Dashboard / dumpy.py
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App init.
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import json
import logging
import os
import argilla as rg
from huggingface_hub import HfApi
logger = logging.getLogger(__name__)
logger.setLevel(logging.INFO)
if __name__ == "__main__":
logger.info("*** Initializing Argilla session ***")
rg.init(
api_url=os.getenv("ARGILLA_API_URL"),
api_key=os.getenv("ARGILLA_API_KEY"),
extra_headers={"Authorization": f"Bearer {os.getenv('HF_TOKEN')}"},
)
logger.info("*** Fetching dataset from Argilla ***")
dataset = rg.FeedbackDataset.from_argilla(
os.getenv("SOURCE_DATASET"),
workspace=os.getenv("SOURCE_WORKSPACE"),
)
logger.info("*** Filtering records by `response_status` ***")
dataset = dataset.filter_by(response_status=["submitted"]) # type: ignore
logger.info("*** Calculating users and annotation count ***")
output = {}
for record in dataset.records:
for response in record.responses:
if response.user_id not in output:
output[response.user_id] = 0
output[response.user_id] += 1
for key in list(output.keys()):
output[rg.User.from_id(key).username] = output.pop(key)
logger.info("*** Users and annotation count successfully calculated! ***")
logger.info("*** Dumping Python dict into `stats.json` ***")
with open("stats.json", "w") as file:
json.dump(output, file, indent=4)
logger.info("*** Uploading `stats.json` to Hugging Face Hub ***")
api = HfApi(token=os.getenv("HF_TOKEN"))
api.upload_file(
path_or_fileobj="stats.json",
path_in_repo="stats.json",
repo_id="DIBT/prompt-collective-dashboard",
repo_type="space",
)
logger.info("*** `stats.json` successfully uploaded to Hugging Face Hub! ***")