import requests import os import gradio as gr from huggingface_hub import HfApi from slugify import slugify import gradio as gr import uuid from typing import Optional 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) print(f"{filename} downloaded.") except requests.exceptions.RequestException as e: print(f"Error downloading file: {e}") def process_url(url, download_files=True, folder="."): json_data = get_json_data(url) if json_data: if check_nsfw(json_data): info = extract_info(json_data) if info: if(download_files): 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) create_readme(info, downloaded_files, folder) try: api = HfApi(token=hf_token) username = api.whoami()["name"] slug_name = slugify(info["name"]) repo_id = f"{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" ) except: raise gr.Error("something went wrong") return "Model uploaded!" def check_civit_link(url): info, _ = process_url(url, download_files=False) return info["creator"] 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) 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.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, make sure it is a SDXL LoRA", ) #is_author = gr.Checkbox(label="Are you the model author?", info="If you are not the author, a disclaimer with information about the author and the CivitAI source will be added", value=False) submit_button_civit = gr.Button("Upload model to Hugging Face and submit") output = gr.Textbox(label="Output progress") 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, make sure it is a SDXL LoRA", ) #is_author = gr.Checkbox(label="Are you the model author?", info="If you are not the author, a disclaimer with information about the author and the CivitAI source will be added", value=False) instructions = gr.HTML("") submit_button_civit = gr.Button("Upload model to Hugging Face") output = gr.Textbox(label="Output progress") demo.load(fn=swap_fill, outputs=[disabled_area, enabled_area]) submit_source_civit.change(fn=check_civit_link, inputs=[submit_source_civit], output=[instructions]) submit_button_civit.click(fn=upload_civit_to_hf, inputs=[submit_source_civit], outputs=[output]) demo.queue() demo.launch()