from toolkit.paths import MODELS_PATH import requests import os import json import tqdm class ModelCache: def __init__(self): self.raw_cache = {} self.cache_path = os.path.join(MODELS_PATH, '.ai_toolkit_cache.json') if os.path.exists(self.cache_path): with open(self.cache_path, 'r') as f: all_cache = json.load(f) if 'models' in all_cache: self.raw_cache = all_cache['models'] else: self.raw_cache = all_cache def get_model_path(self, model_id: int, model_version_id: int = None): if str(model_id) not in self.raw_cache: return None if model_version_id is None: # get latest version model_version_id = max([int(x) for x in self.raw_cache[str(model_id)].keys()]) if model_version_id is None: return None model_path = self.raw_cache[str(model_id)][str(model_version_id)]['model_path'] # check if model path exists if not os.path.exists(model_path): # remove version from cache del self.raw_cache[str(model_id)][str(model_version_id)] self.save() return None return model_path else: if str(model_version_id) not in self.raw_cache[str(model_id)]: return None model_path = self.raw_cache[str(model_id)][str(model_version_id)]['model_path'] # check if model path exists if not os.path.exists(model_path): # remove version from cache del self.raw_cache[str(model_id)][str(model_version_id)] self.save() return None return model_path def update_cache(self, model_id: int, model_version_id: int, model_path: str): if str(model_id) not in self.raw_cache: self.raw_cache[str(model_id)] = {} if str(model_version_id) not in self.raw_cache[str(model_id)]: self.raw_cache[str(model_id)][str(model_version_id)] = {} self.raw_cache[str(model_id)][str(model_version_id)] = { 'model_path': model_path } self.save() def save(self): if not os.path.exists(os.path.dirname(self.cache_path)): os.makedirs(os.path.dirname(self.cache_path), exist_ok=True) all_cache = {'models': {}} if os.path.exists(self.cache_path): # load it first with open(self.cache_path, 'r') as f: all_cache = json.load(f) all_cache['models'] = self.raw_cache with open(self.cache_path, 'w') as f: json.dump(all_cache, f, indent=2) def get_model_download_info(model_id: int, model_version_id: int = None): # curl https://civitai.com/api/v1/models?limit=3&types=TextualInversion \ # -H "Content-Type: application/json" \ # -X GET print( f"Getting model info for model id: {model_id}{f' and version id: {model_version_id}' if model_version_id is not None else ''}") endpoint = f"https://civitai.com/api/v1/models/{model_id}" # get the json response = requests.get(endpoint) response.raise_for_status() model_data = response.json() model_version = None # go through versions and get the top one if one is not set for version in model_data['modelVersions']: if model_version_id is not None: if str(version['id']) == str(model_version_id): model_version = version break else: # get first version model_version = version break if model_version is None: raise ValueError( f"Could not find a model version for model id: {model_id}{f' and version id: {model_version_id}' if model_version_id is not None else ''}") model_file = None # go through files and prefer fp16 safetensors # "metadata": { # "fp": "fp16", # "size": "pruned", # "format": "SafeTensor" # }, # todo check pickle scans and skip if not good # try to get fp16 safetensor for file in model_version['files']: if file['metadata']['fp'] == 'fp16' and file['metadata']['format'] == 'SafeTensor': model_file = file break if model_file is None: # try to get primary for file in model_version['files']: if file['primary']: model_file = file break if model_file is None: # try to get any safetensor for file in model_version['files']: if file['metadata']['format'] == 'SafeTensor': model_file = file break if model_file is None: # try to get any fp16 for file in model_version['files']: if file['metadata']['fp'] == 'fp16': model_file = file break if model_file is None: # try to get any for file in model_version['files']: model_file = file break if model_file is None: raise ValueError(f"Could not find a model file to download for model id: {model_id}") return model_file, model_version['id'] def get_model_path_from_url(url: str): # get query params form url if they are set # https: // civitai.com / models / 25694?modelVersionId = 127742 query_params = {} if '?' in url: query_string = url.split('?')[1] query_params = dict(qc.split("=") for qc in query_string.split("&")) # get model id from url model_id = url.split('/')[-1] # remove query params from model id if '?' in model_id: model_id = model_id.split('?')[0] if model_id.isdigit(): model_id = int(model_id) else: raise ValueError(f"Invalid model id: {model_id}") model_cache = ModelCache() model_path = model_cache.get_model_path(model_id, query_params.get('modelVersionId', None)) if model_path is not None: return model_path else: # download model file_info, model_version_id = get_model_download_info(model_id, query_params.get('modelVersionId', None)) download_url = file_info['downloadUrl'] # url does not work directly size_kb = file_info['sizeKB'] filename = file_info['name'] model_path = os.path.join(MODELS_PATH, filename) # download model print(f"Did not find model locally, downloading from model from: {download_url}") # use tqdm to show status of downlod response = requests.get(download_url, stream=True) response.raise_for_status() total_size_in_bytes = int(response.headers.get('content-length', 0)) block_size = 1024 # 1 Kibibyte progress_bar = tqdm.tqdm(total=total_size_in_bytes, unit='iB', unit_scale=True) tmp_path = os.path.join(MODELS_PATH, f".download_tmp_{filename}") os.makedirs(os.path.dirname(model_path), exist_ok=True) # remove tmp file if it exists if os.path.exists(tmp_path): os.remove(tmp_path) try: with open(tmp_path, 'wb') as f: for data in response.iter_content(block_size): progress_bar.update(len(data)) f.write(data) progress_bar.close() # move to final path os.rename(tmp_path, model_path) model_cache.update_cache(model_id, model_version_id, model_path) return model_path except Exception as e: # remove tmp file os.remove(tmp_path) raise e # if is main if __name__ == '__main__': model_path = get_model_path_from_url("https://civitai.com/models/25694?modelVersionId=127742") print(model_path)