column names that hold the raw text
    text_column_candidates: list = field(default_factory=lambda: [
        "text", "content", "body", "page_content", "extracted_text"
    ])

    # ── Embeddings & Retrieval ─────────────────────────────────────────────────
    embed_model: str          = "sentence-transformers/all-MiniLM-L6-v2"
    chunk_size: int           = 512
    chunk_overlap: int        = 64
    top_k: int                = 5

    # ── App Meta ───────────────────────────────────────────────────────────────
    app_title: str            = "🔭 AstroBot — Astrology Learning Assistant"
    app_description: str      = (
        "Ask me anything about astrology concepts — planets, houses, aspects, "
        "signs, transits, chart reading, and more. "
        "**Note:** This bot explains concepts only; no personal predictions are made."
    )


# Singleton — import this everywhere
cfg = AppConfig()