Delete arch_logic_v16.py

arch_logic_v16.py

@@ -1,87 +0,0 @@
-import os
-import comfy.sd
-import comfy.utils
-import folder_paths
-import json
-import urllib.request
-import urllib.parse
-
-_TRIPLE_LORA_CACHE = {}
-CACHE_FILE = os.path.join(os.path.dirname(__file__), "dolphin_lora_trigger_cache.json")
-
-def get_trigger_words(lora_name):
-    if lora_name == "None": return []
-    cache = {}
-    if os.path.exists(CACHE_FILE):
-        try:
-            with open(CACHE_FILE, "r") as f: cache = json.load(f)
-        except: pass
-    if lora_name in cache: return cache[lora_name]
-
-    try:
-        # 💡 요청하신 civitaired.com 도메인 API로 변경
-        # API 구조가 civitai.com과 동일하다는 가정하에 쿼리 매개변수 적용
-        query = urllib.parse.quote(lora_name.replace(".safetensors", ""))
-        url = f"https://civitaired.com/api/v1/model-versions/by-file?query={query}"
-        
-        req = urllib.request.Request(url, headers={'User-Agent': 'Mozilla/5.0'})
-        with urllib.request.urlopen(req, timeout=5) as res:
-            data = json.load(res)
-            # trainedWords 키는 동일하게 유지
-            triggers = data.get("trainedWords", [])
-            cache[lora_name] = triggers
-            with open(CACHE_FILE, "w") as f: json.dump(cache, f)
-            return triggers
-    except Exception as e:
-        print(f"⚠️ [Dolphin] civitaired.com 트리거 워드 조회 실패: {e}")
-        return []
-
-class DolphinTripleLoraMatrix:
-    @classmethod
-    def INPUT_TYPES(s):
-        loras = ["None"] + folder_paths.get_filename_list("loras")
-        inputs = {
-            "model_base": ("MODEL",), "clip_base": ("CLIP",),
-            "model_high": ("MODEL",), "clip_high": ("CLIP",),
-            "model_low": ("MODEL",),  "clip_low": ("CLIP",),
-        }
-        for i in range(1, 7):
-            inputs[f"lora_{i}"] = (loras, {"default": "None"})
-            inputs[f"weights_{i}"] = ("STRING", {"default": "0.0, 0.0, 0.0"})
-        return {"required": inputs}
-
-    RETURN_TYPES = ("MODEL", "CLIP", "MODEL", "CLIP", "MODEL", "CLIP", "STRING")
-    RETURN_NAMES = ("M_BASE", "C_BASE", "M_HIGH", "C_HIGH", "M_LOW", "C_LOW", "trigger_words")
-    FUNCTION = "apply_matrix"
-    CATEGORY = "Dolphin"
-
-    def apply_matrix(self, model_base, clip_base, model_high, clip_high, model_low, clip_low, **kwargs):
-        m_b, c_b = model_base, clip_base
-        m_h, c_h = model_high, clip_high
-        m_l, c_l = model_low, clip_low
-        all_triggers = []
-
-        for i in range(1, 7):
-            lora_name = kwargs.get(f"lora_{i}")
-            w_str = kwargs.get(f"weights_{i}")
-            
-            if lora_name == "None": continue
-            
-            # 트리거 워드 수집 (civitaired.com 연동)
-            all_triggers.extend(get_trigger_words(lora_name))
-            
-            try:
-                parts = [float(x.strip()) for x in w_str.split(',')]
-                wb, wh, wl = parts[0], parts[1], parts[2]
-            except: continue
-
-            if lora_name not in _TRIPLE_LORA_CACHE:
-                path = folder_paths.get_full_path("loras", lora_name)
-                _TRIPLE_LORA_CACHE[lora_name] = comfy.utils.load_torch_file(path)
-            data = _TRIPLE_LORA_CACHE[lora_name]
-
-            if wb != 0: m_b, c_b = comfy.sd.load_lora_for_models(m_b, c_b, data, wb, wb)
-            if wh != 0: m_h, c_h = comfy.sd.load_lora_for_models(m_h, c_h, data, wh, wh)
-            if wl != 0: m_l, c_l = comfy.sd.load_lora_for_models(m_l, c_l, data, wl, wl)
-        
-        return (m_b, c_b, m_h, c_h, m_l, c_l, ", ".join(list(set(all_triggers))))