app.py

import os, io, csv, json, random
from datetime import datetime
import gradio as gr
from huggingface_hub import HfApi, hf_hub_download

import subprocess, pathlib, hashlib

import secrets, time, string


# 사용자가 '선택'을 완료한 값 (초기엔 None)
selected_action = gr.State(None)
selected_phys   = gr.State(None)

def _recompute_save(pid_text: str, sel_a, sel_p):
    ok = bool(pid_text and pid_text.strip()) and (sel_a is not None) and (sel_p is not None)
    return gr.update(interactive=ok, variant=("primary" if ok else "secondary"))


REWARD_FILE = "reward_codes.csv"   # 리워드 코드 기록용 파일 (HF dataset 안에 저장)
def _read_codes_bytes():
    try:
        p = hf_hub_download(
            repo_id=REPO_ID, filename=REWARD_FILE, repo_type="dataset",
            token=HF_TOKEN, local_dir="/tmp", local_dir_use_symlinks=False
        )
        return open(p, "rb").read()
    except Exception:
        return None

def _append_code(old_bytes, row):
    s = io.StringIO()
    w = csv.writer(s)
    if not old_bytes:
        # 새 헤더
        w.writerow(["ts_iso", "participant_id", "reward_code", "total_done"])
    else:
        s.write(old_bytes.decode("utf-8", errors="ignore"))
    w.writerow(row)
    return s.getvalue().encode("utf-8")

def _persist_reward_code(pid: str, code: str, total_done: int):
    """리워드 코드를 HF에 reward_codes.csv로 누적 저장(append)."""
    old = _read_codes_bytes()
    row = [datetime.utcnow().isoformat(), pid.strip(), code, int(total_done)]
    newb = _append_code(old, row)
    api.upload_file(
        path_or_fileobj=io.BytesIO(newb),
        path_in_repo=REWARD_FILE,
        repo_id=REPO_ID,
        repo_type="dataset",
        token=HF_TOKEN,
        commit_message="append reward code"
    )

def _gen_reward_code(pid: str, length: int = 10, forbid_ambiguous: bool=True) -> str:
    """
    참가자에게 보여줄 랜덤 코드. 충돌 위험 매우 낮음.
    - PID + 시각 + 보안랜덤으로 시드
    - 대문자/숫자 조합
    """
    alphabet = "ABCDEFGHJKLMNPQRSTUVWXYZ23456789" if forbid_ambiguous else string.ascii_uppercase + string.digits
    # secrets 기반 난수 + pid/time 섞어서 해시 비슷한 효과
    rnd = secrets.token_hex(8) + pid + str(time.time_ns())
    # 섞고 뽑기
    rng = secrets.SystemRandom()
    return "".join(rng.choice(alphabet) for _ in range(length))




MUTED_CACHE_DIR = "/tmp/hf_video_cache_muted"
pathlib.Path(MUTED_CACHE_DIR).mkdir(parents=True, exist_ok=True)

def _sha1_8(s: str) -> str:
    return hashlib.sha1(s.encode("utf-8")).hexdigest()[:8]

def ensure_muted_copy(src_path: str) -> str:
    """
    주어진 mp4에서 오디오 트랙을 제거(-an)한 무음 복사본을 캐시에 생성.
    이미 있으면 그 파일 경로 반환.
    실패하면 원본 경로 반환.
    """
    if not src_path or not os.path.exists(src_path):
        return src_path
    out = os.path.join(MUTED_CACHE_DIR, _sha1_8(src_path) + ".mp4")
    if os.path.exists(out):
        return out
    try:
        subprocess.run(
            ["ffmpeg", "-y", "-i", src_path, "-c:v", "copy", "-an", out],
            stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL, check=True
        )
        return out if os.path.exists(out) else src_path
    except Exception:
        return src_path


FEEDBACK_FILE = "final_feedback.csv"

def _read_feedback_bytes():
    try:
        p = hf_hub_download(
            repo_id=REPO_ID, filename=FEEDBACK_FILE, repo_type="dataset",
            token=HF_TOKEN, local_dir="/tmp", local_dir_use_symlinks=False
        )
        return open(p, "rb").read()
    except Exception:
        return None

def _append_feedback(old_bytes, row):
    s = io.StringIO()
    w = csv.writer(s)
    if not old_bytes:
        # 최종 코멘트 전용 CSV 헤더
        w.writerow(["ts_iso", "participant_id", "final_comment"])
    else:
        s.write(old_bytes.decode("utf-8", errors="ignore"))
    w.writerow(row)
    return s.getvalue().encode("utf-8")

def push_final_feedback(participant_id: str, comment: str):
    """마지막에 받는 자유 코멘트를 FEEDBACK_FILE로 저장."""
    if not participant_id or not participant_id.strip():
        return gr.update(visible=True, value="❗ Missing participant ID.")
    if comment is None or not str(comment).strip():
        # 비어있으면 저장하지 않고 안내만
        return gr.update(visible=True, value="ℹ️ No comment entered — nothing to submit.")

    try:
        old = _read_feedback_bytes()
        row = [datetime.utcnow().isoformat(), participant_id.strip(), comment.strip()]
        newb = _append_feedback(old, row)

        if not REPO_ID:
            return gr.update(visible=True, value="❗ RESULTS_REPO is not set.")
        if not HF_TOKEN:
            return gr.update(visible=True, value="❗ HF_TOKEN is missing. Set a write token for the dataset repo.")

        api.upload_file(
            path_or_fileobj=io.BytesIO(newb),
            path_in_repo=FEEDBACK_FILE,
            repo_id=REPO_ID,
            repo_type="dataset",
            token=HF_TOKEN,
            commit_message="append final feedback"
        )
        return gr.update(visible=True, value="✅ Thanks! Your feedback was submitted.")
    except Exception as e:
        return gr.update(
            visible=True,
            value=f"❌ Feedback save failed: {type(e).__name__}: {e}"
        )


# -------------------- Config --------------------
REPO_ID = os.getenv("RESULTS_REPO", "dghadiya/video_eval")  # 업로드한 리포와 일치
HF_TOKEN = os.getenv("HF_TOKEN")
RESULTS_FILE = "results.csv"
TOTAL_PER_PARTICIPANT = 30  # 목표 평가 개수(세션 기준)


# videos.json 예시: {"url": "...mp4", "id": "BodyWeightSquats__XXXX.mp4", "action": "BodyWeightSquats"}
with open("videos.json", "r", encoding="utf-8") as f:
    V = json.load(f)

api = HfApi()

# 교수님 지침(그대로, 굵게 처리 포함)
# INSTRUCTION_MD = """
# **Task:** You will watch a series of **AI-generated videos**. For each video, your job is to rate how well the person’s action in the AI-generated video matches the action specified as "**expected action**". Some things to keep in mind:
# - The generated video should **capture** the expected action **throughout the video**.
# - Try to **focus only** on the expected action and do **not** judge **video quality**, **attractiveness**, **background**, **camera motion**, or **objects**.
# - You will be **paid** once **all the videos are viewed and rated**.
# """
INSTRUCTION_MD = """
**Task:** You will watch a series of **AI-generated videos**.  
For each video, your job is to rate:

1. **Action Consistency** - how well the person’s action matches the action specified as the "**Expected action**".  
2. **Physical Plausibility** - how natural and physically possible the motion looks.

Some things to keep in mind:
- Try to **focus only** on the expected action and motion quality, and do **not** judge **video quality**, **attractiveness**, **background**, **camera motion**, or **objects**.
- For **physical plausibility**, look for **smooth and realistic** motion without impossible poses, missing limbs, or extreme stretching.
- Action consistency and physical plausibility are **not mutually exclusive** with each other.
- **Physically plausible motion does not imply correct depiction of action.**
- **A video cannot portray action consistency if it has physically impossible movements.**
- **0: indicates really poor depiction, 10: represents perfect, realistic depiction**
- The **Save & Next** button will be enabled **only after you have clicked or adjusted both sliders at least once**.
- You will be **paid** once **all the videos are viewed and rated**.
"""

# -------------------- Helper funcs --------------------
def _load_eval_counts():
    """
    Hugging Face dataset의 results.csv를 읽어 video_id별 평가 개수(dict)를 반환.
    없으면 0으로 초기화.
    """
    # 모든 id를 0으로 초기화
    counts = {}
    for v in V:
        vid = _get_video_id(v)
        counts[vid] = 0

    b = _read_csv_bytes()
    if not b:
        return counts

    s = io.StringIO(b.decode("utf-8", errors="ignore"))
    r = csv.reader(s)
    rows = list(r)
    if not rows:
        return counts

    # 헤더 파악
    header = rows[0]
    body = rows[1:] if header and ("video_id" in header or "overall" in header) else rows
    vid_col = None
    if header and "video_id" in header:
        vid_col = header.index("video_id")

    for row in body:
        try:
            vid = row[vid_col] if vid_col is not None else row[2]  # 기본 포맷: ts, pid, video_id, overall, notes
            if vid in counts:
                counts[vid] += 1
        except Exception:
            continue
    return counts

def _get_video_id(v: dict) -> str:
    if "id" in v and v["id"]:
        return v["id"]
    # id가 없으면 URL 파일명으로 대체
    return os.path.basename(v.get("url", ""))

def _read_csv_bytes():
    try:
        p = hf_hub_download(
            repo_id=REPO_ID, filename=RESULTS_FILE, repo_type="dataset",
            token=HF_TOKEN, local_dir="/tmp", local_dir_use_symlinks=False
        )
        return open(p, "rb").read()
    except Exception:
        return None


# def _append(old_bytes, row):
#     s = io.StringIO()
#     w = csv.writer(s)
#     if not old_bytes:
#         # ✅ 새 헤더
#         w.writerow(["ts_iso", "participant_id", "video_id", "overall", "notes"])
#     else:
#         s.write(old_bytes.decode("utf-8", errors="ignore"))
#     w.writerow(row)
#     return s.getvalue().encode("utf-8")

def _append(old_bytes, row):
    s = io.StringIO()
    w = csv.writer(s)
    if not old_bytes:
        # ✅ new header with two scores
        w.writerow(["ts_iso", "participant_id", "video_id",
                    "action_consistency", "physical_plausibility", "notes"])
    else:
        s.write(old_bytes.decode("utf-8", errors="ignore"))
    w.writerow(row)
    return s.getvalue().encode("utf-8")


# def push(participant_id, video_id, score, notes=""):
#     if not participant_id or not participant_id.strip():
#         return gr.update(visible=True, value="❗ Please enter your Participant ID before proceeding.")
#     if not video_id or score is None:
#         return gr.update(visible=True, value="❗ Fill out all fields.")

#     try:
#         old = _read_csv_bytes()
#         row = [
#             datetime.utcnow().isoformat(),
#             participant_id.strip(),
#             video_id,           # ✅ action 대신 video_id 저장
#             float(score),       # overall
#             notes or ""
#         ]
#         newb = _append(old, row)

#         if not REPO_ID:
#             return gr.update(visible=True, value="❗ RESULTS_REPO is not set.")
#         if not HF_TOKEN:
#             return gr.update(visible=True, value="❗ HF_TOKEN is missing. Set a write token for the dataset repo.")

#         api.upload_file(
#             path_or_fileobj=io.BytesIO(newb),
#             path_in_repo=RESULTS_FILE,
#             repo_id=REPO_ID,
#             repo_type="dataset",
#             token=HF_TOKEN,
#             commit_message="append"
#         )
#         return gr.update(visible=True, value=f"✅ Saved successfully!")
#     except Exception as e:
#         return gr.update(
#             visible=True,
#             value=f"❌ Save failed: {type(e).__name__}: {e}\n"
#                   f"- Check HF_TOKEN permission\n- Check REPO_ID\n- Create dataset repo if missing"
#         )

def push(participant_id, video_id, action_score, phys_score, notes=""):
    if not participant_id or not participant_id.strip():
        return gr.update(visible=True, value="❗ Please enter your Participant ID before proceeding.")
    if not video_id or action_score is None or phys_score is None:
        return gr.update(visible=True, value="❗ Fill out all fields.")

    try:
        old = _read_csv_bytes()
        row = [
            datetime.utcnow().isoformat(),
            participant_id.strip(),
            video_id,
            float(action_score),
            float(phys_score),
            notes or ""
        ]
        newb = _append(old, row)

        if not REPO_ID:
            return gr.update(visible=True, value="❗ RESULTS_REPO is not set.")
        if not HF_TOKEN:
            return gr.update(visible=True, value="❗ HF_TOKEN is missing. Set a write token for the dataset repo.")

        api.upload_file(
            path_or_fileobj=io.BytesIO(newb),
            path_in_repo=RESULTS_FILE,
            repo_id=REPO_ID,
            repo_type="dataset",
            token=HF_TOKEN,
            commit_message="append"
        )
        return gr.update(visible=True, value=f"✅ Saved successfully!")
    except Exception as e:
        return gr.update(
            visible=True,
            value=f"❌ Save failed: {type(e).__name__}: {e}\n"
                  f"- Check HF_TOKEN permission\n- Check REPO_ID\n- Create dataset repo if missing"
        )


def _extract_action(v):
    if "action" in v and v["action"]:
        return v["action"]
    raw = v.get("id", "")
    return raw.split("__")[0].split(".")[0]

def pick_one():
    v = random.choice(V)
    return v["url"], _extract_action(v)

def _progress_html(done, total):
    pct = int(100 * done / max(1, total))
    return f"""
    <div style="border:1px solid #ddd; height:20px; border-radius:6px; overflow:hidden; margin-top:6px;">
      <div style="height:100%; width:{pct}%; background:#3b82f6;"></div>
    </div>
    <div style="font-size:12px; margin-top:4px;">{done} / {total}</div>
    """

def _build_order_with_anchor(total:int, anchor_idx:int, repeats:int, pool_size:int, min_gap:int=1):
    """
    total:     TOTAL_PER_PARTICIPANT (e.g., 30)
    anchor_idx: index of the anchor video in V (0 for first item)
    repeats:   how many times to show anchor (e.g., 5)
    pool_size: len(V)
    min_gap:   최소 간격(인접 금지 => 1)

    return: list of indices (length=total)
    """
    assert repeats <= total, "repeats must be <= total"
    assert pool_size >= 1, "videos pool must be non-empty"

    # 1) 다른 비디오 25개(중복 없이) 뽑기
    others_needed = total - repeats
    # anchor를 제외한 후보 인덱스
    candidates = list(range(1, pool_size)) if anchor_idx == 0 else [i for i in range(pool_size) if i != anchor_idx]
    if len(candidates) < others_needed:
        raise ValueError("Not enough unique non-anchor videos to fill the schedule without duplication.")

    others = random.sample(candidates, k=others_needed)

    # 2) 기본 시퀀스(others)를 무작위로 섞기
    random.shuffle(others)

    # 3) 앵커를 min_gap를 만족하도록 삽입할 위치 선정
    #    30개를 5구간으로 나눠, 각 구간 내에서 충돌 덜 나게 배치
    #    (간단하고 안정적인 방식)
    seq = others[:]  # 길이=25
    anchor_positions = []
    segment = total // repeats  # 30//5 = 6

    for k in range(repeats):
        # 각 구간 [k*segment, (k+1)*segment) 안에서 후보 위치를 고름
        lo = k * segment
        hi = (k + 1) * segment if k < repeats - 1 else total  # 마지막은 끝까지
        # 경계 내 임의 오프셋 선택 (여유를 두고 충돌을 피함)
        candidate_pos = random.randrange(lo, hi)

        # 인접 금지 보정: 이미 배정된 anchor 위치들과의 거리가 min_gap 이상 되도록 조정
        # 필요 시 좌우로 근접한 빈 슬롯 탐색
        def ok(pos):
            return all(abs(pos - p) >= min_gap + 1 for p in anchor_positions)  # 연속금지 => 거리 >= 2

        # 근방 탐색 폭
        found = None
        for delta in range(0, segment):  # 구간 크기 내에서 탐색
            # 좌/우 번갈아가며 후보 시도
            for sign in (+1, -1):
                pos = candidate_pos + sign * delta
                if 0 <= pos < total and ok(pos):
                    found = pos
                    break
            if found is not None:
                break

        if found is None:
            # 최후: 0..total-1 범위에서 아무 데나 충돌 없는 곳 찾기
            for pos in range(total):
                if ok(pos):
                    found = pos
                    break
        if found is None:
            raise RuntimeError("Failed to place anchor without adjacency. Try different strategy or loosen min_gap.")

        anchor_positions.append(found)

    # 4) others를 기반으로 길이 total의 빈 시퀀스를 만들고 anchor를 주입
    #    우선 빈 리스트를 만들고 anchor 위치를 채운 후, 나머지를 others로 채움
    result = [None] * total
    for pos in anchor_positions:
        result[pos] = anchor_idx

    # others 포인터
    j = 0
    for i in range(total):
        if result[i] is None:
            result[i] = others[j]
            j += 1

    # 안전체크
    assert len(result) == total
    # 인접 anchor 없는지 확인
    for i in range(1, total):
        assert not (result[i] == anchor_idx and result[i-1] == anchor_idx), "Adjacent anchors found."
    # anchor 개수 확인
    assert sum(1 for x in result if x == anchor_idx) == repeats, "Anchor count mismatch."

    return result


# -------------------- Example videos (download to local cache) --------------------
EXAMPLES = {
    "BodyWeightSquats": {
        "real": "examples/BodyWeightSquats_real.mp4",
        "bad":  "examples/BodyWeightSquats_bad.mp4",
    },
    "WallPushUps": {
        "real": "examples/WallPushUps_real.mp4",
        "bad":  "examples/WallPushUps_bad.mp4",
    },
}
EX_CACHE = {}
for cls, files in EXAMPLES.items():
    EX_CACHE[cls] = {"real": None, "bad": None}
    for kind, fname in files.items():
        try:
            EX_CACHE[cls][kind] = hf_hub_download(
                repo_id=REPO_ID,
                filename=fname,
                repo_type="dataset",
                token=HF_TOKEN,
                local_dir="/tmp",
                local_dir_use_symlinks=False,
            )
        except Exception as e:
            print(f"[WARN] example missing: {cls} {kind} -> {fname}: {e}")

for cls in EX_CACHE:
    for kind in EX_CACHE[cls]:
        if EX_CACHE[cls][kind]:
            EX_CACHE[cls][kind] = ensure_muted_copy(EX_CACHE[cls][kind])


CLEAN_BG_CSS = r"""
/* 전체 페이지 배경을 흰색으로 (Spaces의 회색 배경 제거) */
html, body { background:#ffffff !important; }

/* Intro/Eval 섹션의 래퍼 박스만 투명 처리 (입력창/슬라이더 등 컨트롤은 놔둠) */
#intro .gr-panel, #intro .gr-group, #intro .gr-box, #intro .gr-row, #intro .gr-column,
#eval  .gr-panel, #eval  .gr-group, #eval  .gr-box, #eval  .gr-row, #eval  .gr-column {
  background: transparent !important;
  box-shadow: none !important;
  border-color: transparent !important;
}

/* 비디오 카드 주변 툴바(작은 회색 박스)도 투명하게 */
#intro [data-testid="block-video"] .prose, 
#eval  [data-testid="block-video"] .prose {
  background: transparent !important;
  box-shadow: none !important;
  border-color: transparent !important;
}
"""
# -------------------- UI --------------------

with gr.Blocks(css=CLEAN_BG_CSS) as demo:
    # Blocks 안, 어디서든 한 번만 추가(권장 위치: Blocks 시작 직후)
    gr.HTML("""
    <script>
    (function(){
    // 모든 일반 DOM + Shadow DOM 안의 <video>까지 찾아 음소거
    function eachNodeWithShadow(root, fn){
        const walker = document.createTreeWalker(root, NodeFilter.SHOW_ELEMENT);
        fn(root);
        while (walker.nextNode()){
        const el = walker.currentNode;
        fn(el);
        if (el.shadowRoot){
            eachNodeWithShadow(el.shadowRoot, fn);
        }
        }
    }

    function muteVideoEl(v){
        try{
        // 재생 전에 반드시 muted 속성이 있어야 브라우저가 소리 차단
        v.muted = true;
        v.volume = 0.0;
        v.setAttribute('muted','');
        v.setAttribute('playsinline','');
        v.setAttribute('preload','metadata');

        // 사용자가 볼륨/음소거를 바꿔도 다시 0으로
        if (!v._muteHooked){
            v.addEventListener('volumechange', () => {
            if (!v.muted || v.volume > 0) { v.muted = true; v.volume = 0.0; }
            });
            v.addEventListener('play', () => {
            v.muted = true; v.volume = 0.0;
            });
            v._muteHooked = true;
        }
        }catch(e){}
    }

    function muteAll(root){
        eachNodeWithShadow(root || document, (el)=>{
        if (el.tagName && el.tagName.toLowerCase() === 'video'){
            muteVideoEl(el);
        }else if (el.querySelectorAll){
            el.querySelectorAll('video').forEach(muteVideoEl);
        }
        });
    }

    // 초기 렌더에서
    muteAll(document);

    // 이후 DOM 변화 감시(Shadow DOM 내부 변화도 포착)
    const obs = new MutationObserver(() => muteAll(document));
    obs.observe(document, {subtree:true, childList:true, attributes:false});
    })();
    </script>
    """)


    order_state = gr.State(value=[])   # v4에서는 value= 권장
    ptr_state   = gr.State(value=0)
    cur_video_id = gr.State(value="")
    reward_code_state = gr.State(value="")  # 완료 시 생성한 코드 저장(중복 생성 방지)

    selected_action = gr.State(value=None)   # 아직 선택 없음
    selected_phys   = gr.State(value=None)   # 아직 선택 없음

    # ------------------ PAGE 1: Intro + Examples ------------------
    # page_intro = gr.Group(visible=True)
    page_intro = gr.Group(visible=True, elem_id="intro")
    with page_intro:
        # gr.Markdown("## 🎯 Action Consistency Human Evaluation")
        gr.Markdown("## 🎯 Human Evaluation: Action Consistency & Physical Plausibility")

        gr.Markdown(INSTRUCTION_MD)

        understood = gr.Checkbox(label="I have read and understand the task.", value=False)
        start_btn  = gr.Button("Yes, start", variant="secondary", interactive=False)

        def _toggle_start(checked: bool):
            return gr.update(interactive=checked, variant=("primary" if checked else "secondary"))
        understood.change(_toggle_start, inputs=understood, outputs=start_btn)

        # Examples: Squats
        with gr.Group():
            gr.Markdown("### Examples: BodyWeightSquats")
            with gr.Row():
                with gr.Column():
                    gr.Markdown("**Expected depiction of action**")
                    gr.Video(value=EX_CACHE["BodyWeightSquats"]["real"], height=240, autoplay=False, elem_id="ex_squats_real",)
                with gr.Column():
                    gr.Markdown("**Poorly generated action**")
                    gr.Video(value=EX_CACHE["BodyWeightSquats"]["bad"], height=240, autoplay=False)
            if not (EX_CACHE["BodyWeightSquats"]["real"] and EX_CACHE["BodyWeightSquats"]["bad"]):
                gr.Markdown("> ⚠️ Upload `examples/BodyWeightSquats_real.mp4` and `_bad.mp4` to show both samples.")

        # Examples: WallPushUps
        with gr.Group():
            gr.Markdown("### Examples: WallPushUps")
            with gr.Row():
                with gr.Column():
                    gr.Markdown("**Expected depiction of action**")
                    gr.Video(value=EX_CACHE["WallPushUps"]["real"], height=240, autoplay=False, elem_id="ex_wallpushups_real",)
                with gr.Column():
                    gr.Markdown("**Poorly generated action**")
                    gr.Video(value=EX_CACHE["WallPushUps"]["bad"], height=240, autoplay=False)
            if not (EX_CACHE["WallPushUps"]["real"] and EX_CACHE["WallPushUps"]["bad"]):
                gr.Markdown("> ⚠️ Upload `examples/WallPushUps_real.mp4` and `_bad.mp4` to show both samples.")

        gr.HTML("""
            <script>
            (function(){
            const ids = [
                "ex_squats_real",
                "ex_wallpushups_real",
            ];
            function muteById(id){
                const host = document.getElementById(id);
                if(!host) return;
                // gr.Video는 Shadow DOM 내부에 <video>가 랜더링됨
                const roots = [host, host.shadowRoot].filter(Boolean);
                roots.forEach(root=>{
                const vids = root.querySelectorAll('video');
                vids.forEach(v=>{
                    try{
                    v.muted = true;
                    v.volume = 0.0;
                    v.setAttribute('muted','');
                    v.setAttribute('playsinline','');
                    // 사용자가 바꿔도 즉시 원복
                    if(!v._exMuteHooked){
                        v.addEventListener('volumechange', ()=>{
                        if(!v.muted || v.volume > 0){ v.muted = true; v.volume = 0.0; }
                        });
                        v.addEventListener('play', ()=>{
                        v.muted = true; v.volume = 0.0;
                        });
                        v._exMuteHooked = true;
                    }
                    }catch(e){}
                });
                });
            }
            function apply(){
                ids.forEach(muteById);
            }
            // 초기 + DOM변경 시 적용
            apply();
            new MutationObserver(apply).observe(document, {subtree:true, childList:true});
            })();
            </script>
            """)


    # ------------------ PAGE 2: Evaluation ------------------
    page_eval = gr.Group(visible=False, elem_id="eval")
    with page_eval:
        # PID 입력
        with gr.Row():
            pid = gr.Textbox(label="Participant ID (required)", placeholder="e.g., Youngsun-2025/10/24")

        # 지침(원문) + 비디오 + 진행바 / 오른쪽에 슬라이더 + Save&Next
        with gr.Row(): #equal_height=True
            with gr.Column(scale=1):
                gr.Markdown(INSTRUCTION_MD)  # 교수님 문구 그대로
                video = gr.Video(label="Video", height=360)
                progress = gr.HTML(_progress_html(0, TOTAL_PER_PARTICIPANT))

            with gr.Column(scale=1):
                action_tb = gr.Textbox(label="Expected action", interactive=False)
                # NEW: two separate sliders
                score_action = gr.Slider(
                    minimum=0.0, maximum=10.0, step=0.1, value=5.0,
                    label="Action Consistency (0.0 - 10.0)"
                )
                score_phys = gr.Slider(
                    minimum=0.0, maximum=10.0, step=0.1, value=5.0,
                    label="Physical Plausibility (0.0 - 10.0)"
                )

                save_next = gr.Button("💾 Save & Next ▶", variant="secondary", interactive=False)


        status = gr.Markdown(visible=False)
        done_state = gr.State(0)

        # PID 입력에 따라 Save&Next 토글
        def _toggle_by_pid(pid_text: str):
            enabled = bool(pid_text and pid_text.strip())
            return gr.update(interactive=enabled, variant=("primary" if enabled else "secondary"))
        # pid.change(_toggle_by_pid, inputs=pid, outputs=save_next)


    def _on_action_release(val: float, pid_text: str, sel_p):
        # 사용자가 액션 슬라이더를 한 번이라도 놓으면 선택 완료
        return val, _recompute_save(pid_text, val, sel_p)

    def _on_phys_release(val: float, pid_text: str, sel_a):
        return val, _recompute_save(pid_text, sel_a, val)

    # release: 마우스를 놓을 때 1회 확정
    score_action.release(_on_action_release,
                         inputs=[score_action, pid, selected_phys],
                         outputs=[selected_action, save_next])

    score_phys.release(_on_phys_release,
                       inputs=[score_phys, pid, selected_action],
                       outputs=[selected_phys, save_next])

    # PID가 바뀌면 현재 선택 상태로 Save 버튼 재계산
    pid.change(_recompute_save,
               inputs=[pid, selected_action, selected_phys],
               outputs=save_next)

    page_thanks = gr.Group(visible=False)
    with page_thanks:
        reward_msg = gr.Markdown(visible=False)
        reward_code_box = gr.Textbox(label="Your reward code (copy & paste)", interactive=False, visible=False)
        reward_pid_box = gr.Textbox(label="Your participant ID", interactive=False, visible=False)
        
        gr.Markdown("### Any comments (optional)")
        feedback_tb = gr.Textbox(
            label="Any comments (optional)",
            placeholder="Leave any feedback for the study organizers (optional).",
            lines=4
        )
        feedback_submit = gr.Button("Submit feedback")
        feedback_status = gr.Markdown(visible=False)



    # -------- 페이지 전환 & 첫 로드 --------
    ANCHOR_IDX = 0       # videos.json의 맨 첫 비디오
    ANCHOR_REPEATS = 5   # 앵커 5회
    MIN_GAP = 1          # 앵커 연속 금지(인접 금지)

    def _build_order_least_first_with_anchor(total:int, anchor_idx:int, repeats:int, min_gap:int=1):
        """
        - results.csv를 읽어 video_id별 카운트를 계산
        - 앵커(첫 비디오) 5회 포함, 연속 금지
        - 나머지는 '가장 적게 평가된 순'으로 중복 없이 채움
        """
        assert repeats <= total
        N = len(V)
        assert N >= 1

        # 0) id 매핑
        def vid_of(i): return _get_video_id(V[i])

        # 1) 현재 누적 카운트 로드
        counts = _load_eval_counts()

        # 2) 앵커 제외 후보(중복 없이) 정렬: 카운트 오름차순, 동률은 랜덤 셔플
        anchor_vid = vid_of(anchor_idx)
        candidates = [i for i in range(N) if i != anchor_idx]
        # 동률 랜덤화를 위해 일단 셔플
        random.shuffle(candidates)
        candidates.sort(key=lambda i: counts.get(vid_of(i), 0))

        others_needed = total - repeats
        if len(candidates) < others_needed:
            raise ValueError("Not enough unique non-anchor videos to fill the schedule without duplication.")

        others = candidates[:others_needed]  # 중복 없이 선택

        # 3) others를 베이스 시퀀스로(랜덤 살짝 섞기)
        random.shuffle(others)

        # 4) 앵커를 구간 배치(연속 금지)
        seq = [None] * total
        segment = total // repeats if repeats > 0 else total
        anchor_positions = []
        for k in range(repeats):
            lo = k * segment
            hi = (k + 1) * segment if k < repeats - 1 else total
            cand = random.randrange(lo, hi)

            def ok(pos):
                return all(abs(pos - p) >= (min_gap + 1) for p in anchor_positions)

            found = None
            for d in range(0, max(1, segment)):
                for sgn in (+1, -1):
                    pos = cand + sgn * d
                    if 0 <= pos < total and ok(pos):
                        found = pos
                        break
                if found is not None:
                    break
            if found is None:
                # 마지막 수단: 전체 탐색
                for pos in range(total):
                    if ok(pos):
                        found = pos
                        break
            if found is None:
                raise RuntimeError("Failed to place anchor without adjacency.")
            anchor_positions.append(found)

        for pos in anchor_positions:
            seq[pos] = anchor_idx

        # 5) 빈 자리를 others로 채우기
        j = 0
        for i in range(total):
            if seq[i] is None:
                seq[i] = others[j]
                j += 1

        # 6) 안전 체크
        assert sum(1 for x in seq if x == anchor_idx) == repeats
        for i in range(1, total):
            assert not (seq[i] == anchor_idx and seq[i-1] == anchor_idx), "Adjacent anchors found."

        return seq

    def _start_and_load_first():
        total = TOTAL_PER_PARTICIPANT
        order = _build_order_least_first_with_anchor(
            total=total,
            anchor_idx=ANCHOR_IDX,
            repeats=ANCHOR_REPEATS,
            min_gap=MIN_GAP
        )
        first_idx = order[0]
        v0 = V[first_idx]
        return (
            gr.update(visible=False),
            gr.update(visible=True),
            gr.update(visible=False),
            v0["url"],
            _extract_action(v0),
            5.0,   # score_action default
            5.0,   # score_phys default  ✅ NEW
            gr.update(visible=False, value=""),
            0,
            _progress_html(0, TOTAL_PER_PARTICIPANT),
            order,
            1,
            _get_video_id(v0),  # cur_video_id
            "",
            None,  # ⬅️ selected_action 초기화(= 아직 선택 안됨)
            None,  # ⬅️ selected_phys 초기화

            gr.update(interactive=False, variant="secondary"),  # ⬅️ Save 버튼 잠금
        )


    start_btn.click(
        _start_and_load_first,
        inputs=[],
        outputs=[
            page_intro, page_eval, page_thanks,
            video, action_tb,
            score_action, score_phys,   # <-- two sliders
            status,
            done_state, progress, order_state, ptr_state, cur_video_id,
            reward_code_state,
            selected_action, selected_phys,
            save_next,
        ]
    )



    def save_and_next(participant_id, cur_vid, action_score, phys_score,
                    done_cnt, order, ptr, reward_code):
        try:
            if not participant_id or not participant_id.strip():
                return (
                    gr.update(visible=True),
                    gr.update(visible=False),
                    gr.update(visible=True, value="❗ Please enter your Participant ID."),
                    gr.update(), gr.update(),
                    done_cnt,
                    _progress_html(done_cnt, TOTAL_PER_PARTICIPANT),
                    5.0,  # reset action slider
                    5.0,  # reset phys slider  ✅
                    ptr,
                    cur_vid,
                    reward_code,
                    gr.update(visible=False),
                    gr.update(visible=False),
                    gr.update(visible=False),
                    None,  # ⬅️ selected_action reset
                    None,  # ⬅️ selected_phys reset
                    gr.update(interactive=False, variant="secondary"),  # ⬅️ lock button
                )

            # save both scores
            status_msg = push(participant_id, cur_vid, action_score, phys_score, "")
            new_done = int(done_cnt) + 1

            if new_done >= TOTAL_PER_PARTICIPANT or ptr >= len(order):
                code = reward_code.strip() or _gen_reward_code(participant_id, length=10)
                try:
                    _persist_reward_code(participant_id, code, new_done)
                except Exception:
                    pass

                thanks_text = (
                    "## 🎉 Thank you so much!\n"
                    "Your responses have been recorded. You may now close this window.\n\n"
                    "**Below are your reward code and ID.** Please copy them and submit them to **AMT** to receive your payment."
                )
                return (
                    gr.update(visible=False),
                    gr.update(visible=True),
                    status_msg,
                    None,
                    "",
                    TOTAL_PER_PARTICIPANT,
                    _progress_html(TOTAL_PER_PARTICIPANT, TOTAL_PER_PARTICIPANT),
                    5.0,  # reset action
                    5.0,  # reset phys
                    len(order),
                    cur_vid,
                    code,
                    gr.update(visible=True, value=thanks_text),
                    gr.update(visible=True, value=code),
                    gr.update(visible=True, value=participant_id.strip()),
                    None,  # ⬅️ selected_action reset
                    None,  # ⬅️ selected_phys reset
                    gr.update(interactive=False, variant="secondary"),
                )

            # next video
            next_idx = order[ptr]
            v = V[next_idx]
            next_vid = _get_video_id(v)

            return (
                gr.update(visible=True),
                gr.update(visible=False),
                status_msg,
                v["url"],
                _extract_action(v),
                new_done,
                _progress_html(new_done, TOTAL_PER_PARTICIPANT),
                5.0,  # reset action
                5.0,  # reset phys
                ptr + 1,
                next_vid,
                reward_code,
                gr.update(visible=False),
                gr.update(visible=False),
                gr.update(visible=False),
                None,  # ⬅️ selected_action reset
                None,  # ⬅️ selected_phys reset
                gr.update(interactive=False, variant="secondary"),
            )
        except Exception as e:
            return (
                gr.update(visible=True),
                gr.update(visible=False),
                gr.update(visible=True, value=f"❌ Error: {type(e).__name__}: {e}"),
                gr.update(), gr.update(),
                done_cnt,
                _progress_html(done_cnt, TOTAL_PER_PARTICIPANT),
                5.0,
                5.0,
                ptr,
                cur_vid,
                reward_code,
                gr.update(visible=False),
                gr.update(visible=False),
                gr.update(visible=False),
                None,  # ⬅️ reset on error too
                None,
                gr.update(interactive=False, variant="secondary"),
            )



    save_next.click(
        save_and_next,
        inputs=[pid, cur_video_id, score_action, score_phys, done_state, order_state, ptr_state, reward_code_state],
        outputs=[
            page_eval, page_thanks,
            status, video, action_tb,
            done_state, progress, score_action, score_phys,
            ptr_state, cur_video_id,
            reward_code_state,
            reward_msg, reward_code_box, reward_pid_box,

            selected_action, selected_phys,   # ⬅️ 추가
            save_next,                        # ⬅️ 버튼 상태 갱신
        ]
    )
    feedback_submit.click(
        push_final_feedback,
        # 완료 후 page_thanks에서 보여주는 participant ID 박스를 사용 (값이 채워져 있음)
        inputs=[reward_pid_box, feedback_tb],
        outputs=feedback_status
    )



if __name__ == "__main__":
    # demo.launch()
    demo.launch(ssr_mode=False)