import gradio as gr from huggingface_hub import HfApi, hf_hub_url import os from pathlib import Path import gc import requests from requests.adapters import HTTPAdapter from urllib3.util import Retry from utils import get_token, set_token, is_repo_exists, get_user_agent, get_download_file def upload_safetensors_to_repo(filename, repo_id, repo_type, is_private, progress=gr.Progress(track_tqdm=True)): output_filename = Path(filename).name hf_token = get_token() api = HfApi(token=hf_token) try: if not is_repo_exists(repo_id, repo_type): api.create_repo(repo_id=repo_id, repo_type=repo_type, token=hf_token, private=is_private) progress(0, desc="Start uploading...") api.upload_file(path_or_fileobj=filename, path_in_repo=output_filename, repo_type=repo_type, revision="main", token=hf_token, repo_id=repo_id) progress(1, desc="Uploaded.") url = hf_hub_url(repo_id=repo_id, repo_type=repo_type, filename=output_filename) except Exception as e: print(f"Error: Failed to upload to {repo_id}. {e}") gr.Warning(f"Error: Failed to upload to {repo_id}. {e}") return None return url def download_file(dl_url, civitai_key, progress=gr.Progress(track_tqdm=True)): download_dir = "." progress(0, desc="Start downloading...") output_filename = get_download_file(download_dir, dl_url, civitai_key) return output_filename def download_civitai(dl_url, civitai_key, hf_token, urls, newrepo_id, repo_type="model", is_private=True, progress=gr.Progress(track_tqdm=True)): if hf_token: set_token(hf_token) else: set_token(os.environ.get("HF_TOKEN")) if not civitai_key: civitai_key = os.environ.get("CIVITAI_API_KEY") if not hf_token or not civitai_key: raise gr.Error("HF write token and Civitai API key is required.") file = download_file(dl_url, civitai_key) if not urls: urls = [] url = upload_safetensors_to_repo(file, newrepo_id, repo_type, is_private) progress(1, desc="Processing...") if url: urls.append(url) Path(file).unlink() md = "" for u in urls: md += f"[Uploaded {str(u)}]({str(u)})
" gc.collect() return gr.update(value=urls, choices=urls), gr.update(value=md) CIVITAI_TYPE = ["Checkpoint", "TextualInversion", "Hypernetwork", "AestheticGradient", "LORA", "Controlnet", "Poses"] CIVITAI_BASEMODEL = ["Pony", "SD 1.5", "SDXL 1.0", "Flux.1 D", "Flux.1 S"] CIVITAI_SORT = ["Highest Rated", "Most Downloaded", "Newest"] CIVITAI_PERIOD = ["AllTime", "Year", "Month", "Week", "Day"] def search_on_civitai(query: str, types: list[str], allow_model: list[str] = [], limit: int = 100, sort: str = "Highest Rated", period: str = "AllTime", tag: str = ""): user_agent = get_user_agent() headers = {'User-Agent': user_agent, 'content-type': 'application/json'} base_url = 'https://civitai.com/api/v1/models' params = {'sort': sort, 'period': period, 'limit': limit, 'nsfw': 'true'} if len(types) != 0: params["types"] = types if query: params["query"] = query if tag: params["tag"] = tag session = requests.Session() retries = Retry(total=5, backoff_factor=1, status_forcelist=[500, 502, 503, 504]) session.mount("https://", HTTPAdapter(max_retries=retries)) try: r = session.get(base_url, params=params, headers=headers, stream=True, timeout=(3.0, 30)) except Exception as e: print(e) return None else: if not r.ok: return None json = r.json() if 'items' not in json: return None items = [] for j in json['items']: for model in j['modelVersions']: item = {} if len(allow_model) != 0 and model['baseModel'] not in set(allow_model): continue item['name'] = j['name'] item['creator'] = j['creator']['username'] if 'creator' in j.keys() and 'username' in j['creator'].keys() else "" item['tags'] = j['tags'] if 'tags' in j.keys() else [] item['model_name'] = model['name'] if 'name' in model.keys() else "" item['base_model'] = model['baseModel'] if 'baseModel' in model.keys() else "" item['dl_url'] = model['downloadUrl'] if 'images' in model.keys() and len(model["images"]) != 0: item['md'] = f'thumbnail
[Model URL](https://civitai.com/models/{j["id"]})' else: item['md'] = f'[Model URL](https://civitai.com/models/{j["id"]})' items.append(item) return items civitai_last_results = {} def search_civitai(query, types, base_model=[], sort=CIVITAI_SORT[0], period=CIVITAI_PERIOD[0], tag=""): global civitai_last_results items = search_on_civitai(query, types, 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_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_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_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_item(search_result): if not "http" in search_result: return gr.update(value=""), gr.update(value="None", visible=True) result = civitai_last_results.get(search_result, "None") md = result['md'] if result else "" return gr.update(value=search_result), gr.update(value=md, visible=True)