"""
Latent DAG 图节点增量缓存引擎 (ComfyUI Style)
Author: XiaoZhe (Commercial Contact: janejulius119@gmail.com / WeChat: julius119)
"""

import hashlib
import json
import logging
from typing import Dict, Any, Optional

logger = logging.getLogger("VerseFlow.GraphCache")

class LatentGraphCacheEngine:
    """DAG 中间 Latent 特征缓存器，支持增量重绘与算力节省"""
    def __init__(self):
        self._cache_store: Dict[str, Dict[str, Any]] = {}

    def compute_node_hash(self, node_id: str, inputs: Dict[str, Any], upstream_hashes: Dict[str, str]) -> str:
        hasher = hashlib.sha256()
        hasher.update(node_id.encode('utf-8'))
        inputs_str = json.dumps(inputs, sort_keys=True, default=str)
        hasher.update(inputs_str.encode('utf-8'))
        
        for up_id, up_hash in sorted(upstream_hashes.items()):
            hasher.update(f"{up_id}:{up_hash}".encode('utf-8'))
            
        return hasher.hexdigest()

    def get_cached_latent(self, node_hash: str) -> Optional[Dict[str, Any]]:
        if node_hash in self._cache_store:
            logger.info(f"⚡ [GraphCache Hit] 命中增量缓存 Hash: {node_hash[:12]}...")
            return self._cache_store[node_hash]
        return None

    def store_latent(self, node_hash: str, latent_data: Dict[str, Any]):
        self._cache_store[node_hash] = latent_data
        logger.info(f"💾 [GraphCache Saved] 保存 Latent 特征至缓存 Hash: {node_hash[:12]}...")