Fixed wrong negative prompt acquisition.

scripts/iib/tool.py

@@ -488,6 +488,106 @@ def is_img_created_by_comfyui_with_webui_gen_info(img: Image):
     return is_img_created_by_comfyui(img) and img.info.get('parameters')
 
 
+
+def extract_comfyui_prompt_with_wildcard_support(data: Dict, KSampler_entry: Dict):
+    """
+    Enhanced prompt extraction for workflows using ImpactWildcardProcessor.
+
+    This function handles:
+    - populated_text over wildcard_text
+    - Recursive resolution of upstream prompt nodes
+    - Intermediate conditioning nodes such as FluxGuidance
+
+    Returns:
+        tuple of (positive_prompt, negative_prompt)
+    """
+
+    def get_node(node_id):
+        return data.get(str(node_id)) or data.get(node_id)
+
+    def normalize_text(value):
+        if not isinstance(value, str):
+            return None
+        return value.strip()
+
+    def extract_direct_text(node):
+        if not isinstance(node, dict):
+            return None, False
+
+        class_type = node.get("class_type", "")
+        inputs = node.get("inputs", {}) or {}
+
+        if class_type == "ImpactWildcardProcessor":
+            populated = normalize_text(inputs.get("populated_text"))
+            return (populated or ""), True
+
+        if "CLIPTextEncode" in class_type:
+            for key in ("text", "t5xxl"):
+                if key in inputs:
+                    value = inputs.get(key)
+                    if isinstance(value, str):
+                        return value.strip(), True
+                    if isinstance(value, list) and len(value) >= 1:
+                        return None, False
+                    return "", True
+
+        for key in ("text", "t5xxl", "prompt", "string", "value"):
+            if key in inputs and isinstance(inputs.get(key), str):
+                return inputs.get(key).strip(), True
+
+        return None, False
+
+    def resolve_text_from_ref(ref, visited=None):
+        if visited is None:
+            visited = set()
+
+        node_id = ref[0] if isinstance(ref, list) and len(ref) >= 1 else ref
+        node_key = str(node_id)
+        if not node_key or node_key in visited:
+            return ""
+        visited.add(node_key)
+
+        node = get_node(node_id)
+        if not isinstance(node, dict):
+            return ""
+
+        direct_text, is_terminal = extract_direct_text(node)
+        if direct_text is not None:
+            return direct_text
+        if is_terminal:
+            return ""
+
+        inputs = node.get("inputs", {}) or {}
+        class_type = node.get("class_type", "")
+
+        if class_type == "FluxGuidance":
+            conditioning = inputs.get("conditioning")
+            if isinstance(conditioning, list) and len(conditioning) >= 1:
+                return resolve_text_from_ref(conditioning, visited)
+            return ""
+
+        for key in ("text", "t5xxl", "conditioning", "positive", "negative", "prompt", "string", "value"):
+            value = inputs.get(key)
+            if isinstance(value, list) and len(value) >= 1:
+                resolved = resolve_text_from_ref(value, visited)
+                if resolved or resolved == "":
+                    return resolved
+
+        return ""
+
+    try:
+        positive_ref = KSampler_entry.get("positive")
+        negative_ref = KSampler_entry.get("negative")
+
+        positive_prompt = resolve_text_from_ref(positive_ref) if positive_ref else ""
+        negative_prompt = resolve_text_from_ref(negative_ref) if negative_ref else ""
+
+        return positive_prompt or "", negative_prompt or ""
+    except Exception as e:
+        print(e)
+        return "", ""
+
+
 def get_comfyui_exif_data(img: Image):
     prompt = None
     if img.format == "PNG":
@@ -498,13 +598,11 @@ def get_comfyui_exif_data(img: Image):
             split = [x.decode("utf-8", errors="ignore") for x in exif.split(b"\x00")]
             prompt_str = find(split, lambda x: x.lower().startswith("prompt:"))
             if prompt_str:
-                prompt = prompt_str.split(":", 1)[1]
+                prompt = prompt_str.split(":", 1)[1] if prompt_str else None
-
     if not prompt:
         return {}
 
     data: Dict[str, Any] = json.loads(prompt)
-
     meta_key = '3'
     for i in data.keys():
         try:
@@ -530,157 +628,42 @@ def get_comfyui_exif_data(img: Image):
         meta["Model"] = None
     meta["Source Identifier"] = "ComfyUI"
 
-    text_key_priority = [
+    def get_text_from_clip(idx: str):
-        "populated_text",   # ImpactWildcardProcessor の最終展開結果
-        "text",
-        "prompt",
-        "positive",
-        "negative",
-        "string",
-        "value",
-        "t5xxl",
-    ]
-    text_key_blacklist = {
-        "wildcard_text",            # 展開前テンプレート
-        "Select to add Wildcard",   # UI 用
-        "select_to_add_wildcard",
-        "template",
-        "pattern",
-    }
-
-    wildcard_patterns = [
-        re.compile(r"__[^_\n]+__"),
-        re.compile(r"\{[^{}\n]*\|[^{}\n]*\}"),
-    ]
-
-    def normalize_text(value):
-        if not isinstance(value, str):
-            return None
-        value = value.strip()
-        return value if value else None
-
-    def looks_unexpanded_wildcard(text: str) -> bool:
-        return any(p.search(text) for p in wildcard_patterns)
-
-    def get_node(node_id):
-        key = str(node_id)
-        return data.get(key) or data.get(node_id)
-
-    def get_best_text_from_inputs(inputs: dict):
-        if not isinstance(inputs, dict):
-            return ""
-
-        clean_candidates = []
-        wildcard_candidates = []
-
-        def add_candidate(value):
-            text = normalize_text(value)
-            if not text:
-                return
-            if looks_unexpanded_wildcard(text):
-                wildcard_candidates.append(text)
-            else:
-                clean_candidates.append(text)
-
-        for key in text_key_priority:
-            if key in text_key_blacklist:
-                continue
-            add_candidate(inputs.get(key))
-
-        if clean_candidates:
-            return clean_candidates[0]
-        if wildcard_candidates:
-            return wildcard_candidates[0]
-
-        for key, value in inputs.items():
-            if key in text_key_blacklist:
-                continue
-            add_candidate(value)
-
-        if clean_candidates:
-            return clean_candidates[0]
-        if wildcard_candidates:
-            return wildcard_candidates[0]
-        return ""
-
-    def extract_text_from_node(node: dict):
-        if not isinstance(node, dict):
-            return ""
-
-        class_type = node.get("class_type", "")
-        inputs = node.get("inputs", {}) or {}
-
-        # 明示的な特例: ImpactWildcardProcessor は populated_text を最優先
-        if class_type == "ImpactWildcardProcessor":
-            populated = normalize_text(inputs.get("populated_text"))
-            if populated:
-                return populated
-            # wildcard_text は意図的に返さない
-            return ""
-
-        return get_best_text_from_inputs(inputs)
-
-    def resolve_text_from_ref(ref, visited=None):
-        if visited is None:
-            visited = set()
-
-        node_id = ref[0] if isinstance(ref, list) and len(ref) >= 1 else ref
-        node_key = str(node_id)
-        if node_key in visited:
-            return ""
-        visited.add(node_key)
-
-        node = get_node(node_id)
-        if not isinstance(node, dict):
-            return ""
-
-        direct_text = extract_text_from_node(node)
-        if direct_text:
-            return direct_text
-
-        inputs = node.get("inputs", {}) or {}
-
-        # FluxGuidance の場合は conditioning を優先して辿る
-        if node.get("class_type") == "FluxGuidance":
-            conditioning = inputs.get("conditioning")
-            if isinstance(conditioning, list) and len(conditioning) >= 1:
-                resolved = resolve_text_from_ref(conditioning, visited)
-                if resolved:
-                    return resolved
-
-        # よく使う接続キーを優先
-        preferred_link_keys = [
-            "text",
-            "conditioning",
-            "positive",
-            "negative",
-            "prompt",
-            "string",
-            "value",
-        ]
-        for key in preferred_link_keys:
-            value = inputs.get(key)
-            if isinstance(value, list) and len(value) >= 1:
-                resolved = resolve_text_from_ref(value, visited)
-                if resolved:
-                    return resolved
-
-        # fallback: 全 input を走査
-        for value in inputs.values():
-            if isinstance(value, list) and len(value) >= 1:
-                resolved = resolve_text_from_ref(value, visited)
-                if resolved:
-                    return resolved
-
-        return ""
-
-    def get_text_from_clip(idx):
         try:
-            return resolve_text_from_ref(idx)
+            inputs = data[idx]["inputs"]
+            if "text" in inputs:
+                text = inputs["text"]
+            elif "t5xxl" in inputs:
+                text = inputs["t5xxl"]
+            else:
+                return ""
+            if isinstance(text, list):  # type:CLIPTextEncode (NSP) mode:Wildcards
+                text = data[text[0]]["inputs"]["text"]
+            return text.strip()
         except Exception as e:
             print(e)
             return ""
 
+    has_impact_wildcard = any(
+        node_data.get("class_type") == "ImpactWildcardProcessor"
+        for node_data in data.values()
+        if isinstance(node_data, dict)
+    )
+
+    # Detection Point 1: Check if workflow contains ImpactWildcardProcessor
+    # If yes, immediately use the enhanced extraction and return
+    if has_impact_wildcard:
+        pos_prompt, neg_prompt = extract_comfyui_prompt_with_wildcard_support(
+            data, KSampler_entry
+        )
+        pos_prompt_arr = unique_by(parse_prompt(pos_prompt)["pos_prompt"])
+        return {
+            "meta": meta,
+            "pos_prompt": pos_prompt_arr,
+            "pos_prompt_raw": pos_prompt,
+            "neg_prompt_raw": neg_prompt
+        }
+
     extract_all_prompts = os.getenv("IIB_COMFYUI_EXTRACT_ALL_PROMPTS", "false").lower() == "true"
 
     if extract_all_prompts:
@@ -690,25 +673,45 @@ def get_comfyui_exif_data(img: Image):
         for node_id, node_data in data.items():
             try:
                 class_type = node_data.get("class_type", "")
-                if "CLIPTextEncode" in class_type or class_type == "ImpactWildcardProcessor":
+                inputs = node_data.get("inputs", {})
-                    text = resolve_text_from_ref(node_id)
+
+                if "CLIPTextEncode" in class_type:
+                    text = inputs.get("text", "")
+                    if isinstance(text, list):
+                        text = data[text[0]]["inputs"].get("text", "")
                     if text:
                         all_prompts.append(text.strip())
             except Exception as e:
                 print(e)
                 pass
 
-        all_prompts_str = "\nBREAK\n".join(unique_by(all_prompts)) if all_prompts else ""
+        all_prompts_str = "\nBREAK\n".join(all_prompts) if all_prompts else ""
         pos_prompt = all_prompts_str
         neg_prompt = ""
     else:
-        positive_ref = KSampler_entry.get("positive")
+        in_node = data[str(KSampler_entry["positive"][0])]
-        negative_ref = KSampler_entry.get("negative")
+        if in_node["class_type"] != "FluxGuidance":
+            pos_prompt = get_text_from_clip(KSampler_entry["positive"][0])
+        else:
+            pos_prompt = get_text_from_clip(in_node["inputs"]["conditioning"][0])
 
-        pos_prompt = get_text_from_clip(positive_ref) if positive_ref else ""
+        neg_prompt = get_text_from_clip(KSampler_entry["negative"][0])
-        neg_prompt = get_text_from_clip(negative_ref) if negative_ref else ""
 
     pos_prompt_arr = unique_by(parse_prompt(pos_prompt)["pos_prompt"])
+
+    # Detection Point 2: Fallback if no prompts were extracted
+    # If standard extraction failed, try the enhanced method
+    if has_impact_wildcard and (not pos_prompt_arr or not pos_prompt.strip()):
+        pos_prompt_fallback, neg_prompt_fallback = extract_comfyui_prompt_with_wildcard_support(
+            data, KSampler_entry
+        )
+        if pos_prompt_fallback:
+            pos_prompt = pos_prompt_fallback
+            pos_prompt_arr = unique_by(parse_prompt(pos_prompt_fallback)["pos_prompt"])
+
+        if neg_prompt_fallback:
+            neg_prompt = neg_prompt_fallback
+
     return {
         "meta": meta,
         "pos_prompt": pos_prompt_arr,