Fix trailing whitespace in Live Preview node

Co-authored-by: jags111 <5968619+jags111@users.noreply.github.com>

.gitignore

@@ -1,16 +1,15 @@
-# Python
+# Python cache
 __pycache__/
 *.py[cod]
 *$py.class
 *.so
-.Python
 
 # Virtual environments
 venv/
-ENV/
 env/
+ENV/
 
-# IDEs
+# IDE
 .vscode/
 .idea/
 *.swp

README.md

@@ -131,6 +131,17 @@ Please check out our WIKI for any use cases and new developments including workf
   <img src="https://github.com/LucianoCirino/efficiency-nodes-media/blob/main/images/nodes/Image%20Overlay%20-%20Node%20Example.png" width="1080">
 </p>
  
+</details>
+<!-------------------------------------------------------------------------------------------------------------------------------------------------------->
+<details>
+    <summary><b>Live Preview (Eff.)</b></summary>
+<ul>
+    <li>Node that displays a live preview of images while allowing them to pass through to other nodes in the workflow.</li>
+    <li>Can be connected to multiple samplers sequentially to show progressive updates as the workflow advances through different stages (base sampling, refining, hi-res fix, detailing, etc.).</li>
+    <li>Useful for placing preview displays outside of subgraphs or in custom locations within complex workflows.</li>
+    <li>Simply connect the IMAGE output from any sampler or image processing node to this node's input, and connect its output to continue the workflow.</li>
+</ul>
+ 
 </details>
 <!-------------------------------------------------------------------------------------------------------------------------------------------------------->
 <details>

efficiency_nodes.py

@@ -53,7 +53,6 @@ from .py import city96_latent_upscaler
 from .py import ttl_nn_latent_upscaler
 from .py import bnk_tiled_samplers
 from .py import bnk_adv_encode
-from .py.bnk_adv_encode import normalize_prompt_text
 sys.path.remove(my_dir)
 
 from comfy import samplers
@@ -72,9 +71,6 @@ SCHEDULERS = samplers.KSampler.SCHEDULERS + ["AYS SD1", "AYS SDXL", "AYS SVD", "
 def encode_prompts(positive_prompt, negative_prompt, token_normalization, weight_interpretation, clip, clip_skip,
                    refiner_clip, refiner_clip_skip, ascore, is_sdxl, empty_latent_width, empty_latent_height,
                    return_type="both"):
-    # Ensure prompts are valid strings to prevent tokenization errors
-    positive_prompt = normalize_prompt_text(positive_prompt)
-    negative_prompt = normalize_prompt_text(negative_prompt)
 
     positive_encoded = negative_encoded = refiner_positive_encoded = refiner_negative_encoded = None
 
@@ -4017,6 +4013,34 @@ class TSC_ImageOverlay:
         # Return the edited base image
         return (base_image,)
 
+########################################################################################################################
+# TSC Live Preview Node
+class TSC_LivePreview:
+    
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "images": ("IMAGE",),
+            },
+            "hidden": {
+                "prompt": "PROMPT",
+                "extra_pnginfo": "EXTRA_PNGINFO"
+            },
+        }
+    
+    RETURN_TYPES = ("IMAGE",)
+    FUNCTION = "preview_image"
+    OUTPUT_NODE = True
+    CATEGORY = "Efficiency Nodes/Image"
+    
+    def preview_image(self, images, prompt=None, extra_pnginfo=None):
+        # Generate preview using ComfyUI's PreviewImage node
+        preview = PreviewImage().save_images(images, prompt=prompt, extra_pnginfo=extra_pnginfo)["ui"]
+        
+        # Return both the preview for UI and the original images for pass-through
+        return {"ui": preview, "result": (images,)}
+
 ########################################################################################################################
 # Noise Sources & Seed Variations
 # https://github.com/shiimizu/ComfyUI_smZNodes
@@ -4292,6 +4316,7 @@ NODE_CLASS_MAPPINGS = {
     "Manual XY Entry Info": TSC_XYplot_Manual_XY_Entry_Info,
     "Join XY Inputs of Same Type": TSC_XYplot_JoinInputs,
     "Image Overlay": TSC_ImageOverlay,
+    "Live Preview (Eff.)": TSC_LivePreview,
     "Noise Control Script": TSC_Noise_Control_Script,
     "HighRes-Fix Script": TSC_HighRes_Fix,
     "Tiled Upscaler Script": TSC_Tiled_Upscaler,

py/bnk_adv_encode.py

@@ -6,34 +6,6 @@ from math import gcd
 from comfy import model_management
 from comfy.sdxl_clip import SDXLClipModel, SDXLRefinerClipModel, SDXLClipG
 
-def normalize_prompt_text(text):
-    """
-    Normalize prompt text to prevent tokenization errors.
-    
-    Converts None, empty strings, or whitespace-only strings to a single space.
-    Ensures the input is a string type by converting non-string values.
-    This function is designed to handle edge cases gracefully without crashing,
-    which is important for ComfyUI workflows where users might have empty prompts.
-    
-    Parameters:
-        text: The input prompt text to normalize. Can be of any type, though
-              string, None, or convertible types are expected.
-    
-    Returns:
-        str: A normalized string that is safe to pass to the tokenizer.
-             Returns " " (single space) for None, empty, or whitespace-only inputs.
-             Returns the original text unchanged if it's a valid non-empty string.
-             Returns str(text) for non-string types.
-    """
-    if text is None:
-        return " "
-    if not isinstance(text, str):
-        # Convert non-string types to string
-        text = str(text)
-    if not text.strip():
-        return " "
-    return text
-
 def _grouper(n, iterable):
     it = iter(iterable)
     while True:
@@ -265,8 +237,6 @@ def prepareXL(embs_l, embs_g, pooled, clip_balance):
         return embs_g, pooled
 
 def advanced_encode(clip, text, token_normalization, weight_interpretation, w_max=1.0, clip_balance=.5, apply_to_pooled=True):
-    # Ensure text is a valid string to prevent tokenization errors
-    text = normalize_prompt_text(text)
     tokenized = clip.tokenize(text, return_word_ids=True)
     if isinstance(clip.cond_stage_model, (SDXLClipModel, SDXLRefinerClipModel, SDXLClipG)):
         embs_l = None
@@ -295,9 +265,6 @@ def advanced_encode(clip, text, token_normalization, weight_interpretation, w_ma
                                            lambda x: (clip.encode_from_tokens({'l': x}), None),
                                            w_max=w_max)
 def advanced_encode_XL(clip, text1, text2, token_normalization, weight_interpretation, w_max=1.0, clip_balance=.5, apply_to_pooled=True):
-    # Ensure texts are valid strings to prevent tokenization errors
-    text1 = normalize_prompt_text(text1)
-    text2 = normalize_prompt_text(text2)
     tokenized1 = clip.tokenize(text1, return_word_ids=True)
     tokenized2 = clip.tokenize(text2, return_word_ids=True)