import requests import os import gradio as gr from huggingface_hub import HfApi, update_repo_visibility from slugify import slugify import gradio as gr import uuid from typing import Optional import json def get_json_data(url): api_url = f"https://civitai.com/api/v1/models/{url.split('/')[4]}" try: response = requests.get(api_url) response.raise_for_status() return response.json() except requests.exceptions.RequestException as e: print(f"Error fetching JSON data: {e}") return None def check_nsfw(json_data): if json_data["nsfw"]: return False for model_version in json_data["modelVersions"]: for image in model_version["images"]: if image["nsfw"] != "None": return False return True def extract_info(json_data): if json_data["type"] == "LORA": for model_version in json_data["modelVersions"]: if model_version["baseModel"] in ["SDXL 1.0", "SDXL 0.9"]: for file in model_version["files"]: if file["primary"]: info = { "urls_to_download": [ {"url": file["downloadUrl"], "filename": file["name"], "type": "weightName"}, {"url": model_version["images"][0]["url"], "filename": os.path.basename(model_version["images"][0]["url"]), "type": "imageName"} ], "id": model_version["id"], "modelId": model_version["modelId"], "name": json_data["name"], "description": json_data["description"], "trainedWords": model_version["trainedWords"], "creator": json_data["creator"]["username"] } return info return None def download_files(info, folder="."): downloaded_files = { "imageName": [], "weightName": [] } for item in info["urls_to_download"]: download_file(item["url"], item["filename"], folder) downloaded_files[item["type"]].append(item["filename"]) return downloaded_files def download_file(url, filename, folder="."): try: response = requests.get(url) response.raise_for_status() with open(f"{folder}/{filename}", 'wb') as f: f.write(response.content) except requests.exceptions.RequestException as e: raise gr.Error(f"Error downloading file: {e}") def process_url(url, do_download=True, folder="."): json_data = get_json_data(url) if json_data: if check_nsfw(json_data): info = extract_info(json_data) if info: if(do_download): downloaded_files = download_files(info, folder) else: downloaded_files = [] return info, downloaded_files else: raise gr.Error("Only SDXL LoRAs are supported for now") else: raise gr.Error("This model has content tagged as unsafe by CivitAI") else: raise gr.Error("Something went wrong in fetching CivitAI API") def create_readme(info, downloaded_files, is_author=True, folder="."): readme_content = "" original_url = f"https://civitai.com/models/{info['id']}" non_author_disclaimer = f'This model was originally uploaded on [CivitAI]({original_url}), by [{info["creator"]}](https://civitai.com/user/{info["creator"]}/models). The information below was provided by the author on CivitAI:' content = f"""--- license: other tags: - text-to-image - stable-diffusion - lora - diffusers base_model: stabilityai/stable-diffusion-xl-base-1.0 instance_prompt: {info["trainedWords"][0]} widget: - text: {info["trainedWords"][0]} --- # {info["name"]} {non_author_disclaimer if not is_author else ''} ![Image]({downloaded_files["imageName"][0]}) {info["description"]} """ readme_content += content + "\n" with open(f"{folder}/README.md", "w") as file: file.write(readme_content) def upload_civit_to_hf(profile: Optional[gr.OAuthProfile], url, progress=gr.Progress(track_tqdm=True)): if not profile.name: return gr.Error("Are you sure you are logged in?") folder = str(uuid.uuid4()) os.makedirs(folder, exist_ok=False) info, downloaded_files = process_url(url, folder=folder) create_readme(info, downloaded_files, folder=folder) try: api = HfApi(token=os.environ["HUGGING_FACE_HUB_TOKEN"]) username = api.whoami()["name"] slug_name = slugify(info["name"]) repo_id = f"{username}/{profile.preferred_username}-{slug_name}" api.create_repo(repo_id=repo_id, private=True, exist_ok=True) api.upload_folder( folder_path=folder, repo_id=repo_id, repo_type="model", ) api.update_repo_visibility(repo_id=repo_id, private=False) except: raise gr.Error("something went wrong") transfer_repos = gr.load("multimodalart/transfer_repos", hf_token=os.environ["HUGGING_FACE_HUB_TOKEN"], src="spaces") user_repo_id = f"{profile.preferred_username}/{slug_name}" response_code = transfer_repos(repo_id, user_repo_id) i = 0 while response_code != "200": message = None if response_code == "409": if i < 3: user_repo_id = f"{profile.preferred_username}/{slug_name}-{i}" response_code = transfer_repos(repo_id, user_repo_id) i += 1 else: message = "It seems this model has been uploaded already in your account." elif response_code == "404": message = "Something went wrong with the model upload. Try again." else: message = f"Unexpected response code: {response_code}." if message: api.delete_repo(repo_id=repo_id, repo_type="model") raise gr.Error(message) return f'''# Model uploaded to 🤗! ## Access it here [{user_repo_id}](https://huggingface.co/{user_repo_id}) ''' def get_creator(username): url = f"https://civitai.com/api/trpc/user.getCreator?input=%7B%22json%22%3A%7B%22username%22%3A%22{username}%22%2C%22authed%22%3Atrue%7D%7D" headers = { "authority": "civitai.com", "accept": "*/*", "accept-language": "en-BR,en;q=0.9,pt-BR;q=0.8,pt;q=0.7,es-ES;q=0.6,es;q=0.5,de-LI;q=0.4,de;q=0.3,en-GB;q=0.2,en-US;q=0.1,sk;q=0.1", "content-type": "application/json", "cookie": f'{os.environ["COOKIE_INFO"]}', "if-modified-since": "Tue, 22 Aug 2023 07:18:52 GMT", "referer": f"https://civitai.com/user/{username}/models", "sec-ch-ua": "\"Not.A/Brand\";v=\"8\", \"Chromium\";v=\"114\", \"Google Chrome\";v=\"114\"", "sec-ch-ua-mobile": "?0", "sec-ch-ua-platform": "macOS", "sec-fetch-dest": "empty", "sec-fetch-mode": "cors", "sec-fetch-site": "same-origin", "user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36" } response = requests.get(url, headers=headers) return json.loads(response.text) def extract_huggingface_username(username): data = get_creator(username) links = data.get('result', {}).get('data', {}).get('json', {}).get('links', []) for link in links: url = link.get('url', '') if url.startswith('https://huggingface.co/') or url.startswith('https://www.huggingface.co/'): username = url.split('/')[-1] return username return None def check_civit_link(profile: Optional[gr.OAuthProfile], url): info, _ = process_url(url, do_download=False) hf_username = extract_huggingface_username(info['creator']) attributes_methods = dir(profile) if(not hf_username): no_username_text = 'Oops, your CivitAI profile seems to not have information about your Hugging Face account. Please visit https://civitai.com/user/account and include it there
' return no_username_text, gr.update(), gr.update(visible=True) if(profile.preferred_username != hf_username): unmatched_username_text = 'Oops, the Hugging Face account in your CivitAI profile seems to be different than the one your are using here. This Space only works for model authors to submit their own models to Hugging Face. If you do own the model, please visit https://civitai.com/user/account and update it there
' return unmatched_username_text, gr.update(), gr.update(visible=True) else: return '', gr.update(interactive=True), gr.update(visible=False) def swap_fill(profile: Optional[gr.OAuthProfile]): if profile is None: return gr.update(visible=True), gr.update(visible=False) else: return gr.update(visible=False), gr.update(visible=True) def show_output(): return gr.update(visible=True) css = ''' #login { font-size: 0px; width: 100% !important; margin: 0 auto; } #login:after { content: 'Authorize this app before uploading your model'; visibility: visible; display: block; font-size: var(--button-large-text-size); } #login:disabled{ font-size: var(--button-large-text-size); } #login:disabled:after{ content:'' } #disabled_upload{ opacity: 0.5; pointer-events:none; } ''' with gr.Blocks(css=css) as demo: gr.Markdown('''# Bring your CivitAI SDXL LoRA to Hugging Face Get diffusers compatibility, a free GPU-based Inference Widget and possibility to submit to the [LoRA the Explorer](https://huggingface.co/spaces/multimodalart/LoraTheExplorer) space ''') gr.LoginButton(elem_id="login") with gr.Column(elem_id="disabled_upload") as disabled_area: with gr.Row(): submit_source_civit = gr.Textbox( label="CivitAI model URL", info="URL of the CivitAI model, for now only SDXL LoRAs are supported", ) submit_button_civit = gr.Button("Upload model to Hugging Face and submit", interactive=False) with gr.Column(visible=False) as enabled_area: with gr.Row(): submit_source_civit = gr.Textbox( label="CivitAI model URL", info="URL of the CivitAI model, for now only SDXL LoRAs are supported", ) instructions = gr.HTML("") try_again_button = gr.Button("I have added my HF profile to my account", visible=False) submit_button_civit = gr.Button("Upload model to Hugging Face", interactive=False) output = gr.Markdown(label="Output progress", visible=False) demo.load(fn=swap_fill, outputs=[disabled_area, enabled_area]) submit_source_civit.change(fn=check_civit_link, inputs=[submit_source_civit], outputs=[instructions, submit_button_civit, try_again_button]) try_again_button.click(fn=check_civit_link, inputs=[submit_source_civit], outputs=[instructions, submit_button_civit, try_again_button]) submit_button_civit.click(fn=show_output, inputs=[], outputs=[output]).then(fn=upload_civit_to_hf, inputs=[submit_source_civit], outputs=[output]) demo.queue() demo.launch()