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

Bump version to 1.3.0
Update README.md
2024-01-22 03:08:59 +08:00 · 2024-01-22 03:08:20 +08:00 · 2024-01-22 03:07:45 +08:00 · 2024-01-20 21:01:05 +08:00 · 2024-01-17 21:19:09 +08:00 · 2024-01-17 06:28:20 +08:00
33 changed files with 6905 additions and 799 deletions
@@ -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
@@ -153,3 +153,4 @@ dmypy.json
 cython_debug/

 .idea/
+preview/
@@ -1,4 +1,39 @@
 # 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
@@ -23,7 +23,7 @@ additional metadata to ensure compatibility with metadata detection on websites
    <a href="./CHANGELOG.md">Change Log</a> •
    <a href="#credits">Credits</a>
  </p>
-    <img src="./images/screenshot_v110.png">
+    <img src="./images/screenshot_v130.png">
 </div>


@@ -66,6 +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 
@@ -74,100 +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
- For batch processing, please use the `Batch Loader` node.
-
+#### 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.  
- 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 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`.
-
-   | 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`.
- 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`.
- For the `date_format` and `time_format`, please refer to 
-[strftime.org](https://strftime.org/) or [www.strfti.me](https://www.strfti.me/).
-
 <div align="center">
   <img src="./images/saver.png" width="25%" height="25%" alt="saver node">
 </div>

-## Parameter Generator Node
- 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`.
- 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 
-[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` 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.
+- 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'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's necessary to 
+use the `Parameter Generator` Node to generate parameters and simultaneously output them to 
+the `Prompt Saver` Node and `KSampler` Node.

+<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/generator.png" width="25%" height="25%" alt="generator node">
 </div>

-### Batch Loader Node
- 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.
- For batch processing, please connect the `IMAGE` output of the `Batch Loader` node to the `image` input of 
-the `Prompt Reader` node.
- The `path` supports relative paths such as `./input/` or absolute paths like `C:/Users/receyuki/Pictures`.
- Both `\ ` and `/` are acceptable.
+- 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` 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/).
+<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/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](https://raw.githubusercontent.com/receyuki/comfyui-prompt-reader-node/main/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)
@@ -6,19 +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",
-    "loaderDisplay.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)
@@ -1 +1 @@
-VERSION = "1.1.0"
+VERSION = "1.3.0"
@@ -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]
+                }
+            };
+        }
+    },
+});
@@ -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 file list on the node
 app.registerExtension({
@@ -20,7 +13,8 @@ app.registerExtension({
                const result = onNodeCreated?.apply(this, arguments);

                // Create prompt and setting widgets
-                const fileList = createWidget(app, this, "fileList");
+                const styles = {opacity: 0.7}
+                const fileList =createTextWidget(app, this, "fileList", styles);
                return result;
            };

@@ -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];
@@ -66,10 +59,11 @@ Refiner start at step: ${message.text[6]} (${base_percentage})`;
                    return `${ratio} - ${width*scalingFactor}x${height*scalingFactor}`;
                });
                aspectRatioArray.unshift("custom")
-
-                const aspectRatio = `${message.text[0]} - ${message.text[8][message.text[0]][0]*scalingFactor}x${message.text[8][message.text[0]][1]*scalingFactor}`
+                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
-                this.widgets.find(obj => obj.name === "aspect_ratio").value = aspectRatio
            };
        }
    },
@@ -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];
@@ -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;
            };
        }
    },
@@ -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;
+}
@@ -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
@@ -65,9 +66,17 @@ 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()
        SDPromptReader.files = sorted(
            [
@@ -150,18 +159,21 @@ 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)
+                self.param_parser(
+                    image_data.parameter.get("model", ""), parameter_index
+                )
                or ""
            )
            width = int(image_data.width or 0)
@@ -170,6 +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)
@@ -192,24 +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"
@@ -217,6 +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",),
@@ -229,6 +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",
                    {
@@ -255,6 +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},
@@ -266,7 +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": (
@@ -277,13 +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 = ("STRING", "STRING")
-    RETURN_NAMES = ("FILENAME", "METADATA")
+    RETURN_TYPES = ("STRING", "STRING", "STRING")
+    RETURN_NAMES = ("FILENAME", "FILE_PATH", "METADATA")
    FUNCTION = "save_images"

    OUTPUT_NODE = True
@@ -297,6 +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,
@@ -304,16 +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,
@@ -334,6 +391,7 @@ class SDPromptSaver:
        results = []
        files = []
        comments = []
+        file_paths = []
        for image in images:
            # model_name_str, sampler_name_str, scheduler_str = None, None, None

@@ -365,11 +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"
@@ -378,14 +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:
@@ -397,13 +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,
                )
@@ -417,27 +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}, "result": (files, comments)}
+        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):
@@ -473,6 +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 = {
@@ -584,6 +745,7 @@ class SDParameterGenerator:

    RETURN_TYPES = (
        folder_paths.get_filename_list("checkpoints"),
+        folder_paths.get_filename_list("vae"),
        "MODEL",
        "CLIP",
        "VAE",
@@ -603,6 +765,7 @@ class SDParameterGenerator:

    RETURN_NAMES = (
        "MODEL_NAME",
+        "VAE_NAME",
        "MODEL",
        "CLIP",
        "VAE",
@@ -666,10 +829,15 @@ class SDParameterGenerator:
            )[: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]
@@ -695,6 +863,7 @@ class SDParameterGenerator:

        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"
@@ -721,7 +890,10 @@ class SDParameterGenerator:
                )
            },
            "result": (
-                (ckpt_name,)
+                (
+                    ckpt_name,
+                    vae_name_real,
+                )
                + checkpoint
                + (
                    seed,
@@ -745,7 +917,8 @@ class SDPromptMerger:
    @classmethod
    def INPUT_TYPES(s):
        return {
-            "required": {
+            "required": {},
+            "optional": {
                "text_g": (
                    "STRING",
                    {"default": "", "multiline": True, "forceInput": True},
@@ -761,10 +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:
@@ -827,6 +998,7 @@ class SDBatchLoader:

    RETURN_NAMES = ("IMAGE",)
    OUTPUT_IS_LIST = (True,)
+    OUTPUT_NODE = True
    FUNCTION = "load_path"
    CATEGORY = "SD Prompt Reader"

@@ -836,7 +1008,22 @@ class SDBatchLoader:
        image_load_limit: int = 0,
        start_index: int = 0,
    ):
-        if not Path(path).is_dir():
+        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(
@@ -866,16 +1053,188 @@ class SDBatchLoader:
    ):
        return os.listdir(path)

+
+class SDParameterExtractor:
    @classmethod
-    def VALIDATE_INPUTS(
-        s,
-        path,
-        image_load_limit,
-        start_index,
+    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,
    ):
-        if not Path(path).is_dir():
-            return f"Invalid directory: {path}"
-        return True
+        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 = {
@@ -885,6 +1244,9 @@ NODE_CLASS_MAPPINGS = {
    "SDPromptMerger": SDPromptMerger,
    "SDTypeConverter": SDTypeConverter,
    "SDBatchLoader": SDBatchLoader,
+    "SDParameterExtractor": SDParameterExtractor,
+    "SDLoraLoader": SDLoraLoader,
+    "SDLoraSelector": SDLoraSelector,
 }

 NODE_DISPLAY_NAME_MAPPINGS = {
@@ -894,4 +1256,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
    "SDPromptMerger": "SD Prompt Merger",
    "SDTypeConverter": "SD Type Converter",
    "SDBatchLoader": "SD Batch Loader",
+    "SDParameterExtractor": "SD Parameter Extractor",
+    "SDLoraLoader": "SD Lora Loader",
+    "SDLoraSelector": "SD Lora Selector",
 }
Author	SHA1	Message	Date
receyuki	d6f8598946	Merge remote-tracking branch 'origin/dev' into dev	2024-01-22 03:08:59 +08:00
receyuki	63919f44a4	Bump version to 1.3.0	2024-01-22 03:08:20 +08:00
receyuki	2321ce5ae4	Update README.md Update CHANGELOG.md Update example workflow	2024-01-22 03:07:45 +08:00
Rhys Yang	a8e217d9f1	Fix the error message caused by empty model_name	2024-01-20 21:01:05 +08:00
Rhys Yang	e32a514adc	Add support for embeddings auto-detection on Civitai	2024-01-17 21:19:09 +08:00
Rhys Yang	27bcc7273e	Fix the parsing error caused by the loss of model data #43	2024-01-17 06:28:20 +08:00
Rhys Yang	d1e6940491	Add `Lora Loader` node and `Lora Selector` node Add `lora_name` input to the `Prompt Saver` node Add `resource_hash` input to the `Prompt Saver` node Add support for auto-detection on Civitai #35	2024-01-17 03:36:02 +08:00
Rhys Yang	3457877e2c	Add WEB_DIRECTORY Remove old js directory	2024-01-16 02:19:33 +08:00
Rhys Yang	4d85411aee	Fix the error message caused by aspect_ratio	2024-01-16 02:15:01 +08:00
Rhys Yang	508bc56ca8	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 Update seedGen.js to rgthree's latest code	2024-01-16 02:12:26 +08:00
Rhys Yang	bdcc5c7461	Add `VAE_NAME` output to the `Parameter Generator` node and add `vae_name` input to the `Prompt Saver` node #39	2024-01-06 01:12:04 +08:00
Rhys Yang	f86625d71b	Add resources hashes to metadata for auto-detection on Civitai	2024-01-06 01:12:02 +08:00
Rhys Yang	cf4b85a0a0	Add temporary storage for model hash	2024-01-06 01:12:01 +08:00
Rhys Yang	5241cf50b9	Fix the input validation of the `Batch Loader` node #37 #38	2024-01-06 01:11:59 +08:00
Rhys Yang	6cd2b3414d	Update core to cc3c8b2	2024-01-06 01:09:40 +08:00
Rhys Yang	9194663f09	Update example workflow	2024-01-06 01:08:54 +08:00
receyuki	103a5c826a	Fix example workflow	2024-01-05 19:21:10 +08:00
Rhys Yang	cdd38cb3cd	Bump version to 1.2.1	2024-01-03 00:21:01 +08:00
Rhys Yang	8f3c760bad	Update CHANGELOG.md	2024-01-03 00:20:44 +08:00
Rhys Yang	7ab1628c2a	Code cleanup	2024-01-03 00:19:19 +08:00
Rhys Yang	c4630346e6	Fix the `Batch Loader` node not working when not connected to any node	2024-01-03 00:17:09 +08:00
Rhys Yang	202b1fdb06	Fix the input validation of the `Prompt Reader` node #37	2024-01-02 23:40:08 +08:00
receyuki	a7fd3f11bd	Bump version to 1.2.0	2023-12-11 22:46:30 +08:00
receyuki	50e0456eca	Update README.md	2023-12-11 22:43:05 +08:00
receyuki	b5572bba48	Fix `Parameter Extractor` node	2023-12-11 22:35:55 +08:00
receyuki	d44b01659e	Update core to 1.3.4.post1	2023-12-11 21:41:11 +08:00
Rhys Yang	97c6aa988d	Add `Parameter Extractor` node #24	2023-12-11 19:55:03 +08:00
Rhys Yang	52882ee594	Add a model search feature for the `Prompt Reader` node #24	2023-12-11 02:26:34 +08:00
Rhys Yang	a6107989fb	Add an option to the `Prompt Saver` node for saving metadata as a text file with the same name as the image #30	2023-12-11 01:04:40 +08:00
Rhys Yang	1a5850865f	Fix the issue where the `Prompt Merger` node threw an error when merging empty strings #29	2023-12-11 00:39:36 +08:00
Rhys Yang	6ce83b3828	Enhance the `Batch Loader` node to support processing either a single file or a list of files #26	2023-12-11 00:01:10 +08:00
Rhys Yang	e67c358e2d	Add `FILE_PATH` output to the `Prompt Saver` node #26	2023-12-10 23:52:18 +08:00
Rhys Yang	111bc489d5	Update BUG-REPORT.yml	2023-11-24 04:23:35 +08:00