Merge remote-tracking branch 'origin/dev' into dev

Update CHANGELOG.md
Update example workflow

.github/ISSUE_TEMPLATE/BUG-REPORT.yml

@@ -34,14 +34,3 @@ body:
         ![DESCRIPTION](LINK.png)
     validations:
       required: false
-  - type: dropdown
-    id: version
-    attributes:
-      label: "Version"
-      description: What version are you running?
-      multiple: false
-      options:
-        - 1.0.0
-      default: 0
-    validations:
-      required: false

.gitignore

@@ -153,3 +153,4 @@ dmypy.json
 cython_debug/
 
 .idea/
+preview/

CHANGELOG.md

@@ -1,4 +1,47 @@
 # Change Log
+## v1.3.0
+> Starting from this version, to support auto-detection on Civitai, `calculate_model_hash` will be renamed as 
+> `calculate_hash` and it will be enabled by default. Due to the addition of temporary storage of the model hash values,
+> the first image generated after switching to the new model will take more time to calculate the hash value, 
+> but it will not affect the generation speed afterwards until the server is restarted.
+
+- Add `Lora Loader` node and `Lora Selector` node
+- Add `VAE_NAME` output to the `Parameter Generator` node and add `vae_name` input to the `Prompt Saver` node #39
+- Add `lora_name` input to the `Prompt Saver` node
+- Add `resource_hash` switch to the `Prompt Saver` node
+- Add resources hashes to metadata for auto-detection on Civitai #35
+- Add temporary storage for model hashes
+- Add `WEB_DIRECTORY` and remove old js directory
+- Fix adding the `Parameter Generator` node to a workflow disables the queue button #45
+- Fix the `Parameter Generator` node doesn't load seed value from generated images #44
+- Fix the input validation of the `Batch Loader` node #37 #38
+- Fix the parsing error caused by the loss of model data #43
+- Fix the error message caused by aspect_ratio
+- Rename `calculate_model_hash` as `calculate_hash`
+- Update seedGen.js to rgthree's latest code
+- Update core to cc3c8b2
+
+## v1.2.1
+- Fix the input validation of the `Prompt Reader` node #37
+- Fix the `Batch Loader` node not working when not connected to any node
+
+## v1.2.0
+- Add `Parameter Extractor` node #24
+- Add a model matching feature to the `Prompt Reader` node #24
+- Add `save_metadata_file` option to the `Prompt Saver` node #30
+- Add `FILE_PATH` output to the `Prompt Saver` node #26
+- Fix the issue where the `Prompt Merger` node threw an error when merging empty strings #29
+- Enhance the `Batch Loader` node to support processing either a single file or a list of files #26
+- Update core to 1.3.4.post1
+
+## v1.1.0
+- Add `Batch Loader` node #13
+- Add `MODEL_NAME` output to the `Prompt Reader` node #23
+- Add VAE selector to the `Parameter Generator` node #15
+- Add pixel dimensions display to the `aspect_ratio` in the `Parameter Generator` node #6
+- Add Positive and Negative Aesthetic Score to the `PARAMETERS` in the `Parameter Generator` node #8
+- Add `FILENAME` and `METADATA` output to the `Prompt Saver` node #16
+
 ## v1.0.1
 - Add a new file-naming mechanism to ensure naming uniqueness
 - Fix `%counter` overwriting existing images #11 #14

README.md

@@ -20,9 +20,10 @@ additional metadata to ensure compatibility with metadata detection on websites
     <a href="#supported-formats">Supported Formats</a> •
     <a href="#installation">Installation</a> •
     <a href="#usage">Usage</a> •
+    <a href="./CHANGELOG.md">Change Log</a> •
     <a href="#credits">Credits</a>
   </p>
-    <img src="./images/screenshot_v100.png">
+    <img src="./images/screenshot_v130.png">
 </div>
 
 
@@ -65,6 +66,10 @@ git pull --recurse-submodules
 
 ## Usage
 ### Prompt Reader Node
+<div align="center">
+   <img src="./images/reader.png" width="25%" height="25%" alt="reader node">
+</div>
+
 - The `Prompt Reader` Node works exactly the same as the 
 [standalone SD Prompt Reader](https://github.com/receyuki/stable-diffusion-prompt-reader). 
 It uses the Image Data Reader from the 
@@ -73,87 +78,231 @@ allowing it to support the same formats and receive updates along with the
 [SD Prompt Reader](https://github.com/receyuki/stable-diffusion-prompt-reader).
 - Due to custom nodes and complex workflows potentially causing issues with SD Prompt Reader's ability 
 to read image metadata correctly, it is recommended to embed the `Prompt Saver` Node within the workflow 
-to ensure maximum compatibility.   
+to ensure maximum compatibility.
+<details>
+    <summary><b>More Information</b></summary>
+
+#### `parameter_index`
 - For images containing multiple sets of parameters, such as those processed through `hires-fix` or `refiner`, 
 you will need to modify the `parameter_index` to select the parameters you need
+#### SDXL
 - For images generated by SDXL and containing multiple sets of prompts, 
 the `text_g` will be combined with `text_l` into a single prompt
-
+#### Batch Read
+- For batch processing, please use the `Batch Loader` node. When using the `Batch Loader` node for bulk reading, 
+the preview image will not update, and the text box will only display the metadata of the last image.
 <div align="center">
-   <img src="./images/reader.png" width="25%" height="25%" alt="reader node">
+   <img src="./images/loader2reader.png" width="50%" height="50%" alt="connect batch loader to prompt reader">
 </div>
 
+#### Additional Parameters
+- To read parameters other than the existing output, please connect the `settings` to the `Parameter Extractor` node.
+<div align="center">
+   <img src="./images/reader2extractor.png" width="50%" height="50%" alt="connect prompt reader to parameter extractor">
+</div>
+
+#### `MODEL_NAME`
+- `MODEL_NAME` is a special output that matches the model name in the metadata with the existing models on the server 
+according to the following priority:
+  1. Identical path, filename, and extension.
+  2. Identical filename, and extension. 
+e.g. `sd_xl_base.safetensors` will be matched with `SDXL\sd_xl_base.safetensors`, and vice versa.
+  3. Identical filename.
+e.g. `sd_xl_base` will be matched with `SDXL\sd_xl_base.safetensors`, and vice versa.
+  4. If a matching model cannot be found, the original name will be outputted.
+
+</details>
+
 ### Prompt Saver Node
-- The `Prompt Saver` Node and The `Parameter Generator` Node are designed to be used together.  
+<div align="center">
+   <img src="./images/saver.png" width="25%" height="25%" alt="saver node">
+</div>
+
+- The `Prompt Saver` Node and the `Parameter Generator` Node are designed to be used together.  
 - The `Prompt Saver` Node will write additional metadata in the A1111 format to the output images 
 to be compatible with any tools that support the A1111 format, 
 including SD Prompt Reader and Civitai. 
 Due to custom nodes and complex workflows potentially causing issues with SD Prompt Reader's ability 
-to read image metadata correctly, it is recommended to embed this node within the workflow 
+to read image metadata correctly, it's recommended to embed this node within the workflow 
 to ensure maximum compatibility.   
-- Since it's not possible to directly extract metadata from `KSampler`, it is necessary to 
-use the `Parameter Generator` Node to generate parameters and simultaneously output them to both 
-the `Prompt Saver` Node and `KSampler`.
-- Please refer to the following table for placeholders supported by the `filename` and `path`.
+- Since it's not possible to directly extract metadata from `KSampler`, it's necessary to 
+use the `Parameter Generator` Node to generate parameters and simultaneously output them to 
+the `Prompt Saver` Node and `KSampler` Node.
 
-   | Placeholder |
-   |-------------|
-   | %date       |
-   | %time       |
-   | %counter    |
-   | %seed       |
-   | %steps      |
-   | %cfg        |
-   | %extension  |
-   | %model      |
-   | %sampler    |
-   | %scheduler  |
-   | %quality    |
-- `%counter` cannot be used for the `path`. This `%counter` is slightly different from the `%counter` 
-in the built-in Saver node, it will count all image files in the `path`.
+<details>
+    <summary><b>More Information</b></summary>
+
+#### Duplicate Filename
 - When the filename already exists, an index will be added at the end of the filename, 
 e.g. `file.png, file_1.png, file_2.png`.
+#### Hashes & Auto-Detection on Civitai
+- When `calculate_hash` is enabled, the node will compute the hash values of checkpoint, VAE, Lora, 
+and embedding/Textual Inversion, and write them into the metadata. After the server restarts, or a new checkpoint, 
+VAE, Lora, or embedding/Textual Inversion is loaded, the first image generation may take a longer time for hash calculation. 
+The hash value will be stored in temporary storage without the need for repeated calculation, 
+until the server is restarted.
+- When `resource_hash` is enabled, the resource hashes will be written into the metadata to support auto-detection 
+on Civitai. This function will only run when `calculate_hash` is enabled.
+- If you need to calculate the hash of Lora, please use the `Lora Loader` Node or the `Lora Selector` Node. 
+The hash value of the embedding/Textual Inversion will be automatically detected from the prompt.
+#### `save_metadata_file`
+- When the `save_metadata_file` is turned on, the metadata will be saved as a TXT file with the same name
+alongside the image.
+#### `date_format` & `time_format`
 - For the `date_format` and `time_format`, please refer to 
 [strftime.org](https://strftime.org/) or [www.strfti.me](https://www.strfti.me/).
+#### `filename` & `path`
+- `%counter` cannot be used for `path`, it can only be used for `filename`. This `%counter` is slightly different 
+from the `%counter` in the built-in `Saver` node, it will count all image files in the `path`.
+- Please refer to the following table for placeholders supported by the `filename` and `path`.
 
+   |            |            |
+   |------------|------------|
+   | %seed      | %date      |
+   | %steps     | %time      |
+   | %cfg       | %counter   |
+   | %model     | %extension |
+   | %sampler   | %quality   |
+   | %scheduler |            |
+
+</details>
+
+### Parameter Generator Node
 <div align="center">
-   <img src="./images/saver.png" width="25%" height="25%" alt="generator and saver node">
+   <img src="./images/generator.png" width="25%" height="25%" alt="generator node">
 </div>
 
-## Parameter Generator Node
-- Since it's not possible to directly extract metadata from `KSampler`, it is necessary to 
+- Since it's not possible to directly extract metadata from `KSampler`, it's necessary to 
 use the `Parameter Generator` Node to generate parameters and simultaneously output them to both 
-the `Prompt Saver` Node and `KSampler`.
+the `Prompt Saver` Node and `KSampler` Node.
 - The `Parameter Generator` Node can also be used as a control panel for complex ComfyUI workflows, just like the [AP workflow](https://perilli.com/ai/comfyui/).
-- The `model_version` and `aspect_ratio` are used only for calculating the optimal resolution of the selected model version 
-under the chosen aspect ratio. The calculation method is based on the 
+<details>
+    <summary><b>More Information</b></summary>
+
+#### Optimal Resolution
+- The `model_version` and `aspect_ratio` are used only for calculating the optimal resolution of the selected 
+model version under the chosen aspect ratio. The calculation method is based on the 
 [Stability AI development documentation](https://platform.stability.ai/docs/features/api-parameters#about-dimensions) 
 and the [StableSwarmUI source code](https://github.com/Stability-AI/StableSwarmUI) (developed by Stability AI).
+#### `refiner_start`
 - `refiner_start` refers to the proportion of steps completed when the refiner starts running, 
 i.e., the proportion of base steps to total steps. This is used to calculate the `start_at_step` (`REFINER_START_STEP`)
 required by the refiner `KSampler` under the selected step ratio.
 
+</details>
+
+### Batch Loader Node
 <div align="center">
-   <img src="./images/generator.png" width="25%" height="25%" alt="generator and saver node">
+   <img src="./images/loader.png" width="25%" height="25%" alt="loader node">
 </div>
 
+- The `Batch Loader` Node is specifically designed for the `Prompt Reader` Node to batch-read image files in a directory 
+and cannot be used with other custom nodes.
+<details>
+    <summary><b>More Information</b></summary>
+
+- For batch processing, please connect the `IMAGE` output of the `Batch Loader` Node to the `image` input of 
+the `Prompt Reader` Node.
+<div align="center">
+   <img src="./images/loader2reader.png" width="50%" height="50%" alt="connect prompt reader to parameter extractor">
+</div>
+
+#### `path`
+- The `path` supports relative paths such as `./input/` or absolute paths like `C:/Users/receyuki/Pictures`.
+- Both `\ ` and `/` are acceptable.
+- You can also input a single file or a list of files into the `path`, 
+in which case the `image_load_limit` and `start_index` will not function.
+
+</details>
+
+### Parameter Extractor Node
+<div align="center">
+   <img src="./images/extractor.png" width="25%" height="25%" alt="extractor node">
+</div>
+
+- The `Parameter Extractor` Node is an extension of the `Prompt Reader` Node, designed to retrieve the values 
+of all parameters in the settings (including those parameters that the `Prompt Reader` Node cannot output). 
+e.g. `Hires  upscaler`
+<details>
+    <summary><b>More Information</b></summary>
+
+- Connect the `SETTINGS` of the `Prompt Reader` Node to the `settings` of the `Parameter Extractor` Node. 
+After the first run, the parameter list will be loaded.
+<div align="center">
+   <img src="./images/reader2extractor.png" width="50%" height="50%" alt="connect prompt reader to parameter extractor">
+</div>
+</details>
+
 ### Prompt Merger Node & Type Converter Node
+<div align="center">
+   <img src="./images/merger_converter.png" width="25%" height="25%" alt="merger and converter node">
+</div>
+
 - Since the A1111 format cannot store `text_g` and `text_l` separately, SDXL users need to use 
 the `Prompt Merger` Node to combine `text_g` and `text_l` into a single prompt.
 - Since `model_name`, `sampler_name`, and `scheduler` are special types 
 that cannot be directly used by some other nodes,
 You can use the `Type Converter` Node to convert them into `STRING` type.
 
+### Lora Loader Node & Lora Selector Node
 <div align="center">
-   <img src="./images/merger_converter.png" width="25%" height="25%" alt="merger and converter node">
+   <img src="./images/lora.png" width="50%" height="50%" alt="lora loader and selector node">
 </div>
 
-### [Example Workflow](./workflows/example_workflow.json)
+- The `Lora Loader` Node and `Lora Selector` Node are used to write Lora data into metadata and support auto-detection
+on Civitai. 
+<details>
+    <summary><b>More Information</b></summary>
 
+- Replace the original loader with the `Lora Loader` Node, or connect the `LORA_NAME` output of the `Lora Selector` Node
+to the `lora_name` input of other lora loaders (built-in or custom), and link the `NEXT_LORA` output to the `lora_name` 
+input of the `Prompt Saver` Node. Both of these nodes have the same function, please choose according to your needs.
+#### Multiple Loras
+- If you need to load multiple Loras, please connect the `Lora Loader` Node or `Lora Selector` Node head to tail 
+through `last_lora` and `NEXT_LORA`, and connect the `NEXT_LORA` at the end of the Lora chain to the `lora_name` input 
+of the `Prompt Saver` Node.
+1. Lora Loader chain
 <div align="center">
-   <img src="./images/example_workflow.png" width="100%" height="100%" alt="example workflow">
+    <img src="./images/lora_loader_chain.png" width="100%" height="100%" alt="lora loader chain">
 </div>
 
+2. Lora Selector chain
+<div align="center">
+    <img src="./images/lora_selector_chain.png" width="100%" height="100%" alt="lora loader chain">
+</div>
+
+</details>
+
+### Example Workflow
+<details>
+    <summary><b>Simple Example</b></summary>
+<div align="center">
+   <img src="./workflows/simple_example.png" width="100%" height="100%" alt="example workflow">
+</div>
+</details>
+
+<details>
+    <summary><b>Lora Example</b></summary>
+<div align="center">
+   <img src="./workflows/lora_example.png" width="100%" height="100%" alt="example workflow">
+</div>
+</details>
+
+<details>
+    <summary><b>Hires-fix Example</b></summary>
+<div align="center">
+   <img src="./workflows/hires_fix_example.png" width="100%" height="100%" alt="example workflow">
+</div>
+</details>
+
+<details>
+    <summary><b>SDXL Example</b></summary>
+<div align="center">
+   <img src="./workflows/sdxl_example.png" width="100%" height="100%" alt="example workflow">
+</div>
+</details>
+
+
 ## Credits
 - The SD Prompt Reader node is based on [ComfyUI Load Image With Metadata](https://github.com/tkoenig89/ComfyUI_Load_Image_With_Metadata)
 - The SD Prompt Saver node is based on [Comfy Image Saver](https://github.com/giriss/comfy-image-saver) & [Stable Diffusion Webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui)

__init__.py

@@ -6,14 +6,10 @@ import shutil
 import folder_paths
 import os
 
+WEB_DIRECTORY = "./js"
+
+# remove old directory
 comfy_path = os.path.dirname(folder_paths.__file__)
-tk_nodes_path = os.path.join(os.path.dirname(__file__))
-
-js_dest_path = os.path.join(comfy_path, "web", "extensions", "SDPromptReader")
-os.makedirs(js_dest_path, exist_ok=True)
-
-files_to_copy = ["promptDisplay.js", "parameterDisplay.js", "seedGen.js"]
-
-for file in files_to_copy:
-    js_src_path = os.path.join(tk_nodes_path, "js", file)
-    shutil.copy(js_src_path, js_dest_path)
+old_dir = os.path.join(comfy_path, "web", "extensions", "SDPromptReader")
+if os.path.exists(old_dir):
+    shutil.rmtree(old_dir)

__version__.py

@@ -1 +1 @@
-VERSION = "1.0.1"
+VERSION = "1.3.0"

js/extractorDisplay.js

@@ -0,0 +1,31 @@
+import {app} from "../../scripts/app.js";
+import {ComfyWidgets} from "../../scripts/widgets.js";
+import {createTextWidget} from "./utils.js"
+
+app.registerExtension({
+    name: "sd_prompt_reader.extractorDisplay",
+    async beforeRegisterNodeDef(nodeType, nodeData, app) {
+        if (nodeData.name === "SDParameterExtractor") {
+            const onNodeCreated = nodeType.prototype.onNodeCreated;
+
+            nodeType.prototype.onNodeCreated = function () {
+                const result = onNodeCreated?.apply(this, arguments);
+
+                // Create widgets
+                const styles = {textAlign: "center", fontSize: "0.75rem"}
+                const value_display =  createTextWidget(app, this, "value_display", styles);
+            };
+
+            // Update widgets
+            const onExecuted = nodeType.prototype.onExecuted;
+            nodeType.prototype.onExecuted = function (message) {
+                onExecuted?.apply(this, arguments);
+                this.widgets.find(obj => obj.name === "value_display").value = message.text[1]
+                this.widgets.find(obj => obj.name === "parameter").options.values = message.text[0]
+                if (this.widgets.find(obj => obj.name === "parameter").value === "parameters not loaded") {
+                    this.widgets.find(obj => obj.name === "parameter").value = message.text[0][0]
+                }
+            };
+        }
+    },
+});

js/loaderDisplay.js

@@ -0,0 +1,30 @@
+import {app} from "../../scripts/app.js";
+import {ComfyWidgets} from "../../scripts/widgets.js";
+import {createTextWidget} from "./utils.js"
+
+// Displays file list on the node
+app.registerExtension({
+    name: "sd_prompt_reader.loaderDisplay",
+    async beforeRegisterNodeDef(nodeType, nodeData, app) {
+        if (nodeData.name === "SDBatchLoader") {
+            const onNodeCreated = nodeType.prototype.onNodeCreated;
+
+            nodeType.prototype.onNodeCreated = function () {
+                const result = onNodeCreated?.apply(this, arguments);
+
+                // Create prompt and setting widgets
+                const styles = {opacity: 0.7}
+                const fileList =createTextWidget(app, this, "fileList", styles);
+                return result;
+            };
+
+            // Update widgets
+            const onExecuted = nodeType.prototype.onExecuted;
+            nodeType.prototype.onExecuted = function (message) {
+                onExecuted?.apply(this, arguments);
+                this.widgets.find(obj => obj.name === "fileList").value = message.text[0];
+
+            };
+        }
+    },
+});

js/parameterDisplay.js

@@ -1,14 +1,6 @@
 import {app} from "../../scripts/app.js";
 import {ComfyWidgets} from "../../scripts/widgets.js";
-
-// Create a read-only string widget
-function createWidget(app, node, widgetName, type) {
-    const widget = ComfyWidgets[type](node, widgetName, ["STRING", {multiline: true}], app).widget;
-    widget.inputEl.readOnly = true;
-    widget.inputEl.style.textAlign = "center";
-    widget.inputEl.style.fontSize = "0.75rem";
-    return widget;
-}
+import {createTextWidget} from "./utils.js"
 
 app.registerExtension({
     name: "sd_prompt_reader.parameterDisplay",
@@ -20,8 +12,9 @@ app.registerExtension({
                 const result = onNodeCreated?.apply(this, arguments);
 
                 // Create widgets
-                const steps_display = createWidget(app, this, "steps_display", "STRING");
-                const aspect_ratio_display = createWidget(app, this, "aspect_ratio_display", "STRING");
+                const styles = {textAlign: "center", fontSize: "0.75rem"}
+                const steps_display = createTextWidget(app, this, "steps_display", styles);
+                const aspect_ratio_display = createTextWidget(app, this, "aspect_ratio_display", styles);
 
                 // Resize the node
                 const nodeWidth = this.size[0];
@@ -59,6 +52,18 @@ Refiner start at step: ${message.text[6]} (${base_percentage})`;
 
                 this.widgets.find(obj => obj.name === "steps_display").value = step_message;
                 this.widgets.find(obj => obj.name === "aspect_ratio_display").value = ar_message;
+
+                const scalingFactor = message.text[9][message.text[1]]
+                const aspectRatioArray = Object.entries(message.text[8]).map(([ratio, dimensions]) => {
+                    const [width, height] = dimensions;
+                    return `${ratio} - ${width*scalingFactor}x${height*scalingFactor}`;
+                });
+                aspectRatioArray.unshift("custom")
+                if (message.text[0] !== "custom") {
+                    const aspectRatio = `${message.text[0]} - ${message.text[8][message.text[0]][0]*scalingFactor}x${message.text[8][message.text[0]][1]*scalingFactor}`
+                    this.widgets.find(obj => obj.name === "aspect_ratio").value = aspectRatio
+                }
+                this.widgets.find(obj => obj.name === "aspect_ratio").options.values = aspectRatioArray
             };
         }
     },

js/promptDisplay.js

@@ -1,13 +1,6 @@
 import {app} from "../../scripts/app.js";
 import {ComfyWidgets} from "../../scripts/widgets.js";
-
-// Create a read-only string widget with opacity set
-function createWidget(app, node, widgetName) {
-    const widget = ComfyWidgets["STRING"](node, widgetName, ["STRING", {multiline: true}], app).widget;
-    widget.inputEl.readOnly = true;
-    widget.inputEl.style.opacity = 0.7;
-    return widget;
-}
+import {createTextWidget} from "./utils.js"
 
 // Displays prompt and setting on the node
 app.registerExtension({
@@ -20,9 +13,10 @@ app.registerExtension({
                 const result = onNodeCreated?.apply(this, arguments);
 
                 // Create prompt and setting widgets
-                const positive = createWidget(app, this, "positive");
-                const negative = createWidget(app, this, "negative");
-                const setting = createWidget(app, this, "setting");
+                const styles = {opacity: 0.7}
+                const positive = createTextWidget(app, this, "positive", styles);
+                const negative = createTextWidget(app, this, "negative", styles);
+                const setting = createTextWidget(app, this, "setting", styles);
                 // Resize the node
                 const nodeWidth = this.size[0];
                 const nodeHeight = this.size[1];
@@ -34,9 +28,9 @@ app.registerExtension({
             const onExecuted = nodeType.prototype.onExecuted;
             nodeType.prototype.onExecuted = function (message) {
                 onExecuted?.apply(this, arguments);
-                this.widgets[3].value = message.text[0];
-                this.widgets[4].value = message.text[1];
-                this.widgets[5].value = message.text[2];
+                this.widgets.find(obj => obj.name === "positive").value = message.text[0];
+                this.widgets.find(obj => obj.name === "negative").value = message.text[1];
+                this.widgets.find(obj => obj.name === "setting").value = message.text[2];
             };
         }
     },

js/seedGen.js

@@ -1,16 +1,115 @@
 /**
- * Modified from: https://github.com/rgthree/rgthree-comfy/blob/main/web/seed.js
+ * Modified from: https://github.com/rgthree/rgthree-comfy/blob/main/web/comfyui/seed.js
  * Modified by: receyuki
  */
 import {app} from "../../scripts/app.js";
 import {ComfyWidgets} from "../../scripts/widgets.js";
 
-const LAST_SEED_BUTTON_LABEL = "(Use Last Queued Seed)";
+const LAST_SEED_BUTTON_LABEL = "(Use last queued seed)";
 const SPECIAL_SEED_RANDOM = -1;
 const SPECIAL_SEED_INCREMENT = -2;
 const SPECIAL_SEED_DECREMENT = -3;
 const SPECIAL_SEEDS = [SPECIAL_SEED_RANDOM, SPECIAL_SEED_INCREMENT, SPECIAL_SEED_DECREMENT];
 
+function getResolver(timeout = 5000) {
+    const resolver = {};
+    resolver.id = generateId(8);
+    resolver.completed = false;
+    resolver.resolved = false;
+    resolver.rejected = false;
+    resolver.promise = new Promise((resolve, reject) => {
+        resolver.reject = () => {
+            resolver.completed = true;
+            resolver.rejected = true;
+            reject();
+        };
+        resolver.resolve = (data) => {
+            resolver.completed = true;
+            resolver.resolved = true;
+            resolve(data);
+        };
+    });
+    resolver.timeout = setTimeout(() => {
+        if (!resolver.completed) {
+            resolver.reject();
+        }
+    }, timeout);
+    return resolver;
+}
+
+function generateId(length) {
+    const arr = new Uint8Array(length / 2);
+    crypto.getRandomValues(arr);
+    return Array.from(arr, dec2hex).join('');
+}
+
+function dec2hex(dec) {
+    return dec.toString(16).padStart(2, "0");
+}
+
+let graphResolver = null;
+
+function waitForGraph() {
+    if (graphResolver === null) {
+        graphResolver = getResolver();
+
+        function _wait() {
+            if (!graphResolver.completed) {
+                if (app === null || app === void 0 ? void 0 : app.graph) {
+                    graphResolver.resolve(app.graph);
+                } else {
+                    requestAnimationFrame(_wait);
+                }
+            }
+        }
+
+        _wait();
+    }
+    return graphResolver.promise;
+}
+
+class Rgthree extends EventTarget {
+    constructor() {
+        super();
+        this.processingQueue = false;
+        this.initialGraphToPromptSerializedWorkflowBecauseComfyUIBrokeStuff = null;
+        this.initializeGraphAndCanvasHooks();
+        this.initializeComfyUIHooks();
+    }
+
+    async initializeGraphAndCanvasHooks() {
+        const rgthree = this;
+        const [graph] = await Promise.all([waitForGraph()]);
+        const onSerialize = graph.onSerialize;
+        graph.onSerialize = (data) => {
+            this.initialGraphToPromptSerializedWorkflowBecauseComfyUIBrokeStuff = data;
+            onSerialize === null || onSerialize === void 0 ? void 0 : onSerialize.call(graph, data);
+        };
+    }
+
+    initializeComfyUIHooks() {
+        const rgthree = this;
+        const queuePrompt = app.queuePrompt;
+        app.queuePrompt = async function () {
+            rgthree.dispatchEvent(new CustomEvent("queue"));
+            rgthree.processingQueue = true;
+            try {
+                await queuePrompt.apply(app, [...arguments]);
+            } finally {
+                rgthree.processingQueue = false;
+                rgthree.dispatchEvent(new CustomEvent("queue-end"));
+            }
+        };
+    }
+
+    getNodeFromInitialGraphToPromptSerializedWorkflowBecauseComfyUIBrokeStuff(node) {
+        var _a, _b, _c;
+        return ((_c = (_b = (_a = this.initialGraphToPromptSerializedWorkflowBecauseComfyUIBrokeStuff) === null || _a === void 0 ? void 0 : _a.nodes) === null || _b === void 0 ? void 0 : _b.find((n) => n.id === node.id)) !== null && _c !== void 0 ? _c : null);
+    }
+}
+
+const rgthree = new Rgthree();
+
 class SeedControl {
     constructor(node) {
         this.lastSeed = undefined;
@@ -33,6 +132,7 @@ class SeedControl {
         for (const [i, w] of this.node.widgets.entries()) {
             if (w.name === "seed") {
                 this.seedWidget = w;
+                this.seedWidget.value = SPECIAL_SEED_RANDOM;
             } else if (w.name === "control_after_generate") {
                 this.node.widgets.splice(i, 1);
             }
@@ -58,6 +158,9 @@ class SeedControl {
         this.lastSeedButton.disabled = true;
         this.seedWidget.serializeValue = async (node, index) => {
             const inputSeed = this.seedWidget.value;
+            if (!rgthree.processingQueue) {
+                return inputSeed;
+            }
             this.serializedCtx = {
                 inputSeed: this.seedWidget.value,
             };
@@ -76,7 +179,13 @@ class SeedControl {
             } else {
                 this.serializedCtx.seedUsed = this.seedWidget.value;
             }
-            node.widgets_values[index] = this.serializedCtx.seedUsed;
+            const n = rgthree.getNodeFromInitialGraphToPromptSerializedWorkflowBecauseComfyUIBrokeStuff(node);
+            if (n) {
+                n.widgets_values[index] = this.serializedCtx.seedUsed;
+            } else {
+                console.warn('No serialized node found in workflow. May be attributed to '
+                    + 'https://github.com/comfyanonymous/ComfyUI/issues/2193');
+            }
             this.seedWidget.value = this.serializedCtx.seedUsed;
             this.lastSeed = this.serializedCtx.seedUsed;
             if (SPECIAL_SEEDS.includes(this.serializedCtx.inputSeed)) {
@@ -97,42 +206,6 @@ class SeedControl {
             }
             this.serializedCtx = {};
         };
-        this.node.getExtraMenuOptions = (_, options) => {
-            options.splice(options.length - 1, 0, {
-                content: "Show/Hide Last Seed Value",
-                callback: (_value, _options, _event, _parentMenu, _node) => {
-                    this.node.properties["showLastSeed"] = !this.node.properties["showLastSeed"];
-                    if (this.node.properties["showLastSeed"]) {
-                        this.addLastSeedValue();
-                    } else {
-                        this.removeLastSeedValue();
-                    }
-                },
-            });
-        };
-    }
-
-    addLastSeedValue() {
-        if (this.lastSeedValue)
-            return;
-        this.lastSeedValue = ComfyWidgets["STRING"](this.node, "last_seed", ["STRING", {multiline: true}], app).widget;
-        this.lastSeedValue.inputEl.readOnly = true;
-        this.lastSeedValue.inputEl.style.fontSize = "0.75rem";
-        this.lastSeedValue.inputEl.style.textAlign = "center";
-        this.lastSeedValue.serializeValue = async (node, index) => {
-            node.widgets_values[index] = "";
-            return "";
-        };
-        this.node.computeSize();
-    }
-
-    removeLastSeedValue() {
-        if (!this.lastSeedValue)
-            return;
-        this.lastSeedValue.inputEl.remove();
-        this.node.widgets.splice(this.node.widgets.indexOf(this.lastSeedValue), 1);
-        this.lastSeedValue = null;
-        this.node.computeSize();
     }
 }
 
@@ -142,12 +215,8 @@ app.registerExtension({
         if (nodeData.name === "SDParameterGenerator") {
             const onNodeCreated = nodeType.prototype.onNodeCreated;
             nodeType.prototype.onNodeCreated = function () {
-                const result = onNodeCreated?.apply(this, []);
+                onNodeCreated ? onNodeCreated.apply(this, []) : undefined;
                 this.seedControl = new SeedControl(this);
-                const nodeWidth = this.size[0];
-                const nodeHeight = this.size[1];
-                this.setSize([nodeWidth * 1.5, nodeHeight * 1.1]);
-                return result;
             };
         }
     },

js/utils.js

@@ -0,0 +1,10 @@
+import {app} from "../../scripts/app.js";
+import {ComfyWidgets} from "../../scripts/widgets.js";
+
+// Create a read-only string widget
+export function createTextWidget(app, node, widgetName, styles = {}) {
+    const widget = ComfyWidgets["STRING"](node, widgetName, ["STRING", {multiline: true}], app).widget;
+    widget.inputEl.readOnly = true;
+    Object.assign(widget.inputEl.style, styles);
+    return widget;
+}

nodes.py

@@ -12,6 +12,7 @@ from itertools import chain
 
 import torch
 import json
+import re
 import numpy as np
 from pathlib import Path
 from PIL import Image, ImageOps
@@ -53,18 +54,42 @@ output_to_terminal("Node version: " + NODE_VERSION)
 output_to_terminal("Core version: " + CORE_VERSION)
 
 
+class AnyType(str):
+    """A special type that can be connected to any other types. Credit to pythongosssss"""
+
+    def __ne__(self, __value: object) -> bool:
+        return False
+
+
+any_type = AnyType("*")
+
+
 class SDPromptReader:
+    files = []
+    ckpt_paths = []
+    ckpt_names = []
+    ckpt_stems = []
+
     @classmethod
     def INPUT_TYPES(s):
+        for path in folder_paths.get_filename_list("checkpoints"):
+            SDPromptReader.ckpt_paths.append(path)
+            SDPromptReader.ckpt_names.append(Path(path).name)
+            SDPromptReader.ckpt_stems.append(Path(path).stem)
+
         input_dir = folder_paths.get_input_directory()
-        files = [
-            f
-            for f in os.listdir(input_dir)
-            if os.path.isfile(os.path.join(input_dir, f))
-        ]
+        SDPromptReader.files = sorted(
+            [
+                f
+                for f in os.listdir(input_dir)
+                if os.path.isfile(os.path.join(input_dir, f))
+            ]
+        )
         return {
             "required": {
-                "image": (sorted(files), {"image_upload": True}),
+                "image": (SDPromptReader.files, {"image_upload": True}),
+            },
+            "optional": {
                 "parameter_index": (
                     "INT",
                     {"default": 0, "min": 0, "max": 255, "step": 1},
@@ -82,6 +107,7 @@ class SDPromptReader:
         "FLOAT",
         "INT",
         "INT",
+        any_type,
         "STRING",
         "STRING",
     )
@@ -95,7 +121,8 @@ class SDPromptReader:
         "CFG",
         "WIDTH",
         "HEIGHT",
-        "FILE_NAME",
+        "MODEL_NAME",
+        "FILENAME",
         "SETTINGS",
     )
 
@@ -104,7 +131,10 @@ class SDPromptReader:
     OUTPUT_NODE = True
 
     def load_image(self, image, parameter_index):
-        image_path = folder_paths.get_annotated_filepath(image)
+        if image in SDPromptReader.files:
+            image_path = folder_paths.get_annotated_filepath(image)
+        else:
+            image_path = image
         i = Image.open(image_path)
         i = ImageOps.exif_transpose(i)
         image = i.convert("RGB")
@@ -129,15 +159,22 @@ class SDPromptReader:
                 raise ValueError(MESSAGE["format_error"][1])
 
             seed = int(
-                self.param_parser(image_data.parameter.get("seed"), parameter_index)
+                self.param_parser(image_data.parameter.get("seed", 0), parameter_index)
                 or 0
             )
             steps = int(
-                self.param_parser(image_data.parameter.get("steps"), parameter_index)
+                self.param_parser(image_data.parameter.get("steps", 0), parameter_index)
                 or 0
             )
             cfg = float(
-                self.param_parser(image_data.parameter.get("cfg"), parameter_index) or 0
+                self.param_parser(image_data.parameter.get("cfg", 0), parameter_index)
+                or 0
+            )
+            model = str(
+                self.param_parser(
+                    image_data.parameter.get("model", ""), parameter_index
+                )
+                or ""
             )
             width = int(image_data.width or 0)
             height = int(image_data.height or 0)
@@ -145,6 +182,9 @@ class SDPromptReader:
             output_to_terminal("Positive: \n" + image_data.positive)
             output_to_terminal("Negative: \n" + image_data.negative)
             output_to_terminal("Setting: \n" + image_data.setting)
+
+            model = self.search_model(model)
+
         return {
             "ui": {
                 "text": (image_data.positive, image_data.negative, image_data.setting)
@@ -159,6 +199,7 @@ class SDPromptReader:
                 cfg,
                 width,
                 height,
+                model,
                 file_path.stem,
                 image_data.setting,
             ),
@@ -166,24 +207,54 @@ class SDPromptReader:
 
     @staticmethod
     def param_parser(data: str, index: int):
-        data_list = data.strip("()").split(",")
-        return data_list[0] if len(data_list) == 1 else data_list[index]
+        try:
+            data_list = data.strip("()").split(",")
+        except AttributeError:
+            return None
+        else:
+            return data_list[0] if len(data_list) == 1 else data_list[index]
+
+    @staticmethod
+    def search_model(model: str):
+        if not model or model in SDPromptReader.ckpt_paths:
+            return model
+
+        model_path = Path(model)
+        model_name = model_path.name
+        model_stem = model_path.stem
+
+        if model_name in SDPromptReader.ckpt_names:
+            return SDPromptReader.ckpt_paths[
+                SDPromptReader.ckpt_names.index(model_name)
+            ]
+
+        if model_stem in SDPromptReader.ckpt_stems:
+            return SDPromptReader.ckpt_paths[
+                SDPromptReader.ckpt_stems.index(model_stem)
+            ]
+
+        return model
 
     @classmethod
     def IS_CHANGED(s, image, parameter_index):
-        image_path = folder_paths.get_annotated_filepath(image)
+        if image in SDPromptReader.files:
+            image_path = folder_paths.get_annotated_filepath(image)
+        else:
+            image_path = image
         with open(Path(image_path), "rb") as f:
             image_data = ImageDataReader(f)
         return image_data.props
 
-    @classmethod
-    def VALIDATE_INPUTS(s, image, parameter_index):
-        if not folder_paths.exists_annotated_filepath(image):
-            return "Invalid image file: {}".format(image)
-        return True
-
 
 class SDPromptSaver:
+    model_hash_dict = {}
+    vae_hash_dict = {}
+    lora_hash_dict = {}
+    ti_hash_dict = {}
+    ti_paths = []
+    ti_names = []
+    ti_stems = []
+
     def __init__(self):
         self.output_dir = folder_paths.get_output_directory()
         self.type = "output"
@@ -191,6 +262,10 @@ class SDPromptSaver:
 
     @classmethod
     def INPUT_TYPES(s):
+        for file in folder_paths.get_filename_list("embeddings"):
+            SDPromptSaver.ti_paths.append(file)
+            SDPromptSaver.ti_names.append(Path(file).name)
+            SDPromptSaver.ti_stems.append(Path(file).stem)
         return {
             "required": {
                 "images": ("IMAGE",),
@@ -203,6 +278,7 @@ class SDPromptSaver:
                 "path": ("STRING", {"default": "%date/", "multiline": False}),
                 "model_name": (folder_paths.get_filename_list("checkpoints"),),
                 # "model_name_str": ("STRING", {"default": ""}),
+                "vae_name": (folder_paths.get_filename_list("vae"),),
                 "seed": (
                     "INT",
                     {
@@ -229,6 +305,7 @@ class SDPromptSaver:
                 # "sampler_name_str": ("STRING", {"default": ""}),
                 "scheduler": (comfy.samplers.KSampler.SCHEDULERS,),
                 # "scheduler_str": ("STRING", {"default": ""}),
+                "lora_name": any_type,
                 "width": (
                     "INT",
                     {"default": 1, "min": 1, "max": MAX_RESOLUTION, "step": 8},
@@ -240,7 +317,8 @@ class SDPromptSaver:
                 "positive": ("STRING", {"default": "", "multiline": True}),
                 "negative": ("STRING", {"default": "", "multiline": True}),
                 "extension": (["png", "jpg", "webp"],),
-                "calculate_model_hash": ("BOOLEAN", {"default": False}),
+                "calculate_hash": ("BOOLEAN", {"default": True}),
+                "resource_hash": ("BOOLEAN", {"default": True}),
                 "lossless_webp": ("BOOLEAN", {"default": True}),
                 "jpg_webp_quality": ("INT", {"default": 100, "min": 1, "max": 100}),
                 "date_format": (
@@ -251,12 +329,14 @@ class SDPromptSaver:
                     "STRING",
                     {"default": "%H%M%S", "multiline": False},
                 ),
+                "save_metadata_file": ("BOOLEAN", {"default": False}),
                 "extra_info": ("STRING", {"default": "", "multiline": True}),
             },
             "hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
         }
 
-    RETURN_TYPES = ()
+    RETURN_TYPES = ("STRING", "STRING", "STRING")
+    RETURN_NAMES = ("FILENAME", "FILE_PATH", "METADATA")
     FUNCTION = "save_images"
 
     OUTPUT_NODE = True
@@ -270,6 +350,7 @@ class SDPromptSaver:
         path: str = "%date/",
         model_name: str = "",
         model_name_str: str = "",
+        vae_name: str = "",
         seed: int = 0,
         steps: int = 0,
         cfg: float = 0.0,
@@ -277,16 +358,19 @@ class SDPromptSaver:
         sampler_name_str: str = "",
         scheduler: str = "",
         scheduler_str: str = "",
+        lora_name=None,
         width: int = 1,
         height: int = 1,
         positive: str = "",
         negative: str = "",
         extension: str = "png",
-        calculate_model_hash: bool = False,
+        calculate_hash: bool = True,
+        resource_hash: bool = True,
         lossless_webp: bool = True,
         jpg_webp_quality: int = 100,
         date_format: str = "%Y-%m-%d",
         time_format: str = "%H%M%S",
+        save_metadata_file: bool = False,
         extra_info: str = "",
         prompt=None,
         extra_pnginfo=None,
@@ -304,7 +388,10 @@ class SDPromptSaver:
             images[0].shape[0],
         )
 
-        results = list()
+        results = []
+        files = []
+        comments = []
+        file_paths = []
         for image in images:
             # model_name_str, sampler_name_str, scheduler_str = None, None, None
 
@@ -336,11 +423,68 @@ class SDPromptSaver:
             i = 255.0 * image.cpu().numpy()
             img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8))
             metadata = None
-            model_hash = (
-                f"Model hash: {self.calculate_model_hash(model_name_real)}, "
-                if calculate_model_hash
-                else ""
+
+            model_hash_str = ""
+            vae_hash_str = ""
+            vae_str = ""
+            lora_hash_dict = {}
+            lora_hash_str = ""
+            ti_hash_dict = {}
+            ti_hash_str = ""
+
+            if vae_name:
+                vae_str = f"VAE: {Path(vae_name).stem}, "
+
+            hashes = {}
+            if calculate_hash:
+                if model_name_real:
+                    model_hash = self.calculate_hash(model_name_real, "model")
+                    model_hash_str = f"Model hash: {model_hash}, "
+                    hashes["model"] = model_hash
+
+                if vae_name:
+                    vae_hash = self.calculate_hash(vae_name, "vae")
+                    vae_hash_str = f"VAE hash: {vae_hash}, "
+                    hashes["vae"] = vae_hash
+
+                if lora_name:
+                    lora_names = (
+                        lora_name if isinstance(lora_name, list) else [lora_name]
+                    )
+                    lora_names_unique = list(set(lora_names))
+                    for name in lora_names_unique:
+                        lora_hash = self.calculate_hash(name, "lora")
+                        lora_hash_dict[Path(name).stem] = lora_hash
+                        hashes[f"lora:{Path(name).stem}"] = lora_hash
+                    lora_hash_items = [f"{k}: {v}" for k, v in lora_hash_dict.items()]
+                    lora_hash_str_value = ", ".join(lora_hash_items)
+                    lora_hash_str = f'Lora hashes: "{lora_hash_str_value}", '
+
+                ti_pattern = (
+                    r"(?:\(|\s|,)?"  # match an optional opening parenthesis, space, or comma
+                    r"embedding:"  # match the literal text "embedding:"
+                    r"([^\s:,()]+)"  # match a string that does not contain spaces, colons, commas, or parentheses
+                    r"(?:\.(?:pt|safetensors))?"  # optionally match a file extension ".pt" or ".safetensors"
+                    r"(?::\d+(?:\.\d+)?)?"  # optionally match a colon followed by numbers,
+                    # with an optional decimal part (e.g., ":1" or ":1.0")
+                    r"(?:\)|,|\s)?"  # optionally match a closing parenthesis, comma, or space
+                )
+                ti_names = re.findall(ti_pattern, f"{positive}/n{negative}")
+                ti_names_with_ext = [self.search_ti(name) for name in ti_names]
+
+                for name in ti_names_with_ext:
+                    if name:
+                        ti_hash = self.calculate_hash(name, "ti")
+                        ti_hash_dict[Path(name).stem] = ti_hash
+                        hashes[f"embed:{Path(name).stem}"] = ti_hash
+                ti_hash_items = [f"{k}: {v}" for k, v in ti_hash_dict.items()]
+                ti_hash_str_value = ", ".join(ti_hash_items)
+                ti_hash_str = f'TI hashes: "{ti_hash_str_value}", '
+
+            hashes_str = (
+                f", Hashes: {json.dumps(hashes)}" if (hashes and resource_hash) else ""
             )
+
             comment = (
                 f"{positive}\n"
                 f"Negative prompt: {negative}\n"
@@ -349,14 +493,20 @@ class SDPromptSaver:
                 f"CFG scale: {cfg}, "
                 f"Seed: {seed}, "
                 f"Size: {img.width if width==0 else width}x{img.height if height==0 else height}, "
-                f"{model_hash}"
+                f"{model_hash_str}"
                 f"Model: {Path(model_name_real).stem}, "
+                f"{vae_hash_str}"
+                f"{vae_str}"
+                f"{lora_hash_str}"
+                f"{ti_hash_str}"
                 f"Version: ComfyUI"
+                f"{hashes_str}"
                 f"{extra_info_real}"
             )
 
             stem = self.get_path(filename, variable_map)
             file = self.get_unique_filename(stem, extension, output_folder)
+            file_path = output_folder / file
 
             if extension == "png":
                 if not args.disable_metadata:
@@ -368,13 +518,13 @@ class SDPromptSaver:
                         for x in extra_pnginfo:
                             metadata.add_text(x, json.dumps(extra_pnginfo[x]))
                 img.save(
-                    output_folder / file,
+                    file_path,
                     pnginfo=metadata,
                     compress_level=4,
                 )
             else:
                 img.save(
-                    output_folder / file,
+                    file_path,
                     quality=jpg_webp_quality,
                     lossless=lossless_webp,
                 )
@@ -388,24 +538,54 @@ class SDPromptSaver:
                             },
                         }
                     )
-                    piexif.insert(metadata, str(output_folder / file))
+                    piexif.insert(metadata, str(file_path))
+
+            if save_metadata_file:
+                with open(file_path.with_suffix(".txt"), "w", encoding="utf-8") as f:
+                    f.write(comment)
+
             results.append(
                 {"filename": file.name, "subfolder": str(subfolder), "type": self.type}
             )
+            files.append(str(file))
+            file_paths.append(str(file_path))
+            output_to_terminal("Saved file: " + str(file))
+            comments.append(comment)
 
-        return {"ui": {"images": results}}
+        return {"ui": {"images": results}, "result": (files, file_paths, comments)}
 
     @staticmethod
-    def calculate_model_hash(model_name):
+    def calculate_hash(name, hash_type):
+        match hash_type:
+            case "model":
+                hash_dict = SDPromptSaver.model_hash_dict
+                file_name = folder_paths.get_full_path("checkpoints", name)
+            case "vae":
+                hash_dict = SDPromptSaver.vae_hash_dict
+                file_name = folder_paths.get_full_path("vae", name)
+            case "lora":
+                hash_dict = SDPromptSaver.lora_hash_dict
+                file_name = folder_paths.get_full_path("loras", name)
+            case "ti":
+                hash_dict = SDPromptSaver.ti_hash_dict
+                file_name = folder_paths.get_full_path("embeddings", name)
+            case _:
+                return ""
+
+        if hash_value := hash_dict.get(name):
+            return hash_value
+
         hash_sha256 = hashlib.sha256()
         blksize = 1024 * 1024
-        file_name = folder_paths.get_full_path("checkpoints", model_name)
 
         with open(file_name, "rb") as f:
             for chunk in iter(lambda: f.read(blksize), b""):
                 hash_sha256.update(chunk)
 
-        return hash_sha256.hexdigest()[:10]
+        hash_value = hash_sha256.hexdigest()[:10]
+        hash_dict[name] = hash_value
+
+        return hash_value
 
     @staticmethod
     def get_counter(directory: Path):
@@ -441,6 +621,19 @@ class SDPromptSaver:
 
         return file
 
+    @staticmethod
+    def search_ti(ti: str):
+        if not ti or ti in SDPromptSaver.ti_paths:
+            return ti
+
+        if ti in SDPromptSaver.ti_stems:
+            return SDPromptSaver.ti_paths[SDPromptSaver.ti_stems.index(ti)]
+
+        if ti in SDPromptSaver.ti_names:
+            return SDPromptSaver.ti_paths[SDPromptSaver.ti_names.index(ti)]
+
+        return ""
+
 
 class SDParameterGenerator:
     ASPECT_RATIO_MAP = {
@@ -461,13 +654,35 @@ class SDParameterGenerator:
         "SDXL 1024px": 2.0,
     }
 
+    DEFAULT_ASPECT_RATIO_DISPLAY = list(
+        map(
+            lambda x, scaling_factor=MODEL_SCALING_FACTOR: (
+                f"{x[0]} - "
+                f"{int(x[1][0]*scaling_factor['SDv1 512px'])}x"
+                f"{int(x[1][1]*scaling_factor['SDv1 512px'])} | "
+                f"{int(x[1][0]*scaling_factor['SDv2 768px'])}x"
+                f"{int(x[1][1]*scaling_factor['SDv2 768px'])} | "
+                f"{int(x[1][0]*scaling_factor['SDXL 1024px'])}x"
+                f"{int(x[1][1]*scaling_factor['SDXL 1024px'])}"
+            ),
+            ASPECT_RATIO_MAP.items(),
+        )
+    )
+
+    ckpt_list = []
+
     @classmethod
     def INPUT_TYPES(s):
+        SDParameterGenerator.ckpt_list = folder_paths.get_filename_list("checkpoints")
         return {
             "required": {
-                "ckpt_name": (folder_paths.get_filename_list("checkpoints"),),
+                "ckpt_name": (SDParameterGenerator.ckpt_list,),
             },
             "optional": {
+                "vae_name": (
+                    ["baked VAE"] + folder_paths.get_filename_list("vae"),
+                    {"default": "baked VAE"},
+                ),
                 "model_version": (
                     list(SDParameterGenerator.MODEL_SCALING_FACTOR.keys()),
                     {"default": "SDv1 512px"},
@@ -506,7 +721,7 @@ class SDParameterGenerator:
                     {"default": 6.0, "min": 0.0, "max": 1000.0, "step": 0.01},
                 ),
                 "aspect_ratio": (
-                    ["custom"] + list(SDParameterGenerator.ASPECT_RATIO_MAP.keys()),
+                    ["custom"] + SDParameterGenerator.DEFAULT_ASPECT_RATIO_DISPLAY,
                     {"default": "custom"},
                 ),
                 "width": (
@@ -530,6 +745,7 @@ class SDParameterGenerator:
 
     RETURN_TYPES = (
         folder_paths.get_filename_list("checkpoints"),
+        folder_paths.get_filename_list("vae"),
         "MODEL",
         "CLIP",
         "VAE",
@@ -549,6 +765,7 @@ class SDParameterGenerator:
 
     RETURN_NAMES = (
         "MODEL_NAME",
+        "VAE_NAME",
         "MODEL",
         "CLIP",
         "VAE",
@@ -571,8 +788,9 @@ class SDParameterGenerator:
 
     def generate_parameter(
         self,
-        model_version,
         ckpt_name,
+        vae_name,
+        model_version,
         config_name,
         seed,
         steps,
@@ -589,6 +807,9 @@ class SDParameterGenerator:
         output_vae=True,
         output_clip=True,
     ):
+        if ckpt_name not in SDParameterGenerator.ckpt_list:
+            raise FileNotFoundError(f"Invalid ckpt_name: {ckpt_name}")
+
         ckpt_path = folder_paths.get_full_path("checkpoints", ckpt_name)
         if config_name != "none":
             config_path = folder_paths.get_full_path("configs", config_name)
@@ -607,26 +828,48 @@ class SDParameterGenerator:
                 embedding_directory=folder_paths.get_folder_paths("embeddings"),
             )[:3]
 
+        if vae_name != "baked VAE":
+            vae_name_real = vae_name
+            vae_path = folder_paths.get_full_path("vae", vae_name)
+            sd = comfy.utils.load_torch_file(vae_path)
+            vae = comfy.sd.VAE(sd=sd)
+            checkpoint = (*checkpoint[:2], vae)
+            vae_str = f"VAE: {vae_name}, \n"
+        else:
+            vae_str = ""
+            vae_name_real = ""
+
         if aspect_ratio != "custom":
+            aspect_ratio_value = aspect_ratio.split(" - ")[0]
             width = int(
-                SDParameterGenerator.ASPECT_RATIO_MAP[aspect_ratio][0]
+                SDParameterGenerator.ASPECT_RATIO_MAP[aspect_ratio_value][0]
                 * SDParameterGenerator.MODEL_SCALING_FACTOR[model_version]
             )
             height = int(
-                SDParameterGenerator.ASPECT_RATIO_MAP[aspect_ratio][1]
+                SDParameterGenerator.ASPECT_RATIO_MAP[aspect_ratio_value][1]
                 * SDParameterGenerator.MODEL_SCALING_FACTOR[model_version]
             )
 
         base_steps = int(steps * refiner_start)
         refiner_steps = steps - base_steps
 
+        if model_version == "SDXL 1024px":
+            ascore = (
+                f"Positive aesthetic score: {positive_ascore},\n"
+                f"Negative aesthetic score: {negative_ascore},\n"
+            )
+        else:
+            ascore = ""
+
         parameters = (
             f"Model: {ckpt_name},\n"
+            f"{vae_str}"
             f"Seed: {str(seed)},\n"
             f"Steps: {str(steps)},\n"
             f"CFG scale: {str(cfg)},\n"
             f"Sampler: {sampler_name},\n"
             f"Scheduler: {scheduler},\n"
+            f"{ascore}"
             f"Size: {str(width)}x{str(height)},\n"
             f"Batch size: {str(batch_size)}\n"
         )
@@ -634,7 +877,7 @@ class SDParameterGenerator:
         return {
             "ui": {
                 "text": (
-                    aspect_ratio,
+                    aspect_ratio.split(" - ")[0],
                     model_version,
                     width,
                     height,
@@ -642,10 +885,15 @@ class SDParameterGenerator:
                     refiner_start,
                     base_steps,
                     refiner_steps,
+                    SDParameterGenerator.ASPECT_RATIO_MAP,
+                    SDParameterGenerator.MODEL_SCALING_FACTOR,
                 )
             },
             "result": (
-                (ckpt_name,)
+                (
+                    ckpt_name,
+                    vae_name_real,
+                )
                 + checkpoint
                 + (
                     seed,
@@ -669,7 +917,8 @@ class SDPromptMerger:
     @classmethod
     def INPUT_TYPES(s):
         return {
-            "required": {
+            "required": {},
+            "optional": {
                 "text_g": (
                     "STRING",
                     {"default": "", "multiline": True, "forceInput": True},
@@ -685,10 +934,8 @@ class SDPromptMerger:
     FUNCTION = "merge_prompt"
     CATEGORY = "SD Prompt Reader"
 
-    def merge_prompt(self, text_g, text_l):
-        if text_l == "":
-            return text_g
-        return (text_g + "\n" + text_l,)
+    def merge_prompt(self, text_g="", text_l=""):
+        return (text_g + ("\n" + text_l if text_g and text_l else text_l),)
 
 
 class SDTypeConverter:
@@ -734,12 +981,272 @@ class SDTypeConverter:
         )
 
 
+class SDBatchLoader:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "path": ("STRING", {"default": "./input/"}),
+            },
+            "optional": {
+                "image_load_limit": ("INT", {"default": 0, "min": 0, "step": 1}),
+                "start_index": ("INT", {"default": 0, "min": 0, "step": 1}),
+            },
+        }
+
+    RETURN_TYPES = (any_type,)
+
+    RETURN_NAMES = ("IMAGE",)
+    OUTPUT_IS_LIST = (True,)
+    OUTPUT_NODE = True
+    FUNCTION = "load_path"
+    CATEGORY = "SD Prompt Reader"
+
+    def load_path(
+        self,
+        path: str = "./input/",
+        image_load_limit: int = 0,
+        start_index: int = 0,
+    ):
+        if isinstance(path, list):
+            files_str = [str(Path(p)) for p in path if Path(p).exists()]
+            return {
+                "ui": {
+                    "text": ("\n".join(files_str),),
+                },
+                "result": (files_str,),
+            }
+        elif Path(path).is_file():
+            return {
+                "ui": {
+                    "text": (str(Path(path)),),
+                },
+                "result": ([str(Path(path))],),
+            }
+        elif not Path(path).is_dir():
+            raise FileNotFoundError(f"Invalid directory: {path}")
+
+        files = list(
+            filter(lambda file: file.suffix in SUPPORTED_FORMATS, Path(path).iterdir())
+        )
+
+        files = (
+            sorted(files)[start_index : start_index + image_load_limit]
+            if image_load_limit > 0
+            else sorted(files)[start_index:]
+        )
+
+        files_str = list(map(str, files))
+        return {
+            "ui": {
+                "text": ("\n".join(files_str),),
+            },
+            "result": (files_str,),
+        }
+
+    @classmethod
+    def IS_CHANGED(
+        s,
+        path,
+        image_load_limit,
+        start_index,
+    ):
+        return os.listdir(path)
+
+
+class SDParameterExtractor:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "settings": (
+                    "STRING",
+                    {"default": "", "multiline": True, "forceInput": True},
+                )
+            },
+            "optional": {
+                "parameter": (
+                    ["parameters not loaded"],
+                    {"default": "parameters not loaded"},
+                ),
+                "value_type": (["STRING", "INT", "FLOAT"], {"default": "STRING"}),
+                "parameter_index": (
+                    "INT",
+                    {"default": 0, "min": 0, "max": 255, "step": 1},
+                ),
+            },
+        }
+
+    RETURN_TYPES = (any_type,)
+    RETURN_NAMES = ("VALUE",)
+    OUTPUT_NODE = True
+    FUNCTION = "extract_param"
+    CATEGORY = "SD Prompt Reader"
+
+    def extract_param(
+        self,
+        settings: str = "",
+        parameter: str = "",
+        value_type: str = "STRING",
+        parameter_index: int = 0,
+    ):
+        setting_dict = self.parse_setting(settings)
+        if not settings or not parameter or parameter == "parameters not loaded":
+            return {
+                "ui": {
+                    "text": (list(setting_dict.keys()), ""),
+                },
+                "result": ("",),
+            }
+
+        result = setting_dict.get(parameter)
+
+        try:
+            if isinstance(result, tuple):
+                result = result[parameter_index]
+            if value_type == "INT":
+                result = int(result)
+            elif value_type == "FLOAT":
+                result = float(result)
+        except IndexError:
+            return {
+                "ui": {
+                    "text": (list(setting_dict.keys()), "Parameter index out of range"),
+                },
+                "result": ("",),
+            }
+        except (ValueError, TypeError):
+            return {
+                "ui": {
+                    "text": (
+                        list(setting_dict.keys()),
+                        f"{parameter}: {result}\n"
+                        f"{result} is not a valid number; it will be output as STRING",
+                    ),
+                },
+                "result": (result,),
+            }
+        return {
+            "ui": {
+                "text": (list(setting_dict.keys()), f"{parameter}: {result}"),
+            },
+            "result": (result,),
+        }
+
+    @staticmethod
+    def parse_setting(settings):
+        pattern = re.compile(r"([^:,]+):\s*\(([^)]+)\)|([^:,]+):\s*([^,]+)")
+
+        matches = pattern.findall(settings)
+
+        result = {}
+        for match in matches:
+            key, value_paren, key_nonparen, value_nonparen = match
+            if key:
+                key = key.strip()
+                value = value_paren.strip()
+                value = tuple(v.strip() for v in value.split(","))
+            else:
+                key = key_nonparen.strip()
+                value = value_nonparen.strip()
+            result[key] = value
+
+        return result
+
+
+class SDLoraLoader:
+    def __init__(self):
+        self.loaded_lora = None
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "model": ("MODEL",),
+                "clip": ("CLIP",),
+                "lora_name": (folder_paths.get_filename_list("loras"),),
+                "strength_model": (
+                    "FLOAT",
+                    {"default": 1.0, "min": -20.0, "max": 20.0, "step": 0.01},
+                ),
+                "strength_clip": (
+                    "FLOAT",
+                    {"default": 1.0, "min": -20.0, "max": 20.0, "step": 0.01},
+                ),
+            },
+            "optional": {
+                "last_lora": (any_type,),
+            },
+        }
+
+    RETURN_TYPES = ("MODEL", "CLIP", any_type)
+    RETURN_NAMES = ("MODEL", "CLIP", "NEXT_LORA")
+    FUNCTION = "load_lora"
+
+    CATEGORY = "SD Prompt Reader"
+
+    def load_lora(
+        self, model, clip, lora_name, strength_model, strength_clip, last_lora=None
+    ):
+        if strength_model == 0 and strength_clip == 0:
+            return (model, clip, lora_name)
+
+        lora_path = folder_paths.get_full_path("loras", lora_name)
+        lora = None
+        if self.loaded_lora is not None:
+            if self.loaded_lora[0] == lora_path:
+                lora = self.loaded_lora[1]
+            else:
+                temp = self.loaded_lora
+                self.loaded_lora = None
+                del temp
+
+        if lora is None:
+            lora = comfy.utils.load_torch_file(lora_path, safe_load=True)
+            self.loaded_lora = (lora_path, lora)
+
+        model_lora, clip_lora = comfy.sd.load_lora_for_models(
+            model, clip, lora, strength_model, strength_clip
+        )
+
+        next_lora = last_lora + [lora_name] if last_lora else [lora_name]
+
+        return (model_lora, clip_lora, next_lora)
+
+
+class SDLoraSelector:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "lora_name": (folder_paths.get_filename_list("loras"),),
+            },
+            "optional": {
+                "last_lora": (any_type,),
+            },
+        }
+
+    RETURN_TYPES = (folder_paths.get_filename_list("loras"), any_type)
+    RETURN_NAMES = ("LORA_NAME", "NEXT_LORA")
+    FUNCTION = "get_name"
+
+    CATEGORY = "SD Prompt Reader"
+
+    def get_name(self, lora_name, last_lora=None):
+        next_lora = last_lora + [lora_name] if last_lora else [lora_name]
+        return (lora_name, next_lora)
+
+
 NODE_CLASS_MAPPINGS = {
     "SDPromptReader": SDPromptReader,
     "SDPromptSaver": SDPromptSaver,
     "SDParameterGenerator": SDParameterGenerator,
     "SDPromptMerger": SDPromptMerger,
     "SDTypeConverter": SDTypeConverter,
+    "SDBatchLoader": SDBatchLoader,
+    "SDParameterExtractor": SDParameterExtractor,
+    "SDLoraLoader": SDLoraLoader,
+    "SDLoraSelector": SDLoraSelector,
 }
 
 NODE_DISPLAY_NAME_MAPPINGS = {
@@ -748,4 +1255,8 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "SDParameterGenerator": "SD Parameter Generator",
     "SDPromptMerger": "SD Prompt Merger",
     "SDTypeConverter": "SD Type Converter",
+    "SDBatchLoader": "SD Batch Loader",
+    "SDParameterExtractor": "SD Parameter Extractor",
+    "SDLoraLoader": "SD Lora Loader",
+    "SDLoraSelector": "SD Lora Selector",
 }