miniapp_leaderboard.py

import datetime
import io
import json
import os
import re
import uuid
import requests

import gradio as gr
import pandas as pd
from huggingface_hub import HfApi, hf_hub_download

APP_NAME = "MiniApp"

HF_TOKEN = os.environ.get("HF_TOKEN")
LEADERBOARD_DATASET = os.environ.get("LEADERBOARD_DATASET", "").strip()

PENDING_PREFIX = "pending/"
APPROVED_PREFIX = "approved/"

RESEND_API_KEY = os.environ.get("RESEND_API_KEY", "").strip()
NOTIFY_EMAIL_TO = os.environ.get("NOTIFY_EMAIL_TO", "").strip()
NOTIFY_EMAIL_FROM = os.environ.get("NOTIFY_EMAIL_FROM", "").strip()

COLUMNS = ["model name","model family","avg","easy","mid","hard","submitted_at"]
NUMERIC_COLS = ["avg","easy","mid","hard"]

def _api():
    return HfApi(token=HF_TOKEN)

def _slug(s: str):
    s = re.sub(r"[^a-z0-9]+", "-", (s or "").lower())
    return s.strip("-") or "model"

def _load_df(prefix: str):
    if not HF_TOKEN or not LEADERBOARD_DATASET:
        return pd.DataFrame(columns=COLUMNS)

    api = _api()
    try:
        files = api.list_repo_files(repo_id=LEADERBOARD_DATASET, repo_type="dataset")
    except Exception:
        return pd.DataFrame(columns=COLUMNS)

    files = [f for f in files if f.startswith(prefix) and f.endswith(".json")]
    rows = []
    for f in files:
        try:
            path = hf_hub_download(
                repo_id=LEADERBOARD_DATASET,
                repo_type="dataset",
                filename=f,
                token=HF_TOKEN,
            )
            with open(path, "r") as fp:
                rows.append(json.load(fp))
        except Exception:
            continue

    if not rows:
        return pd.DataFrame(columns=COLUMNS)

    df = pd.DataFrame(rows)
    for c in COLUMNS:
        if c not in df.columns:
            df[c] = ""
    for c in NUMERIC_COLS:
        df[c] = pd.to_numeric(df[c], errors="coerce")

    df = df.sort_values(by="avg", ascending=False)
    return df[COLUMNS]

def refresh():
    return _load_df(APPROVED_PREFIX)

def _today_utc():
    return datetime.datetime.utcnow().date().isoformat()

def _send_email_resend(subject: str, text: str):
    if not (RESEND_API_KEY and NOTIFY_EMAIL_TO and NOTIFY_EMAIL_FROM):
        return
    requests.post(
        "https://api.resend.com/emails",
        headers={"Authorization": f"Bearer {RESEND_API_KEY}", "Content-Type": "application/json"},
        json={"from": NOTIFY_EMAIL_FROM, "to": [NOTIFY_EMAIL_TO], "subject": subject, "text": text},
        timeout=20,
    )

def _already_submitted_today(api: HfApi, day: str, username: str) -> bool:
    marker = f"{PENDING_PREFIX}{day}/{username}/_submitted.json"
    try:
        files = api.list_repo_files(repo_id=LEADERBOARD_DATASET, repo_type="dataset")
        return marker in files
    except Exception:
        return True  # 更安全：查不到就当提交过

# ✅ 改这里：用 profile 取 username
def submit(model_name, model_family, zip_file, profile: gr.OAuthProfile):
    if profile is None or not getattr(profile, "username", None):
        return "Please sign in with Hugging Face first.", refresh()
    username = profile.username

    if not model_name or not model_family or zip_file is None:
        return "All fields are required.", refresh()
    if not zip_file.name.endswith(".zip"):
        return "Please upload a .zip file.", refresh()
    if not HF_TOKEN or not LEADERBOARD_DATASET:
        return "Server is not configured (HF_TOKEN / LEADERBOARD_DATASET).", refresh()

    api = _api()
    day = _today_utc()

    if _already_submitted_today(api, day, username):
        return f"Limit: you can only submit once per day. (user={username}, day={day})", refresh()

    now = datetime.datetime.utcnow().isoformat() + "Z"
    safe_model = _slug(model_name)
    nonce = uuid.uuid4().hex[:6]

    base_dir = f"{PENDING_PREFIX}{day}/{username}/"
    json_path = f"{base_dir}{now}-{safe_model}-{nonce}.json"
    zip_path  = f"{base_dir}{now}-{safe_model}-{nonce}.zip"
    marker_path = f"{base_dir}_submitted.json"

    payload = {
        "model name": model_name,
        "model family": model_family,
        "avg": 0, "easy": 0, "mid": 0, "hard": 0,
        "submitted_at": now,
        "username": username,
        "day": day,
    }

    api.upload_file(
        repo_id=LEADERBOARD_DATASET, repo_type="dataset",
        path_or_fileobj=io.BytesIO(json.dumps(payload, indent=2).encode("utf-8")),
        path_in_repo=json_path,
        commit_message=f"submit {model_name} by {username}",
    )

    api.upload_file(
        repo_id=LEADERBOARD_DATASET, repo_type="dataset",
        path_or_fileobj=zip_file,
        path_in_repo=zip_path,
        commit_message=f"upload zip {model_name} by {username}",
    )

    api.upload_file(
        repo_id=LEADERBOARD_DATASET, repo_type="dataset",
        path_or_fileobj=io.BytesIO(json.dumps({"submitted_at": now, "username": username, "day": day}, indent=2).encode("utf-8")),
        path_in_repo=marker_path,
        commit_message=f"marker {day} {username}",
    )

    _send_email_resend(
        subject=f"[{APP_NAME}] New submission from {username} ({day})",
        text=f"user: {username}\nday: {day}\nmodel: {model_name}\nfamily: {model_family}\njson: {json_path}\nzip: {zip_path}\n",
    )

    return "Submitted. Waiting for review.", refresh()


with gr.Blocks(
    title=f"{APP_NAME} leaderboard",
    css="""
    .gradio-container { font-size: 18px; }
    /* 表格字号单独再加一层，确保生效 */
    .gradio-container table { font-size: 18px; }
    """
) as demo:

    gr.Markdown(f"# {APP_NAME} Leaderboard")

    leaderboard = gr.Dataframe(value=_load_df(APPROVED_PREFIX), interactive=False, wrap=True)
    refresh_btn = gr.Button("Refresh")

    gr.Markdown("## Submit")

    gr.Markdown(
        """
**Submission requirements**
- Please **sign in with Hugging Face** before submitting.
- **One submission per user per day** (UTC).
- Upload a **.zip** file only.
- The `.zip` must contain the HTML outputs for the **test set queries**.
  - Each file should be named using the query index: `<index>.html` (e.g., `1.html`, `2.html`, ...).
- After you submit, we will update the result in 3 days.
""",
    )

    model_name = gr.Textbox(label="Model name", placeholder="e.g. MyModel v1")
    model_family = gr.Textbox(label="Model family", placeholder="e.g. Llama / Qwen / InternLM ...")
    zip_file = gr.File(label="Upload zip (.zip only)", file_types=[".zip"])

    with gr.Row():
        with gr.Column(scale=1, min_width=220):
            login_btn = gr.LoginButton()
        with gr.Column(scale=1, min_width=260):
            submit_btn = gr.Button("Submit", variant="primary")

    status = gr.Markdown()

    submit_btn.click(submit, inputs=[model_name, model_family, zip_file], outputs=[status, leaderboard])

demo.launch()