gen-m3mxs2yu / utils.py
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Deploy Gradio app with multiple files
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import requests
import os
from typing import List, Dict, Optional
def download_model_from_civitai(model_id: int, api_key: str, download_path: str) -> bool:
"""
Download a model from CivitAI (placeholder function)
In a real implementation, this would handle the actual download
"""
try:
headers = {"Authorization": f"Bearer {api_key}"}
# Get model details
model_response = requests.get(
f"https://civitai.com/api/v1/models/{model_id}",
headers=headers
)
if model_response.status_code != 200:
return False
model_data = model_response.json()
# Get download URL (this is simplified - in reality you'd need to get the actual file URL)
# This would typically be from model_data['modelVersions'][0]['files'][0]['downloadUrl']
# Download the model file
# response = requests.get(download_url, headers=headers)
# with open(download_path, 'wb') as f:
# f.write(response.content)
return True
except Exception as e:
print(f"Error downloading model: {e}")
return False
def apply_lora_to_model(pipe, lora_id: int, api_key: str) -> bool:
"""
Apply a LoRA to a model (placeholder function)
In a real implementation, this would handle LoRA integration
"""
try:
# Download and apply LoRA
# This is highly dependent on the specific model and LoRA format
return True
except Exception as e:
print(f"Error applying LoRA: {e}")
return False
def validate_api_key(api_key: str) -> bool:
"""Validate the CivitAI API key"""
try:
headers = {"Authorization": f"Bearer {api_key}"}
response = requests.get(
"https://civitai.com/api/v1/models?limit=1",
headers=headers
)
return response.status_code == 200
except Exception:
return False