import os
from dataclasses import dataclass

@dataclass
class AppConfig:
    # --- Hugging Face model repos (set via environment variables on Spaces) ---
    HF_GAT_BASELINE_REPO: str = os.getenv("HF_GAT_BASELINE_REPO", "org/name_gat_baseline")
    HF_GATV2_REPO: str = os.getenv("HF_GATV2_REPO", "org/name_gatv2")

    # Expected input dim of Elliptic-trained models (given by user)
    IN_CHANNELS: int = int(os.getenv("IN_CHANNELS", "165"))
    HIDDEN_CHANNELS: int = int(os.getenv("HIDDEN_CHANNELS", "128"))
    HEADS: int = int(os.getenv("HEADS", "8"))
    NUM_BLOCKS: int = int(os.getenv("NUM_BLOCKS", "2"))
    DROPOUT: float = float(os.getenv("DROPOUT", "0.5"))

    # Data providers
    DATA_PROVIDER: str = os.getenv("DATA_PROVIDER", "mempool")  # mempool | blockstream | blockchair
    HTTP_TIMEOUT: int = int(os.getenv("HTTP_TIMEOUT", "10"))
    HTTP_RETRIES: int = int(os.getenv("HTTP_RETRIES", "2"))

    # Graph limits (safeguard)
    MAX_NODES: int = int(os.getenv("MAX_NODES", "5000"))
    MAX_EDGES: int = int(os.getenv("MAX_EDGES", "15000"))

    # Feature handling
    USE_FEATURE_ADAPTER: bool = os.getenv("USE_FEATURE_ADAPTER", "true").lower() == "true"
    MAKE_UNDIRECTED: bool = os.getenv("MAKE_UNDIRECTED", "false").lower() == "true"

    # Threshold fallback
    DEFAULT_THRESHOLD: float = float(os.getenv("DEFAULT_THRESHOLD", "0.5"))

    # Rate limit
    MAX_CALLS_PER_MIN: int = int(os.getenv("MAX_CALLS_PER_MIN", "20"))
    WINDOW_SECONDS: int = int(os.getenv("WINDOW_SECONDS", "60"))

    # Queue config
    QUEUE_CONCURRENCY: int = int(os.getenv("QUEUE_CONCURRENCY", "2"))

    # Blockchair API key (optional)
    BLOCKCHAIR_API_KEY: str = os.getenv("BLOCKCHAIR_API_KEY", "").strip()