comfyui-civitai

ComfyUI CivitAI 集成

搜索和下载 CivitAI 上的模型。

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预注入变量

run_python 已注入：folder_paths

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核心功能

1. 搜索模型

from comfyui_civitai import search_models

results = search_models(
    query="anime style",
    model_type="LORA",  # Checkpoint, LORA, TextualInversion, etc.
    sort="Most Downloaded",  # or "Highest Rated", "Newest"
    limit=10
)

for model in results:
    print(f"{model['name']} by {model['creator']}")
    print(f"  Downloads: {model['downloads']}, Rating: {model['rating']}")
    print(f"  URL: {model['civitai_url']}")

2. 获取模型详情

from comfyui_civitai import get_model_info

info = get_model_info(model_id=12345)
print(f"Name: {info['name']}")
print(f"Description: {info['description'][:200]}...")
print(f"Versions: {len(info['versions'])}")

3. 下载模型

from comfyui_civitai import download_model

# 下载最新版本
result = download_model(
    model_id=12345,
    model_type="loras",  # 保存到 models/loras/
    filename="my_lora.safetensors"
)

print(f"Downloaded to: {result['path']}")

4. 下载特定版本

from comfyui_civitai import download_model_version

result = download_model_version(
    version_id=67890,
    model_type="checkpoints"
)

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完整示例

搜索并下载 LoRA

from comfyui_civitai import search_models, download_model

# 1. 搜索
results = search_models(
    query="studio ghibli style",
    model_type="LORA",
    sort="Most Downloaded",
    limit=5
)

# 2. 显示结果
for i, model in enumerate(results):
    print(f"{i+1}. {model['name']}")
    print(f"   {model['description'][:100]}...")

# 3. 下载第一个
if results:
    model = results[0]
    print(f"\nDownloading {model['name']}...")
    
    result = download_model(
        model_id=model['id'],
        model_type="loras"
    )
    
    if result['success']:
        print(f"✅ Downloaded to {result['path']}")
    else:
        print(f"❌ Error: {result['error']}")

批量下载 Checkpoint

from comfyui_civitai import search_models, download_model

# 搜索高质量 checkpoints
results = search_models(
    query="photorealistic",
    model_type="Checkpoint",
    sort="Highest Rated",
    limit=3
)

# 批量下载
for model in results:
    print(f"Downloading {model['name']}...")
    download_model(model['id'], model_type="checkpoints")