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14 Commits
Author SHA1 Message Date
Dijkstra 2bd6769b78 fix: now can use the output lora_name as an input for override_lora_name 2024-04-09 18:11:46 +02:00
Dijkstra 96a69f7cbe feat: added lora name to output 2024-04-09 17:05:22 +02:00
dijkstra 9d8b79844f Merge pull request #13 from idrirap/issue12
fix: broken preview when using both enable preview and override_lora_name
2024-03-14 23:26:17 +01:00
Dijkstra f3815b7ce4 fix: broken preview when using both enable preview and override_lora_name 2024-03-14 23:23:35 +01:00
dijkstra d5641ba745 Merge pull request #11 from deipfei/json-error-change
don't delete loras_tags.json on JSONDecodeError
2024-03-08 21:21:03 +01:00
Dustin Pfeiffer 5b5eaf3a81 don't delete loras_tags.json on JSONDecodeError 2024-02-23 15:28:01 -08:00
dijkstra 517b8a8a12 Merge pull request #9 from idrirap/issue8
feat: added tags only node. Added node to load lora names as string. …
2023-12-12 18:58:03 +01:00
Dijkstra 0be7528f10 feat: added tags only node. Added node to load lora names as string. Added the ability to override lora name from dropdown menu. + fixed bad parameters for strenght_model 2023-12-12 18:51:00 +01:00
dijkstra b63862f2e3 Merge pull request #7 from idrirap/fix_civitai_initial_search
fix: tags were never pulled from civitai the first time they were req…
2023-11-20 18:12:13 +01:00
Dijkstra 8ed3d36eaf fix: tags were never pulled from civitai the first time they were requested 2023-11-20 18:11:23 +01:00
dijkstra 8af8cce210 Merge pull request #5 from idrirap/fix_cache_stacker
fix: bug where lora_stack input get stacked with the lora_stack output exponentially
2023-11-17 18:36:32 +01:00
Dijkstra d7530a3326 fix: bug where lora_stack input get stacked with the lora_stack output exponentially 2023-11-17 18:33:28 +01:00
Dijkstra 05de5959e1 Merge branch 'main' of github.com:idrirap/ComfyUI-Lora-Auto-Trigger-Words into main 2023-11-01 18:49:28 +01:00
dijkstra 049fd1eb71 Merge pull request #3 from idrirap/dev/fix_issue2
Dev/fix issue2
2023-11-01 18:45:53 +01:00
3 changed files with 118 additions and 43 deletions
+81 -28
View File
@@ -16,19 +16,24 @@ class LoraLoaderVanilla:
"model": ("MODEL",),
"clip": ("CLIP", ),
"lora_name": (LORA_LIST, ),
"strength_model": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 2.0, "step": 0.1}),
"strength_clip": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 2.0, "step": 0.1}),
"strength_model": ("FLOAT", {"default": 1.0, "min": -10.0, "max": 10.0, "step": 0.01}),
"strength_clip": ("FLOAT", {"default": 1.0, "min": -10.0, "max": 10.0, "step": 0.01}),
"force_fetch": ("BOOLEAN", {"default": False}),
"append_loraname_if_empty": ("BOOLEAN", {"default": False}),
},
"optional": {
"override_lora_name":("STRING", {"forceInput": True}),
}
}
RETURN_TYPES = ("MODEL", "CLIP", "LIST", "LIST")
RETURN_NAMES = ("MODEL", "CLIP", "civitai_tags_list", "meta_tags_list")
RETURN_TYPES = ("MODEL", "CLIP", "LIST", "LIST", "STRING")
RETURN_NAMES = ("MODEL", "CLIP", "civitai_tags_list", "meta_tags_list", "lora_name")
FUNCTION = "load_lora"
CATEGORY = "autotrigger"
def load_lora(self, model, clip, lora_name, strength_model, strength_clip, force_fetch, append_loraname_if_empty):
def load_lora(self, model, clip, lora_name, strength_model, strength_clip, force_fetch, append_loraname_if_empty, override_lora_name=""):
if override_lora_name != "":
lora_name = override_lora_name
meta_tags_list = sort_tags_by_frequency(get_metadata(lora_name, "loras"))
civitai_tags_list = load_and_save_tags(lora_name, force_fetch)
@@ -51,7 +56,7 @@ class LoraLoaderVanilla:
model_lora, clip_lora = load_lora_for_models(model, clip, lora, strength_model, strength_clip)
return (model_lora, clip_lora, civitai_tags_list, meta_tags_list)
return (model_lora, clip_lora, civitai_tags_list, meta_tags_list, lora_name)
class LoraLoaderStackedVanilla:
@classmethod
@@ -66,16 +71,19 @@ class LoraLoaderStackedVanilla:
},
"optional": {
"lora_stack": ("LORA_STACK", ),
"override_lora_name":("STRING", {"forceInput": True}),
}
}
RETURN_TYPES = ("LIST", "LIST", "LORA_STACK",)
RETURN_NAMES = ("civitai_tags_list", "meta_tags_list", "LORA_STACK",)
RETURN_TYPES = ("LIST", "LIST", "LORA_STACK", "STRING")
RETURN_NAMES = ("civitai_tags_list", "meta_tags_list", "LORA_STACK", "lora_name")
FUNCTION = "set_stack"
#OUTPUT_NODE = False
CATEGORY = "autotrigger"
def set_stack(self, lora_name, lora_weight, force_fetch, append_loraname_if_empty, lora_stack=None):
def set_stack(self, lora_name, lora_weight, force_fetch, append_loraname_if_empty, lora_stack=None, override_lora_name=""):
if override_lora_name != "":
lora_name = override_lora_name
civitai_tags_list = load_and_save_tags(lora_name, force_fetch)
meta_tags = get_metadata(lora_name, "loras")
@@ -84,12 +92,11 @@ class LoraLoaderStackedVanilla:
civitai_tags_list = append_lora_name_if_empty(civitai_tags_list, lora_name, append_loraname_if_empty)
meta_tags_list = append_lora_name_if_empty(meta_tags_list, lora_name, append_loraname_if_empty)
loras = [(lora_name,lora_weight,lora_weight,)]
if lora_stack is not None:
lora_stack.append((lora_name,lora_weight,lora_weight,))
else:
lora_stack = [(lora_name,lora_weight,lora_weight,)]
loras.extend(lora_stack)
return (civitai_tags_list, meta_tags_list, lora_stack)
return (civitai_tags_list, meta_tags_list, loras, lora_name)
class LoraLoaderAdvanced:
def __init__(self):
@@ -104,20 +111,28 @@ class LoraLoaderAdvanced:
"model": ("MODEL",),
"clip": ("CLIP", ),
"lora_name": (LORA_LIST, ),
"strength_model": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 2.0, "step": 0.1}),
"strength_clip": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 2.0, "step": 0.1}),
"strength_model": ("FLOAT", {"default": 1.0, "min": -10.0, "max": 10.0, "step": 0.01}),
"strength_clip": ("FLOAT", {"default": 1.0, "min": -10.0, "max": 10.0, "step": 0.01}),
"force_fetch": ("BOOLEAN", {"default": False}),
"enable_preview": ("BOOLEAN", {"default": False}),
"append_loraname_if_empty": ("BOOLEAN", {"default": False}),
},
"optional": {
"override_lora_name":("STRING", {"forceInput": True}),
}
}
RETURN_TYPES = ("MODEL", "CLIP", "LIST", "LIST")
RETURN_NAMES = ("MODEL", "CLIP", "civitai_tags_list", "meta_tags_list")
RETURN_TYPES = ("MODEL", "CLIP", "LIST", "LIST", "STRING")
RETURN_NAMES = ("MODEL", "CLIP", "civitai_tags_list", "meta_tags_list", "lora_name")
FUNCTION = "load_lora"
CATEGORY = "autotrigger"
def load_lora(self, model, clip, lora_name, strength_model, strength_clip, force_fetch, enable_preview, append_loraname_if_empty):
def load_lora(self, model, clip, lora_name, strength_model, strength_clip, force_fetch, enable_preview, append_loraname_if_empty, override_lora_name=""):
if override_lora_name != "":
has_preview, prev = get_preview_path(override_lora_name, "loras")
prev = f"loras/{prev}" if has_preview else None
lora_name = {"content": override_lora_name, "image": prev, "type": "loras"}
meta_tags_list = sort_tags_by_frequency(get_metadata(lora_name["content"], "loras"))
civitai_tags_list = load_and_save_tags(lora_name["content"], force_fetch)
@@ -147,10 +162,10 @@ class LoraLoaderAdvanced:
"subfolder": "lora_preview",
"type": "temp"
}
return {"ui": {"images": [preview_output]}, "result": (model_lora, clip_lora, civitai_tags_list, meta_tags_list)}
return {"ui": {"images": [preview_output]}, "result": (model_lora, clip_lora, civitai_tags_list, meta_tags_list, lora_name["content"])}
return (model_lora, clip_lora, civitai_tags_list, meta_tags_list)
return (model_lora, clip_lora, civitai_tags_list, meta_tags_list, lora_name["content"])
class LoraLoaderStackedAdvanced:
@classmethod
@@ -167,16 +182,22 @@ class LoraLoaderStackedAdvanced:
},
"optional": {
"lora_stack": ("LORA_STACK", ),
"override_lora_name":("STRING", {"forceInput": True}),
}
}
RETURN_TYPES = ("LIST", "LIST", "LORA_STACK",)
RETURN_NAMES = ("civitai_tags_list", "meta_tags_list", "LORA_STACK",)
RETURN_TYPES = ("LIST", "LIST", "LORA_STACK", "STRING")
RETURN_NAMES = ("civitai_tags_list", "meta_tags_list", "LORA_STACK", "lora_name")
FUNCTION = "set_stack"
#OUTPUT_NODE = False
CATEGORY = "autotrigger"
def set_stack(self, lora_name, lora_weight, force_fetch, enable_preview, append_loraname_if_empty, lora_stack=None):
def set_stack(self, lora_name, lora_weight, force_fetch, enable_preview, append_loraname_if_empty, lora_stack=None, override_lora_name=""):
if override_lora_name != "":
has_preview, prev = get_preview_path(override_lora_name, "loras")
prev = f"loras/{prev}" if has_preview else None
lora_name = {"content": override_lora_name, "image": prev, "type": "loras"}
civitai_tags_list = load_and_save_tags(lora_name["content"], force_fetch)
meta_tags = get_metadata(lora_name["content"], "loras")
@@ -185,10 +206,9 @@ class LoraLoaderStackedAdvanced:
civitai_tags_list = append_lora_name_if_empty(civitai_tags_list, lora_name["content"], append_loraname_if_empty)
meta_tags_list = append_lora_name_if_empty(meta_tags_list, lora_name["content"], append_loraname_if_empty)
loras = [(lora_name["content"],lora_weight,lora_weight,)]
if lora_stack is not None:
lora_stack.append((lora_name["content"],lora_weight,lora_weight,))
else:
lora_stack = [(lora_name["content"],lora_weight,lora_weight,)]
loras.extend(lora_stack)
if enable_preview:
_, preview = copy_preview_to_temp(lora_name["image"])
@@ -198,9 +218,40 @@ class LoraLoaderStackedAdvanced:
"subfolder": "lora_preview",
"type": "temp"
}
return {"ui": {"images": [preview_output]}, "result": (civitai_tags_list, meta_tags_list, lora_stack)}
return {"ui": {"images": [preview_output]}, "result": (civitai_tags_list, meta_tags_list, loras, lora_name["content"])}
return {"result": (civitai_tags_list, meta_tags_list, lora_stack)}
return {"result": (civitai_tags_list, meta_tags_list, loras, lora_name["content"])}
class LoraTagsOnly:
@classmethod
def INPUT_TYPES(s):
LORA_LIST = sorted(folder_paths.get_filename_list("loras"), key=str.lower)
return {
"required": {
"lora_name": (LORA_LIST,),
"force_fetch": ("BOOLEAN", {"default": False}),
"append_loraname_if_empty": ("BOOLEAN", {"default": False}),
},
"optional": {
"override_lora_name":("STRING", {"forceInput": True}),
}
}
RETURN_TYPES = ("LIST", "LIST")
RETURN_NAMES = ("civitai_tags_list", "meta_tags_list")
FUNCTION = "ask_lora"
CATEGORY = "autotrigger"
def ask_lora(self, lora_name, force_fetch, append_loraname_if_empty, override_lora_name=""):
if override_lora_name != "":
lora_name = override_lora_name
meta_tags_list = sort_tags_by_frequency(get_metadata(lora_name, "loras"))
civitai_tags_list = load_and_save_tags(lora_name, force_fetch)
meta_tags_list = append_lora_name_if_empty(meta_tags_list, lora_name, append_loraname_if_empty)
civitai_tags_list = append_lora_name_if_empty(civitai_tags_list, lora_name, append_loraname_if_empty)
return (civitai_tags_list, meta_tags_list)
# A dictionary that contains all nodes you want to export with their names
@@ -210,6 +261,7 @@ NODE_CLASS_MAPPINGS = {
"LoraLoaderStackedVanilla": LoraLoaderStackedVanilla,
"LoraLoaderAdvanced": LoraLoaderAdvanced,
"LoraLoaderStackedAdvanced": LoraLoaderStackedAdvanced,
"LoraTagsOnly": LoraTagsOnly,
}
# A dictionary that contains the friendly/humanly readable titles for the nodes
@@ -218,4 +270,5 @@ NODE_DISPLAY_NAME_MAPPINGS = {
"LoraLoaderStackedVanilla": "LoraLoaderStackedVanilla",
"LoraLoaderAdvanced": "LoraLoaderAdvanced",
"LoraLoaderStackedAdvanced": "LoraLoaderStackedAdvanced",
"LoraTagsOnly": "LoraTagsOnly",
}
+27 -7
View File
@@ -1,5 +1,3 @@
import random
from .utils import *
class FusionText:
@@ -20,11 +18,13 @@ class Randomizer:
return {
"required": {
"text_1":("STRING", {"forceInput": True}),
"lora_1":("LORA_STACK", ),
"text_2":("STRING", {"forceInput": True} ),
"lora_2":("LORA_STACK", ),
"seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}),
},
"optional": {
"lora_1":("LORA_STACK", ),
"lora_2":("LORA_STACK", ),
}
}
RETURN_TYPES = ("STRING", "LORA_STACK")
@@ -35,9 +35,8 @@ class Randomizer:
CATEGORY = "autotrigger"
def randomize(self, text_1, lora_1, text_2, lora_2, seed):
random.seed(seed)
if random.random() < .5:
def randomize(self, text_1, text_2, seed, lora_1=[], lora_2=[]):
if seed %2 == 0:
return (text_1, lora_1)
return (text_2, lora_2)
@@ -121,6 +120,25 @@ class TagsFormater:
return (output,)
class LoraListNames:
@classmethod
def INPUT_TYPES(s):
LORA_LIST = sorted(folder_paths.get_filename_list("loras"), key=str.lower)
return {
"required": {
"lora_name": (LORA_LIST,),
}
}
RETURN_TYPES = ("STRING",)
RETURN_NAMES = ("lora_name",)
FUNCTION = "output_selected"
CATEGORY = "autotrigger"
def output_selected(self, lora_name):
name = lora_name
return (name,)
# A dictionary that contains all nodes you want to export with their names
# NOTE: names should be globally unique
NODE_CLASS_MAPPINGS = {
@@ -129,6 +147,7 @@ NODE_CLASS_MAPPINGS = {
"TextInputBasic": TextInputBasic,
"TagsSelector": TagsSelector,
"TagsFormater": TagsFormater,
"LoraListNames": LoraListNames,
}
# A dictionary that contains the friendly/humanly readable titles for the nodes
@@ -138,4 +157,5 @@ NODE_DISPLAY_NAME_MAPPINGS = {
"TextInputBasic": "TextInputBasic",
"TagsSelector": "TagsSelector",
"TagsFormater": "TagsFormater",
"LoraListNames": "LoraListNames",
}
+10 -8
View File
@@ -31,6 +31,8 @@ def copy_preview_to_temp(file_name):
lora_less = "/".join(file_name.split("/")[1:])
file_path = folder_paths.get_full_path("loras", lora_less)
if file_path is None:
return None, None
temp_path = folder_paths.get_temp_directory()
preview_path = os.path.join(temp_path, "lora_preview")
@@ -66,7 +68,7 @@ def load_json_from_file(file_path):
return None
except json.JSONDecodeError:
print(f"Error decoding JSON in file: {file_path}")
return None
raise
def save_dict_to_json(data_dict, file_path):
try:
@@ -103,21 +105,21 @@ def load_and_save_tags(lora_name, force_fetch):
output_tags_list = []
lora_path = folder_paths.get_full_path("loras", lora_name)
if lora_tags is None or force_fetch: # search on civitai only if no local cache or forced
print("calculating lora hash")
if lora_tags is None or force_fetch or output_tags is None: # search on civitai only if no local cache or forced
print("[Lora-Auto-Trigger] calculating lora hash")
LORAsha256 = calculate_sha256(lora_path)
print("requesting infos")
print("[Lora-Auto-Trigger] requesting infos")
model_info = get_model_version_info(LORAsha256)
if model_info is not None:
if "trainedWords" in model_info:
print("tags found!")
print("[Lora-Auto-Trigger] tags found!")
if lora_tags is None:
lora_tags = {}
lora_tags[lora_name] = model_info["trainedWords"]
save_dict_to_json(lora_tags,json_tags_path)
save_dict_to_json(lora_tags, json_tags_path)
output_tags_list = model_info["trainedWords"]
else:
print("No informations found.")
print("[Lora-Auto-Trigger] No informations found.")
if lora_tags is None:
lora_tags = {}
lora_tags[lora_name] = []
@@ -219,4 +221,4 @@ def append_lora_name_if_empty(tags_list, lora_path, enabled):
filename = os.path.basename(filename)
tags_list.append(filename)
return tags_list
return tags_list