civitai_to_hf / civitai_to_hf.py
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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, list_uniq
import re
from PIL import Image
import json
import pandas as pd
TEMP_DIR = "."
def parse_urls(s):
url_pattern = "https?://[\\w/:%#\\$&\\?\\(\\)~\\.=\\+\\-]+"
try:
urls = re.findall(url_pattern, s)
return list(urls)
except Exception:
return []
def to_urls(l: list[str]):
return "\n".join(l)
def uniq_urls(s):
return to_urls(list_uniq(parse_urls(s)))
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=f"Start uploading... {filename} to {repo_id}")
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
finally:
Path(filename).unlink()
return url
def download_file(dl_url, civitai_key, progress=gr.Progress(track_tqdm=True)):
download_dir = TEMP_DIR
progress(0, desc=f"Start downloading... {dl_url}")
output_filename = get_download_file(download_dir, dl_url, civitai_key)
return output_filename
def save_civitai_info(dl_url, filename, progress=gr.Progress(track_tqdm=True)):
json_str, html_str, image_path = get_civitai_json(dl_url, True, filename)
if not json_str: return "", "", ""
json_path = str(Path(TEMP_DIR, Path(filename).stem + ".json"))
html_path = str(Path(TEMP_DIR, Path(filename).stem + ".html"))
try:
with open(json_path, 'w') as f:
json.dump(json_str, f, indent=2)
with open(html_path, mode='w', encoding="utf-8") as f:
f.write(html_str)
return json_path, html_path, image_path
except Exception as e:
print(f"Error: Failed to save info file {json_path}, {html_path} {e}")
return "", "", ""
def upload_info_to_repo(dl_url, filename, repo_id, repo_type, is_private, progress=gr.Progress(track_tqdm=True)):
def upload_file(api, filename, repo_id, repo_type, hf_token):
if not Path(filename).exists(): return
api.upload_file(path_or_fileobj=filename, path_in_repo=Path(filename).name, repo_type=repo_type, revision="main", token=hf_token, repo_id=repo_id)
Path(filename).unlink()
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=f"Downloading info... {filename}")
json_path, html_path, image_path = save_civitai_info(dl_url, filename)
progress(0, desc=f"Start uploading info... {filename} to {repo_id}")
if not json_path: return
else: upload_file(api, json_path, repo_id, repo_type, hf_token)
if html_path: upload_file(api, html_path, repo_id, repo_type, hf_token)
if image_path: upload_file(api, image_path, repo_id, repo_type, hf_token)
progress(1, desc="Info uploaded.")
return
except Exception as e:
print(f"Error: Failed to upload info to {repo_id}. {e}")
gr.Warning(f"Error: Failed to upload info to {repo_id}. {e}")
return
def download_civitai(dl_url, civitai_key, hf_token, urls,
newrepo_id, repo_type="model", is_private=True, is_info=False, progress=gr.Progress(track_tqdm=True)):
if hf_token: set_token(hf_token)
else: set_token(os.environ.get("HF_TOKEN")) # default huggingface write token
if not civitai_key: civitai_key = os.environ.get("CIVITAI_API_KEY") # default Civitai API key
if not newrepo_id: newrepo_id = os.environ.get("HF_REPO") # default repo to upload
if not get_token() or not civitai_key: raise gr.Error("HF write token and Civitai API key is required.")
dl_urls = parse_urls(dl_url)
if not urls: urls = []
for u in dl_urls:
file = download_file(u, civitai_key)
if not Path(file).exists() or not Path(file).is_file(): continue
url = upload_safetensors_to_repo(file, newrepo_id, repo_type, is_private)
if url:
urls.append(url)
if is_info: upload_info_to_repo(u, file, newrepo_id, repo_type, is_private)
progress(1, desc="Processing...")
md = f'### Your repo: [{newrepo_id}]({"https://huggingface.co/datasets/" if repo_type == "dataset" else "https://huggingface.co/"}{newrepo_id})\n'
for u in urls:
md += f"- Uploaded [{str(u)}]({str(u)})\n"
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: 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
if user: params["username"] = user
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['description'] = model['description'] if 'description' in model.keys() else ""
item['dl_url'] = model['downloadUrl']
item['md'] = ""
if 'images' in model.keys() and len(model["images"]) != 0:
item['md'] += f'<img src="{model["images"][0]["url"]}#float" alt="thumbnail" width="150" height="240"><br>'
item['md'] += f'''Model URL: [https://civitai.com/models/{j["id"]}](https://civitai.com/models/{j["id"]})<br>Model Name: {item["name"]}<br>
Creator: {item["creator"]}<br>Tags: {", ".join(item["tags"])}<br>Base Model: {item["base_model"]}<br>Description: {item["description"]}'''
items.append(item)
return items
civitai_last_results = {}
def search_civitai(query, types, base_model=[], sort=CIVITAI_SORT[0], period=CIVITAI_PERIOD[0], tag="", user=""):
global civitai_last_results
items = search_on_civitai(query, types, base_model, 100, sort, period, tag, user)
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 get_civitai_json(dl_url: str, is_html: bool=False, image_baseurl: str=""):
if not image_baseurl: image_baseurl = dl_url
default = ("", "", "") if is_html else ""
if "https://civitai.com/api/download/models/" not in dl_url: return default
user_agent = get_user_agent()
headers = {'User-Agent': user_agent, 'content-type': 'application/json'}
base_url = 'https://civitai.com/api/v1/model-versions/'
params = {}
session = requests.Session()
retries = Retry(total=5, backoff_factor=1, status_forcelist=[500, 502, 503, 504])
session.mount("https://", HTTPAdapter(max_retries=retries))
url = base_url + str(dl_url.split("/")[-1])
try:
r = session.get(url, params=params, headers=headers, stream=True, timeout=(3.0, 15))
if not r.ok: return default
json = dict(r.json()).copy()
html = ""
image = ""
if "modelId" in json.keys():
url = f"https://civitai.com/models/{json['modelId']}"
r = session.get(url, params=params, headers=headers, stream=True, timeout=(3.0, 15))
if not r.ok: return json, html, image
html = r.text
if 'images' in json.keys() and len(json["images"]) != 0:
url = json["images"][0]["url"]
r = session.get(url, params=params, headers=headers, stream=True, timeout=(3.0, 15))
if not r.ok: return json, html, image
image_temp = str(Path(TEMP_DIR, "image" + Path(url.split("/")[-1]).suffix))
image = str(Path(TEMP_DIR, Path(image_baseurl.split("/")[-1]).stem + ".png"))
with open(image_temp, 'wb') as f:
f.write(r.content)
Image.open(image_temp).convert('RGBA').save(image)
return json, html, image
except Exception as e:
print(e)
return default
def get_civitai_tag():
default = [""]
user_agent = get_user_agent()
headers = {'User-Agent': user_agent, 'content-type': 'application/json'}
base_url = 'https://civitai.com/api/v1/tags'
params = {'limit': 200}
session = requests.Session()
retries = Retry(total=5, backoff_factor=1, status_forcelist=[500, 502, 503, 504])
session.mount("https://", HTTPAdapter(max_retries=retries))
url = base_url
try:
r = session.get(url, params=params, headers=headers, stream=True, timeout=(3.0, 15))
if not r.ok: return default
j = dict(r.json()).copy()
if "items" not in j.keys(): return default
items = []
for item in j["items"]:
items.append([str(item.get("name", "")), int(item.get("modelCount", 0))])
df = pd.DataFrame(items)
df.sort_values(1, ascending=False)
tags = df.values.tolist()
tags = [""] + [l[0] for l in tags]
return tags
except Exception as e:
print(e)
return default
def select_civitai_item(results: list[str]):
if "http" not in "".join(results): return gr.update(value="None", visible=True)
result = civitai_last_results.get(results[-1], "None")
md = result['md'] if result else ""
json = {}
#json, html, image = get_civitai_json(results[-1], True) # for debugging
return gr.update(value=md, visible=True), gr.update(value=json, visible=False)
def add_civitai_item(results: list[str], dl_url: str):
if "http" not in "".join(results): return gr.update(value=dl_url)
new_url = dl_url if dl_url else ""
for result in results:
if "http" not in result: continue
new_url += f"\n{result}" if new_url else f"{result}"
new_url = uniq_urls(new_url)
return gr.update(value=new_url)