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import json
import os
from datetime import datetime, timezone
from src.display.formatting import styled_error, styled_message, styled_warning
from src.envs import API, EVAL_REQUESTS_PATH, TOKEN, QUEUE_REPO
from src.submission.check_validity import (
already_submitted_models,
check_model_card,
get_model_size,
)
REQUESTED_MODELS = None
USERS_TO_SUBMISSION_DATES = None
def add_new_eval(
model: str,
link: str,
):
global REQUESTED_MODELS
global USERS_TO_SUBMISSION_DATES
if not REQUESTED_MODELS:
REQUESTED_MODELS, USERS_TO_SUBMISSION_DATES = already_submitted_models(EVAL_REQUESTS_PATH)
user_name = ""
model_path = model
if model_path.startswith('https:'):
return styled_error("Huggingface model should be referred to by its name, not by its URL")
if "/" in model:
user_name = model.split("/")[0]
model_path = model.split("/")[1]
current_time = datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ")
revision = "main"
# Is the model info correctly filled?
try:
model_info = API.model_info(repo_id=model, revision=revision)
except Exception:
return styled_error("Could not get your model information. Please fill it up properly.")
model_size = get_model_size(model_info=model_info)
# Were the model card and license filled?
try:
license = model_info.cardData["license"]
except Exception:
return styled_error("Please select a license for your model")
modelcard_OK, error_msg = check_model_card(model)
if not modelcard_OK:
return styled_error(error_msg)
# Seems good, creating the eval
print("Adding new eval")
eval_entry = {
"model": model,
"revision": revision,
"link": link,
"status": "PENDING",
"submitted_time": current_time,
"params": model_size,
"license": license,
"private": False,
}
# Check for duplicate submission
if f"{model}_{revision}" in REQUESTED_MODELS:
return styled_warning("This model has been already submitted.")
print("Creating eval file")
OUT_DIR = f"{EVAL_REQUESTS_PATH}/{user_name}"
os.makedirs(OUT_DIR, exist_ok=True)
out_path = f"{OUT_DIR}/{model_path}_eval_request_False.json"
with open(out_path, "w") as f:
f.write(json.dumps(eval_entry))
print("Uploading eval file")
API.upload_file(
path_or_fileobj=out_path,
path_in_repo=out_path.split("eval-queue/")[1],
repo_id=QUEUE_REPO,
repo_type="dataset",
commit_message=f"Add {model} to eval queue",
)
# Remove the local file
os.remove(out_path)
return styled_message(
"Your request has been submitted to the evaluation queue!\nPlease wait for up to an hour for the model to show in the PENDING list."
)
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