src/submission/submit.py

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, QUEUE_REPO_TEST
from src.submission.check_validity import (
    already_submitted_models,
    check_model_card,
    get_model_size,
    is_model_on_hub,
)

REQUESTED_MODELS = None
USERS_TO_SUBMISSION_DATES = None



def add_new_open_model_eval(
    model: str,
):
    """通过提交模型到评估队列,将信息自动保存到requests数据集中"""
    global REQUESTED_MODELS
    global USERS_TO_SUBMISSION_DATES
    if not REQUESTED_MODELS:
        REQUESTED_MODELS, USERS_TO_SUBMISSION_DATES = already_submitted_models(EVAL_REQUESTS_PATH)
    print(REQUESTED_MODELS)
    current_time = datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ")

    # Is the model info correctly filled?

    try:
        model_info = API.model_info(repo_id=model)
    except Exception:
        return styled_error("Could not get your model information. Please fill it up properly.")

    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_name": model,
        "model_show": model.split("/")[1],
        "open_source": True,
        "status": "PENDING",
        "submitted_time": str(current_time),
    }

    # Check for duplicate submission
    if f"{model}" in REQUESTED_MODELS:
        return styled_warning("This model has been already submitted.")

    print("Creating eval file")

    user_name = model.split("/")[0] 
    OUT_DIR = f"{EVAL_REQUESTS_PATH}/{user_name}"
    os.makedirs(OUT_DIR, exist_ok=True)
    out_path = f"{EVAL_REQUESTS_PATH}/{model}_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_TEST,
        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."
    )