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Author: if-ai

IFDisplayOmniNode.py

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+import json
+
+class IFDisplayOmni:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {},
+            "optional": {"omni_input": ("OMNI", {})},
+            "hidden": {"unique_id": "UNIQUE_ID", "extra_pnginfo": "EXTRA_PNGINFO"},
+        }
+
+    RETURN_TYPES = ("OMOST_CANVAS_CONDITIONING", "STRING")
+    RETURN_NAMES = ("canvas_conditioning", "text_output")
+    INPUT_IS_LIST = True
+    OUTPUT_NODE = True
+    FUNCTION = "display_omni"
+    CATEGORY = "ImpactFrames💥🎞️"
+
+    def display_omni(self, unique_id=None, extra_pnginfo=None, **kwargs):
+        values = []
+        canvas_conditioning = None
+        text_output = ""
+
+        if "omni_input" in kwargs:
+            for val in kwargs['omni_input']:
+                try:
+                    if isinstance(val, dict) and "conditionings" in val:
+                        # Handle batched canvas conditionings
+                        canvas_conditioning = val["conditionings"]  
+                        # The responses will come from IF_DisplayText
+                        text_output = val.get("error", "")
+                        values.append(text_output)
+                        
+                    elif isinstance(val, list) and all(isinstance(item, dict) for item in val):
+                        # Direct canvas conditioning list
+                        canvas_conditioning = val
+                        values.append(str(val))
+                        
+                    elif isinstance(val, str):
+                        values.append(val)
+                        text_output = val
+                        
+                    else:
+                        json_val = json.dumps(val)
+                        values.append(str(json_val))
+                        text_output = str(json_val)
+                        
+                except Exception as e:
+                    print(f"Error processing omni input: {str(e)}")
+                    values.append(str(val))
+                    text_output = str(val)
+
+        # Update workflow info if available
+        if unique_id is not None and extra_pnginfo is not None:
+            if isinstance(extra_pnginfo, list) and len(extra_pnginfo) > 0:
+                extra_pnginfo = extra_pnginfo[0]
+            
+            if isinstance(extra_pnginfo, dict) and "workflow" in extra_pnginfo:
+                workflow = extra_pnginfo["workflow"]
+                node = next((x for x in workflow["nodes"] if str(x["id"]) == unique_id), None)
+                if node:
+                    node["widgets_values"] = [values]
+
+        return {
+            "ui": {"text": values},
+            "result": (canvas_conditioning, text_output)
+        }

IFDisplayTextNode.py

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+import sys
+import logging
+from typing import Optional
+
+# Initialize logger
+logger = logging.getLogger(__name__)
+
+class IFDisplayText:
+    def __init__(self):
+        self.type = "output"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {        
+                "text": ("STRING", {"forceInput": True}),
+                "select": ("INT", {
+                    "default": 0, 
+                    "min": 0, 
+                    "max": sys.maxsize,  # No practical upper limit
+                    "step": 1,
+                    "tooltip": "Select which line to output (cycles through available lines)"
+                }),     
+            },
+            "hidden": {},
+        }
+
+    RETURN_TYPES = ("STRING", "STRING", "INT", "STRING")
+    RETURN_NAMES = ("text", "text_list", "count", "selected")
+    OUTPUT_IS_LIST = (False, True, False, False)
+    FUNCTION = "display_text"
+    OUTPUT_NODE = True
+    CATEGORY = "ImpactFrames💥🎞️"
+    
+    def display_text(self, text: Optional[str], select):
+        if text is None:
+            logger.error("Received None for text input in display_text.")
+            return ""  # Or handle appropriately
+
+        print("==================")
+        print("IF_AI_tool_output:")
+        print("==================")
+        print(text)
+        
+        # Split text into lines and filter out empty lines
+        text_list = [line.strip() for line in text.split('\n') if line.strip()]
+        count = len(text_list)
+        
+        # Select line using modulo to handle cycling
+        if count == 0:
+            selected = text  # If no valid lines, return original text
+        else:
+            selected = text_list[select % count]
+        
+        # Return both UI update and the multiple outputs
+        return {
+            "ui": {"string": [text]}, 
+            "result": (
+                text,        # complete text
+                text_list,   # list of individual lines as separate string outputs
+                count,       # number of lines
+                selected    # selected line based on select input
+            )
+        }
+
+NODE_CLASS_MAPPINGS = {"IF_DisplayText": IFDisplayText}
+NODE_DISPLAY_NAME_MAPPINGS = {"IF_DisplayText": "IF Display Text📟"}
+
+