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civitai enable embedding download

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Vladimir Mandic
2024-01-29 09:55:16 -05:00
parent 682da607a9
commit f45655f077
3 changed files with 31 additions and 16 deletions
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modules/ui_models.py
+24 -13
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@@ -417,13 +417,19 @@ def create_ui():
def civit_search_model(name, tag, model_type):
# types = 'LORA' if model_type == 'LoRA' else 'Checkpoint'
url = 'https://civitai.com/api/v1/models?limit=25&&Sort=Newest'
url = 'https://civitai.com/api/v1/models?limit=25&Sort=Newest'
if model_type == 'SD 1.5' or model_type == 'SD XL':
url += '&types=Checkpoint'
elif model_type == 'LoRA':
url += '&types=LORA'
elif model_type == 'Embedding':
url += '&types=TextualInversion'
if name is not None and len(name) > 0:
url += f'&query={name}'
if tag is not None and len(tag) > 0:
url += f'&tag={tag}'
r = req(url)
log.debug(f'CivitAI search: name="{name}" tag={tag or "none"} status={r.status_code}')
log.debug(f'CivitAI search: name="{name}" tag={tag or "none"} url="{url}" status={r.status_code}')
if r.status_code != 200:
return [], [], []
body = r.json()
@@ -434,16 +440,21 @@ def create_ui():
found = 0
if model_type == 'LoRA' and model['type'] in ['LORA', 'LoCon']:
found += 1
for variant in model['modelVersions']:
if model_type == 'SD 1.5':
if 'SD 1.' in variant['baseModel']:
found += 1
if model_type == 'SD XL':
if 'SDXL' in variant['baseModel']:
found += 1
else:
if 'SD 1.' not in variant['baseModel'] and 'SDXL' not in variant['baseModel']:
found += 1
elif model_type == 'Embedding' and model['type'] == 'TextualInversion':
found += 1
elif model_type.startswith('SD') and model['type'] == 'Checkpoint':
for variant in model['modelVersions']:
if model_type == 'SD 1.5':
if 'SD 1.' in variant['baseModel']:
found += 1
if model_type == 'SD XL':
if 'SDXL' in variant['baseModel']:
found += 1
else:
if 'SD 1.' not in variant['baseModel'] and 'SDXL' not in variant['baseModel']:
found += 1
elif model_type == 'Other':
found += 1
if found > 0:
data1.append([
model['id'],
@@ -581,7 +592,7 @@ def create_ui():
gr.HTML('<h2>Search for models</h2>')
with gr.Row():
with gr.Column(scale=1):
civit_model_type = gr.Dropdown(label='Model type', choices=['SD 1.5', 'SD XL', 'LoRA', 'Other'], value='LoRA')
civit_model_type = gr.Dropdown(label='Model type', choices=['SD 1.5', 'SD XL', 'LoRA', 'Embedding', 'Other'], value='LoRA')
with gr.Column(scale=15):
with gr.Row():
civit_search_text = gr.Textbox('', label='Search models', placeholder='keyword')