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| import requests | |
| import os | |
| import gradio as gr | |
| from huggingface_hub import update_repo_visibility, whoami, upload_folder, create_repo, upload_file, update_repo_visibility | |
| from slugify import slugify | |
| import gradio as gr | |
| import re | |
| import uuid | |
| from typing import Optional | |
| import json | |
| from bs4 import BeautifulSoup | |
| TRUSTED_UPLOADERS = ["KappaNeuro", "CiroN2022", "multimodalart", "Norod78", "joachimsallstrom", "blink7630", "e-n-v-y", "DoctorDiffusion", "RalFinger", "artificialguybr"] | |
| def get_json_data(url): | |
| url_split = url.split('/') | |
| 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, profile): | |
| if json_data["nsfw"]: | |
| return False | |
| print(profile) | |
| if(profile.username in TRUSTED_UPLOADERS): | |
| return True | |
| for model_version in json_data["modelVersions"]: | |
| for image in model_version["images"]: | |
| if image["nsfwLevel"] > 5: | |
| return False | |
| return True | |
| def get_prompts_from_image(image_id): | |
| url = f'https://civitai.com/images/{image_id}' | |
| response = requests.get(url) | |
| soup = BeautifulSoup(response.text, 'html.parser') | |
| content = soup.find_all(class_='mantine-Code-root mantine-Code-block mantine-2v44jn') | |
| if(content): | |
| if(len(content) > 1): | |
| return content[0].text, content[1].text | |
| else: | |
| return content[0].text, "" | |
| else: | |
| return "", "" | |
| 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", "SD 1.5", "SD 1.4", "SD 2.1", "SD 2.0", "SD 2.0 768", "SD 2.1 768"]: | |
| for file in model_version["files"]: | |
| print(file) | |
| if "primary" in file: | |
| # Start by adding the primary file to the list | |
| urls_to_download = [{"url": file["downloadUrl"], "filename": file["name"], "type": "weightName"}] | |
| # Then append all image URLs to the list | |
| for image in model_version["images"]: | |
| image_id = image["url"].split("/")[-1].split(".")[0] | |
| prompt, negative_prompt = get_prompts_from_image(image_id) | |
| if image["nsfwLevel"] > 5: | |
| pass #ugly before checking the actual logic | |
| else: | |
| urls_to_download.append({ | |
| "url": image["url"], | |
| "filename": os.path.basename(image["url"]), | |
| "type": "imageName", | |
| "prompt": prompt, #if "meta" in image and "prompt" in image["meta"] else "" | |
| "negative_prompt": negative_prompt | |
| }) | |
| model_mapping = { | |
| "SDXL 1.0": "stabilityai/stable-diffusion-xl-base-1.0", | |
| "SDXL 0.9": "stabilityai/stable-diffusion-xl-base-1.0", | |
| "SD 1.5": "runwayml/stable-diffusion-v1-5", | |
| "SD 1.4": "CompVis/stable-diffusion-v1-4", | |
| "SD 2.1": "stabilityai/stable-diffusion-2-1-base", | |
| "SD 2.0": "stabilityai/stable-diffusion-2-base", | |
| "SD 2.1 768": "stabilityai/stable-diffusion-2-1", | |
| "SD 2.0 768": "stabilityai/stable-diffusion-2" | |
| } | |
| base_model = model_mapping[model_version["baseModel"]] | |
| info = { | |
| "urls_to_download": urls_to_download, | |
| "id": model_version["id"], | |
| "baseModel": base_model, | |
| "modelId": model_version.get("modelId", ""), | |
| "name": json_data["name"], | |
| "description": json_data["description"], | |
| "trainedWords": model_version["trainedWords"] if "trainedWords" in model_version else [], | |
| "creator": json_data["creator"]["username"], | |
| "tags": json_data["tags"], | |
| "allowNoCredit": json_data["allowNoCredit"], | |
| "allowCommercialUse": json_data["allowCommercialUse"], | |
| "allowDerivatives": json_data["allowDerivatives"], | |
| "allowDifferentLicense": json_data["allowDifferentLicense"] | |
| } | |
| return info | |
| return None | |
| def download_files(info, folder="."): | |
| downloaded_files = { | |
| "imageName": [], | |
| "imagePrompt": [], | |
| "imageNegativePrompt": [], | |
| "weightName": [] | |
| } | |
| for item in info["urls_to_download"]: | |
| download_file(item["url"], item["filename"], folder) | |
| downloaded_files[item["type"]].append(item["filename"]) | |
| if(item["type"] == "imageName"): | |
| prompt_clean = re.sub(r'<.*?>', '', item["prompt"]) | |
| negative_prompt_clean = re.sub(r'<.*?>', '', item["negative_prompt"]) | |
| downloaded_files["imagePrompt"].append(prompt_clean) | |
| downloaded_files["imageNegativePrompt"].append(negative_prompt_clean) | |
| return downloaded_files | |
| def download_file(url, filename, folder="."): | |
| headers = {} | |
| try: | |
| response = requests.get(url, headers=headers) | |
| response.raise_for_status() | |
| except requests.exceptions.HTTPError as e: | |
| print(e) | |
| if response.status_code == 401: | |
| headers['Authorization'] = f'Bearer {os.environ["CIVITAI_API"]}' | |
| try: | |
| response = requests.get(url, headers=headers) | |
| response.raise_for_status() | |
| except requests.exceptions.RequestException as e: | |
| raise gr.Error(f"Error downloading file: {e}") | |
| else: | |
| raise gr.Error(f"Error downloading file: {e}") | |
| except requests.exceptions.RequestException as e: | |
| raise gr.Error(f"Error downloading file: {e}") | |
| with open(f"{folder}/{filename}", 'wb') as f: | |
| f.write(response.content) | |
| def process_url(url, profile, do_download=True, folder="."): | |
| json_data = get_json_data(url) | |
| if json_data: | |
| if check_nsfw(json_data, profile): | |
| 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, user_repo_id, link_civit=False, is_author=True, folder="."): | |
| readme_content = "" | |
| original_url = f"https://civitai.com/models/{info['modelId']}" | |
| link_civit_disclaimer = f'([CivitAI]({original_url}))' | |
| 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:' | |
| default_tags = ["text-to-image", "stable-diffusion", "lora", "diffusers", "template:sd-lora", "migrated"] | |
| civit_tags = [t.replace(":", "") for t in info["tags"] if t not in default_tags] | |
| tags = default_tags + civit_tags | |
| unpacked_tags = "\n- ".join(tags) | |
| trained_words = info['trainedWords'] if 'trainedWords' in info and info['trainedWords'] else [] | |
| formatted_words = ', '.join(f'`{word}`' for word in trained_words) | |
| if formatted_words: | |
| trigger_words_section = f"""## Trigger words | |
| You should use {formatted_words} to trigger the image generation. | |
| """ | |
| else: | |
| trigger_words_section = "" | |
| widget_content = "" | |
| for index, (prompt, negative_prompt, image) in enumerate(zip(downloaded_files["imagePrompt"], downloaded_files["imageNegativePrompt"], downloaded_files["imageName"])): | |
| escaped_prompt = prompt.replace("'", "''") | |
| negative_prompt_content = f"""parameters: | |
| negative_prompt: {negative_prompt} | |
| """ if negative_prompt else "" | |
| widget_content += f"""- text: '{escaped_prompt if escaped_prompt else ' ' }' | |
| {negative_prompt_content} | |
| output: | |
| url: >- | |
| {image} | |
| """ | |
| content = f"""--- | |
| license: other | |
| license_name: bespoke-lora-trained-license | |
| license_link: https://multimodal.art/civitai-licenses?allowNoCredit={info["allowNoCredit"]}&allowCommercialUse={info["allowCommercialUse"][0] if info["allowCommercialUse"] else 1}&allowDerivatives={info["allowDerivatives"]}&allowDifferentLicense={info["allowDifferentLicense"]} | |
| tags: | |
| - {unpacked_tags} | |
| base_model: {info["baseModel"]} | |
| instance_prompt: {info['trainedWords'][0] if 'trainedWords' in info and len(info['trainedWords']) > 0 else ''} | |
| widget: | |
| {widget_content} | |
| --- | |
| # {info["name"]} | |
| <Gallery /> | |
| {non_author_disclaimer if not is_author else ''} | |
| {link_civit_disclaimer if link_civit else ''} | |
| ## Model description | |
| {info["description"]} | |
| {trigger_words_section} | |
| ## Download model | |
| Weights for this model are available in Safetensors format. | |
| [Download](/{user_repo_id}/tree/main) them in the Files & versions tab. | |
| ## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers) | |
| ```py | |
| from diffusers import AutoPipelineForText2Image | |
| import torch | |
| pipeline = AutoPipelineForText2Image.from_pretrained('{info["baseModel"]}', torch_dtype=torch.float16).to('cuda') | |
| pipeline.load_lora_weights('{user_repo_id}', weight_name='{downloaded_files["weightName"][0]}') | |
| image = pipeline('{prompt if prompt else (formatted_words if formatted_words else 'Your custom prompt')}').images[0] | |
| ``` | |
| For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters) | |
| """ | |
| #for index, (image, prompt) in enumerate(zip(downloaded_files["imageName"], downloaded_files["imagePrompt"])): | |
| # if index == 1: | |
| # content += f"## Image examples for the model:\n\n> {prompt}\n" | |
| # elif index > 1: | |
| # content += f"\n\n> {prompt}\n" | |
| readme_content += content + "\n" | |
| with open(f"{folder}/README.md", "w") as file: | |
| file.write(readme_content) | |
| 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 response.json() | |
| 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, profile, do_download=False) | |
| hf_username = extract_huggingface_username(info['creator']) | |
| attributes_methods = dir(profile) | |
| if(profile.username == "multimodalart"): | |
| return '', gr.update(interactive=True), gr.update(visible=False), gr.update(visible=True) | |
| if(not hf_username): | |
| no_username_text = f'If you are {info["creator"]} on CivitAI, hi! Your CivitAI profile seems to not have information about your Hugging Face account. Please visit <a href="https://civitai.com/user/account" target="_blank">https://civitai.com/user/account</a> and include your 🤗 username there, here\'s mine:<br><img width="60%" src="https://i.imgur.com/hCbo9uL.png" /><br>(if you are not {info["creator"]}, you cannot submit their model at this time)' | |
| return no_username_text, gr.update(interactive=False), gr.update(visible=True), gr.update(visible=False) | |
| if(profile.username != hf_username): | |
| unmatched_username_text = '<h4>Oops, the Hugging Face account in your CivitAI profile seems to be different than the one your are using here. Please visit <a href="https://civitai.com/user/account">https://civitai.com/user/account</a> and update it there to match your Hugging Face account<br><img src="https://i.imgur.com/hCbo9uL.png" /></h4>' | |
| return unmatched_username_text, gr.update(interactive=False), gr.update(visible=True), gr.update(visible=False) | |
| else: | |
| return '', gr.update(interactive=True), gr.update(visible=False), gr.update(visible=True) | |
| 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) | |
| def list_civit_models(username): | |
| url = f"https://civitai.com/api/v1/models?username={username}&limit=100" | |
| json_models_list = [] | |
| while url: | |
| response = requests.get(url) | |
| data = response.json() | |
| # Add current page items to the list | |
| json_models_list.extend(data.get('items', [])) | |
| # Check if there is a nextPage URL in the metadata | |
| metadata = data.get('metadata', {}) | |
| url = metadata.get('nextPage', None) | |
| urls = "" | |
| for model in json_models_list: | |
| urls += f'https://civitai.com/models/{model["id"]}/{slugify(model["name"])}\n' | |
| return urls | |
| def upload_civit_to_hf(profile: Optional[gr.OAuthProfile], oauth_token: gr.OAuthToken, url, link_civit=False): | |
| if not profile.name: | |
| return gr.Error("Are you sure you are logged in?") | |
| folder = str(uuid.uuid4()) | |
| os.makedirs(folder, exist_ok=False) | |
| gr.Info(f"Starting download of model {url}") | |
| info, downloaded_files = process_url(url, profile, folder=folder) | |
| username = {profile.username} | |
| slug_name = slugify(info["name"]) | |
| user_repo_id = f"{profile.username}/{slug_name}" | |
| create_readme(info, downloaded_files, user_repo_id, link_civit, folder=folder) | |
| try: | |
| create_repo(repo_id=user_repo_id, private=True, exist_ok=True, token=oauth_token.token) | |
| gr.Info(f"Starting to upload repo {user_repo_id} to Hugging Face...") | |
| upload_folder( | |
| folder_path=folder, | |
| repo_id=user_repo_id, | |
| repo_type="model", | |
| token=oauth_token.token | |
| ) | |
| update_repo_visibility(repo_id=user_repo_id, private=False, token=oauth_token.token) | |
| gr.Info(f"Model uploaded!") | |
| except Exception as e: | |
| print(e) | |
| raise gr.Error("Your Hugging Face Token expired. Log out and in again to upload your models.") | |
| return f'''# Model uploaded to 🤗! | |
| ## Access it here [{user_repo_id}](https://huggingface.co/{user_repo_id}) ''' | |
| def bulk_upload(profile: Optional[gr.OAuthProfile], oauth_token: gr.OAuthToken, urls, link_civit=False): | |
| urls = urls.split("\n") | |
| print(urls) | |
| upload_results = "" | |
| for url in urls: | |
| if(url): | |
| try: | |
| upload_result = upload_civit_to_hf(profile, oauth_token, url, link_civit) | |
| upload_results += upload_result+"\n" | |
| except Exception as e: | |
| gr.Warning(f"Error uploading the model {url}") | |
| return upload_results | |
| css = ''' | |
| #login { | |
| width: 100% !important; | |
| margin: 0 auto; | |
| } | |
| #disabled_upload{ | |
| opacity: 0.5; | |
| pointer-events:none; | |
| } | |
| ''' | |
| with gr.Blocks(css=css) as demo: | |
| gr.Markdown('''# Upload your CivitAI LoRA to Hugging Face 🤗 | |
| By uploading your LoRAs to Hugging Face you get diffusers compatibility, a free GPU-based Inference Widget, and possibility to submit your model to the [LoRA the Explorer](https://huggingface.co/spaces/multimodalart/LoraTheExplorer) ✨ | |
| ''') | |
| gr.LoginButton(elem_id="login") | |
| with gr.Column(elem_id="disabled_upload") as disabled_area: | |
| with gr.Row(): | |
| submit_source_civit = gr.Textbox( | |
| placeholder="https://civitai.com/models/144684/pixelartredmond-pixel-art-loras-for-sd-xl", | |
| label="CivitAI model URL", | |
| info="URL of the CivitAI LoRA", | |
| ) | |
| submit_button_civit = gr.Button("Upload model to Hugging Face and submit", interactive=False) | |
| with gr.Column(visible=False) as enabled_area: | |
| with gr.Column(): | |
| submit_source_civit = gr.Textbox( | |
| placeholder="https://civitai.com/models/144684/pixelartredmond-pixel-art-loras-for-sd-xl", | |
| label="CivitAI model URL", | |
| info="URL of the CivitAI LoRA", | |
| ) | |
| with gr.Accordion("Bulk upload (bring in multiple LoRAs)", open=False): | |
| civit_username_to_bulk = gr.Textbox(label="CivitAI username (optional)", info="Type your CivitAI username here to automagically fill the bulk models URLs list below (optional, you can paste links down here directly)") | |
| submit_bulk_civit = gr.Textbox( | |
| label="CivitAI bulk models URLs", | |
| info="Add one URL per line", | |
| lines=6, | |
| ) | |
| link_civit = gr.Checkbox(label="Link back to CivitAI?", value=False) | |
| bulk_button = gr.Button("Bulk upload") | |
| instructions = gr.HTML("") | |
| try_again_button = gr.Button("I have added my HF profile to my account (it may take 1 minute to refresh)", 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], queue=False) | |
| submit_source_civit.change(fn=check_civit_link, inputs=[submit_source_civit], outputs=[instructions, submit_button_civit, try_again_button, submit_button_civit]) | |
| civit_username_to_bulk.change(fn=list_civit_models, inputs=[civit_username_to_bulk], outputs=[submit_bulk_civit]) | |
| try_again_button.click(fn=check_civit_link, inputs=[submit_source_civit], outputs=[instructions, submit_button_civit, try_again_button, submit_button_civit]) | |
| submit_button_civit.click(fn=show_output, inputs=[], outputs=[output]).then(fn=upload_civit_to_hf, inputs=[submit_source_civit, link_civit], outputs=[output]) | |
| bulk_button.click(fn=show_output, inputs=[], outputs=[output]).then(fn=bulk_upload, inputs=[submit_bulk_civit, link_civit], outputs=[output]) | |
| #gr.LogoutButton(elem_id="logout") | |
| demo.queue(default_concurrency_limit=50) | |
| demo.launch() |