trackio-1234 / deploy.py
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Upload folder using huggingface_hub
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import io
import os
from importlib.resources import files
from pathlib import Path
import gradio
import huggingface_hub
def deploy_as_space(
title: str,
dataset_id: str | None = None,
):
if (
os.getenv("SYSTEM") == "spaces"
): # in case a repo with this function is uploaded to spaces
return
trackio_path = files("trackio")
hf_api = huggingface_hub.HfApi()
whoami = None
login = False
try:
whoami = hf_api.whoami()
if whoami["auth"]["accessToken"]["role"] != "write":
login = True
except OSError:
login = True
if login:
print("Need 'write' access token to create a Spaces repo.")
huggingface_hub.login(add_to_git_credential=False)
whoami = hf_api.whoami()
space_id = huggingface_hub.create_repo(
title,
space_sdk="gradio",
repo_type="space",
exist_ok=True,
).repo_id
assert space_id == title # not sure why these would differ
with open(Path(trackio_path, "README.md"), "r") as f:
readme_content = f.read()
readme_content = readme_content.replace("{GRADIO_VERSION}", gradio.__version__)
readme_buffer = io.BytesIO(readme_content.encode("utf-8"))
hf_api.upload_file(
path_or_fileobj=readme_buffer,
path_in_repo="README.md",
repo_id=space_id,
repo_type="space",
)
huggingface_hub.utils.disable_progress_bars()
hf_api.upload_folder(
repo_id=space_id,
repo_type="space",
folder_path=trackio_path,
ignore_patterns=["README.md"],
)
hf_token = huggingface_hub.utils.get_token()
if hf_token is not None:
huggingface_hub.add_space_secret(space_id, "HF_TOKEN", hf_token)
if dataset_id is not None:
huggingface_hub.add_space_variable(space_id, "TRACKIO_DATASET_ID", dataset_id)
# So that the dataset id is available to the sqlite_storage.py file
# if running locally as well.
os.environ["TRACKIO_DATASET_ID"] = dataset_id