src/submission/submit.py

import json
import yaml
import os
import re
from datetime import datetime, timezone, timedelta
from typing import Optional
from src.display.formatting import styled_error, styled_message, styled_warning
from src.envs import API, EVAL_REQUESTS_PATH, FAILED_EVAL_REQUESTS_PATH, TOKEN, FAILED_QUEUE_REPO, QUEUE_REPO, REPO_ID
from src.submission.check_validity import (
    already_submitted_models,
    check_model_card,
    get_model_size
)
import gradio as gr
from utils import download_with_restart
from huggingface_hub import snapshot_download

REQUESTED_MODELS = None
USERS_TO_SUBMISSION_DATES = None

def restart_space():
    API.restart_space(repo_id=REPO_ID)

def add_new_eval_option(
    contact_email: str,
    model: str,
    model_type: str,
    think_type: str,
    precision: str,
    response_prefix: str,
    requirements: str,
    user_state: str,
    organization_list: list,
    yml_textbox: str,
    upbox,
):
    
    ERROR_MESSAGE = None

    # Validate email format
    email_regex = r"^[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Za-z]{2,}$"
    if not re.match(email_regex, contact_email):
        if ERROR_MESSAGE is None:
            ERROR_MESSAGE = "Please provide a valid email address."

    # Synchronize: Just before submission, copy the latest QUEUE_REPO to EVAL_REQUESTS_PATH
    download_with_restart(
        snapshot_download,
        repo_id=QUEUE_REPO,
        local_dir=EVAL_REQUESTS_PATH,
        repo_type="dataset",
        token=TOKEN,
        restart_func=restart_space
    )

    # Synchronize: Just before submission, copy the latest FAILED_QUEUE_REPO to FAILED_EVAL_REQUESTS_PATH
    download_with_restart(
        snapshot_download,
        repo_id=FAILED_QUEUE_REPO,
        local_dir=FAILED_EVAL_REQUESTS_PATH,
        repo_type="dataset",
        token=TOKEN,
        restart_func=restart_space
    )

    REQUESTED_MODELS, USERS_TO_SUBMISSION_DATES = already_submitted_models(EVAL_REQUESTS_PATH)

    user_name = ""
    model_path = model
    if "/" in model:
        user_name = model.split("/")[0]
        model_path = model.split("/")[1]

    precision = precision.split(" ")[0]
    KST = timezone(timedelta(hours=9))
    current_time = datetime.now(KST).strftime("%Y-%m-%dT%H:%M:%S %z")

    # Remove space in benchmark name
    benchmark = "TRUEBench"

    # Check submitter qualification

    if user_name != user_state and user_name not in organization_list:
        if ERROR_MESSAGE is None:
            ERROR_MESSAGE = "The submitter does not have submission rights for this model."
        
    # Does the organization submit more than three times in a day?
    submission_times = [item['submitted_time'] for item in USERS_TO_SUBMISSION_DATES[user_name] if item['benchmark'] == benchmark]
    submission_cnt = 0
    for i in range(len(submission_times)):
        hours_diff = (datetime.strptime(current_time, "%Y-%m-%dT%H:%M:%S %z") - datetime.strptime(submission_times[i], "%Y-%m-%dT%H:%M:%S %z")).total_seconds() / 3600
        if hours_diff <= 24:
            submission_cnt += 1
    if submission_cnt >= 3:
        if ERROR_MESSAGE is None:
            ERROR_MESSAGE = "The organization already submitted three times for this benchmark today."

    # Does the model actually exist?
    revision = "main"

    # Is the model info correctly filled?
    model_info = None
    model_size = "Unknown"
    try:
        model_info = API.model_info(repo_id=model, revision=revision)
        model_size = get_model_size(model_info=model_info, precision=precision)
    except Exception:
        if ERROR_MESSAGE is None:
            ERROR_MESSAGE = "Could not get your model information. Please fill it up properly."

    # Were the model card and license filled?
    license = "Unknown"
    if model_info is not None:
        try:
            license = model_info.cardData["license"]
        except Exception:
            if ERROR_MESSAGE is None:
                ERROR_MESSAGE = "Please select a license for your model."

        modelcard_OK, error_msg = check_model_card(model)
        if not modelcard_OK:
            if ERROR_MESSAGE is None:
                ERROR_MESSAGE = error_msg
    
    # Response prefix check
    if think_type == "On":
        if response_prefix == "":
            if ERROR_MESSAGE is None:
                ERROR_MESSAGE = "It is required to fill in the response prefix when 'Think' is 'On'."
    else:
        response_prefix = ""
        
    # Handle YAML config input (file or textbox)
    config_dict = None

    # Case 1: File uploaded
    if upbox is not None and getattr(upbox, "name", ""):
        file_name = upbox.name
        if not file_name.lower().endswith(".yaml") and not file_name.lower().endswith(".yml"):
            if ERROR_MESSAGE is None:
                ERROR_MESSAGE = "Please submit a .yaml or .yml file."
        try:
            with open(file_name, 'r', encoding='utf-8') as f:
                config_dict = yaml.safe_load(f)
        except yaml.YAMLError:
            if ERROR_MESSAGE is None:
                ERROR_MESSAGE = "The file is not a valid YAML format."
        except Exception as e:
            if ERROR_MESSAGE is None:
                ERROR_MESSAGE = f"An error occurred while reading the file. {e}"
        if config_dict is None:
            if ERROR_MESSAGE is None:
                ERROR_MESSAGE = "The YAML file is empty or invalid."
    else:
        # Case 2: No file uploaded
        if not yml_textbox or not yml_textbox.strip():
            if ERROR_MESSAGE is None:
                ERROR_MESSAGE = "Please fill in the configuration box or submit a YAML file."
        try:
            config_dict = yaml.safe_load(yml_textbox)
        except yaml.YAMLError:
            if ERROR_MESSAGE is None:
                ERROR_MESSAGE = "Please provide a valid configuration."
        if config_dict is None:
            if ERROR_MESSAGE is None:
                ERROR_MESSAGE = "Please provide a valid configuration."

    # Restrict config keys
    allowed_keys = {"llm_serve_args", "sampling_params", "extra_body"}
    if not isinstance(config_dict, dict):
        if ERROR_MESSAGE is None:
            ERROR_MESSAGE = "The configuration must be a YAML dictionary at the top level."
    extra_keys = set(config_dict.keys()) - allowed_keys
    if extra_keys:
        if ERROR_MESSAGE is None:
            ERROR_MESSAGE = f"Only the following keys are allowed in the configuration: llm_serve_args, sampling_params, extra_body. Found invalid keys: {', '.join(sorted(extra_keys))}."

    configs = json.dumps(config_dict, indent=4, ensure_ascii=False)

    # Check for duplicate submission
    submission_times = [item['submitted_time'] for item in USERS_TO_SUBMISSION_DATES[user_name] if item['benchmark'] == benchmark and item['model'] == model]
    submission_cnt = 0
    submission_total_cnt = 0
    for i in range(len(submission_times)):
        submission_total_cnt += 1
        hours_diff = (datetime.strptime(current_time, "%Y-%m-%dT%H:%M:%S %z") - datetime.strptime(submission_times[i], "%Y-%m-%dT%H:%M:%S %z")).total_seconds() / 3600
        if hours_diff <= 24:
            submission_cnt += 1
    if submission_cnt >= 1:
        if ERROR_MESSAGE is None:
            ERROR_MESSAGE = "This model has been already submitted within 24 hours."
    if submission_total_cnt >= 3:
        if ERROR_MESSAGE is None:
            ERROR_MESSAGE = "This model has been already submitted three times for this benchmark."

    print("Creating eval file")
    if ERROR_MESSAGE is None:
        OUT_DIR = f"{EVAL_REQUESTS_PATH}/{user_name}/{benchmark}_{model_path}"
    else:
        OUT_DIR = f"{FAILED_EVAL_REQUESTS_PATH}/{user_name}/{benchmark}_{model_path}"
    os.makedirs(OUT_DIR, exist_ok=True)
    current_time_replaced = current_time.replace("-", "").replace(":", "").replace("T", "_").split()[0]
    out_path = f"{OUT_DIR}/{current_time_replaced}.json"

    # Seems good, creating the eval
    print("Adding new eval")

    if ERROR_MESSAGE is None:
        eval_entry = {
            "benchmark": benchmark,
            "contact_email": contact_email,
            "model": model,
            "type": "open",
            "model_type": model_type,
            "think_type": think_type,
            "precision": precision,
            "response_prefix": response_prefix,
            "requirements": requirements,
            "status": "PENDING",
            "submitted_time": current_time,
            "likes": getattr(model_info, "likes", -1),
            "params": model_size,
            "license": license,
            "private": False,
            "configs": configs
        }
    else:
        eval_entry = {
            "benchmark": benchmark,
            "contact_email": contact_email,
            "model": model,
            "type": "open",
            "model_type": model_type,
            "think_type": think_type,
            "precision": precision,
            "response_prefix": response_prefix,
            "requirements": requirements,
            "status": "Failed",
            "submitted_time": current_time,
            "likes": getattr(model_info, "likes", -1),
            "params": model_size,
            "license": license,
            "private": False,
            "configs": configs,
            "error_message": ERROR_MESSAGE
        }

    with open(out_path, "w") as f:
        f.write(json.dumps(eval_entry))

    print("Uploading eval file")
    if ERROR_MESSAGE is None:
        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",
        )
    else:
        API.upload_file(
            path_or_fileobj=out_path,
            path_in_repo=out_path.split("failed-eval-queue/")[1],
            repo_id=FAILED_QUEUE_REPO,
            repo_type="dataset",
            commit_message=f"Add {model} to failed eval queue",
        )

    # Remove the local file
    os.remove(out_path)

    if ERROR_MESSAGE is None:
        return styled_message(
            "Your request has been submitted to the evaluation queue!"
        )
    else:
        return styled_error(
            ERROR_MESSAGE
        )