Adding support to inline prompt references

modules/async_worker.py

@@ -39,8 +39,17 @@ def worker():
     from modules.sdxl_styles import apply_style, apply_wildcards, fooocus_expansion
     from modules.private_logger import log
     from extras.expansion import safe_str
-    from modules.util import remove_empty_str, HWC3, resize_image, \
+    from modules.util import (
-        get_image_shape_ceil, set_image_shape_ceil, get_shape_ceil, resample_image, erode_or_dilate, ordinal_suffix
+        remove_empty_str, 
+        HWC3, resize_image, 
+        get_image_shape_ceil, 
+        set_image_shape_ceil, 
+        get_shape_ceil, 
+        resample_image, 
+        erode_or_dilate, 
+        ordinal_suffix, 
+        parse_lora_references_from_prompt
+    )
     from modules.upscaler import perform_upscale
 
     try:
@@ -370,6 +379,10 @@ def worker():
             extra_negative_prompts = negative_prompts[1:] if len(negative_prompts) > 1 else []
 
             progressbar(async_task, 3, 'Loading models ...')
+
+            # Parse lora references from prompt
+            loras = parse_lora_references_from_prompt(prompt, loras)
+
             pipeline.refresh_everything(refiner_model_name=refiner_model_name, base_model_name=base_model_name,
                                         loras=loras, base_model_additional_loras=base_model_additional_loras,
                                         use_synthetic_refiner=use_synthetic_refiner)

modules/util.py

@@ -4,6 +4,8 @@ import random
 import math
 import os
 import cv2
+import re
+from typing import List, Tuple, AnyStr
 
 from PIL import Image
 
@@ -179,3 +181,23 @@ def get_files_from_folder(folder_path, exensions=None, name_filter=None):
 
 def ordinal_suffix(number: int) -> str:
     return 'th' if 10 <= number % 100 <= 20 else {1: 'st', 2: 'nd', 3: 'rd'}.get(number % 10, 'th')
+
+
+def parse_lora_references_from_prompt(items: str, loras: List[Tuple[AnyStr, float]]):
+    pattern = re.compile(".*<lora:(.+):(([0-9]*[.])?[0-9]+)>.*")
+    new_loras = []
+
+    for token in items.split(","):
+        print(token)
+        m = pattern.match(token)
+
+        if m:
+            new_loras.append((f"{m.group(1)}.safetensors", float(m.group(2))))
+
+    updated_loras = []
+    for lora in loras + new_loras:
+
+        if lora[0] != "None":
+            updated_loras.append(lora)
+
+    return updated_loras