app.py

import json
import math
import time
import hashlib
from pathlib import Path
from datetime import datetime, timezone
from typing import Any, Dict, List, Tuple

import gradio as gr
from huggingface_hub import HfApi, hf_hub_download

# -----------------------------------------------------------------------------
# CROVIA — CEP Terminal v2.0.0 (PRISM CONSOLE + OMISSION ORACLE)
# Custom HTML/CSS/JS frontend, Gradio backend + events
# Global Standard Release - EU AI Act Compliance
# -----------------------------------------------------------------------------

CEP_DATASET_ID = "Crovia/cep-capsules"
OMISSIONS_DATASET_ID = "Crovia/global-ai-training-omissions"
OPEN_DEMO_MODE = True
ENGINE_VERSION = "2.0.0"

_CAPSULE_LIST_CACHE = {"ts": 0.0, "items": []}
_CAPSULE_LIST_TTL_SEC = 300  # 5 min
_OMISSIONS_CACHE = {"ts": 0.0, "data": {}}

# =============================================================================
# OMISSION ORACLE v2.0.0 - Shadow Score Engine
# =============================================================================

NECESSITY_CANON = {
    "NEC#1": {"name": "Missing data provenance", "severity": 75, "category": "provenance"},
    "NEC#2": {"name": "Missing license attribution", "severity": 80, "category": "license"},
    "NEC#7": {"name": "Missing usage scope", "severity": 45, "category": "scope"},
    "NEC#10": {"name": "Missing temporal validity", "severity": 40, "category": "validity"},
    "NEC#13": {"name": "Missing accountable entity", "severity": 70, "category": "identity"},
}

def _load_omissions_ranking() -> Dict[str, Any]:
    """Load global omissions ranking from HuggingFace."""
    now = time.time()
    if (now - _OMISSIONS_CACHE["ts"]) < _CAPSULE_LIST_TTL_SEC and _OMISSIONS_CACHE["data"]:
        return _OMISSIONS_CACHE["data"]
    
    try:
        path = hf_hub_download(
            repo_id=OMISSIONS_DATASET_ID,
            filename="EVIDENCE.json",
            repo_type="dataset",
        )
        with open(path, "r", encoding="utf-8") as f:
            data = json.load(f)
        _OMISSIONS_CACHE["ts"] = now
        _OMISSIONS_CACHE["data"] = data
        return data
    except Exception:
        return {}


def analyze_model_shadow_score(model_data: Dict[str, Any]) -> Dict[str, Any]:
    """
    Omission Oracle: Analyze model for NEC# violations and compute Shadow Score.
    """
    model_id = model_data.get("id", model_data.get("model_id", "unknown"))
    license_val = model_data.get("license", model_data.get("cardData", {}).get("license"))
    datasets = model_data.get("datasets", model_data.get("cardData", {}).get("datasets", []))
    author = model_data.get("author", "")
    tags = model_data.get("tags", [])
    
    violations = []
    
    # NEC#1: Missing data provenance
    if not datasets and "fine-tuned" not in " ".join(tags).lower():
        violations.append({
            "id": "NEC#1",
            "name": NECESSITY_CANON["NEC#1"]["name"],
            "severity": NECESSITY_CANON["NEC#1"]["severity"],
            "reason": "No training data provenance declared"
        })
    
    # NEC#2: Missing license attribution
    if not license_val:
        violations.append({
            "id": "NEC#2",
            "name": NECESSITY_CANON["NEC#2"]["name"],
            "severity": NECESSITY_CANON["NEC#2"]["severity"],
            "reason": "No license attribution declared"
        })
    
    # NEC#7: Missing usage scope
    has_intended_use = any("intended" in t.lower() or "use" in t.lower() for t in tags)
    if not has_intended_use:
        violations.append({
            "id": "NEC#7",
            "name": NECESSITY_CANON["NEC#7"]["name"],
            "severity": NECESSITY_CANON["NEC#7"]["severity"],
            "reason": "No intended use or usage scope declared"
        })
    
    # NEC#13: Missing accountable entity
    if not author:
        violations.append({
            "id": "NEC#13",
            "name": NECESSITY_CANON["NEC#13"]["name"],
            "severity": NECESSITY_CANON["NEC#13"]["severity"],
            "reason": "No accountable author or organization"
        })
    
    # Compute Shadow Score (100 = perfect, 0 = critical)
    total_severity = sum(v["severity"] for v in violations)
    shadow_score = max(0, min(100, 100 - int(total_severity * 0.15)))
    
    # Determine badge
    if shadow_score >= 90:
        badge, badge_color = "GOLD", "#F59E0B"
    elif shadow_score >= 75:
        badge, badge_color = "SILVER", "#94A3B8"
    elif shadow_score >= 60:
        badge, badge_color = "BRONZE", "#D97706"
    else:
        badge, badge_color = "UNVERIFIED", "#EF4444"
    
    # Severity classification
    if not violations:
        severity = "CLEAN"
    elif shadow_score >= 75:
        severity = "LOW"
    elif shadow_score >= 60:
        severity = "MEDIUM"
    elif shadow_score >= 40:
        severity = "HIGH"
    else:
        severity = "CRITICAL"
    
    return {
        "model_id": model_id,
        "shadow_score": shadow_score,
        "badge": badge,
        "badge_color": badge_color,
        "severity": severity,
        "violations": violations,
        "violation_count": len(violations),
        "license": license_val or "not declared",
        "author": author or "unknown",
        "analyzed_at": _nowz(),
        "oracle_version": ENGINE_VERSION,
    }


def _nowz() -> str:
    return datetime.now(timezone.utc).isoformat().replace("+00:00", "Z")


def _canonical_json_bytes(obj: dict) -> bytes:
    return json.dumps(obj, sort_keys=True, separators=(",", ":"), ensure_ascii=False).encode("utf-8")


def _sha256_hex(b: bytes) -> str:
    return hashlib.sha256(b).hexdigest()


def _short(s: str, n: int = 16) -> str:
    if not isinstance(s, str) or not s:
        return ""
    return s[:n] + "…"


def _list_capsules() -> List[str]:
    now = time.time()
    if (now - _CAPSULE_LIST_CACHE["ts"]) < _CAPSULE_LIST_TTL_SEC and _CAPSULE_LIST_CACHE["items"]:
        return _CAPSULE_LIST_CACHE["items"]

    items: List[str] = []
    try:
        files = HfApi().list_repo_files(repo_id=CEP_DATASET_ID, repo_type="dataset")
        for f in files:
            if f.endswith(".json") and f.startswith("CEP-") and not f.lower().endswith("index.json"):
                items.append(Path(f).stem)
        items = sorted(set(items))[:350]
    except Exception:
        items = []

    _CAPSULE_LIST_CACHE["ts"] = now
    _CAPSULE_LIST_CACHE["items"] = items
    return items


def fetch_capsule(cep_id: str) -> Dict[str, Any]:
    path = hf_hub_download(
        repo_id=CEP_DATASET_ID,
        filename=f"{cep_id}.json",
        repo_type="dataset",
    )
    with open(path, "r", encoding="utf-8") as f:
        return json.load(f)


def compute_trust(checks: Dict[str, bool]) -> Tuple[str, str, float]:
    missing = [k for k, v in checks.items() if not v]

    if not missing:
        return ("GREEN", "Fully anchored: evidence + signature + hashchain bound.", 1.0)

    if missing == ["hashchain_root"]:
        return ("YELLOW", "Evidence present, but not bound to a verifiable training run (missing hashchain).", 0.62)

    if missing == ["signature"]:
        return ("YELLOW", "Evidence present, but missing signature metadata (publisher not authenticated).", 0.58)

    if "evidence" in missing:
        return ("RED", "No evidence nodes inside capsule (cannot inspect annex/payout anchors).", 0.18)

    return ("RED", "Incomplete evidence: missing critical verification anchors.", 0.28)


def make_terminal_and_inspector(capsule: Dict[str, Any], cep_id: str) -> Dict[str, Any]:
    terminal: List[str] = []
    inspector: List[str] = []

    schema = capsule.get("schema", "unknown")
    period = capsule.get("period", "unknown")
    model = capsule.get("model", {})
    model_id = model.get("model_id", "unknown-model") if isinstance(model, dict) else "unknown-model"

    evidence = capsule.get("evidence", {})
    if not isinstance(evidence, dict):
        evidence = {}

    meta = capsule.get("meta", {}) if isinstance(capsule.get("meta"), dict) else {}
    hashchain_root = meta.get("hashchain_sha256", "")
    hashchain_present = isinstance(hashchain_root, str) and bool(hashchain_root.strip())
    sig_present = "signature" in capsule

    cap_sha = _sha256_hex(_canonical_json_bytes(capsule))

    checks = {
        "schema": isinstance(schema, str) and schema != "unknown",
        "period": isinstance(period, str) and len(period) >= 4,
        "model_id": isinstance(model_id, str) and model_id != "unknown-model",
        "evidence": isinstance(evidence, dict) and len(evidence) > 0,
        "signature": bool(sig_present),
        "hashchain_root": bool(hashchain_present),
    }

    trust_level, trust_reason, trust_score = compute_trust(checks)

    terminal.append("CROVIA // PRISM CONSOLE v1")
    terminal.append(f"capsule    {cep_id}")
    terminal.append(f"timestamp  {_nowz()}")
    terminal.append(f"mode       {'OPEN DEMO (light checks)' if OPEN_DEMO_MODE else 'FULL'}")
    terminal.append("")
    terminal.append("[STRUCTURE]")
    terminal.append(f"schema     {schema}")
    terminal.append(f"model      {model_id}")
    terminal.append(f"period     {period}")
    terminal.append(f"evidence   {len(evidence)} nodes")
    terminal.append("")
    terminal.append("[TRUST]")
    terminal.append(f"level      {trust_level}")
    terminal.append(f"reason     {trust_reason}")
    terminal.append("")
    terminal.append("[INTEGRITY]")
    terminal.append(f"capsule_sha256  {cap_sha}")
    terminal.append(f"signature       {'present' if sig_present else 'missing'}")
    terminal.append(f"hashchain       {('sha256:' + _short(hashchain_root, 16)) if hashchain_present else 'missing'}")
    terminal.append("")

    proof = f"crovia:v1;m={model_id};p={period};h={cap_sha};u=hf://{CEP_DATASET_ID}/{cep_id}.json"
    terminal.append("[PROOF STRING]")
    terminal.append(proof)
    terminal.append("")
    if trust_level != "GREEN":
        terminal.append("[WHY THIS MATTERS]")
        if not hashchain_present:
            terminal.append("- Not bound to a verifiable training run (no hashchain anchor).")
        if not sig_present:
            terminal.append("- Publisher not authenticated (no signature metadata).")
        if len(evidence) == 0:
            terminal.append("- No inspectable annex/payout nodes in evidence.")
        terminal.append("")

    inspector.append("INSPECTOR (real checks)")
    for k in ["schema", "period", "model_id", "evidence", "signature", "hashchain_root"]:
        inspector.append(f"- {k:13s} : {'OK' if checks[k] else 'FAIL'}")
    inspector.append("")
    inspector.append("TRUST SIGNAL")
    inspector.append(f"- level : {trust_level}")
    inspector.append(f"- score : {trust_score:.2f}")
    inspector.append(f"- note  : {trust_reason}")
    inspector.append("")
    inspector.append("EVIDENCE NODES (first 18)")
    if evidence:
        for ek, ev in list(evidence.items())[:18]:
            if isinstance(ev, dict):
                sha = ev.get("sha256", "")
                url = ev.get("url", "")
                path = ev.get("path", "")
                line = f"- {ek}"
                if sha:
                    line += f" | sha256:{_short(str(sha), 16)}"
                if url:
                    line += f" | url:{str(url)[:88]}"
                if path:
                    line += f" | path:{str(path)[:88]}"
                inspector.append(line)
            else:
                inspector.append(f"- {ek} | (non-object)")
    else:
        inspector.append("- (none)")

    nodes = list(evidence.keys())
    anchors = ["receipts", "payouts", "signature", "hashchain"]
    for a in anchors:
        if a not in nodes:
            nodes.append(a)

    return {
        "cep_id": cep_id,
        "schema": schema,
        "period": period,
        "model_id": model_id,
        "trust_level": trust_level,
        "trust_reason": trust_reason,
        "trust_score": trust_score,
        "capsule_sha256": cap_sha,
        "signature_present": sig_present,
        "hashchain_present": hashchain_present,
        "hashchain_sha256": hashchain_root if hashchain_present else "",
        "proof": proof,
        "terminal": "\n".join(terminal),
        "inspector": "\n".join(inspector),
        "nodes": nodes,
    }


def inspect_payload(cep_id: str) -> str:
    cep_id = (cep_id or "").strip()
    if not cep_id:
        return json.dumps({"error": "empty"}, ensure_ascii=False)

    try:
        cap = fetch_capsule(cep_id)
    except Exception as e:
        return json.dumps(
            {
                "error": "fetch_failed",
                "cep_id": cep_id,
                "detail": f"{type(e).__name__}: {e}",
            },
            ensure_ascii=False,
        )

    payload = make_terminal_and_inspector(cap, cep_id)
    return json.dumps(payload, ensure_ascii=False)


CSS = r"""
<style>
  :root{
    --bg0:#05060a;
    --bg1:#070a12;
    --panel:#0b1020;
    --ink:#e7eaf1;
    --ink-strong:#f8fafc;
    --mut:#cbd5e1;
    --line:rgba(255,255,255,.10);
    --glow:rgba(56,189,248,.35);
    --good:#22c55e;
    --warn:#f59e0b;
    --bad:#ef4444;
    --cyan:#38bdf8;
    --shadow: 0 18px 55px rgba(0,0,0,.55);
    --radius:16px;
    --p:0.62;
  }

  html,body,#root,.gradio-container{
    background:var(--bg0) !important;
  }

  .gradio-container{
    max-width:1320px !important;
    margin:0 auto !important;
    padding:26px 18px 70px !important;
    font-family:ui-sans-serif,system-ui,-apple-system,Segoe UI,Roboto,Arial;
    color:var(--ink) !important;
  }

  footer{display:none !important;}
  .gradio-container .wrap{border:0 !important;}
  .gradio-container label{display:none !important;}
  .gradio-container .prose{max-width:none !important;}

  /* HARD VISIBILITY (HF dimming killer) */
  .gradio-container, .gradio-container *{
    opacity:1 !important;
    filter:none !important;
    mix-blend-mode:normal !important;
    visibility:visible !important;
  }

  /* HERO */
  .crovia-hero{
    position:relative;
    border-radius:var(--radius);
    border:1px solid var(--line);
    background:
      radial-gradient(1000px 320px at 22% 10%, rgba(56,189,248,.18), transparent 60%),
      radial-gradient(800px 320px at 70% 0%, rgba(34,197,94,.14), transparent 55%),
      linear-gradient(180deg,#070a12,#05060a);
    box-shadow:var(--shadow);
    padding:22px 22px 18px;
    overflow:hidden;
    isolation:isolate;
  }

  .hero-top{
    display:flex;
    align-items:center;
    gap:14px;
  }

  .hero-logo{
    width:64px;height:64px;
    border-radius:16px;
    background:#070a12;
    border:1px solid rgba(255,255,255,.14);
    box-shadow:0 0 34px rgba(56,189,248,.28);
    display:flex;
    align-items:center;
    justify-content:center;
    overflow:hidden;
    flex:0 0 auto;
  }

  .hero-logo img{width:100%;height:100%;object-fit:cover;display:block;}

  .hero-title{
    margin:0;
    display:inline-block;
    padding:6px 10px;
    border-radius:12px;
    font-size:34px;
    font-weight:900;
    letter-spacing:.22em;
    text-transform:uppercase;
    color:#ffffff !important;
    background:rgba(0,0,0,.28);
    border:1px solid rgba(255,255,255,.08);
    text-shadow:
      0 0 26px rgba(56,189,248,.55),
      0 2px 14px rgba(0,0,0,.85);
  }

  .hero-sub{
    margin:10px 0 0;
    color:#e5e7eb !important;
    font-size:15px;
    line-height:1.7;
    max-width:900px;
  }

  .hero-sub strong{color:var(--ink-strong) !important;font-weight:700;}

  .hero-row{
    margin-top:14px;
    display:flex;
    gap:10px;
    flex-wrap:wrap;
    align-items:center;
  }

  .pill{
    display:inline-flex;
    align-items:center;
    gap:8px;
    padding:6px 12px;
    border-radius:999px;
    border:1px solid rgba(255,255,255,.14);
    background:rgba(255,255,255,.05);
    color:var(--ink-strong) !important;
    font-size:11px;
    letter-spacing:.14em;
    text-transform:uppercase;
  }

  .dot{
    width:8px;height:8px;
    border-radius:999px;
    background:var(--cyan);
    box-shadow:0 0 16px var(--glow);
  }

  .pill.good .dot{background:var(--good);box-shadow:0 0 16px rgba(34,197,94,.40);}
  .pill.warn .dot{background:var(--warn);box-shadow:0 0 16px rgba(245,158,11,.40);}
  .pill.bad  .dot{background:var(--bad); box-shadow:0 0 16px rgba(239,68,68,.40);}

  .mini{
    font-size:12.5px;
    color:#f8fafc !important;
    opacity:.85;
  }

  .status-line{
    margin-top:14px;
    padding:8px 14px;
    border-radius:10px;
    border:1px solid rgba(255,255,255,.14);
    background:rgba(0,0,0,.35);
    font-size:12px;
    letter-spacing:.14em;
    text-transform:uppercase;
    color:#e5e7eb !important;
    box-shadow: inset 0 0 18px rgba(56,189,248,.12);
  }

  /* === CEP PICKER (HTML select) — NO GRADIO MOVE === */
  #cep_picker{
    margin-top:10px;
    width:620px;
    max-width:100%;
  }

  #cep_select{
    width:100%;
    height:44px;
    border-radius:12px;
    background:#05060a;
    color:#f8fafc;
    border:1px solid rgba(255,255,255,.16);
    padding:0 42px 0 14px;
    outline:none;
    appearance:none;
    -webkit-appearance:none;
    -moz-appearance:none;
    cursor:pointer;
  }

  #cep_picker{
    position:relative;
  }
  #cep_picker::after{
    content:"⌄";
    position:absolute;
    right:16px;
    top:50%;
    transform:translateY(-50%);
    pointer-events:none;
    color:#38bdf8;
    font-size:18px;
    opacity:.85;
  }

  /* GRID */
  .grid{
    margin-top:18px;
    display:grid;
    grid-template-columns:1fr 1fr;
    gap:16px;
  }
  @media (max-width:980px){ .grid{grid-template-columns:1fr;} }

  .card{
    border-radius:var(--radius);
    border:1px solid var(--line);
    background:
      radial-gradient(600px 240px at 10% 10%, rgba(56,189,248,.10), transparent 55%),
      linear-gradient(180deg,#070a12,#05060a);
    box-shadow:var(--shadow);
    overflow:hidden;
  }

  .card-h{
    padding:10px 14px;
    border-bottom:1px solid var(--line);
    letter-spacing:.18em;
    text-transform:uppercase;
    font-weight:800;
    font-size:12px;
    color:var(--ink-strong) !important;
    background:linear-gradient(90deg,rgba(255,255,255,.05),transparent 55%);
  }

  .card-b{padding:12px 14px;}

  pre.term{
    margin:0;
    padding:12px;
    border-radius:12px;
    border:1px solid rgba(255,255,255,.10);
    background:
      radial-gradient(500px 220px at 20% 10%, rgba(56,189,248,.10), transparent 55%),
      #05060a;
    color:#e5e7eb !important;
    font-family:ui-monospace,SFMono-Regular,Menlo,Monaco,Consolas,"Liberation Mono",monospace;
    font-size:12.6px;
    line-height:1.55;
    min-height:330px;
    white-space:pre-wrap;
  }

  svg#constellation{
    width:100%;
    min-height:330px;
    border-radius:12px;
    border:1px solid rgba(255,255,255,.10);
    background:
      radial-gradient(520px 240px at 25% 15%, rgba(56,189,248,.12), transparent 60%),
      radial-gradient(420px 240px at 75% 80%, rgba(34,197,94,.10), transparent 55%),
      #05060a;
  }

  /* TRUST pill — make state readable (container, not only dot) */
  .pill.good{
    background: rgba(34,197,94,.14) !important;
    border-color: rgba(34,197,94,.45) !important;
  }
  .pill.warn{
    background: rgba(245,158,11,.14) !important;
    border-color: rgba(245,158,11,.45) !important;
  }
  .pill.bad{
    background: rgba(239,68,68,.14) !important;
    border-color: rgba(239,68,68,.45) !important;
  }
  #trust_text{
    color:#f8fafc !important;
    text-shadow:0 1px 12px rgba(0,0,0,.6);
  }

</style>
"""


UI_HTML = r"""
<div class="crovia-hero">
  <div class="hero-top">
    <div class="hero-logo">
      <img src="https://huggingface.co/spaces/Crovia/cep-terminal/resolve/main/crovia-logo.png" alt="CROVIA logo"/>
    </div>
    <div>
      <h1 class="hero-title">CROVIA · CEP TERMINAL</h1>
      <p class="hero-sub">
        Public inspection of AI training evidence capsules.
        <strong>No simulations. No assumptions.</strong> Only what exists.
      </p>
      <div class="hero-row">
        <div id="pill_trust" class="pill warn"><span class="dot"></span><span id="trust_text">TRUST: —</span></div>
        <div class="pill"><span class="dot"></span><span>DATASET: Crovia/cep-capsules</span></div>
        <div class="pill"><span class="dot"></span><span>MODE: OPEN DEMO</span></div>
      </div>
      <div class="mini" id="mini_line">
        ▶ Select a <strong>CEP fingerprint</strong> to inspect real training evidence.
      </div>

      <div class="status-line" id="status_line">
        STATUS: — awaiting capsule selection
      </div>

      <div id="cep_picker"></div>
    </div>
  </div>
</div>

<div class="grid">
  <div class="card">
    <div class="card-h">C-LINE OUTPUT</div>
    <div class="card-b">
      <pre id="crovia_terminal" class="term">Loading…</pre>
      <div class="mini" id="copy_hint">—</div>
    </div>
  </div>

  <div class="card">
    <div class="card-h">PRISM MAP</div>
    <div class="card-b">
      <svg id="constellation" viewBox="0 0 820 360" preserveAspectRatio="xMidYMid meet"></svg>
    </div>
  </div>

  <div class="card" style="grid-column: 1 / -1;">
    <div class="card-h">INSPECTOR</div>
    <div class="card-b">
      <pre id="crovia_inspector" class="term" style="min-height:240px;">—</pre>
    </div>
  </div>
</div>
"""


JS = r"""
() => {
  const $ = (q) => document.querySelector(q);

  function setPill(level){
    const pill = $("#pill_trust");
    if(!pill) return;
    pill.classList.remove("good","warn","bad");
    if(level==="GREEN") pill.classList.add("good");
    else if(level==="YELLOW") pill.classList.add("warn");
    else pill.classList.add("bad");
  }

  function drawConstellation(payload){
    const svg = $("#constellation");
    if(!svg) return;
    while(svg.firstChild) svg.removeChild(svg.firstChild);

    const W = 820, H = 360;
    const cx = W/2, cy = H/2 + 6;
    const r = 130;

    const nodes = (payload.nodes || []).slice(0, 28);
    const anchors = new Set(["receipts","payouts","signature","hashchain"]);
    const sigOn = !!payload.signature_present;
    const hcOn  = !!payload.hashchain_present;

    function colorOf(name){
      if(name==="signature") return sigOn ? "#22c55e" : "rgba(255,255,255,.35)";
      if(name==="hashchain") return hcOn  ? "#22c55e" : "rgba(255,255,255,.35)";
      if(name==="receipts" || name==="payouts") return "#38bdf8";
      return anchors.has(name) ? "#38bdf8" : "rgba(231,234,241,.72)";
    }

    const bg = document.createElementNS("http://www.w3.org/2000/svg","circle");
    bg.setAttribute("cx", cx); bg.setAttribute("cy", cy);
    bg.setAttribute("r", 150);
    bg.setAttribute("fill", "rgba(56,189,248,.06)");
    svg.appendChild(bg);

    nodes.forEach((name, i) => {
      const a = (Math.PI * 2) * (i / Math.max(1, nodes.length));
      const x = cx + r * Math.cos(a);
      const y = cy + r * Math.sin(a);

      const line = document.createElementNS("http://www.w3.org/2000/svg","line");
      line.setAttribute("x1", cx); line.setAttribute("y1", cy);
      line.setAttribute("x2", x);  line.setAttribute("y2", y);
      line.setAttribute("stroke", "rgba(255,255,255,.16)");
      line.setAttribute("stroke-width", "1");
      svg.appendChild(line);
    });

    const center = document.createElementNS("http://www.w3.org/2000/svg","circle");
    center.setAttribute("cx", cx); center.setAttribute("cy", cy);
    center.setAttribute("r", 10);
    center.setAttribute("fill", "#38bdf8");
    svg.appendChild(center);

    const ctext = document.createElementNS("http://www.w3.org/2000/svg","text");
    ctext.setAttribute("x", cx);
    ctext.setAttribute("y", cy + 28);
    ctext.setAttribute("text-anchor", "middle");
    ctext.setAttribute("fill", "rgba(231,234,241,.92)");
    ctext.setAttribute("font-size", "12");
    ctext.textContent = payload.cep_id || "CEP";
    svg.appendChild(ctext);

    nodes.forEach((name, i) => {
      const a = (Math.PI * 2) * (i / Math.max(1, nodes.length));
      const x = cx + r * Math.cos(a);
      const y = cy + r * Math.sin(a);

      const dot = document.createElementNS("http://www.w3.org/2000/svg","circle");
      dot.setAttribute("cx", x); dot.setAttribute("cy", y);
      dot.setAttribute("r", anchors.has(name) ? 7 : 5);
      dot.setAttribute("fill", colorOf(name));
      svg.appendChild(dot);

      const t = document.createElementNS("http://www.w3.org/2000/svg","text");
      t.setAttribute("x", x);
      t.setAttribute("y", y - 10);
      t.setAttribute("text-anchor", "middle");
      t.setAttribute("fill", "rgba(231,234,241,.78)");
      t.setAttribute("font-size", "11");
      t.textContent = name;
      svg.appendChild(t);
    });
  }

  function updateUI(payload){
    if(!payload || payload.error){
      $("#crovia_terminal").textContent =
        "CROVIA // PRISM CONSOLE v1\n\n[ERROR]\n" + (payload?.detail || payload?.error || "unknown");
      $("#crovia_inspector").textContent = "—";
      $("#trust_text").textContent = "TRUST: ERROR";
      setPill("RED");
      drawConstellation({
        cep_id: payload?.cep_id || "CEP",
        nodes:["receipts","payouts","signature","hashchain"],
        signature_present:false,
        hashchain_present:false
      });
      return;
    }

    $("#crovia_terminal").textContent = payload.terminal || "—";
    $("#crovia_inspector").textContent = payload.inspector || "—";

    const level = payload.trust_level || "YELLOW";
    $("#trust_text").textContent = "TRUST: " + level;
    setPill(level);

    $("#mini_line").textContent = payload.trust_reason || "Select a CEP fingerprint to light up the Prism.";
    drawConstellation(payload);
  }

  function attachPayloadWatcher(){
    const root = document.querySelector("#crovia_payload");
    if(!root) return false;

    const input = root.querySelector("textarea, input");
    if(!input) return false;

    let last = "";
    const tick = () => {
      const val = input.value || "";
      if(val && val !== last){
        last = val;
        try{ updateUI(JSON.parse(val)); }catch(e){}
      }
    };

    input.addEventListener("input", tick);
    setInterval(tick, 250);
    return true;
  }

  // Build a REAL HTML <select> inside #cep_picker (no Gradio DOM move)
  function mountCepSelect(){
    const host = $("#cep_picker");
    if(!host) return false;

    // already mounted
    if(host.querySelector("#cep_select")) return true;

    const capsRoot = document.querySelector("#capsules_json");
    const capsInput = capsRoot ? capsRoot.querySelector("textarea, input") : null;
    if(!capsInput) return false;

    let caps = [];
    try{ caps = JSON.parse(capsInput.value || "[]"); }catch(e){ caps = []; }

    const cepRoot = document.querySelector("#cep_in");
    const cepInput = cepRoot ? cepRoot.querySelector("textarea, input") : null;
    if(!cepInput) return false;

    const sel = document.createElement("select");
    sel.id = "cep_select";

    caps.forEach((c) => {
      const opt = document.createElement("option");
      opt.value = c;
      opt.textContent = c;
      sel.appendChild(opt);
    });

    if(cepInput.value){
      sel.value = cepInput.value;
    }else if(caps.length){
      sel.value = caps[0];
      cepInput.value = caps[0];
      cepInput.dispatchEvent(new Event("input", { bubbles:true }));
    }

    sel.addEventListener("change", () => {
      cepInput.value = sel.value;
      // Trigger Gradio
      cepInput.dispatchEvent(new Event("input", { bubbles:true }));
      cepInput.dispatchEvent(new Event("change", { bubbles:true }));
    });

    host.appendChild(sel);
    return true;
  }

  const boot = setInterval(() => {
    const ok1 = mountCepSelect();
    const ok2 = attachPayloadWatcher();
    if(ok1 && ok2) clearInterval(boot);
  }, 200);

  return [];
}
"""

capsules = _list_capsules()
default_cep = capsules[0] if capsules else "CEP-2511-K4I7X2"

# =============================================================================
# ORACLE UI - Model Trust Analysis
# =============================================================================

ORACLE_CSS = """
.oracle-section {
    margin-top: 24px;
    padding: 20px;
    background: linear-gradient(180deg, #0a0c14, #05060a);
    border: 1px solid rgba(139, 92, 246, 0.3);
    border-radius: 16px;
}
.oracle-title {
    color: #a78bfa !important;
    font-size: 18px;
    font-weight: 700;
    margin-bottom: 16px;
    letter-spacing: 0.1em;
}
.oracle-result {
    padding: 16px;
    background: rgba(0,0,0,0.4);
    border-radius: 12px;
    font-family: 'JetBrains Mono', monospace;
}
.score-gold { color: #F59E0B !important; }
.score-silver { color: #94A3B8 !important; }
.score-bronze { color: #D97706 !important; }
.score-red { color: #EF4444 !important; }
"""

def analyze_hf_model(model_id: str) -> str:
    """Analyze a HuggingFace model with the Omission Oracle."""
    model_id = (model_id or "").strip()
    if not model_id:
        return "Enter a model ID (e.g., meta-llama/Llama-3-8B)"
    
    try:
        api = HfApi()
        info = api.model_info(model_id, securityStatus=False)
        
        model_data = {
            "id": info.id,
            "author": info.author or "",
            "tags": info.tags or [],
            "license": info.card_data.get("license") if info.card_data else None,
            "cardData": info.card_data or {},
            "downloads": info.downloads or 0,
            "likes": info.likes or 0,
        }
        
        result = analyze_model_shadow_score(model_data)
        
        # Format output
        badge_emoji = {"GOLD": "🟢", "SILVER": "🟡", "BRONZE": "🟠", "UNVERIFIED": "🔴"}
        emoji = badge_emoji.get(result["badge"], "⚪")
        
        violations_str = ""
        if result["violations"]:
            for v in result["violations"]:
                violations_str += f"\n  • {v['id']}: {v['reason']}"
        else:
            violations_str = "\n  ✓ No violations detected"
        
        output = f"""╔══════════════════════════════════════════════════════════════╗
║  CROVIA OMISSION ORACLE v{ENGINE_VERSION}                              ║
╚══════════════════════════════════════════════════════════════╝

MODEL: {result['model_id']}
AUTHOR: {result['author']}

┌─────────────────────────────────────┐
│  SHADOW SCORE: {result['shadow_score']:3d}/100  {emoji} {result['badge']:12s}│
│  SEVERITY: {result['severity']:10s}                  │
└─────────────────────────────────────┘

DECLARATIONS:
  License: {result['license']}
  
VIOLATIONS ({result['violation_count']}): {violations_str}

ANALYSIS: {result['analyzed_at'][:19]}Z
EVIDENCE: {hashlib.sha256(model_id.encode()).hexdigest()[:16]}

─────────────────────────────────────
Powered by Crovia Omission Oracle
https://huggingface.co/datasets/Crovia/global-ai-training-omissions
"""
        return output
        
    except Exception as e:
        return f"Error analyzing model: {type(e).__name__}: {e}"


with gr.Blocks(
    title="CROVIA · CEP Terminal v2.0",
    css=CSS + ORACLE_CSS,
    js=JS
) as demo:

    gr.HTML(UI_HTML)

    # Provide capsules list to JS via hidden textbox
    capsules_json = gr.Textbox(value=json.dumps(capsules, ensure_ascii=False), visible=False, elem_id="capsules_json")

    # CEP input for backend (JS writes into this)
    cep_in = gr.Textbox(value=default_cep, visible=False, elem_id="cep_in")

    # Payload output watched by JS
    payload = gr.Textbox(value="", visible=False, elem_id="crovia_payload")

    def _run(cep_id: str) -> str:
        return inspect_payload(cep_id)

    # When cep_in changes -> compute payload
    cep_in.change(_run, inputs=cep_in, outputs=payload)
    demo.load(_run, inputs=cep_in, outputs=payload)
    
    # ==========================================================================
    # OMISSION ORACLE SECTION
    # ==========================================================================
    
    gr.HTML("""
    <div class="oracle-section">
        <div class="oracle-title">🔮 OMISSION ORACLE — Model Trust Scanner</div>
        <p style="color:#a1a1aa;font-size:13px;margin-bottom:12px;">
            Analyze any HuggingFace model for trust declaration gaps (NEC#1, NEC#2, NEC#7, NEC#13)
        </p>
    </div>
    """)
    
    with gr.Row():
        model_input = gr.Textbox(
            label="Model ID",
            placeholder="meta-llama/Llama-3-8B",
            scale=3
        )
        analyze_btn = gr.Button("🔍 Analyze", variant="primary", scale=1)
    
    oracle_output = gr.Code(
        label="Oracle Analysis",
        language=None,
        lines=25
    )
    
    analyze_btn.click(analyze_hf_model, inputs=model_input, outputs=oracle_output)
    model_input.submit(analyze_hf_model, inputs=model_input, outputs=oracle_output)

demo.launch()