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Zero
File size: 8,379 Bytes
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import spaces
import os
import gradio as gr
import json
import logging
logging.getLogger("diffusers").setLevel(logging.ERROR)
import diffusers
diffusers.utils.logging.set_verbosity(40)
import warnings
warnings.filterwarnings(action="ignore", category=FutureWarning, module="diffusers")
warnings.filterwarnings(action="ignore", category=UserWarning, module="diffusers")
warnings.filterwarnings(action="ignore", category=FutureWarning, module="transformers")
from pathlib import Path
from huggingface_hub import HfApi
from env import (HF_TOKEN, hf_read_token, # to use only for private repos
CIVITAI_API_KEY, HF_LORA_PRIVATE_REPOS1, HF_LORA_PRIVATE_REPOS2, HF_LORA_ESSENTIAL_PRIVATE_REPO,
HF_VAE_PRIVATE_REPO, directory_models, directory_loras, directory_vaes,
download_model_list, download_lora_list, download_vae_list)
from modutils import (to_list, list_uniq, list_sub, get_lora_model_list, download_private_repo,
safe_float, escape_lora_basename, to_lora_key, to_lora_path, get_local_model_list, download_things,
get_private_lora_model_lists, get_valid_lora_name, get_valid_lora_path, get_valid_lora_wt,
get_lora_info, normalize_prompt_list, get_civitai_info, search_lora_on_civitai, MODEL_TYPE_DICT)
# - **Download Models**
download_model = ", ".join(download_model_list)
# - **Download VAEs**
download_vae = ", ".join(download_vae_list)
# - **Download LoRAs**
download_lora = ", ".join(download_lora_list)
#download_private_repo(HF_LORA_ESSENTIAL_PRIVATE_REPO, directory_loras, True)
#download_private_repo(HF_VAE_PRIVATE_REPO, directory_vaes, False)
CIVITAI_API_KEY = os.environ.get("CIVITAI_API_KEY")
hf_token = os.environ.get("HF_TOKEN")
# Download stuffs
for url in [url.strip() for url in download_model.split(',')]:
if not os.path.exists(f"./models/{url.split('/')[-1]}"):
download_things(directory_models, url, hf_token, CIVITAI_API_KEY)
for url in [url.strip() for url in download_vae.split(',')]:
if not os.path.exists(f"./vaes/{url.split('/')[-1]}"):
download_things(directory_vaes, url, hf_token, CIVITAI_API_KEY)
for url in [url.strip() for url in download_lora.split(',')]:
if not os.path.exists(f"./loras/{url.split('/')[-1]}"):
download_things(directory_loras, url, hf_token, CIVITAI_API_KEY)
lora_model_list = get_lora_model_list()
vae_model_list = get_local_model_list(directory_vaes)
vae_model_list.insert(0, "None")
private_lora_dict = {"": ["", "", "", "", ""]}
try:
with open('lora_dict.json', encoding='utf-8') as f:
d = json.load(f)
for k, v in d.items():
private_lora_dict[escape_lora_basename(k)] = v
except Exception:
pass
private_lora_model_list = get_private_lora_model_lists()
loras_dict = {"None": ["", "", "", "", ""], "": ["", "", "", "", ""]} | private_lora_dict.copy()
loras_url_to_path_dict = {} # {"URL to download": "local filepath", ...}
civitai_lora_last_results = {} # {"URL to download": {search results}, ...}
all_lora_list = []
def get_all_lora_list():
global all_lora_list
loras = get_lora_model_list()
all_lora_list = loras.copy()
return loras
def get_all_lora_tupled_list():
global loras_dict
models = get_all_lora_list()
if not models: return []
tupled_list = []
for model in models:
#if not model: continue # to avoid GUI-related bug
basename = Path(model).stem
key = to_lora_key(model)
items = None
if key in loras_dict.keys():
items = loras_dict.get(key, None)
else:
items = get_civitai_info(model)
if items != None:
loras_dict[key] = items
name = basename
value = model
if items and items[2] != "":
if items[1] == "Pony":
name = f"{basename} (for {items[1]}🐴, {items[2]})"
else:
name = f"{basename} (for {items[1]}, {items[2]})"
tupled_list.append((name, value))
return tupled_list
def update_lora_dict(path: str):
global loras_dict
key = to_lora_key(path)
if key in loras_dict.keys(): return
items = get_civitai_info(path)
if items == None: return
loras_dict[key] = items
def download_lora(dl_urls: str):
global loras_url_to_path_dict
dl_path = ""
before = get_local_model_list(directory_loras)
urls = []
for url in [url.strip() for url in dl_urls.split(',')]:
local_path = f"{directory_loras}/{url.split('/')[-1]}"
if not Path(local_path).exists():
download_things(directory_loras, url, hf_token, CIVITAI_API_KEY)
urls.append(url)
after = get_local_model_list(directory_loras)
new_files = list_sub(after, before)
for i, file in enumerate(new_files):
path = Path(file)
if path.exists():
new_path = Path(f'{path.parent.name}/{escape_lora_basename(path.stem)}{path.suffix}')
path.resolve().rename(new_path.resolve())
loras_url_to_path_dict[urls[i]] = str(new_path)
update_lora_dict(str(new_path))
dl_path = str(new_path)
return dl_path
def copy_lora(path: str, new_path: str):
import shutil
if path == new_path: return new_path
cpath = Path(path)
npath = Path(new_path)
if cpath.exists():
try:
shutil.copy(str(cpath.resolve()), str(npath.resolve()))
except Exception:
return None
update_lora_dict(str(npath))
return new_path
else:
return None
def download_my_lora(dl_urls: str, lora):
path = download_lora(dl_urls)
if path: lora = path
choices = get_all_lora_tupled_list()
return gr.update(value=lora, choices=choices)
def apply_lora_prompt(lora_info: str):
if lora_info == "None": return ""
lora_tag = lora_info.replace("/",",")
lora_tags = lora_tag.split(",") if str(lora_info) != "None" else []
lora_prompts = normalize_prompt_list(lora_tags)
prompt = ", ".join(list_uniq(lora_prompts))
return prompt
def update_loras(prompt, lora, lora_wt):
on, label, tag, md = get_lora_info(lora)
choices = get_all_lora_tupled_list()
return gr.update(value=prompt), gr.update(value=lora, choices=choices), gr.update(value=lora_wt),\
gr.update(value=tag, label=label, visible=on), gr.update(value=md, visible=on)
def search_civitai_lora(query, base_model, sort="Highest Rated", period="AllTime", tag=""):
global civitai_lora_last_results
items = search_lora_on_civitai(query, base_model, 100, sort, period, tag)
if not items: return gr.update(choices=[("", "")], value="", visible=False),\
gr.update(value="", visible=False), gr.update(visible=True), gr.update(visible=True)
civitai_lora_last_results = {}
choices = []
for item in items:
base_model_name = "Pony🐴" if item['base_model'] == "Pony" else item['base_model']
name = f"{item['name']} (for {base_model_name} / By: {item['creator']} / Tags: {', '.join(item['tags'])})"
value = item['dl_url']
choices.append((name, value))
civitai_lora_last_results[value] = item
if not choices: return gr.update(choices=[("", "")], value="", visible=False),\
gr.update(value="", visible=False), gr.update(visible=True), gr.update(visible=True)
result = civitai_lora_last_results.get(choices[0][1], "None")
md = result['md'] if result else ""
return gr.update(choices=choices, value=choices[0][1], visible=True), gr.update(value=md, visible=True),\
gr.update(visible=True), gr.update(visible=True)
def select_civitai_lora(search_result):
if not "http" in search_result: return gr.update(value=""), gr.update(value="None", visible=True)
result = civitai_lora_last_results.get(search_result, "None")
md = result['md'] if result else ""
return gr.update(value=search_result), gr.update(value=md, visible=True)
def search_civitai_lora_json(query, base_model):
results = {}
items = search_lora_on_civitai(query, base_model)
if not items: return gr.update(value=results)
for item in items:
results[item['dl_url']] = item
return gr.update(value=results)
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