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import json | |
from tempfile import mktemp | |
import argilla as rg | |
from huggingface_hub import HfApi | |
from defaults import REMOTE_CODE_PATHS, SEED_DATA_PATH | |
hf_api = HfApi() | |
with open("DATASET_README_BASE.md") as f: | |
DATASET_README_BASE = f.read() | |
def create_readme(domain_seed_data, project_name, domain): | |
# create a readme for the project that shows the domain and project name | |
readme = DATASET_README_BASE | |
readme += f"# {project_name}\n\n## Domain: {domain}" | |
perspectives = domain_seed_data.get("perspectives") | |
topics = domain_seed_data.get("topics") | |
examples = domain_seed_data.get("examples") | |
if perspectives: | |
readme += "\n\n## Perspectives\n\n" | |
for p in perspectives: | |
readme += f"- {p}\n" | |
if topics: | |
readme += "\n\n## Topics\n\n" | |
for t in topics: | |
readme += f"- {t}\n" | |
if examples: | |
readme += "\n\n## Examples\n\n" | |
for example in examples: | |
readme += f"### {example['question']}\n\n{example['answer']}\n\n" | |
temp_file = mktemp() | |
with open(temp_file, "w") as f: | |
f.write(readme) | |
return temp_file | |
def setup_dataset_on_hub(repo_id, hub_token): | |
# create an empty dataset repo on the hub | |
hf_api.create_repo( | |
repo_id=repo_id, | |
token=hub_token, | |
repo_type="dataset", | |
exist_ok=True, | |
) | |
def push_dataset_to_hub( | |
domain_seed_data_path, | |
project_name, | |
domain, | |
pipeline_path, | |
hub_username, | |
hub_token: str, | |
): | |
repo_id = f"{hub_username}/{project_name}" | |
setup_dataset_on_hub(repo_id=repo_id, hub_token=hub_token) | |
# upload the seed data and readme to the hub | |
hf_api.upload_file( | |
path_or_fileobj=domain_seed_data_path, | |
path_in_repo="seed_data.json", | |
token=hub_token, | |
repo_id=repo_id, | |
repo_type="dataset", | |
) | |
# upload the readme to the hub | |
domain_seed_data = json.load(open(domain_seed_data_path)) | |
hf_api.upload_file( | |
path_or_fileobj=create_readme( | |
domain_seed_data=domain_seed_data, project_name=project_name, domain=domain | |
), | |
path_in_repo="README.md", | |
token=hub_token, | |
repo_id=repo_id, | |
repo_type="dataset", | |
) | |
def push_pipeline_to_hub( | |
pipeline_path, | |
hub_username, | |
hub_token: str, | |
project_name, | |
): | |
repo_id = f"{hub_username}/{project_name}" | |
# upload the pipeline to the hub | |
hf_api.upload_file( | |
path_or_fileobj=pipeline_path, | |
path_in_repo="pipeline.py", | |
token=hub_token, | |
repo_id=repo_id, | |
repo_type="dataset", | |
) | |
for code_path in REMOTE_CODE_PATHS: | |
hf_api.upload_file( | |
path_or_fileobj=code_path, | |
path_in_repo=code_path, | |
token=hub_token, | |
repo_id=repo_id, | |
repo_type="dataset", | |
) | |
print(f"Dataset uploaded to {repo_id}") | |
def pull_seed_data_from_repo(repo_id, hub_token): | |
# pull the dataset repo from the hub | |
hf_api.hf_hub_download( | |
repo_id=repo_id, token=hub_token, repo_type="dataset", filename=SEED_DATA_PATH | |
) | |
return json.load(open(SEED_DATA_PATH)) | |
def push_argilla_dataset_to_hub( | |
name: str, | |
repo_id: str, | |
url: str, | |
api_key: str, | |
hub_token: str, | |
workspace: str = "admin", | |
): | |
rg.init(api_url=url, api_key=api_key) | |
feedback_dataset = rg.FeedbackDataset.from_argilla(name=name, workspace=workspace) | |
local_dataset = feedback_dataset.pull() | |
local_dataset.push_to_huggingface(repo_id=repo_id, token=hub_token) | |
def push_pipeline_params( | |
pipeline_params, | |
hub_username, | |
hub_token: str, | |
project_name, | |
): | |
repo_id = f"{hub_username}/{project_name}" | |
temp_path = mktemp() | |
with open(temp_path, "w") as f: | |
json.dump(pipeline_params, f) | |
# upload the pipeline to the hub | |
hf_api.upload_file( | |
path_or_fileobj=temp_path, | |
path_in_repo="pipeline_params.json", | |
token=hub_token, | |
repo_id=repo_id, | |
repo_type="dataset", | |
) | |
print(f"Pipeline params uploaded to {repo_id}") | |