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Update logbook: Repro - The Optimal Sample Complexity of Linear Contracts

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Files changed (16) hide show
  1. README.md +12 -4
  2. bucket-icon.svg +5 -0
  3. index.html +52 -17
  4. logbook.css +1602 -0
  5. logbook.js +2275 -0
  6. logbook.json +61 -0
  7. pages/claim-1/page.md +450 -0
  8. pages/claim-2/page.md +450 -0
  9. pages/conclusion/page.md +20 -0
  10. pages/index.md +12 -0
  11. pages/methods/page.md +10 -0
  12. pages/negative-controls/page.md +28 -0
  13. pages/overview/page.md +10 -0
  14. trackio-logo-light.png +0 -0
  15. trackio-logo.png +0 -0
  16. trackio-wordmark-dark.png +0 -0
README.md CHANGED
@@ -1,10 +1,18 @@
1
  ---
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- title: Ry5HitnXzc
3
- emoji: 🦀
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  colorFrom: yellow
5
- colorTo: green
6
  sdk: static
7
  pinned: false
 
 
 
 
 
 
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  ---
9
 
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- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
 
 
1
  ---
2
+ title: "Repro - The Optimal Sample Complexity of Linear Contracts"
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+ emoji: 🎯
4
  colorFrom: yellow
5
+ colorTo: red
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  sdk: static
7
  pinned: false
8
+ tags:
9
+ - trackio
10
+ - trackio-logbook
11
+ - open-experiment
12
+ - icml2026-repro
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+ - paper-ry5HitnXzc
14
  ---
15
 
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+ # Repro - The Optimal Sample Complexity of Linear Contracts
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+
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+ An open experiment logbook, published with [Trackio](https://github.com/gradio-app/trackio).
bucket-icon.svg ADDED
index.html CHANGED
@@ -1,19 +1,54 @@
1
  <!doctype html>
2
- <html>
3
- <head>
4
- <meta charset="utf-8" />
5
- <meta name="viewport" content="width=device-width" />
6
- <title>My static Space</title>
7
- <link rel="stylesheet" href="style.css" />
8
- </head>
9
- <body>
10
- <div class="card">
11
- <h1>Welcome to your static Space!</h1>
12
- <p>You can modify this app directly by editing <i>index.html</i> in the Files and versions tab.</p>
13
- <p>
14
- Also don't forget to check the
15
- <a href="https://huggingface.co/docs/hub/spaces" target="_blank">Spaces documentation</a>.
16
- </p>
17
- </div>
18
- </body>
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  </html>
 
1
  <!doctype html>
2
+ <html lang="en">
3
+ <head>
4
+ <meta charset="utf-8" />
5
+ <meta name="viewport" content="width=device-width, initial-scale=1" />
6
+ <title>Repro - The Optimal Sample Complexity of Linear Contracts</title>
7
+ <link rel="stylesheet" href="./logbook.css" />
8
+ </head>
9
+ <body>
10
+ <div id="app">
11
+ <aside id="sidebar">
12
+ <div id="book-head">
13
+ <img id="book-wordmark" src="./trackio-wordmark-dark.png" alt="" />
14
+ <div id="book-title" class="sr-only">Logbook</div>
15
+ </div>
16
+ <nav id="tree"></nav>
17
+ <div id="sidebar-foot" hidden>
18
+ <button id="connect-btn" type="button">
19
+ <span class="ico">ⓘ</span> Collaborate with your agent
20
+ </button>
21
+ </div>
22
+ </aside>
23
+ <main id="content">
24
+ <div id="page"></div>
25
+ </main>
26
+ </div>
27
+
28
+ <div id="modal" hidden>
29
+ <div class="modal-backdrop"></div>
30
+ <div class="modal-card" role="dialog" aria-modal="true">
31
+ <div class="modal-head">
32
+ <div class="modal-title">
33
+ <img class="modal-logo" src="./trackio-logo.png" alt="" />
34
+ Collaborate with your agent
35
+ </div>
36
+ <div class="modal-actions">
37
+ <button id="copy-agent" class="btn">Copy for agent</button>
38
+ <button id="modal-close" class="btn icon" aria-label="Close">×</button>
39
+ </div>
40
+ </div>
41
+ <div class="modal-body">
42
+ <p class="modal-intro">
43
+ Point your coding agent at this logbook. It reads a compact,
44
+ token-efficient version — and if you've given it write access to this
45
+ Space, it can add findings that sync back automatically.
46
+ </p>
47
+ <ol id="connect-steps"></ol>
48
+ </div>
49
+ </div>
50
+ </div>
51
+
52
+ <script src="./logbook.js"></script>
53
+ </body>
54
  </html>
logbook.css ADDED
@@ -0,0 +1,1602 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ :root {
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+ --code-bg: #f3f4f6;
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+ --radius: 12px;
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+ --serif: ui-serif, "Iowan Old Style", "Palatino Linotype", Georgia, serif;
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+ sans-serif;
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+ body {
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+ background: var(--bg);
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+ color: var(--ink);
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+ font-family: var(--sans);
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+ font-size: 13px;
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+ line-height: 1.65;
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+ -webkit-font-smoothing: antialiased;
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+ }
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+
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+ #app {
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+ display: flex;
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+ min-height: 100vh;
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+ }
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+
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+ /* ---- sidebar (composition-book cover) ---- */
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+ #sidebar {
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+ width: 280px;
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+ flex: 0 0 280px;
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+ background: #17181c;
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+ color: #e7e7ea;
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+ position: sticky;
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+ top: 0;
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+ height: 100vh;
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+ overflow-y: auto;
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+ padding: 22px 16px;
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+ display: flex;
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+ flex-direction: column;
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+ }
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+
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+ #book-head {
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+ display: flex;
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+ align-items: center;
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+ gap: 10px;
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+ padding: 8px;
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+ margin-bottom: 12px;
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+ border-radius: 10px;
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+ cursor: pointer;
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+ transition: background 0.12s;
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+ }
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+ #book-head:hover {
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+ background: rgba(255, 255, 255, 0.05);
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+ }
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+ #book-wordmark {
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+ width: 154px;
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+ height: auto;
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+ object-fit: contain;
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+ padding-top: 8px;
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+
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+ display: block;
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+ padding: 6px 10px;
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+ border-radius: 8px;
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+ color: #c3c4cb;
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+ font-size: 14px;
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+ transition: background 0.12s, color 0.12s;
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+
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+ background: rgba(255, 255, 255, 0.06);
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+ color: #ffffff;
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+ background: rgba(249, 115, 22, 0.16);
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+ font-weight: 600;
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+ color: #6b6d76;
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+ #tree a:hover .tree-mark,
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+ padding-left: 22px;
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+ padding-left: 34px;
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+ }
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+ #tree .depth-3 {
138
+ padding-left: 46px;
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+ }
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+
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+
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+ /* ---- content ---- */
143
+ #content {
144
+ flex: 1;
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+ min-width: 0;
146
+ padding: 48px 40px 120px;
147
+ background-color: var(--paper);
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+ linear-gradient(90deg, var(--grid-line) 1px, transparent 1px);
151
+ background-size: 26px 26px;
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+ background-position: center top;
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+ width: 100%;
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159
+ margin: 0 auto;
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+ display: grid;
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+ grid-template-columns: minmax(0, 760px) 248px;
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+ gap: 44px;
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+ align-items: start;
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+ }
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+
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+ .page-body {
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+ min-width: 0;
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+ }
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+
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+ .resource-anchor {
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+ display: block;
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+ height: 0;
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+ overflow: hidden;
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+ }
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+
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+ /* ---- pinned notes ---- */
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+ .pinned-notes {
191
+ margin: 30px 0 0;
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+ }
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+ .pinned-notes-list .cell {
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+ margin: 0;
195
+ border-color: rgba(249, 115, 22, 0.55);
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+ }
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+ .pinned-notes-list .cell + .cell {
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+ margin-top: 12px;
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+ border-color: rgba(249, 115, 22, 0.55);
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+ .book-intro.has-pinned-notes {
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+ border-bottom: none;
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+ padding-bottom: 22px;
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+ margin-bottom: 30px;
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+ .book-intro.book-intro-tight {
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+ padding-bottom: 4px;
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+ margin-bottom: 20px;
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+
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+ #page h1 {
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+ font-family: var(--serif);
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+ font-size: 34px;
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+ letter-spacing: -0.02em;
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+ margin: 0 0 8px;
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+ overflow-wrap: anywhere;
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+ }
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+
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+ #page .page-section:not(.book-intro) h1 {
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+ font-size: 26px;
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+ }
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+
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+ #page h2 {
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+ font-family: var(--serif);
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+ font-size: 24px;
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+ margin: 36px 0 10px;
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+ }
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+
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+ #page h3 {
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+ font-size: 17px;
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+ font-weight: 700;
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+ margin: 26px 0 2px;
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+ letter-spacing: -0.01em;
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+ }
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+
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+ #page h3::before {
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+ content: "";
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+ display: inline-block;
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+ width: 7px;
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+ transform: translateY(-1px);
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271
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280
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281
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284
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287
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+ /* ---- code blocks + collapsible accordion ---- */
290
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291
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292
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294
+ font-size: 13px;
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298
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299
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300
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302
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303
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305
+ margin: 12px 0;
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307
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309
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310
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311
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312
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313
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314
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315
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316
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317
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318
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321
+ overflow-wrap: anywhere;
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324
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327
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328
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329
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330
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331
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332
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333
+ .code-accordion[open] summary::after {
334
+ transform: rotate(90deg);
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337
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338
+ font-weight: 700;
339
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340
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341
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343
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347
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+ font-size: 12px;
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+ color: var(--muted);
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+ background: none;
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+
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+ /* ---- notebook-style cells ---- */
377
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378
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380
+ border-radius: 10px;
381
+ background: rgba(255, 255, 255, 0.86);
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+ box-shadow: 0 2px 10px rgba(31, 41, 55, 0.035);
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+ gap: 16px;
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392
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+ border-bottom: 1px solid var(--line);
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+ padding-top: 10px;
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404
+ font-weight: 650;
405
+ color: var(--ink);
406
+ line-height: 1.35;
407
+ overflow-wrap: anywhere;
408
+ }
409
+ .cell-meta {
410
+ flex: 0 0 auto;
411
+ display: flex;
412
+ align-items: center;
413
+ gap: 10px;
414
+ font-family: var(--sans);
415
+ font-size: 13px;
416
+ color: var(--muted);
417
+ }
418
+ .cell-open {
419
+ flex: 0 0 auto;
420
+ font-family: var(--mono);
421
+ font-size: 12px;
422
+ color: var(--accent);
423
+ text-decoration: none;
424
+ }
425
+ .cell-open:hover {
426
+ color: var(--accent-strong);
427
+ }
428
+ .cell-body {
429
+ min-width: 0;
430
+ padding: 14px 18px 18px;
431
+ }
432
+ .cell.dashboard .cell-body {
433
+ padding: 0;
434
+ }
435
+ #page .cell-body h1,
436
+ #page .cell-body h2 {
437
+ font-family: var(--sans);
438
+ font-size: 17px;
439
+ font-weight: 700;
440
+ letter-spacing: -0.01em;
441
+ line-height: 1.35;
442
+ margin: 22px 0 6px;
443
+ }
444
+ #page .cell-body > :first-child {
445
+ margin-top: 0;
446
+ }
447
+ #page .cell-body > :last-child {
448
+ margin-bottom: 0;
449
+ }
450
+ .cell.code .cell-head {
451
+ background: #fbfbfc;
452
+ }
453
+ .figure-fit {
454
+ position: relative;
455
+ overflow: hidden;
456
+ min-height: 160px;
457
+ border: 1px solid var(--line);
458
+ border-radius: 8px;
459
+ background: #fff;
460
+ }
461
+ .figure-fit[hidden] {
462
+ display: none;
463
+ }
464
+ .figure-fit:fullscreen,
465
+ .figure-fit:-webkit-full-screen {
466
+ width: 100%;
467
+ height: 100%;
468
+ border: none;
469
+ border-radius: 0;
470
+ }
471
+ .figure-frame {
472
+ display: block;
473
+ width: 100%;
474
+ min-height: 160px;
475
+ border: none;
476
+ background: #fff;
477
+ }
478
+ .figure-frame[hidden],
479
+ .figure-raw[hidden] {
480
+ display: none;
481
+ }
482
+ .fig-switch {
483
+ position: relative;
484
+ display: inline-flex;
485
+ flex: 0 0 auto;
486
+ border: 1px solid var(--line);
487
+ border-radius: 999px;
488
+ background: var(--code-bg);
489
+ padding: 2px;
490
+ }
491
+ .fig-switch button {
492
+ position: relative;
493
+ z-index: 1;
494
+ flex: 1;
495
+ min-width: 62px;
496
+ border: none;
497
+ background: none;
498
+ font-family: var(--sans);
499
+ font-size: 12px;
500
+ font-weight: 600;
501
+ color: var(--muted);
502
+ padding: 3px 12px;
503
+ border-radius: 999px;
504
+ cursor: pointer;
505
+ transition: color 0.15s;
506
+ }
507
+ .fig-switch button.active {
508
+ color: var(--accent-strong);
509
+ }
510
+ .fig-switch-thumb {
511
+ position: absolute;
512
+ top: 2px;
513
+ bottom: 2px;
514
+ left: 2px;
515
+ width: calc(50% - 2px);
516
+ border-radius: 999px;
517
+ background: var(--panel);
518
+ border: 1px solid rgba(249, 115, 22, 0.35);
519
+ box-shadow: 0 1px 4px rgba(31, 41, 55, 0.08);
520
+ transition: transform 0.18s ease;
521
+ }
522
+ .fig-switch.raw .fig-switch-thumb {
523
+ transform: translateX(100%);
524
+ }
525
+ #page .figure-raw pre {
526
+ margin: 0;
527
+ max-height: 420px;
528
+ overflow: auto;
529
+ font-family: var(--mono);
530
+ font-size: 13px;
531
+ line-height: 1.55;
532
+ background: var(--code-bg);
533
+ border: 1px solid var(--line);
534
+ border-radius: 8px;
535
+ padding: 12px 14px;
536
+ }
537
+ /* ---- figure fullscreen ---- */
538
+ .cell-fullscreen {
539
+ position: relative;
540
+ display: inline-flex;
541
+ flex: 0 0 auto;
542
+ }
543
+ .cell-fullscreen-btn {
544
+ display: inline-flex;
545
+ align-items: center;
546
+ justify-content: center;
547
+ width: 26px;
548
+ height: 26px;
549
+ padding: 0;
550
+ border: 1px solid var(--line);
551
+ border-radius: 999px;
552
+ background: var(--code-bg);
553
+ color: var(--muted);
554
+ cursor: pointer;
555
+ transition: color 0.15s, border-color 0.15s, background 0.15s;
556
+ }
557
+ .cell-fullscreen-btn:hover {
558
+ color: var(--accent-strong);
559
+ border-color: rgba(249, 115, 22, 0.35);
560
+ background: var(--accent-soft);
561
+ }
562
+ .cell-fullscreen-btn svg {
563
+ width: 14px;
564
+ height: 14px;
565
+ }
566
+ /* ---- copyable snippets ---- */
567
+ .snippet {
568
+ position: relative;
569
+ }
570
+ .copy-snippet {
571
+ position: absolute;
572
+ top: 7px;
573
+ right: 8px;
574
+ width: 24px;
575
+ height: 24px;
576
+ border: none;
577
+ border-radius: 6px;
578
+ background: rgba(255, 255, 255, 0.08);
579
+ color: #9a9da8;
580
+ font-size: 12px;
581
+ line-height: 1;
582
+ cursor: pointer;
583
+ opacity: 0;
584
+ transition: opacity 0.12s, color 0.12s, background 0.12s;
585
+ }
586
+ .snippet:hover .copy-snippet,
587
+ .jp-out:hover .copy-snippet,
588
+ .figure-raw:hover .copy-snippet,
589
+ .code-accordion summary:hover .copy-snippet {
590
+ opacity: 1;
591
+ }
592
+ .copy-snippet:hover {
593
+ color: #ffffff;
594
+ background: rgba(255, 255, 255, 0.16);
595
+ }
596
+ .copy-snippet.copied {
597
+ color: #52d08a;
598
+ opacity: 1;
599
+ }
600
+ .code-accordion .code-name {
601
+ user-select: text;
602
+ cursor: text;
603
+ }
604
+ .jp-out,
605
+ .figure-raw {
606
+ position: relative;
607
+ }
608
+ .jp-out .copy-snippet,
609
+ .figure-raw .copy-snippet {
610
+ background: var(--code-bg);
611
+ color: var(--muted);
612
+ border: 1px solid var(--line);
613
+ }
614
+ .jp-out .copy-snippet:hover,
615
+ .figure-raw .copy-snippet:hover {
616
+ color: var(--accent-strong);
617
+ background: var(--panel);
618
+ }
619
+
620
+ /* ---- jupyter-style code cells ---- */
621
+ .jp {
622
+ border: 1px solid var(--line);
623
+ border-radius: 10px;
624
+ overflow: hidden;
625
+ margin: 12px 0;
626
+ background: var(--panel);
627
+ }
628
+ .jp-gutter {
629
+ flex: 0 0 46px;
630
+ padding: 13px 0 0 13px;
631
+ font-family: var(--mono);
632
+ font-size: 10.5px;
633
+ letter-spacing: 0.07em;
634
+ text-transform: uppercase;
635
+ font-weight: 600;
636
+ user-select: none;
637
+ }
638
+ .jp-in {
639
+ display: flex;
640
+ background: #17181c;
641
+ }
642
+ .jp-in .jp-gutter {
643
+ color: #6f727d;
644
+ }
645
+ .jp-in-body {
646
+ flex: 1;
647
+ min-width: 0;
648
+ }
649
+ #page .jp-in-body pre.hl {
650
+ margin: 0;
651
+ border: none;
652
+ border-radius: 0;
653
+ background: none;
654
+ padding: 12px 16px 12px 0;
655
+ }
656
+ .jp-in-body .code-accordion {
657
+ margin: 0;
658
+ border: none;
659
+ border-top: 1px solid rgba(255, 255, 255, 0.09);
660
+ border-radius: 0;
661
+ background: none;
662
+ }
663
+ .jp-in-body .code-accordion summary {
664
+ background: none;
665
+ padding: 9px 16px 9px 0;
666
+ }
667
+ .jp-in-body .code-accordion pre.hl {
668
+ border-top: 1px solid rgba(255, 255, 255, 0.09);
669
+ }
670
+ .jp-meta {
671
+ padding: 5px 14px;
672
+ font-family: var(--mono);
673
+ font-size: 11.5px;
674
+ color: var(--muted);
675
+ background: #fbfbfc;
676
+ border-top: 1px solid var(--line);
677
+ }
678
+ .jp-out {
679
+ display: flex;
680
+ border-top: 1px solid var(--line);
681
+ background: var(--panel);
682
+ }
683
+ .jp-out .jp-gutter {
684
+ color: var(--accent-strong);
685
+ }
686
+ .jp-out-body {
687
+ flex: 1;
688
+ min-width: 0;
689
+ }
690
+ #page .jp-out-pre {
691
+ min-width: 0;
692
+ margin: 0;
693
+ border: none;
694
+ border-radius: 0;
695
+ background: none;
696
+ color: var(--ink);
697
+ font-family: var(--mono);
698
+ font-size: 13px;
699
+ line-height: 1.55;
700
+ padding: 12px 16px 12px 0;
701
+ white-space: pre;
702
+ overflow-x: auto;
703
+ overflow-y: auto;
704
+ max-height: 26em;
705
+ }
706
+ .jp-artifacts {
707
+ display: flex;
708
+ flex-direction: column;
709
+ }
710
+ .jp-out-body .jp-out-pre + .jp-artifacts {
711
+ border-top: 1px solid var(--line);
712
+ }
713
+ .out-artifact {
714
+ display: flex;
715
+ align-items: baseline;
716
+ gap: 8px;
717
+ padding: 9px 16px 9px 0;
718
+ text-decoration: none;
719
+ color: inherit;
720
+ }
721
+ .out-artifact + .out-artifact {
722
+ border-top: 1px solid var(--line);
723
+ }
724
+ a.out-artifact:hover .out-artifact-name {
725
+ color: var(--accent-strong);
726
+ }
727
+ .out-artifact-ico {
728
+ flex: 0 0 auto;
729
+ font-size: 13px;
730
+ }
731
+ .out-artifact-name {
732
+ font-family: var(--mono);
733
+ font-size: 12.5px;
734
+ font-weight: 600;
735
+ color: var(--ink);
736
+ overflow: hidden;
737
+ text-overflow: ellipsis;
738
+ white-space: nowrap;
739
+ }
740
+ .out-artifact-meta {
741
+ flex: 0 0 auto;
742
+ margin-left: auto;
743
+ padding-left: 12px;
744
+ font-size: 12px;
745
+ color: var(--muted);
746
+ white-space: nowrap;
747
+ }
748
+ .out-artifact-state.open {
749
+ color: var(--accent);
750
+ font-weight: 600;
751
+ }
752
+ .trackio-embed {
753
+ border: 1px solid var(--line);
754
+ border-radius: var(--radius);
755
+ overflow: hidden;
756
+ background: var(--panel);
757
+ }
758
+ .trackio-cell-meta {
759
+ display: flex;
760
+ gap: 6px;
761
+ flex-wrap: wrap;
762
+ justify-content: flex-end;
763
+ }
764
+
765
+ /* ---- unfurl cards ---- */
766
+ .unfurl {
767
+ display: block;
768
+ border: 1px solid var(--line);
769
+ border-radius: var(--radius);
770
+ background: var(--panel);
771
+ margin: 12px 0;
772
+ overflow: hidden;
773
+ text-decoration: none;
774
+ color: inherit;
775
+ transition: border-color 0.14s, box-shadow 0.14s;
776
+ }
777
+ .unfurl:hover {
778
+ border-color: #cfcbe6;
779
+ box-shadow: 0 4px 18px rgba(30, 20, 80, 0.06);
780
+ }
781
+
782
+ .unfurl-body {
783
+ padding: 13px 16px;
784
+ display: flex;
785
+ gap: 12px;
786
+ align-items: flex-start;
787
+ }
788
+
789
+ .unfurl-ico {
790
+ font-size: 20px;
791
+ line-height: 1.3;
792
+ flex: 0 0 auto;
793
+ }
794
+
795
+ .unfurl-main {
796
+ min-width: 0;
797
+ flex: 1;
798
+ }
799
+
800
+ .unfurl-kind {
801
+ font-family: var(--mono);
802
+ font-size: 10.5px;
803
+ text-transform: uppercase;
804
+ letter-spacing: 0.08em;
805
+ color: var(--accent);
806
+ font-weight: 600;
807
+ }
808
+
809
+ .unfurl-title {
810
+ font-weight: 650;
811
+ font-size: 15px;
812
+ margin: 1px 0 2px;
813
+ white-space: nowrap;
814
+ overflow: hidden;
815
+ text-overflow: ellipsis;
816
+ }
817
+
818
+ .unfurl-desc {
819
+ color: var(--muted);
820
+ font-size: 13.5px;
821
+ line-height: 1.45;
822
+ }
823
+
824
+ .unfurl-meta {
825
+ margin-top: 6px;
826
+ display: flex;
827
+ flex-wrap: wrap;
828
+ gap: 6px;
829
+ }
830
+
831
+ .chip {
832
+ font-size: 11.5px;
833
+ background: var(--code-bg);
834
+ border-radius: 999px;
835
+ padding: 2px 9px;
836
+ color: var(--muted);
837
+ font-family: var(--mono);
838
+ }
839
+
840
+ .unfurl-raw {
841
+ font-family: var(--mono);
842
+ font-size: 11px;
843
+ color: var(--muted);
844
+ border-top: 1px solid var(--line);
845
+ padding: 7px 16px;
846
+ white-space: nowrap;
847
+ overflow: hidden;
848
+ text-overflow: ellipsis;
849
+ }
850
+
851
+ .unfurl.embed {
852
+ padding: 0;
853
+ overflow: hidden;
854
+ }
855
+ .embed-head {
856
+ display: flex;
857
+ align-items: center;
858
+ gap: 10px;
859
+ padding: 10px 14px;
860
+ border-bottom: 1px solid var(--line);
861
+ }
862
+ .embed-head .unfurl-kind {
863
+ flex: 0 0 auto;
864
+ }
865
+ .embed-title {
866
+ flex: 1;
867
+ min-width: 0;
868
+ font-weight: 650;
869
+ font-size: 14px;
870
+ color: var(--ink);
871
+ text-decoration: none;
872
+ white-space: nowrap;
873
+ overflow: hidden;
874
+ text-overflow: ellipsis;
875
+ }
876
+ .embed-title:hover {
877
+ color: var(--accent);
878
+ }
879
+ .embed-open {
880
+ flex: 0 0 auto;
881
+ font-family: var(--mono);
882
+ font-size: 12px;
883
+ color: var(--accent);
884
+ text-decoration: none;
885
+ }
886
+ .embed-frame {
887
+ display: block;
888
+ width: 100%;
889
+ height: 560px;
890
+ border: 0;
891
+ background: var(--code-bg);
892
+ }
893
+
894
+ .dashboard-shell {
895
+ display: block;
896
+ }
897
+ .dashboard-shell .dashboard-frame {
898
+ display: block;
899
+ width: 100%;
900
+ height: 900px;
901
+ border: 0;
902
+ background: var(--code-bg);
903
+ }
904
+
905
+ .unfurl.image {
906
+ padding: 0;
907
+ }
908
+ .unfurl.image img {
909
+ display: block;
910
+ width: 100%;
911
+ height: auto;
912
+ max-height: 460px;
913
+ object-fit: contain;
914
+ background: var(--code-bg);
915
+ }
916
+
917
+ .artifact-chip {
918
+ border: 1px solid var(--line);
919
+ background: var(--panel);
920
+ border-radius: var(--radius);
921
+ padding: 10px 14px;
922
+ margin: 8px 0;
923
+ font-size: 14px;
924
+ }
925
+ .cell.dashboard .artifact-chip {
926
+ margin: 14px 18px 18px;
927
+ }
928
+ .artifact-chip code {
929
+ color: var(--accent);
930
+ }
931
+
932
+ /* ---- task board ---- */
933
+ .board-wrap {
934
+ overflow-x: auto;
935
+ border: 1px solid var(--line);
936
+ border-radius: var(--radius);
937
+ margin: 12px 0 20px;
938
+ background: var(--panel);
939
+ }
940
+ table.board {
941
+ border-collapse: collapse;
942
+ width: 100%;
943
+ font-size: 14px;
944
+ }
945
+ table.board th,
946
+ table.board td {
947
+ text-align: left;
948
+ padding: 9px 14px;
949
+ border-bottom: 1px solid var(--line);
950
+ vertical-align: top;
951
+ }
952
+ table.board thead th {
953
+ background: var(--accent-soft);
954
+ font-size: 12px;
955
+ text-transform: uppercase;
956
+ letter-spacing: 0.05em;
957
+ color: #9a4a12;
958
+ font-weight: 600;
959
+ border-bottom: 1px solid var(--line);
960
+ }
961
+ table.board tbody tr:last-child td {
962
+ border-bottom: none;
963
+ }
964
+ table.board .col-check {
965
+ text-align: center;
966
+ width: 92px;
967
+ white-space: nowrap;
968
+ }
969
+ table.board tr.section-row td {
970
+ background: var(--accent-soft);
971
+ text-align: center;
972
+ font-weight: 700;
973
+ font-size: 13px;
974
+ color: var(--accent-strong);
975
+ padding: 7px 14px;
976
+ letter-spacing: 0.02em;
977
+ }
978
+ .box {
979
+ display: inline-flex;
980
+ align-items: center;
981
+ justify-content: center;
982
+ width: 18px;
983
+ height: 18px;
984
+ border: 1.5px solid #cfcbe0;
985
+ border-radius: 5px;
986
+ font-size: 12px;
987
+ color: #fff;
988
+ line-height: 1;
989
+ }
990
+ .box.on {
991
+ background: var(--accent);
992
+ border-color: var(--accent);
993
+ }
994
+ .who-chip {
995
+ display: inline-block;
996
+ padding: 3px 12px;
997
+ border-radius: 999px;
998
+ font-size: 12.5px;
999
+ font-weight: 600;
1000
+ white-space: nowrap;
1001
+ }
1002
+ .who-chip.muted {
1003
+ background: var(--code-bg);
1004
+ color: var(--muted);
1005
+ font-weight: 500;
1006
+ }
1007
+
1008
+ /* ---- status badges + clickable rows ---- */
1009
+ table.board .col-status {
1010
+ width: 130px;
1011
+ white-space: nowrap;
1012
+ }
1013
+ .badge {
1014
+ display: inline-block;
1015
+ padding: 3px 11px;
1016
+ border-radius: 999px;
1017
+ font-size: 12px;
1018
+ font-weight: 600;
1019
+ letter-spacing: 0.01em;
1020
+ }
1021
+ .badge.gray {
1022
+ background: var(--code-bg);
1023
+ color: var(--muted);
1024
+ }
1025
+ .badge.amber {
1026
+ background: var(--accent-soft);
1027
+ color: #b45309;
1028
+ }
1029
+ .badge.green {
1030
+ background: #e6f7ee;
1031
+ color: #1a8a55;
1032
+ }
1033
+ .badge.red {
1034
+ background: #fde8ec;
1035
+ color: #c62a4b;
1036
+ }
1037
+ table.board tr.linked-row {
1038
+ cursor: pointer;
1039
+ }
1040
+ table.board tr.linked-row:hover td {
1041
+ background: var(--accent-soft);
1042
+ }
1043
+ table.board tr.linked-row a {
1044
+ color: var(--ink);
1045
+ font-weight: 600;
1046
+ text-decoration: none;
1047
+ }
1048
+ table.board tr.linked-row:hover a {
1049
+ color: var(--accent-strong);
1050
+ }
1051
+
1052
+ /* ---- agent read hint ---- */
1053
+ .agent-hint {
1054
+ display: flex;
1055
+ align-items: center;
1056
+ flex-wrap: wrap;
1057
+ gap: 8px;
1058
+ margin: 4px 0 22px;
1059
+ font-size: 12.5px;
1060
+ color: var(--muted);
1061
+ }
1062
+ #page .agent-hint code {
1063
+ background: var(--code-bg);
1064
+ padding: 2px 9px;
1065
+ border-radius: 6px;
1066
+ font-family: var(--mono);
1067
+ font-size: 12px;
1068
+ font-weight: 500;
1069
+ color: var(--ink);
1070
+ }
1071
+ .agent-hint .copy {
1072
+ flex: 0 0 auto;
1073
+ background: none;
1074
+ color: var(--muted);
1075
+ border: 1px solid var(--line);
1076
+ border-radius: 6px;
1077
+ width: 22px;
1078
+ height: 22px;
1079
+ font-size: 11px;
1080
+ line-height: 1;
1081
+ cursor: pointer;
1082
+ transition: color 0.12s, border-color 0.12s;
1083
+ }
1084
+ .agent-hint .copy:hover {
1085
+ color: var(--accent-strong);
1086
+ border-color: var(--accent);
1087
+ }
1088
+ .agent-hint .copy.copied {
1089
+ color: #1a8a55;
1090
+ border-color: #1a8a55;
1091
+ }
1092
+ .agent-hint-note {
1093
+ margin-left: auto;
1094
+ font-size: 12px;
1095
+ color: var(--muted);
1096
+ }
1097
+
1098
+ /* ---- logbook summary stats ---- */
1099
+ .logbook-stats {
1100
+ display: flex;
1101
+ flex-wrap: wrap;
1102
+ gap: 12px;
1103
+ margin: 0 0 28px;
1104
+ }
1105
+ .stat-tile {
1106
+ position: relative;
1107
+ display: inline-flex;
1108
+ align-items: center;
1109
+ gap: 11px;
1110
+ border: 1px solid var(--line);
1111
+ background: var(--panel);
1112
+ border-radius: var(--radius);
1113
+ padding: 12px 23px;
1114
+ font: inherit;
1115
+ text-align: left;
1116
+ cursor: pointer;
1117
+ transition: border-color 0.12s, box-shadow 0.12s;
1118
+ }
1119
+ .stat-tile:hover:not([disabled]) {
1120
+ border-color: rgba(249, 115, 22, 0.45);
1121
+ box-shadow: 0 3px 12px rgba(31, 41, 55, 0.06);
1122
+ }
1123
+ .stat-tile:focus-visible {
1124
+ outline: 2px solid var(--accent);
1125
+ outline-offset: 2px;
1126
+ }
1127
+ .stat-tile[disabled] {
1128
+ cursor: default;
1129
+ opacity: 0.7;
1130
+ }
1131
+ .stat-tile.open {
1132
+ border-color: rgba(249, 115, 22, 0.6);
1133
+ box-shadow: 0 3px 12px rgba(31, 41, 55, 0.08);
1134
+ }
1135
+ .stat-icon {
1136
+ width: 24px;
1137
+ height: 24px;
1138
+ flex: 0 0 24px;
1139
+ object-fit: contain;
1140
+ align-self: center;
1141
+ }
1142
+ .stat-text {
1143
+ display: flex;
1144
+ align-items: baseline;
1145
+ gap: 8px;
1146
+ white-space: nowrap;
1147
+ line-height: 1;
1148
+ }
1149
+ .stat-num {
1150
+ font-family: var(--mono);
1151
+ font-size: 20px;
1152
+ font-weight: 600;
1153
+ line-height: 1;
1154
+ color: var(--accent-strong);
1155
+ }
1156
+ .stat-label {
1157
+ font-size: 15px;
1158
+ line-height: 1;
1159
+ color: var(--muted);
1160
+ }
1161
+ .stat-caret {
1162
+ margin-left: 2px;
1163
+ font-size: 10px;
1164
+ color: var(--muted);
1165
+ align-self: center;
1166
+ transition: transform 0.12s;
1167
+ }
1168
+ .stat-tile.open .stat-caret {
1169
+ transform: rotate(180deg);
1170
+ }
1171
+ .stat-popover {
1172
+ position: absolute;
1173
+ top: 100%;
1174
+ left: 0;
1175
+ margin-top: 6px;
1176
+ min-width: 300px;
1177
+ max-width: min(460px, 92vw);
1178
+ max-height: 340px;
1179
+ overflow-y: auto;
1180
+ z-index: 20;
1181
+ background: var(--panel);
1182
+ border: 1px solid var(--line);
1183
+ border-radius: var(--radius);
1184
+ box-shadow: 0 8px 28px rgba(31, 41, 55, 0.12);
1185
+ padding: 6px;
1186
+ }
1187
+ .stat-popover[hidden] {
1188
+ display: none;
1189
+ }
1190
+ .stat-pop-head {
1191
+ padding: 6px 10px 8px;
1192
+ font-size: 11.5px;
1193
+ font-weight: 700;
1194
+ letter-spacing: 0.03em;
1195
+ text-transform: uppercase;
1196
+ color: var(--muted);
1197
+ }
1198
+ .stat-row {
1199
+ display: flex;
1200
+ align-items: flex-start;
1201
+ gap: 10px;
1202
+ padding: 9px 11px;
1203
+ border-radius: 9px;
1204
+ border: 1px solid transparent;
1205
+ text-decoration: none;
1206
+ color: inherit;
1207
+ cursor: pointer;
1208
+ }
1209
+ .stat-row:hover {
1210
+ border-color: rgba(249, 115, 22, 0.4);
1211
+ background: var(--accent-soft);
1212
+ }
1213
+ .stat-row-ico {
1214
+ font-size: 15px;
1215
+ line-height: 1.3;
1216
+ flex: 0 0 auto;
1217
+ }
1218
+ .stat-row-main {
1219
+ min-width: 0;
1220
+ flex: 1;
1221
+ }
1222
+ .stat-row-title {
1223
+ font-family: var(--mono);
1224
+ font-size: 12.5px;
1225
+ font-weight: 600;
1226
+ color: var(--ink);
1227
+ overflow: hidden;
1228
+ text-overflow: ellipsis;
1229
+ white-space: nowrap;
1230
+ }
1231
+ .stat-row-meta {
1232
+ margin-top: 2px;
1233
+ font-size: 12px;
1234
+ color: var(--muted);
1235
+ }
1236
+ .stat-row-state.open {
1237
+ color: var(--accent);
1238
+ font-weight: 600;
1239
+ border-radius: 5px;
1240
+ padding: 1px 5px;
1241
+ margin: -1px -2px;
1242
+ }
1243
+ .stat-row-state.open:hover {
1244
+ background: rgba(249, 115, 22, 0.14);
1245
+ text-decoration: underline;
1246
+ }
1247
+ .art-ico {
1248
+ width: 1em;
1249
+ height: 1em;
1250
+ object-fit: contain;
1251
+ vertical-align: -0.15em;
1252
+ }
1253
+
1254
+ /* ---- scroll-to-resource highlight ---- */
1255
+ .res-flash {
1256
+ animation: res-flash 1.5s ease;
1257
+ border-radius: 8px;
1258
+ }
1259
+ @keyframes res-flash {
1260
+ 0%,
1261
+ 25% {
1262
+ box-shadow: 0 0 0 3px var(--accent);
1263
+ }
1264
+ 100% {
1265
+ box-shadow: 0 0 0 3px rgba(249, 115, 22, 0);
1266
+ }
1267
+ }
1268
+
1269
+ /* ---- inline resource chips ---- */
1270
+ #page .res-chip {
1271
+ display: inline-flex;
1272
+ align-items: center;
1273
+ gap: 5px;
1274
+ max-width: 100%;
1275
+ padding: 0 9px 0 6px;
1276
+ margin: 0 1px;
1277
+ border: 1px solid var(--line);
1278
+ border-radius: 999px;
1279
+ background: var(--panel);
1280
+ font-family: var(--mono);
1281
+ font-size: 0.78em;
1282
+ font-weight: 600;
1283
+ color: var(--ink);
1284
+ text-decoration: none;
1285
+ white-space: nowrap;
1286
+ overflow: hidden;
1287
+ text-overflow: ellipsis;
1288
+ vertical-align: middle;
1289
+ line-height: 1.65;
1290
+ transform: translateY(-0.08em);
1291
+ transition: border-color 0.12s, background 0.12s, color 0.12s;
1292
+ }
1293
+ .res-chip-ico {
1294
+ font-size: 1.05em;
1295
+ line-height: 1;
1296
+ }
1297
+ #page .res-chip:hover,
1298
+ #page .res-chip.res-hl {
1299
+ border-color: var(--accent);
1300
+ background: var(--accent-soft);
1301
+ color: var(--accent-strong);
1302
+ }
1303
+ #page a.res-link.res-hl {
1304
+ background: var(--accent-soft);
1305
+ border-radius: 4px;
1306
+ }
1307
+ .rail-item.res-hl {
1308
+ border-color: var(--accent);
1309
+ background: var(--accent-soft);
1310
+ box-shadow: 0 3px 12px rgba(249, 115, 22, 0.14);
1311
+ }
1312
+ .rail-item.res-hl .rail-title {
1313
+ color: var(--accent-strong);
1314
+ }
1315
+ .rail-item.rail-local {
1316
+ cursor: default;
1317
+ }
1318
+ .artifact-chip.res-hl {
1319
+ border-color: var(--accent);
1320
+ background: var(--accent-soft);
1321
+ }
1322
+
1323
+ /* ---- contextual resources rail ---- */
1324
+ .context-rail {
1325
+ position: relative;
1326
+ width: 248px;
1327
+ }
1328
+ .context-rail[hidden] {
1329
+ display: none;
1330
+ }
1331
+ .rail-kind {
1332
+ display: flex;
1333
+ align-items: center;
1334
+ gap: 5px;
1335
+ font-family: var(--mono);
1336
+ font-size: 10px;
1337
+ text-transform: uppercase;
1338
+ letter-spacing: 0.08em;
1339
+ font-weight: 600;
1340
+ color: var(--accent);
1341
+ margin-bottom: 4px;
1342
+ }
1343
+ .rail-item {
1344
+ position: absolute;
1345
+ left: 0;
1346
+ right: 0;
1347
+ display: block;
1348
+ border: 1px solid var(--line);
1349
+ border-radius: 10px;
1350
+ background: var(--panel);
1351
+ padding: 9px 12px;
1352
+ margin-bottom: 8px;
1353
+ text-decoration: none;
1354
+ color: inherit;
1355
+ transition: border-color 0.14s, box-shadow 0.14s;
1356
+ }
1357
+ .rail-item:hover {
1358
+ border-color: rgba(249, 115, 22, 0.45);
1359
+ box-shadow: 0 3px 12px rgba(31, 41, 55, 0.06);
1360
+ }
1361
+ .rail-title {
1362
+ font-family: var(--mono);
1363
+ font-size: 12.5px;
1364
+ font-weight: 600;
1365
+ color: var(--ink);
1366
+ overflow-wrap: anywhere;
1367
+ line-height: 1.4;
1368
+ }
1369
+ .rail-item:hover .rail-title {
1370
+ color: var(--accent-strong);
1371
+ }
1372
+ .rail-meta {
1373
+ font-size: 11.5px;
1374
+ color: var(--muted);
1375
+ margin-top: 2px;
1376
+ }
1377
+
1378
+ @media (max-width: 1400px) {
1379
+ .page-layout {
1380
+ display: block;
1381
+ }
1382
+ .context-rail {
1383
+ width: 100%;
1384
+ margin-top: 28px;
1385
+ position: static;
1386
+ min-height: 0 !important;
1387
+ display: grid;
1388
+ grid-template-columns: repeat(auto-fit, minmax(220px, 1fr));
1389
+ gap: 10px;
1390
+ }
1391
+ .context-rail[hidden] {
1392
+ display: none;
1393
+ }
1394
+ .context-rail .rail-item {
1395
+ position: static;
1396
+ margin-bottom: 0;
1397
+ }
1398
+ }
1399
+
1400
+ /* ---- connect footer + modal ---- */
1401
+ #sidebar-foot {
1402
+ margin-top: auto;
1403
+ padding-top: 14px;
1404
+ border-top: 1px solid rgba(255, 255, 255, 0.1);
1405
+ }
1406
+
1407
+ #connect-btn {
1408
+ width: 100%;
1409
+ display: flex;
1410
+ align-items: center;
1411
+ gap: 8px;
1412
+ background: rgba(255, 255, 255, 0.05);
1413
+ color: #c3c4cb;
1414
+ border: 1px solid rgba(255, 255, 255, 0.12);
1415
+ border-radius: 9px;
1416
+ padding: 9px 12px;
1417
+ font-size: 13.5px;
1418
+ font-family: var(--sans);
1419
+ cursor: pointer;
1420
+ transition: background 0.12s, color 0.12s, border-color 0.12s;
1421
+ }
1422
+ #connect-btn:hover {
1423
+ background: rgba(249, 115, 22, 0.14);
1424
+ border-color: rgba(249, 115, 22, 0.4);
1425
+ color: #fdba74;
1426
+ }
1427
+ #connect-btn .ico {
1428
+ font-size: 15px;
1429
+ }
1430
+
1431
+ #modal[hidden] {
1432
+ display: none;
1433
+ }
1434
+ #modal {
1435
+ position: fixed;
1436
+ inset: 0;
1437
+ z-index: 100;
1438
+ display: flex;
1439
+ align-items: center;
1440
+ justify-content: center;
1441
+ padding: 24px;
1442
+ }
1443
+ .modal-backdrop {
1444
+ position: absolute;
1445
+ inset: 0;
1446
+ background: rgba(20, 18, 30, 0.5);
1447
+ backdrop-filter: blur(2px);
1448
+ }
1449
+ .modal-card {
1450
+ position: relative;
1451
+ background: var(--panel);
1452
+ border-radius: 16px;
1453
+ width: 100%;
1454
+ max-width: 620px;
1455
+ max-height: 85vh;
1456
+ overflow-y: auto;
1457
+ box-shadow: 0 24px 70px rgba(20, 15, 50, 0.28);
1458
+ }
1459
+ .modal-head {
1460
+ display: flex;
1461
+ align-items: center;
1462
+ justify-content: space-between;
1463
+ gap: 12px;
1464
+ padding: 18px 22px;
1465
+ border-bottom: 1px solid var(--line);
1466
+ position: sticky;
1467
+ top: 0;
1468
+ background: var(--panel);
1469
+ }
1470
+ .modal-title {
1471
+ display: flex;
1472
+ align-items: center;
1473
+ gap: 10px;
1474
+ font-family: var(--serif);
1475
+ font-size: 21px;
1476
+ letter-spacing: -0.01em;
1477
+ }
1478
+ .modal-logo {
1479
+ width: 26px;
1480
+ height: 26px;
1481
+ object-fit: contain;
1482
+ }
1483
+ .modal-actions {
1484
+ display: flex;
1485
+ align-items: center;
1486
+ gap: 8px;
1487
+ }
1488
+ .btn {
1489
+ font-family: var(--sans);
1490
+ font-size: 13.5px;
1491
+ font-weight: 600;
1492
+ border: 1px solid var(--line);
1493
+ background: var(--panel);
1494
+ color: var(--ink);
1495
+ border-radius: 9px;
1496
+ padding: 8px 13px;
1497
+ cursor: pointer;
1498
+ transition: background 0.12s, border-color 0.12s, color 0.12s;
1499
+ }
1500
+ .btn:hover {
1501
+ border-color: var(--accent);
1502
+ color: var(--accent-strong);
1503
+ }
1504
+ .btn.copied {
1505
+ border-color: #1a8a55;
1506
+ color: #1a8a55;
1507
+ }
1508
+ .btn.icon {
1509
+ font-size: 18px;
1510
+ line-height: 1;
1511
+ padding: 6px 11px;
1512
+ font-weight: 400;
1513
+ }
1514
+ .modal-body {
1515
+ padding: 20px 22px 26px;
1516
+ }
1517
+ .modal-intro {
1518
+ margin: 0 0 20px;
1519
+ color: var(--muted);
1520
+ line-height: 1.55;
1521
+ }
1522
+ #connect-steps {
1523
+ list-style: none;
1524
+ margin: 0;
1525
+ padding: 0;
1526
+ }
1527
+ #connect-steps li {
1528
+ margin-bottom: 18px;
1529
+ }
1530
+ .step-title {
1531
+ font-weight: 600;
1532
+ font-size: 14.5px;
1533
+ margin-bottom: 8px;
1534
+ }
1535
+ .codeblock {
1536
+ display: flex;
1537
+ align-items: center;
1538
+ gap: 8px;
1539
+ background: #17181c;
1540
+ border-radius: 10px;
1541
+ padding: 11px 12px 11px 15px;
1542
+ }
1543
+ .codeblock code {
1544
+ flex: 1;
1545
+ min-width: 0;
1546
+ overflow-x: auto;
1547
+ white-space: nowrap;
1548
+ font-family: var(--mono);
1549
+ font-size: 13px;
1550
+ color: #f0efff;
1551
+ background: none;
1552
+ padding: 0;
1553
+ }
1554
+ .codeblock .copy {
1555
+ flex: 0 0 auto;
1556
+ background: rgba(255, 255, 255, 0.08);
1557
+ color: #c3c4cb;
1558
+ border: 1px solid rgba(255, 255, 255, 0.14);
1559
+ border-radius: 7px;
1560
+ width: 30px;
1561
+ height: 30px;
1562
+ font-size: 14px;
1563
+ cursor: pointer;
1564
+ transition: background 0.12s, color 0.12s;
1565
+ }
1566
+ .codeblock .copy:hover {
1567
+ background: rgba(249, 115, 22, 0.2);
1568
+ color: #fdba74;
1569
+ }
1570
+ .codeblock .copy.copied {
1571
+ color: #52d08a;
1572
+ }
1573
+
1574
+ @media (max-width: 720px) {
1575
+ #app {
1576
+ flex-direction: column;
1577
+ }
1578
+ #sidebar {
1579
+ width: 100%;
1580
+ flex: none;
1581
+ height: auto;
1582
+ position: static;
1583
+ }
1584
+ #content {
1585
+ display: block;
1586
+ width: 100%;
1587
+ padding: 28px 20px 80px;
1588
+ overflow-x: hidden;
1589
+ }
1590
+ #page {
1591
+ width: 100%;
1592
+ max-width: 100%;
1593
+ }
1594
+ #page h1 {
1595
+ font-size: 30px;
1596
+ }
1597
+ .cell-head {
1598
+ align-items: flex-start;
1599
+ flex-direction: column;
1600
+ gap: 4px;
1601
+ }
1602
+ }
logbook.js ADDED
@@ -0,0 +1,2275 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ (function () {
2
+ "use strict";
3
+
4
+ let MANIFEST = null;
5
+ const PAGE_CACHE = {};
6
+ const UNFURL_CACHE = {};
7
+ const LIVE_RELOAD_MS = 1500;
8
+ const FIGURE_FRAME_WINDOWS = new Set();
9
+ let FIGURE_NAVIGATION_READY = false;
10
+
11
+ function esc(s) {
12
+ return String(s)
13
+ .replace(/&/g, "&amp;")
14
+ .replace(/</g, "&lt;")
15
+ .replace(/>/g, "&gt;")
16
+ .replace(/"/g, "&quot;")
17
+ .replace(/'/g, "&#39;");
18
+ }
19
+
20
+ function flattenTree(node, depth, acc) {
21
+ acc.push({ node: node, depth: depth });
22
+ (node.children || []).forEach((c) => flattenTree(c, depth + 1, acc));
23
+ return acc;
24
+ }
25
+
26
+ function findNode(node, slug) {
27
+ if (node.slug === slug) return node;
28
+ for (const c of node.children || []) {
29
+ const hit = findNode(c, slug);
30
+ if (hit) return hit;
31
+ }
32
+ return null;
33
+ }
34
+
35
+ /* -------------------- minimal markdown -------------------- */
36
+
37
+ function inline(text) {
38
+ let t = esc(text);
39
+ t = t.replace(/`([^`]+)`/g, (_, c) => `<code>${c}</code>`);
40
+ t = t.replace(/\*\*([^*]+)\*\*/g, (_, c) => `<strong>${c}</strong>`);
41
+ t = t.replace(/\[([^\]]+)\]\(([^)]+)\)/g, (_, txt, url) => {
42
+ const safe = esc(url);
43
+ const attrs = /^https?:/.test(url) ? ' target="_blank" rel="noopener"' : "";
44
+ const item = /^https?:/.test(url) ? classifyResource(url) : null;
45
+ const data = item
46
+ ? ` class="res-link" data-res-url="${esc(item.url)}"`
47
+ : "";
48
+ return `<a href="${safe}"${attrs}${data}>${txt}</a>`;
49
+ });
50
+ t = t.replace(/(^|[\s(])(https?:\/\/[^\s<>)"'`]+)/g, (m, pre, url) => {
51
+ let rest = "";
52
+ const cut = url.search(/&quot;|&#39;|&lt;|&gt;/);
53
+ if (cut !== -1) {
54
+ rest = url.slice(cut);
55
+ url = url.slice(0, cut);
56
+ }
57
+ const trailing = (url.match(/[.,;:!?`]+$/) || [""])[0];
58
+ const clean = trailing ? url.slice(0, -trailing.length) : url;
59
+ if (!clean) return m;
60
+ const item = classifyResource(clean);
61
+ if (item) return `${pre}${resChipHtml(item)}${trailing}${rest}`;
62
+ return `${pre}<a href="${clean}" target="_blank" rel="noopener">${clean}</a>${trailing}${rest}`;
63
+ });
64
+ return t;
65
+ }
66
+
67
+ function resChipHtml(item) {
68
+ return (
69
+ `<a class="res-chip" href="${esc(item.url)}" target="_blank" ` +
70
+ `rel="noopener" data-res-url="${esc(item.url)}">` +
71
+ `<span class="res-chip-ico">${RESOURCE_ICONS[item.kind]}</span>` +
72
+ `${esc(item.id)}</a>`
73
+ );
74
+ }
75
+
76
+ const URL_ONLY = /^(https?:\/\/[^\s]+)$/;
77
+ const DETECTED_URL =
78
+ /(https?:\/\/[^\s<>)\]"'`]+|trackio-local-dashboard:\/\/[^\s<>)\]"'`]+|trackio-artifact:\/\/[^\s<>)\]"'`]+|trackio-local-path:\/\/[^\s<>)\]"'`]+)/g;
79
+
80
+ function renderMarkdown(md, container) {
81
+ const cellRe = /(^|\n)---\n<!-- trackio-cell\n([\s\S]*?)\n-->\n([\s\S]*?)(?=\n---\n<!-- trackio-cell\n|\s*$)/g;
82
+ const tokens = [];
83
+ let pos = 0;
84
+ let found = false;
85
+ let match;
86
+ while ((match = cellRe.exec(md))) {
87
+ found = true;
88
+ tokens.push({
89
+ kind: "md",
90
+ text: md.slice(pos, match.index + match[1].length),
91
+ });
92
+ tokens.push({
93
+ kind: "cell",
94
+ meta: parseCellMeta(match[2]),
95
+ body: match[3],
96
+ });
97
+ pos = match.index + match[0].length;
98
+ }
99
+ tokens.push({ kind: "md", text: found ? md.slice(pos) : md });
100
+
101
+ for (let i = 0; i < tokens.length; i++) {
102
+ const t = tokens[i];
103
+ if (t.kind === "md") {
104
+ renderMarkdownPlain(t.text, container);
105
+ continue;
106
+ }
107
+ if (t.consumed) continue;
108
+ if (t.meta.type === "code") {
109
+ const arts = [];
110
+ for (let j = i + 1; j < tokens.length; j++) {
111
+ const n = tokens[j];
112
+ if (n.kind === "md") {
113
+ if (n.text.trim() === "") continue;
114
+ break;
115
+ }
116
+ if (n.meta.type === "artifact") {
117
+ arts.push(n);
118
+ n.consumed = true;
119
+ continue;
120
+ }
121
+ break;
122
+ }
123
+ renderCell(t.meta, t.body, container, arts);
124
+ } else {
125
+ renderCell(t.meta, t.body, container);
126
+ }
127
+ }
128
+ }
129
+
130
+ function parseCellMeta(raw) {
131
+ try {
132
+ return JSON.parse(raw);
133
+ } catch (e) {
134
+ return { type: "markdown", title: "Note" };
135
+ }
136
+ }
137
+
138
+ function renderMarkdownPlain(md, container) {
139
+ const lines = md.replace(/<!--[\s\S]*?-->/g, "").split("\n");
140
+ let i = 0;
141
+ let para = [];
142
+
143
+ function flushPara() {
144
+ if (!para.length) return;
145
+ const joined = para.join(" ").trim();
146
+ para = [];
147
+ if (!joined) return;
148
+ if (/^trackio-artifact:\/\/\S+$/.test(joined)) return;
149
+ if (/^trackio-local-path:\/\/\S+$/.test(joined)) return;
150
+ if (joined.indexOf("📦 Artifact") !== -1) {
151
+ const div = document.createElement("div");
152
+ div.className = "artifact-chip";
153
+ div.innerHTML = ARTIFACT_ICON_IMG + inline(joined.replace(/📦\s*/, ""));
154
+ container.appendChild(div);
155
+ return;
156
+ }
157
+ if (URL_ONLY.test(joined) || IMG_PATH.test(joined)) {
158
+ const el = renderStandaloneUrl(joined);
159
+ if (el) container.appendChild(el);
160
+ return;
161
+ }
162
+ const p = document.createElement("p");
163
+ p.innerHTML = inline(joined);
164
+ container.appendChild(p);
165
+ }
166
+
167
+ while (i < lines.length) {
168
+ const line = lines[i];
169
+ const trimmed = line.trim();
170
+
171
+ if (trimmed === "") {
172
+ flushPara();
173
+ i++;
174
+ continue;
175
+ }
176
+ const fence = trimmed.match(/^(`{3,}|~{3,})(.*)$/);
177
+ if (fence) {
178
+ flushPara();
179
+ const marker = fence[1][0];
180
+ const closeRe = new RegExp("^" + marker + "{" + fence[1].length + ",}\\s*$");
181
+ const info = fence[2].trim();
182
+ const buf = [];
183
+ i++;
184
+ while (i < lines.length && !closeRe.test(lines[i].trim())) {
185
+ buf.push(lines[i]);
186
+ i++;
187
+ }
188
+ i++;
189
+ const lang = (info.split(/\s+/)[0] || "").toLowerCase();
190
+ const tm = info.match(/title=(\S+)/);
191
+ container.appendChild(
192
+ renderCode(buf.join("\n"), lang, tm ? tm[1] : null)
193
+ );
194
+ continue;
195
+ }
196
+ if (trimmed === "---") {
197
+ flushPara();
198
+ container.appendChild(document.createElement("hr"));
199
+ i++;
200
+ continue;
201
+ }
202
+ const h = trimmed.match(/^(#{1,4})\s+(.*)$/);
203
+ if (h) {
204
+ flushPara();
205
+ const el = document.createElement("h" + h[1].length);
206
+ el.innerHTML = inline(h[2]);
207
+ container.appendChild(el);
208
+ i++;
209
+ continue;
210
+ }
211
+ if (
212
+ trimmed.startsWith("|") &&
213
+ i + 1 < lines.length &&
214
+ /^\|?[\s:|-]*-{2,}[\s:|-]*\|?$/.test(lines[i + 1].trim())
215
+ ) {
216
+ flushPara();
217
+ const rows = [];
218
+ while (i < lines.length && lines[i].trim().startsWith("|")) {
219
+ rows.push(parseRow(lines[i].trim()));
220
+ i++;
221
+ }
222
+ renderTable(rows, container);
223
+ continue;
224
+ }
225
+ if (trimmed.startsWith("> ")) {
226
+ flushPara();
227
+ const bq = document.createElement("blockquote");
228
+ bq.innerHTML = inline(trimmed.slice(2));
229
+ container.appendChild(bq);
230
+ i++;
231
+ continue;
232
+ }
233
+ if (/^`[^`]+`$/.test(trimmed)) {
234
+ flushPara();
235
+ const el = document.createElement("div");
236
+ el.className = "ts";
237
+ el.textContent = trimmed.replace(/`/g, "");
238
+ container.appendChild(el);
239
+ i++;
240
+ continue;
241
+ }
242
+ if (trimmed.startsWith("- ")) {
243
+ flushPara();
244
+ const items = [];
245
+ while (i < lines.length && lines[i].trim().startsWith("- ")) {
246
+ items.push(lines[i].trim().slice(2).trim());
247
+ i++;
248
+ }
249
+ renderList(items, container);
250
+ continue;
251
+ }
252
+ para.push(trimmed);
253
+ i++;
254
+ }
255
+ flushPara();
256
+ }
257
+
258
+ function renderCell(meta, body, container, artifacts) {
259
+ const cell = document.createElement("section");
260
+ cell.className = `cell ${meta.type || "markdown"}`;
261
+ if (meta.id) cell.dataset.cellId = meta.id;
262
+ if (isPinned(meta)) cell.classList.add("pinned-source");
263
+
264
+ const head = document.createElement("div");
265
+ head.className = "cell-head";
266
+ const rawTitle = (meta.title || "").trim();
267
+ const title = rawTitle && rawTitle.toLowerCase() !== "untitled" ? esc(rawTitle) : "";
268
+ const when = meta.created_at ? `<span>${esc(formatTime(meta.created_at))}</span>` : "";
269
+ head.innerHTML =
270
+ (title ? `<div class="cell-title">${title}</div>` : "") +
271
+ `<div class="cell-meta">${when}</div>`;
272
+ if (!title) head.classList.add("no-title");
273
+ cell.appendChild(head);
274
+
275
+ const bodyEl = document.createElement("div");
276
+ bodyEl.className = "cell-body";
277
+ if (meta.type === "code") {
278
+ renderCodeCell(body, bodyEl, artifacts);
279
+ } else if (meta.type === "figure") {
280
+ cell.dataset.resUrl = `trackio-figure://${(meta.title || "Figure").trim()}`;
281
+ renderFigureCell(body, bodyEl, head);
282
+ } else if (meta.type === "artifact") {
283
+ renderMarkdownPlain(body, bodyEl);
284
+ const chip = bodyEl.querySelector(".artifact-chip");
285
+ const uri = body.match(
286
+ /(trackio-artifact:\/\/\S+|trackio-local-path:\/\/\S+|https:\/\/huggingface\.co\/buckets\/[^\s<)]+#\S+)/
287
+ );
288
+ if (chip && uri) chip.dataset.resUrl = uri[1];
289
+ } else if (meta.type === "dashboard") {
290
+ const sp = body.match(/https:\/\/huggingface\.co\/spaces\/[^\s<>)"'`]+/);
291
+ cell.dataset.resUrl = sp
292
+ ? sp[0]
293
+ : `trackio-local-dashboard://${(meta.dashboard_project || "").trim()}`;
294
+ renderDashboardCell(meta, body, bodyEl, head);
295
+ } else {
296
+ const cleaned = stripDuplicateTitle(body, meta.title);
297
+ renderMarkdownPlain(cleaned, bodyEl);
298
+ renderDetectedEmbeds(cleaned, bodyEl);
299
+ }
300
+ cell.appendChild(bodyEl);
301
+ container.appendChild(cell);
302
+ return cell;
303
+ }
304
+
305
+ function isPinned(meta) {
306
+ return Boolean(meta && (meta.pinned === true || meta.pinned === "true"));
307
+ }
308
+
309
+ function stripDuplicateTitle(body, title) {
310
+ if (!title) return body;
311
+ const m = body.match(/^\s*#{1,6}\s+([^\n]+)\n?/);
312
+ if (!m) return body;
313
+ const norm = (s) =>
314
+ s
315
+ .toLowerCase()
316
+ .replace(/[*_`#]/g, "")
317
+ .replace(/\s+/g, " ")
318
+ .trim();
319
+ return norm(m[1]) === norm(title) ? body.slice(m[0].length) : body;
320
+ }
321
+
322
+ function formatTime(iso) {
323
+ const d = new Date(iso);
324
+ if (Number.isNaN(d.getTime())) return iso;
325
+ return d.toLocaleString(undefined, {
326
+ month: "short",
327
+ day: "numeric",
328
+ hour: "2-digit",
329
+ minute: "2-digit",
330
+ });
331
+ }
332
+
333
+ function parseFences(text) {
334
+ const fenceRe = /(`{3,4}|~{3,4})([^\n]*)\n([\s\S]*?)\n\1/g;
335
+ const parts = [];
336
+ let pos = 0;
337
+ let match;
338
+ while ((match = fenceRe.exec(text))) {
339
+ if (match.index > pos) {
340
+ parts.push({ kind: "text", text: text.slice(pos, match.index) });
341
+ }
342
+ const info = match[2].trim();
343
+ const lang = (info.split(/\s+/)[0] || "").toLowerCase();
344
+ const titleMatch = info.match(/title=(\S+)/);
345
+ parts.push({
346
+ kind: lang === "result" || lang === "output" ? "output" : "code",
347
+ lang,
348
+ title: titleMatch ? titleMatch[1] : null,
349
+ text: match[3],
350
+ });
351
+ pos = match.index + match[0].length;
352
+ }
353
+ if (pos < text.length) parts.push({ kind: "text", text: text.slice(pos) });
354
+ return parts;
355
+ }
356
+
357
+ function fitFigureFrame(frame, wrap) {
358
+ let doc;
359
+ try {
360
+ doc = frame.contentDocument;
361
+ } catch (e) {
362
+ return;
363
+ }
364
+ if (!doc || !doc.body) return;
365
+ frame.style.transform = "none";
366
+ frame.style.width = "100%";
367
+ frame.style.height = "auto";
368
+ frame.style.position = "";
369
+ frame.style.left = "";
370
+ frame.style.top = "";
371
+ const avail = wrap.clientWidth;
372
+ const isFullscreen =
373
+ document.fullscreenElement === wrap ||
374
+ document.webkitFullscreenElement === wrap;
375
+ const availHeight = isFullscreen ? wrap.clientHeight : Infinity;
376
+ const cw = Math.max(doc.body.scrollWidth, doc.documentElement.scrollWidth, 1);
377
+ const ch = Math.max(doc.body.scrollHeight, doc.documentElement.scrollHeight, 1);
378
+ const scale = Math.min(avail / cw, availHeight / ch);
379
+ if (avail && scale < 1 - 1e-3) {
380
+ frame.style.width = `${cw}px`;
381
+ frame.style.height = `${ch}px`;
382
+ frame.style.transformOrigin = "top left";
383
+ frame.style.transform = `scale(${scale})`;
384
+ if (isFullscreen) {
385
+ frame.style.position = "absolute";
386
+ frame.style.left = `${Math.max(0, (avail - cw * scale) / 2)}px`;
387
+ frame.style.top = `${Math.max(0, (availHeight - ch * scale) / 2)}px`;
388
+ wrap.style.height = "100%";
389
+ } else {
390
+ wrap.style.height = `${Math.ceil(ch * scale)}px`;
391
+ }
392
+ } else {
393
+ frame.style.width = "100%";
394
+ frame.style.height = `${ch}px`;
395
+ wrap.style.height = isFullscreen ? "100%" : `${ch}px`;
396
+ }
397
+ }
398
+
399
+ function attachFigureFit(frame, wrap) {
400
+ const refit = () => fitFigureFrame(frame, wrap);
401
+ frame.addEventListener("load", refit);
402
+ if (window.ResizeObserver) {
403
+ const ro = new ResizeObserver(() => refit());
404
+ ro.observe(wrap);
405
+ }
406
+ }
407
+
408
+ function renderFigureCell(text, container, head) {
409
+ const parts = parseFences(text);
410
+ const htmlPart = parts.find((part) => part.lang === "html");
411
+ const rawPart = parts.find((part) => part.lang === "raw");
412
+ if (!htmlPart || !htmlPart.text.trim()) {
413
+ const empty = document.createElement("p");
414
+ empty.className = "muted";
415
+ empty.textContent = "No figure HTML.";
416
+ container.appendChild(empty);
417
+ return;
418
+ }
419
+ const frame = document.createElement("iframe");
420
+ frame.className = "figure-frame";
421
+ frame.sandbox = "allow-scripts allow-same-origin";
422
+ frame.loading = "lazy";
423
+ frame.srcdoc = htmlPart.text;
424
+ registerFigureNavigation(frame);
425
+ const figWrap = document.createElement("div");
426
+ figWrap.className = "figure-fit";
427
+ figWrap.appendChild(frame);
428
+ attachFigureFit(frame, figWrap);
429
+ if (head) {
430
+ const metaEl = head.querySelector(".cell-meta");
431
+ if (metaEl)
432
+ metaEl.insertBefore(buildFullscreenControl(figWrap, frame), metaEl.firstChild);
433
+ }
434
+ if (!rawPart || !rawPart.text.trim()) {
435
+ container.appendChild(figWrap);
436
+ return;
437
+ }
438
+ const sw = document.createElement("div");
439
+ sw.className = "fig-switch";
440
+ const thumb = document.createElement("span");
441
+ thumb.className = "fig-switch-thumb";
442
+ const figBtn = document.createElement("button");
443
+ figBtn.type = "button";
444
+ figBtn.className = "active";
445
+ figBtn.textContent = "Figure";
446
+ const rawBtn = document.createElement("button");
447
+ rawBtn.type = "button";
448
+ rawBtn.textContent = "Raw";
449
+ sw.appendChild(thumb);
450
+ sw.appendChild(figBtn);
451
+ sw.appendChild(rawBtn);
452
+ const rawView = document.createElement("div");
453
+ rawView.className = "figure-raw";
454
+ rawView.hidden = true;
455
+ const pre = document.createElement("pre");
456
+ const code = document.createElement("code");
457
+ code.textContent = rawPart.text;
458
+ pre.appendChild(code);
459
+ rawView.appendChild(pre);
460
+ rawView.appendChild(copySnippetBtn(rawPart.text));
461
+ const select = (showRaw) => {
462
+ sw.classList.toggle("raw", showRaw);
463
+ figBtn.classList.toggle("active", !showRaw);
464
+ rawBtn.classList.toggle("active", showRaw);
465
+ figWrap.hidden = showRaw;
466
+ rawView.hidden = !showRaw;
467
+ };
468
+ figBtn.addEventListener("click", () => select(false));
469
+ rawBtn.addEventListener("click", () => select(true));
470
+ if (head) {
471
+ head.insertBefore(sw, head.querySelector(".cell-meta"));
472
+ } else {
473
+ container.appendChild(sw);
474
+ }
475
+ container.appendChild(figWrap);
476
+ container.appendChild(rawView);
477
+ }
478
+
479
+ // Poster embeds can send `{ type: "trackio-logbook:navigate", target: "..." }`
480
+ // from their iframe. Only accept messages from figure frames we created, and
481
+ // only route to pages that are present in this logbook's manifest.
482
+ function registerFigureNavigation(frame) {
483
+ const registerFrameWindow = () => {
484
+ if (frame.contentWindow) FIGURE_FRAME_WINDOWS.add(frame.contentWindow);
485
+ };
486
+ // `srcdoc` replaces the initial about:blank document. Register after that
487
+ // navigation as well, so messages come from the live figure document.
488
+ frame.addEventListener("load", registerFrameWindow);
489
+ registerFrameWindow();
490
+ if (FIGURE_NAVIGATION_READY) return;
491
+ FIGURE_NAVIGATION_READY = true;
492
+ window.addEventListener("message", (event) => {
493
+ if (!FIGURE_FRAME_WINDOWS.has(event.source)) return;
494
+ const message = event.data;
495
+ if (!message || message.type !== "trackio-logbook:navigate") return;
496
+ const target = String(message.target || "").replace(/^#?\//, "");
497
+ if (!target || !MANIFEST || !findNode(MANIFEST.root, target)) return;
498
+ const hash = "#/" + target;
499
+ if (location.hash === hash) scrollToHash();
500
+ else location.hash = hash;
501
+ });
502
+ }
503
+
504
+ const FULLSCREEN_ICON =
505
+ '<svg viewBox="0 0 24 24" fill="none" stroke="currentColor" ' +
506
+ 'stroke-width="2" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true">' +
507
+ '<path d="M8 3H3v5M16 3h5v5M21 16v5h-5M3 16v5h5"/>' +
508
+ '<path d="M3 8 8 3M16 3l5 5M21 16l-5 5M8 21l-5-5"/></svg>';
509
+
510
+ // Figures are rendered in same-origin iframes, so fullscreen the fitted
511
+ // wrapper rather than the iframe document. This uses the browser's native
512
+ // fullscreen UI and preserves the figure's existing responsive sizing.
513
+ function buildFullscreenControl(figWrap, frame) {
514
+ const wrap = document.createElement("span");
515
+ wrap.className = "cell-fullscreen";
516
+ const btn = document.createElement("button");
517
+ btn.type = "button";
518
+ btn.className = "cell-fullscreen-btn";
519
+ btn.setAttribute("aria-label", "Open figure in fullscreen");
520
+ btn.title = "Open figure in fullscreen";
521
+ btn.innerHTML = FULLSCREEN_ICON;
522
+ wrap.appendChild(btn);
523
+
524
+ btn.addEventListener("click", async () => {
525
+ const request = figWrap.requestFullscreen || figWrap.webkitRequestFullscreen;
526
+ if (!request) return;
527
+ try {
528
+ await request.call(figWrap);
529
+ } catch (_) {
530
+ // Fullscreen can be disabled by the embedding browser or policy.
531
+ }
532
+ });
533
+ document.addEventListener("fullscreenchange", () => {
534
+ if (document.fullscreenElement === figWrap) fitFigureFrame(frame, figWrap);
535
+ });
536
+ return wrap;
537
+ }
538
+
539
+ function extractUrls(text) {
540
+ const seen = new Set();
541
+ const urls = [];
542
+ let match;
543
+ while ((match = DETECTED_URL.exec(text))) {
544
+ const url = match[1].replace(/[.,;:!?'"`]+$/, "");
545
+ if (!seen.has(url)) {
546
+ seen.add(url);
547
+ urls.push(url);
548
+ }
549
+ }
550
+ DETECTED_URL.lastIndex = 0;
551
+ return urls;
552
+ }
553
+
554
+ const IMG_URL = /(\.(png|jpe?g|gif|svg|webp)(\?|$)|\/artifact_blob\/)/i;
555
+
556
+ function renderDetectedEmbeds(text, container) {
557
+ extractUrls(text).forEach((url) => {
558
+ if (url.startsWith("trackio-local-dashboard://")) {
559
+ const div = document.createElement("div");
560
+ div.className = "artifact-chip";
561
+ div.dataset.resUrl = url;
562
+ div.innerHTML =
563
+ "🎯 <strong>Local Trackio dashboard</strong> — publish the logbook to share it";
564
+ container.appendChild(div);
565
+ } else if (IMG_URL.test(url)) {
566
+ container.appendChild(renderImage(url));
567
+ } else if (/huggingface\.co\/spaces\//.test(url)) {
568
+ maybeEmbedTrackioSpace(url, container);
569
+ }
570
+ });
571
+ }
572
+
573
+ function renderStandaloneUrl(url) {
574
+ if (IMG_URL.test(url) || IMG_PATH.test(url)) return renderImage(url);
575
+ const item = classifyResource(url);
576
+ if (item) {
577
+ const marker = document.createElement("span");
578
+ marker.className = "resource-anchor";
579
+ marker.dataset.resUrl = item.url;
580
+ marker.setAttribute("aria-hidden", "true");
581
+ return marker;
582
+ }
583
+ const p = document.createElement("p");
584
+ p.innerHTML = inline(url);
585
+ return p;
586
+ }
587
+
588
+ function renderImage(url) {
589
+ const a = document.createElement("a");
590
+ a.className = "unfurl image";
591
+ a.href = url;
592
+ a.target = "_blank";
593
+ a.rel = "noopener";
594
+ const img = document.createElement("img");
595
+ img.loading = "lazy";
596
+ img.src = url;
597
+ img.alt = "artifact image";
598
+ a.appendChild(img);
599
+ return a;
600
+ }
601
+
602
+ function maybeEmbedTrackioSpace(url, container) {
603
+ const id = url.split("/spaces/")[1].split(/[?#]/)[0].replace(/\/$/, "");
604
+ const holder = document.createElement("div");
605
+ container.appendChild(holder);
606
+ getJSON(`https://huggingface.co/api/spaces/${id}`).then((d) => {
607
+ const tags = (d && d.tags) || [];
608
+ if (tags.some((t) => String(t).toLowerCase() === "trackio")) {
609
+ renderTrackioSpaceEmbed(holder, url, id);
610
+ } else {
611
+ holder.remove();
612
+ }
613
+ });
614
+ }
615
+
616
+ function jpGutter(label) {
617
+ const g = document.createElement("div");
618
+ g.className = "jp-gutter";
619
+ g.textContent = label;
620
+ return g;
621
+ }
622
+
623
+ function renderOutArtifact(info) {
624
+ const remote = !info.local && !!info.url;
625
+ const el = document.createElement(remote ? "a" : "div");
626
+ el.className = "out-artifact";
627
+ if (remote) {
628
+ el.href = info.url;
629
+ el.target = "_blank";
630
+ el.rel = "noopener";
631
+ }
632
+ el.dataset.resUrl = info.resUrl;
633
+ const parts = [info.type, info.size].filter(Boolean).map(esc);
634
+ const state = remote
635
+ ? `<span class="out-artifact-state open">Open ↗</span>`
636
+ : `<span class="out-artifact-state">publish to share</span>`;
637
+ const meta = parts.length ? `${parts.join(" · ")} · ${state}` : state;
638
+ el.innerHTML =
639
+ `<span class="out-artifact-ico">${ARTIFACT_ICON_IMG}</span>` +
640
+ `<span class="out-artifact-name">${esc(info.name)}</span>` +
641
+ `<span class="out-artifact-meta">${meta}</span>`;
642
+ return el;
643
+ }
644
+
645
+ function renderCodeCell(body, container, artifacts) {
646
+ const parts = parseFences(body);
647
+ const block = document.createElement("div");
648
+ block.className = "jp";
649
+ const input = document.createElement("div");
650
+ input.className = "jp-in";
651
+ const inputBody = document.createElement("div");
652
+ inputBody.className = "jp-in-body";
653
+ input.appendChild(jpGutter("In"));
654
+ input.appendChild(inputBody);
655
+ let metaEl = null;
656
+ let outputEl = null;
657
+ let outBody = null;
658
+ const ensureOut = () => {
659
+ if (outputEl) return;
660
+ outputEl = document.createElement("div");
661
+ outputEl.className = "jp-out";
662
+ outputEl.appendChild(jpGutter("Out"));
663
+ outBody = document.createElement("div");
664
+ outBody.className = "jp-out-body";
665
+ outputEl.appendChild(outBody);
666
+ };
667
+ const embedTexts = [];
668
+ parts.forEach((part) => {
669
+ if (part.kind === "text") {
670
+ const text = part.text.trim();
671
+ if (!text) return;
672
+ if (/^exit\s+\S+(\s|·)/.test(text)) {
673
+ metaEl = document.createElement("div");
674
+ metaEl.className = "jp-meta";
675
+ metaEl.textContent = text.replace(
676
+ /\s*·\s*[A-Z][a-z]{2} \d{1,2}, \d{4}.*$/,
677
+ ""
678
+ );
679
+ } else {
680
+ renderMarkdownPlain(text, container);
681
+ embedTexts.push(text);
682
+ }
683
+ return;
684
+ }
685
+ if (part.kind === "output") {
686
+ ensureOut();
687
+ const pre = document.createElement("pre");
688
+ pre.className = "jp-out-pre";
689
+ const c = document.createElement("code");
690
+ c.textContent = part.text;
691
+ pre.appendChild(c);
692
+ outBody.appendChild(pre);
693
+ outputEl.appendChild(copySnippetBtn(part.text));
694
+ embedTexts.push(part.text);
695
+ return;
696
+ }
697
+ inputBody.appendChild(renderCode(part.text, part.lang, part.title));
698
+ });
699
+ if (artifacts && artifacts.length) {
700
+ ensureOut();
701
+ const artWrap = document.createElement("div");
702
+ artWrap.className = "jp-artifacts";
703
+ artifacts.forEach((a) => {
704
+ artWrap.appendChild(
705
+ renderOutArtifact(artifactInfoFromCell(a.meta, a.body))
706
+ );
707
+ });
708
+ outBody.appendChild(artWrap);
709
+ }
710
+ if (inputBody.childNodes.length > 0) block.appendChild(input);
711
+ if (metaEl) block.appendChild(metaEl);
712
+ if (outputEl) block.appendChild(outputEl);
713
+ if (block.childNodes.length) container.appendChild(block);
714
+ embedTexts.forEach((text) => renderDetectedEmbeds(text, container));
715
+ }
716
+
717
+ function parseRow(line) {
718
+ let s = line.trim();
719
+ if (s.startsWith("|")) s = s.slice(1);
720
+ if (s.endsWith("|")) s = s.slice(0, -1);
721
+ return s.split(/(?<!\\)\|/).map((c) => c.replace(/\\\|/g, "|").trim());
722
+ }
723
+
724
+ const TRUTHY = ["x", "✓", "✔", "yes", "done", "true", "[x]"];
725
+ const CHIP_COLORS = [
726
+ ["#e7f0ff", "#2158d0"],
727
+ ["#fde8ec", "#c62a4b"],
728
+ ["#e6f7ee", "#1a8a55"],
729
+ ["#fdf0e0", "#b26a12"],
730
+ ["#efe9ff", "#5b3bd6"],
731
+ ["#e6f6f8", "#127b88"],
732
+ ];
733
+
734
+ function chipColor(name) {
735
+ let h = 0;
736
+ for (let i = 0; i < name.length; i++) h = (h * 31 + name.charCodeAt(i)) >>> 0;
737
+ return CHIP_COLORS[h % CHIP_COLORS.length];
738
+ }
739
+
740
+ const STATUS_MAP = {
741
+ "": ["Planned", "gray"],
742
+ planned: ["Planned", "gray"],
743
+ todo: ["Planned", "gray"],
744
+ "to do": ["Planned", "gray"],
745
+ backlog: ["Planned", "gray"],
746
+ "in progress": ["In progress", "amber"],
747
+ "in-progress": ["In progress", "amber"],
748
+ wip: ["In progress", "amber"],
749
+ running: ["In progress", "amber"],
750
+ active: ["In progress", "amber"],
751
+ done: ["Done", "green"],
752
+ complete: ["Done", "green"],
753
+ completed: ["Done", "green"],
754
+ blocked: ["Blocked", "red"],
755
+ failed: ["Failed", "red"],
756
+ abandoned: ["Abandoned", "gray"],
757
+ };
758
+
759
+ function statusBadge(val) {
760
+ const [label, tone] = STATUS_MAP[val.toLowerCase()] || [val || "—", "gray"];
761
+ return `<span class="badge ${tone}">${esc(label)}</span>`;
762
+ }
763
+
764
+ function renderTable(rows, container) {
765
+ if (rows.length < 2) return;
766
+ const header = rows[0];
767
+ const body = rows.slice(2);
768
+ const roles = header.map((h) => {
769
+ const t = h.toLowerCase();
770
+ if (t.includes("status") || t.includes("state")) return "status";
771
+ if (t.includes("progress") || t.includes("complete") || t.includes("done"))
772
+ return "check";
773
+ if (t === "who" || t.includes("assign") || t.includes("owner")) return "who";
774
+ return "text";
775
+ });
776
+ const table = document.createElement("table");
777
+ table.className = "board";
778
+ const thead = document.createElement("thead");
779
+ const htr = document.createElement("tr");
780
+ header.forEach((h, c) => {
781
+ const th = document.createElement("th");
782
+ th.textContent = h;
783
+ if (roles[c] === "check") th.className = "col-check";
784
+ htr.appendChild(th);
785
+ });
786
+ thead.appendChild(htr);
787
+ table.appendChild(thead);
788
+ const tbody = document.createElement("tbody");
789
+ body.forEach((cells) => {
790
+ const nonEmpty = cells.filter((x) => x !== "").length;
791
+ if (header.length > 1 && nonEmpty === 1 && cells[0]) {
792
+ const tr = document.createElement("tr");
793
+ tr.className = "section-row";
794
+ const td = document.createElement("td");
795
+ td.colSpan = header.length;
796
+ td.innerHTML = inline(cells[0]);
797
+ tr.appendChild(td);
798
+ tbody.appendChild(tr);
799
+ return;
800
+ }
801
+ const tr = document.createElement("tr");
802
+ header.forEach((_, c) => {
803
+ const td = document.createElement("td");
804
+ const val = (cells[c] || "").trim();
805
+ if (roles[c] === "status") {
806
+ td.className = "col-status";
807
+ td.innerHTML = statusBadge(val);
808
+ } else if (roles[c] === "check") {
809
+ td.className = "col-check";
810
+ const on = TRUTHY.indexOf(val.toLowerCase()) !== -1;
811
+ td.innerHTML = `<span class="box ${on ? "on" : ""}">${on ? "✓" : ""}</span>`;
812
+ } else if (roles[c] === "who") {
813
+ if (!val || /^to assign$/i.test(val)) {
814
+ td.innerHTML = `<span class="who-chip muted">${esc(val || "—")}</span>`;
815
+ } else {
816
+ const [bg, fg] = chipColor(val);
817
+ td.innerHTML = `<span class="who-chip" style="background:${bg};color:${fg}">${esc(val)}</span>`;
818
+ }
819
+ } else {
820
+ td.innerHTML = inline(val);
821
+ }
822
+ tr.appendChild(td);
823
+ });
824
+ const link = tr.querySelector('a[href^="#/"]');
825
+ if (link) {
826
+ tr.classList.add("linked-row");
827
+ tr.addEventListener("click", (e) => {
828
+ if (e.target.tagName !== "A") location.hash = link.getAttribute("href");
829
+ });
830
+ }
831
+ tbody.appendChild(tr);
832
+ });
833
+ table.appendChild(tbody);
834
+ const wrap = document.createElement("div");
835
+ wrap.className = "board-wrap";
836
+ wrap.appendChild(table);
837
+ container.appendChild(wrap);
838
+ }
839
+
840
+ const HL_RULES = {
841
+ python: [
842
+ ["comment", /#[^\n]*/],
843
+ ["string", /'''[\s\S]*?'''|"""[\s\S]*?"""|'(?:\\.|[^'\\])*'|"(?:\\.|[^"\\])*"/],
844
+ [
845
+ "keyword",
846
+ /\b(?:def|class|return|if|elif|else|for|while|import|from|as|with|try|except|finally|raise|in|not|and|or|is|None|True|False|lambda|yield|global|nonlocal|assert|pass|break|continue|async|await|print)\b/,
847
+ ],
848
+ ["number", /\b\d[\d_.eE+-]*\b/],
849
+ ],
850
+ bash: [
851
+ ["comment", /#[^\n]*/],
852
+ ["string", /'(?:\\.|[^'\\])*'|"(?:\\.|[^"\\])*"/],
853
+ ["keyword", /\b(?:if|then|else|fi|for|in|do|done|while|case|esac|function|export|source|echo|cd|return|local)\b/],
854
+ ["number", /(?<=\s)-{1,2}[a-zA-Z][\w-]*/],
855
+ ],
856
+ json: [
857
+ ["string", /"(?:\\.|[^"\\])*"/],
858
+ ["keyword", /\b(?:true|false|null)\b/],
859
+ ["number", /-?\b\d[\d.eE+-]*\b/],
860
+ ],
861
+ yaml: [
862
+ ["comment", /#[^\n]*/],
863
+ ["string", /'(?:\\.|[^'\\])*'|"(?:\\.|[^"\\])*"/],
864
+ ["keyword", /\b(?:true|false|null|yes|no)\b/],
865
+ ["number", /-?\b\d[\d.eE+-]*\b/],
866
+ ],
867
+ };
868
+ HL_RULES.javascript = HL_RULES.python;
869
+ HL_RULES.typescript = HL_RULES.python;
870
+ HL_RULES.sql = [
871
+ ["comment", /--[^\n]*/],
872
+ ["string", /'(?:\\.|[^'\\])*'/],
873
+ [
874
+ "keyword",
875
+ /\b(?:SELECT|FROM|WHERE|JOIN|LEFT|RIGHT|INNER|OUTER|ON|GROUP|BY|ORDER|LIMIT|INSERT|INTO|VALUES|UPDATE|SET|DELETE|CREATE|TABLE|AS|AND|OR|NOT|NULL|COUNT|DISTINCT|IN)\b/i,
876
+ ],
877
+ ["number", /\b\d[\d.]*\b/],
878
+ ];
879
+
880
+ function highlightCode(code, lang) {
881
+ const rules = HL_RULES[lang];
882
+ if (!rules) return esc(code);
883
+ const combined = new RegExp(rules.map((r) => "(" + r[1].source + ")").join("|"), "g");
884
+ let out = "";
885
+ let last = 0;
886
+ let m;
887
+ while ((m = combined.exec(code))) {
888
+ if (m[0] === "") {
889
+ combined.lastIndex++;
890
+ continue;
891
+ }
892
+ out += esc(code.slice(last, m.index));
893
+ let gi = 1;
894
+ while (gi < m.length && m[gi] === undefined) gi++;
895
+ out += `<span class="tok-${rules[gi - 1][0]}">${esc(m[0])}</span>`;
896
+ last = m.index + m[0].length;
897
+ }
898
+ out += esc(code.slice(last));
899
+ return out;
900
+ }
901
+
902
+ function copySnippetBtn(text) {
903
+ const btn = document.createElement("button");
904
+ btn.type = "button";
905
+ btn.className = "copy-snippet";
906
+ btn.title = "Copy";
907
+ btn.textContent = "⧉";
908
+ btn.addEventListener("click", (e) => {
909
+ e.preventDefault();
910
+ e.stopPropagation();
911
+ copyText(text, btn, "⧉");
912
+ });
913
+ return btn;
914
+ }
915
+
916
+ function renderCode(code, lang, title) {
917
+ const pre = document.createElement("pre");
918
+ pre.className = "hl";
919
+ const c = document.createElement("code");
920
+ c.innerHTML = highlightCode(code, lang);
921
+ pre.appendChild(c);
922
+ if (!title) {
923
+ const wrap = document.createElement("div");
924
+ wrap.className = "snippet";
925
+ wrap.appendChild(pre);
926
+ wrap.appendChild(copySnippetBtn(code));
927
+ return wrap;
928
+ }
929
+ const det = document.createElement("details");
930
+ det.className = "code-accordion";
931
+ det.dataset.resUrl = `trackio-script://${title}`;
932
+ const sum = document.createElement("summary");
933
+ sum.innerHTML =
934
+ `<span class="code-ico">&lt;/&gt;</span>` +
935
+ `<span class="code-name">${esc(title)}</span>`;
936
+ sum
937
+ .querySelector(".code-name")
938
+ .addEventListener("click", (e) => e.preventDefault());
939
+ det.appendChild(sum);
940
+ const wrap = document.createElement("div");
941
+ wrap.className = "snippet";
942
+ wrap.appendChild(pre);
943
+ wrap.appendChild(copySnippetBtn(code));
944
+ det.appendChild(wrap);
945
+ return det;
946
+ }
947
+
948
+ const IMG_PATH = /^[^\s]+\.(png|jpe?g|gif|svg|webp)$/i;
949
+
950
+ function renderList(items, container) {
951
+ let ul = null;
952
+ items.forEach((item) => {
953
+ if (URL_ONLY.test(item) || IMG_PATH.test(item)) {
954
+ const el = renderStandaloneUrl(item);
955
+ if (el) {
956
+ ul = null;
957
+ container.appendChild(el);
958
+ }
959
+ } else if (item.indexOf("📦 Artifact") !== -1) {
960
+ ul = null;
961
+ const div = document.createElement("div");
962
+ div.className = "artifact-chip";
963
+ div.innerHTML = inline(item.replace("📦", "🪣"));
964
+ container.appendChild(div);
965
+ } else if (item.indexOf("trackio-local-dashboard://") !== -1) {
966
+ ul = null;
967
+ const uri = item.match(/trackio-local-dashboard:\/\/\S+/)?.[0] || "";
968
+ const div = document.createElement("div");
969
+ div.className = "artifact-chip";
970
+ if (uri) div.dataset.resUrl = uri;
971
+ div.innerHTML =
972
+ "🎯 <strong>Local dashboard</strong> — publish the logbook to share it";
973
+ container.appendChild(div);
974
+ } else {
975
+ if (!ul) {
976
+ ul = document.createElement("ul");
977
+ container.appendChild(ul);
978
+ }
979
+ const li = document.createElement("li");
980
+ li.innerHTML = inline(item);
981
+ ul.appendChild(li);
982
+ }
983
+ });
984
+ }
985
+
986
+ /* -------------------- resources rail -------------------- */
987
+
988
+ function fmt(n) {
989
+ if (n == null) return null;
990
+ if (n >= 1e6) return (n / 1e6).toFixed(1) + "M";
991
+ if (n >= 1e3) return (n / 1e3).toFixed(1) + "k";
992
+ return String(n);
993
+ }
994
+
995
+ const RESOURCE_SECTIONS = [
996
+ ["dashboard", "Dashboards", "🎯"],
997
+ ["model", "Models", "🤗"],
998
+ ["dataset", "Datasets", "📊"],
999
+ ["space", "Spaces", "🚀"],
1000
+ ["artifact", "Artifacts", "🪣"],
1001
+ ["paper", "Papers", "📄"],
1002
+ ["repo", "Code", "🐙"],
1003
+ ["job", "Jobs", "⚙️"],
1004
+ ["bucket", "Buckets", "🪣"],
1005
+ ];
1006
+
1007
+ const RESOURCE_ICONS = Object.fromEntries(
1008
+ RESOURCE_SECTIONS.map(([kind, , icon]) => [kind, icon])
1009
+ );
1010
+
1011
+ const ARTIFACT_ICON_IMG = `<img class="art-ico" src="./bucket-icon.svg" alt="" />`;
1012
+ const DASHBOARD_ICON_IMG = `<img class="art-ico" src="./trackio-logo-light.png" alt="" />`;
1013
+
1014
+ const RESOURCE_DESC = {
1015
+ dashboard: "Dashboard",
1016
+ model: "Model",
1017
+ dataset: "Dataset",
1018
+ space: "Space",
1019
+ artifact: "Artifact — in Bucket",
1020
+ paper: "Paper",
1021
+ repo: "Repository",
1022
+ job: "Job — status & logs",
1023
+ bucket: "Bucket — artifacts & data",
1024
+ };
1025
+
1026
+ const HF_NON_MODEL_PREFIX =
1027
+ /^(datasets|spaces|jobs|buckets|papers|blog|docs|api|posts|collections|organizations|settings|new|join|login|pricing|tasks|learn|chat|models)(\/|$)/;
1028
+
1029
+ function hfId(url, marker) {
1030
+ return url.split(marker)[1].split(/[?#]/)[0].replace(/\/$/, "");
1031
+ }
1032
+
1033
+ function classifyResource(url) {
1034
+ if (IMG_URL.test(url)) {
1035
+ return null;
1036
+ }
1037
+ let m;
1038
+ if (url.startsWith("trackio-local-dashboard://")) {
1039
+ return {
1040
+ kind: "dashboard",
1041
+ id: url.slice("trackio-local-dashboard://".length),
1042
+ url,
1043
+ local: true,
1044
+ };
1045
+ }
1046
+ if (url.startsWith("trackio-artifact://")) {
1047
+ return {
1048
+ kind: "artifact",
1049
+ id: url.slice("trackio-artifact://".length),
1050
+ url,
1051
+ local: true,
1052
+ };
1053
+ }
1054
+ if (url.startsWith("trackio-local-path://")) {
1055
+ return {
1056
+ kind: "artifact",
1057
+ id: url.slice("trackio-local-path://".length),
1058
+ url,
1059
+ local: true,
1060
+ };
1061
+ }
1062
+ if ((m = url.match(/huggingface\.co\/buckets\/[^#\s]+#(.+)/))) {
1063
+ return { kind: "artifact", id: decodeURIComponent(m[1]), url };
1064
+ }
1065
+ if (/huggingface\.co\/datasets\/[^/]+\/[^/]+/.test(url)) {
1066
+ return { kind: "dataset", id: hfId(url, "/datasets/"), url };
1067
+ }
1068
+ if (/huggingface\.co\/spaces\/[^/]+\/[^/]+/.test(url)) {
1069
+ return { kind: "space", id: hfId(url, "/spaces/"), url };
1070
+ }
1071
+ if (/huggingface\.co\/jobs\//.test(url)) {
1072
+ const parts = hfId(url, "/jobs/").split("/");
1073
+ const jid = parts[1] || "";
1074
+ return {
1075
+ kind: "job",
1076
+ id: parts[0] + (jid ? ` · ${jid.slice(0, 12)}${jid.length > 12 ? "…" : ""}` : ""),
1077
+ url,
1078
+ };
1079
+ }
1080
+ if (/huggingface\.co\/buckets\//.test(url)) {
1081
+ return { kind: "bucket", id: hfId(url, "/buckets/"), url };
1082
+ }
1083
+ if (/huggingface\.co\/papers\//.test(url)) {
1084
+ return { kind: "paper", id: `Paper ${hfId(url, "/papers/")}`, url };
1085
+ }
1086
+ if ((m = url.match(/arxiv\.org\/(?:abs|pdf)\/([^?#\s]+)/))) {
1087
+ return { kind: "paper", id: `arXiv:${m[1].replace(/\.pdf$/, "")}`, url };
1088
+ }
1089
+ if ((m = url.match(/github\.com\/([^/?#]+\/[^/?#]+)/))) {
1090
+ return { kind: "repo", id: m[1], url };
1091
+ }
1092
+ if ((m = url.match(/huggingface\.co\/([^?#]+)/))) {
1093
+ const rest = m[1].replace(/\/$/, "");
1094
+ if (/^[^/]+\/[^/]+$/.test(rest) && !HF_NON_MODEL_PREFIX.test(rest)) {
1095
+ return { kind: "model", id: rest, url };
1096
+ }
1097
+ }
1098
+ return null;
1099
+ }
1100
+
1101
+ async function fillRailMeta(item, el) {
1102
+ if (item.local) return;
1103
+ const meta = el.querySelector(".rail-meta");
1104
+ const set = (parts) => {
1105
+ const text = parts.filter(Boolean).join(" · ");
1106
+ if (text) meta.textContent = text;
1107
+ };
1108
+ if (item.kind === "model") {
1109
+ const d = await getJSON(`https://huggingface.co/api/models/${item.id}`);
1110
+ if (d) set([d.pipeline_tag, `↓ ${fmt(d.downloads)}`, `♥ ${fmt(d.likes)}`]);
1111
+ } else if (item.kind === "dataset") {
1112
+ const d = await getJSON(`https://huggingface.co/api/datasets/${item.id}`);
1113
+ if (d) set([`↓ ${fmt(d.downloads)}`, `♥ ${fmt(d.likes)}`]);
1114
+ } else if (item.kind === "space" || item.kind === "dashboard") {
1115
+ const d = await getJSON(`https://huggingface.co/api/spaces/${item.id}`);
1116
+ if (d) set([d.sdk, `♥ ${fmt(d.likes)}`]);
1117
+ } else if (item.kind === "repo") {
1118
+ const d = await getJSON(`https://api.github.com/repos/${item.id}`);
1119
+ if (d) set([`★ ${fmt(d.stargazers_count)}`, d.language]);
1120
+ } else if (item.kind === "paper") {
1121
+ const m = item.id.match(/^(?:arXiv:|Paper )(.+)$/);
1122
+ if (!m) return;
1123
+ const arxivId = m[1].replace(/v\d+$/, "");
1124
+ const d = await getJSON(`https://huggingface.co/api/papers/${arxivId}`);
1125
+ if (d && d.id) {
1126
+ if (el.href) el.href = `https://huggingface.co/papers/${d.id}`;
1127
+ const title =
1128
+ d.title && d.title.length > 70 ? `${d.title.slice(0, 69)}…` : d.title;
1129
+ set([title, d.upvotes ? `▲ ${fmt(d.upvotes)}` : null]);
1130
+ }
1131
+ }
1132
+ }
1133
+
1134
+ const BARE_ID_SKIP_DIRS = new Set([
1135
+ "scripts",
1136
+ "configs",
1137
+ "config",
1138
+ "results",
1139
+ "figures",
1140
+ "data",
1141
+ "datasets",
1142
+ "src",
1143
+ "tests",
1144
+ "test",
1145
+ "examples",
1146
+ "pages",
1147
+ "assets",
1148
+ "docs",
1149
+ "outputs",
1150
+ "output",
1151
+ "checkpoints",
1152
+ "models",
1153
+ "utils",
1154
+ "lib",
1155
+ "bin",
1156
+ "tmp",
1157
+ "node_modules",
1158
+ "dist",
1159
+ "build",
1160
+ ]);
1161
+ const FILE_EXT_RE =
1162
+ /\.(py|pyc|js|ts|jsx|tsx|json|jsonl|yaml|yml|csv|tsv|md|txt|sh|bash|html|css|png|jpe?g|svg|gif|webp|ipynb|toml|cfg|ini|lock|pdf|whl|gz|zip|tar|pt|pth|bin|safetensors|db|sqlite)$/i;
1163
+
1164
+ async function detectBareModelIds(text, groups) {
1165
+ const stripped = text.replace(DETECTED_URL, " ");
1166
+ DETECTED_URL.lastIndex = 0;
1167
+ const seen = new Set();
1168
+ const candidates = [];
1169
+ const re = /(^|[\s"'`(=[])([A-Za-z0-9][\w.-]*\/[A-Za-z0-9][\w.-]*)/g;
1170
+ let m;
1171
+ while ((m = re.exec(stripped)) && candidates.length < 15) {
1172
+ const id = m[2].replace(/[.:,]+$/, "");
1173
+ if (seen.has(id)) continue;
1174
+ seen.add(id);
1175
+ if (FILE_EXT_RE.test(id)) continue;
1176
+ if (BARE_ID_SKIP_DIRS.has(id.split("/")[0].toLowerCase())) continue;
1177
+ candidates.push(id);
1178
+ }
1179
+ const results = await Promise.all(
1180
+ candidates.map((id) => getJSON(`https://huggingface.co/api/models/${id}`))
1181
+ );
1182
+ let added = false;
1183
+ const confirmed = [];
1184
+ results.forEach((d, i) => {
1185
+ if (!d || !d.id) return;
1186
+ const id = candidates[i];
1187
+ confirmed.push(id);
1188
+ const url = `https://huggingface.co/${id}`;
1189
+ if (!groups.has("model")) groups.set("model", new Map());
1190
+ if (!groups.get("model").has(url)) {
1191
+ groups.get("model").set(url, { kind: "model", id, url });
1192
+ added = true;
1193
+ }
1194
+ });
1195
+ return { added, confirmed };
1196
+ }
1197
+
1198
+ function chipifyBareIds(ids, container) {
1199
+ if (!ids.length) return;
1200
+ const escaped = ids.map((id) => id.replace(/[.*+?^${}()|[\]\\]/g, "\\$&"));
1201
+ const pattern = new RegExp("(" + escaped.join("|") + ")");
1202
+ const splitter = new RegExp(pattern.source, "g");
1203
+ container
1204
+ .querySelectorAll(".cell.markdown .cell-body")
1205
+ .forEach((body) => {
1206
+ const walker = document.createTreeWalker(body, NodeFilter.SHOW_TEXT, {
1207
+ acceptNode(node) {
1208
+ if (!pattern.test(node.nodeValue)) return NodeFilter.FILTER_REJECT;
1209
+ for (
1210
+ let el = node.parentElement;
1211
+ el && el !== body;
1212
+ el = el.parentElement
1213
+ ) {
1214
+ if (["A", "CODE", "PRE", "BUTTON"].indexOf(el.tagName) !== -1) {
1215
+ return NodeFilter.FILTER_REJECT;
1216
+ }
1217
+ }
1218
+ return NodeFilter.FILTER_ACCEPT;
1219
+ },
1220
+ });
1221
+ const nodes = [];
1222
+ while (walker.nextNode()) nodes.push(walker.currentNode);
1223
+ nodes.forEach((node) => {
1224
+ const frag = document.createDocumentFragment();
1225
+ node.nodeValue.split(splitter).forEach((part) => {
1226
+ if (ids.indexOf(part) !== -1) {
1227
+ const holder = document.createElement("span");
1228
+ holder.innerHTML = resChipHtml({
1229
+ kind: "model",
1230
+ id: part,
1231
+ url: `https://huggingface.co/${part}`,
1232
+ });
1233
+ frag.appendChild(holder.firstChild);
1234
+ } else if (part) {
1235
+ frag.appendChild(document.createTextNode(part));
1236
+ }
1237
+ });
1238
+ node.parentNode.replaceChild(frag, node);
1239
+ });
1240
+ });
1241
+ }
1242
+
1243
+ let RAIL_TOKEN = 0;
1244
+ const RAIL_EXCLUDE_KINDS = new Set(["paper", "repo", "artifact", "dashboard"]);
1245
+
1246
+ function railDashboardItem(it) {
1247
+ return {
1248
+ kind: "dashboard",
1249
+ id: it.id,
1250
+ url: it.local ? it.resUrl : it.url || it.resUrl,
1251
+ local: it.local,
1252
+ railLabel: "Dashboard",
1253
+ };
1254
+ }
1255
+
1256
+ function promoteTrackioSpacesInRail(groups, dashResUrls, body, rail, token) {
1257
+ const spaceGroup = groups.get("space");
1258
+ if (!spaceGroup || !spaceGroup.size) return;
1259
+ spaceGroup.forEach((item, url) => {
1260
+ getJSON(`https://huggingface.co/api/spaces/${item.id}`)
1261
+ .then((d) => {
1262
+ if (rail.dataset.renderToken !== token) return;
1263
+ const tags = (d && d.tags) || [];
1264
+ if (!tags.some((t) => String(t).toLowerCase() === "trackio")) return;
1265
+ if (dashResUrls.has(url)) return;
1266
+ spaceGroup.delete(url);
1267
+ if (!spaceGroup.size) groups.delete("space");
1268
+ if (!groups.has("dashboard")) groups.set("dashboard", new Map());
1269
+ groups.get("dashboard").set(url, {
1270
+ kind: "dashboard",
1271
+ id: item.id,
1272
+ url: item.url,
1273
+ local: false,
1274
+ railLabel: "Dashboard",
1275
+ });
1276
+ dashResUrls.add(url);
1277
+ paintRail(groups, body, rail);
1278
+ })
1279
+ .catch(() => {});
1280
+ });
1281
+ }
1282
+
1283
+ function renderRail(md, body, rail) {
1284
+ const token = String(++RAIL_TOKEN);
1285
+ rail.dataset.renderToken = token;
1286
+ const scanText = md.replace(
1287
+ /(`{3,4}|~{3,4})(html|raw)[^\n]*\n[\s\S]*?\n\1/g,
1288
+ " "
1289
+ );
1290
+ const groups = new Map();
1291
+ const dashMap = new Map();
1292
+ const dashResUrls = new Set();
1293
+ cellDashboardItems(md).forEach((it) => {
1294
+ if (dashMap.has(it.resUrl)) return;
1295
+ dashMap.set(it.resUrl, railDashboardItem(it));
1296
+ dashResUrls.add(it.resUrl);
1297
+ });
1298
+ if (dashMap.size) groups.set("dashboard", dashMap);
1299
+ extractUrls(scanText).forEach((url) => {
1300
+ const item = classifyResource(url);
1301
+ if (!item) return;
1302
+ if (RAIL_EXCLUDE_KINDS.has(item.kind)) return;
1303
+ if (dashResUrls.has(url)) return;
1304
+ if (!groups.has(item.kind)) groups.set(item.kind, new Map());
1305
+ groups.get(item.kind).set(item.url, item);
1306
+ });
1307
+ const artMap = new Map();
1308
+ cellArtifactItems(md).forEach((it) => {
1309
+ if (artMap.has(it.resUrl)) return;
1310
+ const label = it.type
1311
+ ? it.type.charAt(0).toUpperCase() + it.type.slice(1)
1312
+ : "Artifact";
1313
+ artMap.set(it.resUrl, {
1314
+ kind: "artifact",
1315
+ id: it.name,
1316
+ url: it.local ? it.resUrl : it.url || it.resUrl,
1317
+ local: it.local,
1318
+ railLabel: label,
1319
+ size: it.size,
1320
+ });
1321
+ });
1322
+ if (artMap.size) groups.set("artifact", artMap);
1323
+ paintRail(groups, body, rail);
1324
+ promoteTrackioSpacesInRail(groups, dashResUrls, body, rail, token);
1325
+ detectBareModelIds(scanText, groups)
1326
+ .then((result) => {
1327
+ if (rail.dataset.renderToken !== token) return;
1328
+ chipifyBareIds(result.confirmed, body);
1329
+ if (result.added) paintRail(groups, body, rail);
1330
+ })
1331
+ .catch(() => {});
1332
+ }
1333
+
1334
+ function paintRail(groups, body, rail) {
1335
+ rail.innerHTML = "";
1336
+ RESOURCE_SECTIONS.forEach(([kind, label, icon]) => {
1337
+ const group = groups.get(kind);
1338
+ if (!group || !group.size) return;
1339
+ group.forEach((item) => {
1340
+ const el = document.createElement(item.local ? "div" : "a");
1341
+ el.className = item.local ? "rail-item rail-local" : "rail-item";
1342
+ if (!item.local) {
1343
+ el.href = item.url;
1344
+ el.target = "_blank";
1345
+ el.rel = "noopener";
1346
+ }
1347
+ el.dataset.resUrl = item.url;
1348
+ let desc;
1349
+ if (kind === "artifact") {
1350
+ const state = item.local ? "publish to share" : "Open ↗";
1351
+ desc = item.size ? `${item.size} · ${state}` : state;
1352
+ } else if (kind === "dashboard") {
1353
+ desc = item.local ? "publish to share" : "Open ↗";
1354
+ } else {
1355
+ desc = item.local ? "publish to share" : RESOURCE_DESC[kind];
1356
+ }
1357
+ const kindLabel = item.railLabel || label.replace(/s$/, "");
1358
+ const iconHtml =
1359
+ kind === "artifact"
1360
+ ? ARTIFACT_ICON_IMG
1361
+ : kind === "dashboard"
1362
+ ? DASHBOARD_ICON_IMG
1363
+ : `<span>${icon}</span>`;
1364
+ el.innerHTML =
1365
+ `<div class="rail-kind">${iconHtml}${esc(kindLabel)}</div>` +
1366
+ `<div class="rail-title">${esc(item.id)}</div>` +
1367
+ `<div class="rail-meta">${esc(desc)}</div>`;
1368
+ rail.appendChild(el);
1369
+ fillRailMeta(item, el)
1370
+ .catch(() => {})
1371
+ .finally(() => scheduleRailPosition(body, rail));
1372
+ });
1373
+ });
1374
+ rail.hidden = !rail.childElementCount;
1375
+ scheduleRailPosition(body, rail);
1376
+ }
1377
+
1378
+ function resourceAnchor(body, url) {
1379
+ return body.querySelector(`[data-res-url="${CSS.escape(url)}"]`);
1380
+ }
1381
+
1382
+ function positionRail(body, rail) {
1383
+ if (rail.hidden || !rail.isConnected) return;
1384
+ const bodyRect = body.getBoundingClientRect();
1385
+ const items = Array.from(rail.querySelectorAll(".rail-item")).map((el, index) => {
1386
+ const anchor = resourceAnchor(body, el.dataset.resUrl);
1387
+ return {
1388
+ el,
1389
+ index,
1390
+ desired: anchor
1391
+ ? Math.max(0, anchor.getBoundingClientRect().top - bodyRect.top)
1392
+ : 0,
1393
+ };
1394
+ });
1395
+ items.sort((a, b) => a.desired - b.desired || a.index - b.index);
1396
+ let cursor = 0;
1397
+ items.forEach(({ el, desired }) => {
1398
+ const top = Math.max(desired, cursor);
1399
+ el.style.top = `${top}px`;
1400
+ cursor = top + el.offsetHeight + 10;
1401
+ });
1402
+ rail.style.minHeight = `${Math.max(body.offsetHeight, cursor)}px`;
1403
+ }
1404
+
1405
+ function scheduleRailPosition(body, rail) {
1406
+ cancelAnimationFrame(Number(rail.dataset.positionFrame || 0));
1407
+ rail.dataset.positionFrame = String(
1408
+ requestAnimationFrame(() => positionRail(body, rail))
1409
+ );
1410
+ }
1411
+
1412
+ function dashboardSubdomainFromUrl(url) {
1413
+ return spaceIdFromUrl(url).toLowerCase().replace(/[^a-z0-9-]/g, "-");
1414
+ }
1415
+
1416
+ function dashboardOpenLink(head, url) {
1417
+ if (!head || !url) return;
1418
+ const meta = head.querySelector(".cell-meta");
1419
+ if (!meta) return;
1420
+ let link = meta.querySelector(".cell-open");
1421
+ if (!link) {
1422
+ link = document.createElement("a");
1423
+ link.className = "cell-open";
1424
+ link.target = "_blank";
1425
+ link.rel = "noopener";
1426
+ meta.insertBefore(link, meta.firstChild);
1427
+ }
1428
+ link.href = url;
1429
+ link.textContent = "Open ↗";
1430
+ }
1431
+
1432
+ function dashboardFrame(src) {
1433
+ const iframe = document.createElement("iframe");
1434
+ iframe.className = "dashboard-frame";
1435
+ iframe.src = src;
1436
+ iframe.loading = "lazy";
1437
+ iframe.allow = "clipboard-read; clipboard-write; fullscreen";
1438
+ return iframe;
1439
+ }
1440
+
1441
+ function renderDashboardCell(meta, body, container, head) {
1442
+ const project = meta.dashboard_project || "";
1443
+ const holder = document.createElement("div");
1444
+ holder.className = "dashboard-shell";
1445
+ container.appendChild(holder);
1446
+ const space = body.match(/https:\/\/huggingface\.co\/spaces\/[^\s<>)"'`]+/);
1447
+ if (space) {
1448
+ const url = space[0];
1449
+ dashboardOpenLink(head, url);
1450
+ holder.appendChild(
1451
+ dashboardFrame(
1452
+ `https://${dashboardSubdomainFromUrl(url)}.hf.space/?sidebar=hidden&hide_empty_tabs=true`
1453
+ )
1454
+ );
1455
+ return;
1456
+ }
1457
+ if (!isLocalPreview()) {
1458
+ holder.className = "artifact-chip";
1459
+ holder.dataset.resUrl = `trackio-local-dashboard://${project}`;
1460
+ holder.innerHTML =
1461
+ "🎯 <strong>Local Trackio dashboard</strong> — publish the logbook to share it";
1462
+ return;
1463
+ }
1464
+ const open = "/dashboard/?project=" + encodeURIComponent(project);
1465
+ dashboardOpenLink(head, open);
1466
+ holder.appendChild(
1467
+ dashboardFrame(open + "&sidebar=hidden&hide_empty_tabs=true"),
1468
+ );
1469
+ }
1470
+
1471
+ const CACHE_PREFIX = "trackio-logbook:";
1472
+ const CACHE_TTL_MS = 24 * 60 * 60 * 1000;
1473
+ const CACHE_MISS_TTL_MS = 60 * 60 * 1000;
1474
+
1475
+ function cacheGet(url) {
1476
+ try {
1477
+ const raw = localStorage.getItem(CACHE_PREFIX + url);
1478
+ if (!raw) return undefined;
1479
+ const entry = JSON.parse(raw);
1480
+ const ttl = entry.d === null ? CACHE_MISS_TTL_MS : CACHE_TTL_MS;
1481
+ if (Date.now() - entry.t > ttl) {
1482
+ localStorage.removeItem(CACHE_PREFIX + url);
1483
+ return undefined;
1484
+ }
1485
+ return entry.d;
1486
+ } catch (e) {
1487
+ return undefined;
1488
+ }
1489
+ }
1490
+
1491
+ function cacheSet(url, data) {
1492
+ try {
1493
+ localStorage.setItem(
1494
+ CACHE_PREFIX + url,
1495
+ JSON.stringify({ t: Date.now(), d: data })
1496
+ );
1497
+ } catch (e) {}
1498
+ }
1499
+
1500
+ async function getJSON(url) {
1501
+ if (UNFURL_CACHE[url] !== undefined) return UNFURL_CACHE[url];
1502
+ const cached = cacheGet(url);
1503
+ if (cached !== undefined) {
1504
+ UNFURL_CACHE[url] = cached;
1505
+ return cached;
1506
+ }
1507
+ try {
1508
+ const r = await fetch(url);
1509
+ if (!r.ok) throw new Error(r.status);
1510
+ const j = await r.json();
1511
+ UNFURL_CACHE[url] = j;
1512
+ cacheSet(url, j);
1513
+ return j;
1514
+ } catch (e) {
1515
+ UNFURL_CACHE[url] = null;
1516
+ cacheSet(url, null);
1517
+ return null;
1518
+ }
1519
+ }
1520
+
1521
+ /* -------------------- routing / render -------------------- */
1522
+
1523
+ function buildTree() {
1524
+ const tree = document.getElementById("tree");
1525
+ tree.innerHTML = "";
1526
+ const nodes = [];
1527
+ (MANIFEST.root.children || []).forEach((c) => flattenTree(c, 0, nodes));
1528
+ nodes.forEach(({ node, depth }) => {
1529
+ const a = document.createElement("a");
1530
+ a.href = "#/" + node.slug;
1531
+ a.className = "depth-" + depth;
1532
+ a.dataset.slug = node.slug;
1533
+ const mark = document.createElement("span");
1534
+ mark.className = "tree-mark";
1535
+ mark.textContent = "§";
1536
+ a.appendChild(mark);
1537
+ a.appendChild(document.createTextNode(" " + node.title));
1538
+ tree.appendChild(a);
1539
+ });
1540
+ }
1541
+
1542
+ function highlight(slug) {
1543
+ document
1544
+ .querySelectorAll("#tree a")
1545
+ .forEach((a) => a.classList.toggle("active", a.dataset.slug === slug));
1546
+ document
1547
+ .getElementById("book-head")
1548
+ .classList.toggle("active", slug === MANIFEST.root.slug);
1549
+ }
1550
+
1551
+ function clearPageCache() {
1552
+ Object.keys(PAGE_CACHE).forEach((key) => {
1553
+ delete PAGE_CACHE[key];
1554
+ });
1555
+ }
1556
+
1557
+ function isLocalPreview() {
1558
+ return ["localhost", "127.0.0.1", "::1"].includes(location.hostname);
1559
+ }
1560
+
1561
+ async function fetchManifest() {
1562
+ const suffix = isLocalPreview() ? `?t=${Date.now()}` : "";
1563
+ return await (await fetch("./logbook.json" + suffix, { cache: "no-store" })).json();
1564
+ }
1565
+
1566
+ async function fetchPage(node) {
1567
+ if (PAGE_CACHE[node.file]) return PAGE_CACHE[node.file];
1568
+ try {
1569
+ const suffix = isLocalPreview()
1570
+ ? `?rev=${encodeURIComponent(MANIFEST.revision || "")}`
1571
+ : "";
1572
+ const r = await fetch("./" + node.file + suffix, { cache: "no-store" });
1573
+ PAGE_CACHE[node.file] = await r.text();
1574
+ } catch (e) {
1575
+ PAGE_CACHE[node.file] = "# " + node.title + "\n\n_Could not load section._";
1576
+ }
1577
+ return PAGE_CACHE[node.file];
1578
+ }
1579
+
1580
+ function allNodes() {
1581
+ const nodes = [];
1582
+ flattenTree(MANIFEST.root, 0, nodes);
1583
+ return nodes.map(({ node }) => node);
1584
+ }
1585
+
1586
+ function collectPinnedCells(markdown, nodes) {
1587
+ const cells = [];
1588
+ markdown.forEach((text, index) => {
1589
+ const cellRe = /(^|\n)---\n<!-- trackio-cell\n([\s\S]*?)\n-->\n([\s\S]*?)(?=\n---\n<!-- trackio-cell\n|\s*$)/g;
1590
+ let match;
1591
+ let cellIndex = 0;
1592
+ while ((match = cellRe.exec(text))) {
1593
+ const meta = parseCellMeta(match[2]);
1594
+ if (isPinned(meta)) {
1595
+ cells.push({
1596
+ meta,
1597
+ body: match[3],
1598
+ node: nodes[index],
1599
+ index: cells.length,
1600
+ order: meta.pinned_at || meta.created_at || "",
1601
+ cellIndex,
1602
+ });
1603
+ }
1604
+ cellIndex++;
1605
+ }
1606
+ });
1607
+ return cells.sort(
1608
+ (a, b) =>
1609
+ a.order.localeCompare(b.order) ||
1610
+ a.index - b.index ||
1611
+ a.cellIndex - b.cellIndex
1612
+ );
1613
+ }
1614
+
1615
+ function renderPinnedNotes(cells, container) {
1616
+ if (!cells.length) return;
1617
+ const deck = document.createElement("section");
1618
+ deck.className = "pinned-notes";
1619
+ const list = document.createElement("div");
1620
+ list.className = "pinned-notes-list";
1621
+ cells.forEach(({ meta, body }) => {
1622
+ const cell = renderCell(meta, body, list);
1623
+ cell.classList.add("pinned-copy");
1624
+ });
1625
+ deck.appendChild(list);
1626
+ const anchor =
1627
+ container.querySelector(".logbook-stats") ||
1628
+ container.querySelector(".agent-hint");
1629
+ container.insertBefore(deck, anchor ? anchor.nextSibling : container.firstChild);
1630
+ container.closest(".book-intro").classList.add("has-pinned-notes");
1631
+ }
1632
+
1633
+ function removeIndexProse(body) {
1634
+ const h1 = Array.from(body.children).find((el) => el.tagName === "H1");
1635
+ if (!h1) return;
1636
+ let current = h1.nextElementSibling;
1637
+ while (current && current.tagName !== "H2") {
1638
+ const next = current.nextElementSibling;
1639
+ current.remove();
1640
+ current = next;
1641
+ }
1642
+ }
1643
+
1644
+ function removePageDirectory(body) {
1645
+ const heading = Array.from(body.children).find(
1646
+ (el) => el.tagName === "H2" && el.textContent.trim().toLowerCase() === "pages"
1647
+ );
1648
+ if (!heading) return;
1649
+ let current = heading;
1650
+ while (current) {
1651
+ const next = current.nextElementSibling;
1652
+ current.remove();
1653
+ if (next && ["H1", "H2"].includes(next.tagName)) break;
1654
+ current = next;
1655
+ }
1656
+ }
1657
+
1658
+ const RAIL_OBSERVERS = [];
1659
+
1660
+ async function renderLogbook(opts = {}) {
1661
+ const scrollY = window.scrollY;
1662
+ const page = document.getElementById("page");
1663
+ RAIL_OBSERVERS.splice(0).forEach((observer) => observer.disconnect());
1664
+ page.innerHTML = "";
1665
+ const nodes = allNodes();
1666
+ const markdown = await Promise.all(nodes.map(fetchPage));
1667
+ const pinnedCells = collectPinnedCells(markdown, nodes);
1668
+ let bookIntroBody = null;
1669
+ nodes.forEach((node, index) => {
1670
+ const section = document.createElement("section");
1671
+ section.className = "page-section";
1672
+ section.id = "/" + node.slug;
1673
+ section.dataset.slug = node.slug;
1674
+
1675
+ const layout = document.createElement("div");
1676
+ layout.className = "page-layout";
1677
+ const body = document.createElement("div");
1678
+ body.className = "page-body";
1679
+ const rail = document.createElement("aside");
1680
+ rail.className = "context-rail";
1681
+ rail.setAttribute("aria-label", `Resources for ${node.title}`);
1682
+
1683
+ renderMarkdown(markdown[index], body);
1684
+ if (node.slug === MANIFEST.root.slug) {
1685
+ section.classList.add("book-intro");
1686
+ removeIndexProse(body);
1687
+ removePageDirectory(body);
1688
+ const hint = buildAgentHint();
1689
+ const h1 = body.querySelector("h1");
1690
+ if (h1 && h1.parentNode === body) {
1691
+ body.insertBefore(hint, h1.nextSibling);
1692
+ } else {
1693
+ body.prepend(hint);
1694
+ }
1695
+ hint.after(buildLogbookStats(markdown));
1696
+ bookIntroBody = body;
1697
+ }
1698
+ layout.appendChild(body);
1699
+ layout.appendChild(rail);
1700
+ section.appendChild(layout);
1701
+ page.appendChild(section);
1702
+ renderRail(markdown[index], body, rail);
1703
+ if (window.ResizeObserver) {
1704
+ const observer = new ResizeObserver(() => scheduleRailPosition(body, rail));
1705
+ observer.observe(body);
1706
+ observer.observe(rail);
1707
+ RAIL_OBSERVERS.push(observer);
1708
+ }
1709
+ });
1710
+ if (bookIntroBody) renderPinnedNotes(pinnedCells, bookIntroBody);
1711
+ if (bookIntroBody) {
1712
+ const section = bookIntroBody.closest(".book-intro");
1713
+ const hasExtra = Array.from(bookIntroBody.children).some(
1714
+ (el) =>
1715
+ el.tagName !== "H1" &&
1716
+ !el.classList.contains("agent-hint") &&
1717
+ !el.classList.contains("logbook-stats") &&
1718
+ !el.classList.contains("pinned-notes")
1719
+ );
1720
+ if (section && !section.classList.contains("has-pinned-notes") && !hasExtra) {
1721
+ section.classList.add("book-intro-tight");
1722
+ }
1723
+ }
1724
+ requestAnimationFrame(() => {
1725
+ if (opts.preserveScroll) {
1726
+ window.scrollTo(0, scrollY);
1727
+ } else {
1728
+ scrollToHash({ behavior: "auto" });
1729
+ }
1730
+ updateActiveSection();
1731
+ });
1732
+ }
1733
+
1734
+ function setupResourceHover() {
1735
+ document.addEventListener("mouseover", (e) => {
1736
+ const el = e.target.closest && e.target.closest("[data-res-url]");
1737
+ if (!el || el.classList.contains("rail-item")) return;
1738
+ const url = el.getAttribute("data-res-url");
1739
+ const section = el.closest(".page-section");
1740
+ const scope = section || document;
1741
+ scope.querySelectorAll(".context-rail [data-res-url]").forEach((n) => {
1742
+ n.classList.toggle("res-hl", n.getAttribute("data-res-url") === url);
1743
+ });
1744
+ });
1745
+ document.addEventListener("mouseout", (e) => {
1746
+ const el = e.target.closest && e.target.closest("[data-res-url]");
1747
+ if (!el || el.classList.contains("rail-item")) return;
1748
+ document.querySelectorAll(".context-rail .res-hl").forEach((n) => {
1749
+ n.classList.remove("res-hl");
1750
+ });
1751
+ });
1752
+ }
1753
+
1754
+ let STATS_TOKEN = 0;
1755
+ let STATS_LISTENERS = false;
1756
+
1757
+ function fmtBytes(n) {
1758
+ if (n == null || isNaN(n)) return null;
1759
+ if (n < 1000) return `${n} B`;
1760
+ const units = ["kB", "MB", "GB", "TB"];
1761
+ let v = n;
1762
+ let i = -1;
1763
+ do {
1764
+ v /= 1000;
1765
+ i++;
1766
+ } while (v >= 1000 && i < units.length - 1);
1767
+ return `${v.toFixed(v < 10 ? 1 : 0)} ${units[i]}`;
1768
+ }
1769
+
1770
+ function spaceIdFromUrl(url) {
1771
+ return url.split("/spaces/")[1].split(/[?#]/)[0].replace(/\/$/, "");
1772
+ }
1773
+
1774
+ const LB_CELL_RE = /(^|\n)---\n<!-- trackio-cell\n([\s\S]*?)\n-->\n([\s\S]*?)(?=\n---\n<!-- trackio-cell\n|\s*$)/g;
1775
+
1776
+ function cellDashboardItems(md) {
1777
+ const re = new RegExp(LB_CELL_RE.source, "g");
1778
+ const items = [];
1779
+ let m;
1780
+ while ((m = re.exec(md))) {
1781
+ const meta = parseCellMeta(m[2]);
1782
+ if (meta.type !== "dashboard") continue;
1783
+ const body = m[3];
1784
+ const project = meta.dashboard_project || "";
1785
+ const sp = body.match(/https:\/\/huggingface\.co\/spaces\/[^\s<>)"'`]+/);
1786
+ const local = !sp;
1787
+ const url = sp ? sp[0] : "";
1788
+ const resUrl = local ? `trackio-local-dashboard://${project}` : url;
1789
+ items.push({
1790
+ id: local ? project : spaceIdFromUrl(url),
1791
+ local,
1792
+ url,
1793
+ resUrl,
1794
+ });
1795
+ }
1796
+ return items;
1797
+ }
1798
+
1799
+ function artifactInfoFromCell(meta, body) {
1800
+ const name = meta.artifact || meta.path || "";
1801
+ let size = null;
1802
+ const sm = body.match(/·\s*([\d.]+\s*[kMGT]?B)\b/);
1803
+ if (sm) size = sm[1].trim();
1804
+ if (!size && meta.size != null) size = fmtBytes(meta.size);
1805
+ const bucket = body.match(/https:\/\/huggingface\.co\/buckets\/[^\s<>)"'`]+/);
1806
+ const artUri = body.match(/trackio-artifact:\/\/\S+/);
1807
+ const pathUri = body.match(/trackio-local-path:\/\/\S+/);
1808
+ const url = bucket ? bucket[0] : "";
1809
+ const local = !bucket;
1810
+ const resUrl =
1811
+ url || (artUri ? artUri[0] : pathUri ? pathUri[0] : `trackio-artifact://${name}`);
1812
+ return {
1813
+ name,
1814
+ type: meta.artifact_type || "",
1815
+ size,
1816
+ local,
1817
+ isPathRef: !!meta.path,
1818
+ url,
1819
+ resUrl,
1820
+ };
1821
+ }
1822
+
1823
+ function cellArtifactItems(md) {
1824
+ const re = new RegExp(LB_CELL_RE.source, "g");
1825
+ const items = [];
1826
+ let m;
1827
+ while ((m = re.exec(md))) {
1828
+ const meta = parseCellMeta(m[2]);
1829
+ const body = m[3];
1830
+ const order = meta.created_at || "";
1831
+ if (meta.type === "artifact") {
1832
+ const info = artifactInfoFromCell(meta, body);
1833
+ if (info.name) items.push({ ...info, order });
1834
+ }
1835
+ }
1836
+ return items;
1837
+ }
1838
+
1839
+ function collectLogbookResources(markdownList) {
1840
+ const re = new RegExp(LB_CELL_RE.source, "g");
1841
+ const dashboards = new Map();
1842
+ markdownList.forEach((md) => {
1843
+ let m;
1844
+ while ((m = re.exec(md))) {
1845
+ const meta = parseCellMeta(m[2]);
1846
+ const body = m[3];
1847
+ if (meta.type !== "dashboard") continue;
1848
+ const project = meta.dashboard_project || "";
1849
+ const space = body.match(/https:\/\/huggingface\.co\/spaces\/[^\s<>)"'`]+/);
1850
+ const local = !space;
1851
+ const url = space ? space[0] : "";
1852
+ const key = local ? `local:${project}` : `space:${spaceIdFromUrl(url)}`;
1853
+ const resUrl = local ? `trackio-local-dashboard://${project}` : url;
1854
+ if (!dashboards.has(key))
1855
+ dashboards.set(key, { project, local, url, resUrl });
1856
+ }
1857
+ });
1858
+ const artifacts = new Map();
1859
+ markdownList.forEach((md) => {
1860
+ cellArtifactItems(md).forEach((it) => {
1861
+ const key = `${it.type}:${it.name}`;
1862
+ const prev = artifacts.get(key);
1863
+ if (!prev || it.order >= prev.order) artifacts.set(key, it);
1864
+ });
1865
+ });
1866
+ return {
1867
+ dashboards: Array.from(dashboards.values()).sort((a, b) =>
1868
+ a.project.localeCompare(b.project)
1869
+ ),
1870
+ artifacts: Array.from(artifacts.values()).sort((a, b) =>
1871
+ a.name.localeCompare(b.name)
1872
+ ),
1873
+ };
1874
+ }
1875
+
1876
+ function closeStatPopovers() {
1877
+ document
1878
+ .querySelectorAll(".stat-popover")
1879
+ .forEach((p) => (p.hidden = true));
1880
+ document
1881
+ .querySelectorAll(".stat-tile.open")
1882
+ .forEach((t) => t.classList.remove("open"));
1883
+ }
1884
+
1885
+ function ensureStatListeners() {
1886
+ if (STATS_LISTENERS) return;
1887
+ STATS_LISTENERS = true;
1888
+ document.addEventListener("click", closeStatPopovers);
1889
+ document.addEventListener("keydown", (e) => {
1890
+ if (e.key === "Escape") closeStatPopovers();
1891
+ });
1892
+ }
1893
+
1894
+ function stateHtml(remote, url) {
1895
+ return remote
1896
+ ? `<a class="stat-row-state open" href="${esc(url)}" target="_blank" rel="noopener" title="Open in a new tab">Open ↗</a>`
1897
+ : `<span class="stat-row-state">publish to share</span>`;
1898
+ }
1899
+
1900
+ function scrollToResource(resUrl) {
1901
+ closeStatPopovers();
1902
+ if (!resUrl) return;
1903
+ const el = document.querySelector(
1904
+ `#page .page-body [data-res-url="${CSS.escape(resUrl)}"]:not(.stat-row)`
1905
+ );
1906
+ if (!el) return;
1907
+ el.scrollIntoView({ behavior: "smooth", block: "center" });
1908
+ el.classList.add("res-flash");
1909
+ setTimeout(() => el.classList.remove("res-flash"), 1500);
1910
+ }
1911
+
1912
+ function dashRowHtml(d) {
1913
+ const inner =
1914
+ `<span class="stat-row-ico">${DASHBOARD_ICON_IMG}</span>` +
1915
+ `<div class="stat-row-main"><div class="stat-row-title">${esc(d.project)}</div>` +
1916
+ `<div class="stat-row-meta">${stateHtml(!d.local, d.url)}</div></div>`;
1917
+ return `<div class="stat-row" data-res-url="${esc(d.resUrl)}" title="Jump to it in the logbook">${inner}</div>`;
1918
+ }
1919
+
1920
+ function artRowHtml(a) {
1921
+ const remote = !a.local && !!a.url;
1922
+ const parts = [a.type, a.size].filter(Boolean).map(esc);
1923
+ const meta = parts.length
1924
+ ? `${parts.join(" · ")} · ${stateHtml(remote, a.url)}`
1925
+ : stateHtml(remote, a.url);
1926
+ const inner =
1927
+ `<span class="stat-row-ico">${ARTIFACT_ICON_IMG}</span>` +
1928
+ `<div class="stat-row-main"><div class="stat-row-title">${esc(a.name)}</div>` +
1929
+ `<div class="stat-row-meta">${meta}</div></div>`;
1930
+ return `<div class="stat-row" data-res-url="${esc(a.resUrl)}" title="Jump to it in the logbook">${inner}</div>`;
1931
+ }
1932
+
1933
+ function statTile(icon, alt, singular, plural, head, rowFn) {
1934
+ const tile = document.createElement("button");
1935
+ tile.type = "button";
1936
+ tile.className = "stat-tile";
1937
+ const render = (items) => {
1938
+ const count = items.length;
1939
+ const label = count === 1 ? singular : plural;
1940
+ const caret = count > 0 ? `<span class="stat-caret">▾</span>` : "";
1941
+ tile.innerHTML =
1942
+ `<img class="stat-icon" src="${icon}" alt="${esc(alt)}" />` +
1943
+ `<div class="stat-text"><div class="stat-num">${count}</div>` +
1944
+ `<div class="stat-label">${esc(label)}</div></div>` +
1945
+ caret;
1946
+ tile.disabled = count === 0;
1947
+ if (count > 0) {
1948
+ const pop = document.createElement("div");
1949
+ pop.className = "stat-popover";
1950
+ pop.hidden = true;
1951
+ pop.innerHTML =
1952
+ `<div class="stat-pop-head">${esc(head)}</div>` +
1953
+ items.map(rowFn).join("");
1954
+ pop.addEventListener("click", (e) => {
1955
+ if (e.target.closest("a.stat-row-state")) {
1956
+ e.stopPropagation();
1957
+ return;
1958
+ }
1959
+ e.stopPropagation();
1960
+ const row = e.target.closest(".stat-row");
1961
+ if (row) scrollToResource(row.dataset.resUrl);
1962
+ });
1963
+ tile.appendChild(pop);
1964
+ }
1965
+ };
1966
+ tile.addEventListener("click", (e) => {
1967
+ if (tile.disabled) return;
1968
+ e.stopPropagation();
1969
+ const pop = tile.querySelector(".stat-popover");
1970
+ if (!pop) return;
1971
+ const isOpen = !pop.hidden;
1972
+ closeStatPopovers();
1973
+ if (!isOpen) {
1974
+ pop.hidden = false;
1975
+ tile.classList.add("open");
1976
+ }
1977
+ });
1978
+ return { tile, render };
1979
+ }
1980
+
1981
+ function buildLogbookStats(markdownList) {
1982
+ const token = ++STATS_TOKEN;
1983
+ ensureStatListeners();
1984
+ const { dashboards, artifacts } = collectLogbookResources(markdownList);
1985
+
1986
+ const el = document.createElement("div");
1987
+ el.className = "logbook-stats";
1988
+ const dash = statTile(
1989
+ "./trackio-logo-light.png",
1990
+ "Trackio",
1991
+ "Trackio Dashboard",
1992
+ "Trackio Dashboards",
1993
+ "Dashboards created in this logbook",
1994
+ dashRowHtml
1995
+ );
1996
+ const art = statTile(
1997
+ "./bucket-icon.svg",
1998
+ "Bucket",
1999
+ "Artifact",
2000
+ "Artifacts",
2001
+ "Artifacts created in this logbook",
2002
+ artRowHtml
2003
+ );
2004
+ dash.render(dashboards);
2005
+ art.render(artifacts);
2006
+ el.appendChild(dash.tile);
2007
+ el.appendChild(art.tile);
2008
+
2009
+ const scanText = markdownList
2010
+ .map((md) =>
2011
+ md.replace(/(`{3,4}|~{3,4})(html|raw)[^\n]*\n[\s\S]*?\n\1/g, " ")
2012
+ )
2013
+ .join("\n");
2014
+ const seen = new Set(
2015
+ dashboards.map((d) =>
2016
+ d.local ? `local:${d.project}` : `space:${spaceIdFromUrl(d.url)}`
2017
+ )
2018
+ );
2019
+ const remoteSpaces = new Map();
2020
+ extractUrls(scanText).forEach((url) => {
2021
+ const item = classifyResource(url);
2022
+ if (item && item.kind === "space" && !item.local) {
2023
+ remoteSpaces.set(item.url, item);
2024
+ }
2025
+ });
2026
+ remoteSpaces.forEach((s) => {
2027
+ const key = `space:${s.id}`;
2028
+ if (seen.has(key)) return;
2029
+ getJSON(`https://huggingface.co/api/spaces/${s.id}`)
2030
+ .then((d) => {
2031
+ if (STATS_TOKEN !== token) return;
2032
+ const tags = (d && d.tags) || [];
2033
+ if (
2034
+ !seen.has(key) &&
2035
+ tags.some((t) => String(t).toLowerCase() === "trackio")
2036
+ ) {
2037
+ seen.add(key);
2038
+ dashboards.push({
2039
+ project: s.id,
2040
+ local: false,
2041
+ url: s.url,
2042
+ resUrl: s.url,
2043
+ });
2044
+ dashboards.sort((a, b) => a.project.localeCompare(b.project));
2045
+ dash.render(dashboards);
2046
+ }
2047
+ })
2048
+ .catch(() => {});
2049
+ });
2050
+ return el;
2051
+ }
2052
+
2053
+ function buildAgentHint() {
2054
+ const onSpaces =
2055
+ /\.hf\.space$/.test(location.hostname) ||
2056
+ /(^|\.)huggingface\.co$/.test(location.hostname);
2057
+ let source = "";
2058
+ if (onSpaces && MANIFEST.space_id) {
2059
+ source = ` ${MANIFEST.space_id}`;
2060
+ } else if (/^https?:$/.test(location.protocol)) {
2061
+ source = ` ${location.origin}/`;
2062
+ }
2063
+ const command = `trackio logbook read${source}`;
2064
+ const tokens = MANIFEST.agent_view_tokens;
2065
+ const div = document.createElement("div");
2066
+ div.className = "agent-hint";
2067
+ const label = document.createElement("span");
2068
+ label.className = "agent-hint-label";
2069
+ label.textContent = "Read from the CLI:";
2070
+ const code = document.createElement("code");
2071
+ code.textContent = command;
2072
+ const copy = document.createElement("button");
2073
+ copy.className = "copy";
2074
+ copy.type = "button";
2075
+ copy.title = "Copy";
2076
+ copy.textContent = "⧉";
2077
+ copy.addEventListener("click", () => copyText(command, copy, "⧉"));
2078
+ const note = document.createElement("span");
2079
+ note.className = "agent-hint-note";
2080
+ note.textContent =
2081
+ "compact view for agents" + (tokens ? ` · ~${fmt(tokens)} tokens` : "");
2082
+ div.appendChild(label);
2083
+ div.appendChild(code);
2084
+ div.appendChild(copy);
2085
+ div.appendChild(note);
2086
+ return div;
2087
+ }
2088
+
2089
+ function currentSlug() {
2090
+ const slug = (location.hash || "").replace(/^#\//, "") || MANIFEST.root.slug;
2091
+ return findNode(MANIFEST.root, slug) ? slug : MANIFEST.root.slug;
2092
+ }
2093
+
2094
+ function scrollToHash(opts = {}) {
2095
+ const slug = currentSlug();
2096
+ if (!location.hash) {
2097
+ window.scrollTo({ top: 0, behavior: opts.behavior || "auto" });
2098
+ highlight(slug);
2099
+ return;
2100
+ }
2101
+ const section = document.getElementById("/" + slug);
2102
+ if (section) section.scrollIntoView({ behavior: opts.behavior || "smooth" });
2103
+ highlight(slug);
2104
+ }
2105
+
2106
+ function navigateToLogbookSlug(target) {
2107
+ const slug = String(target || "").replace(/^#?\//, "").trim();
2108
+ if (!slug || !findNode(MANIFEST.root, slug)) return;
2109
+ const hash = "#/" + slug;
2110
+ if (location.hash === hash) {
2111
+ scrollToHash({ behavior: "smooth" });
2112
+ } else {
2113
+ location.hash = hash;
2114
+ }
2115
+ }
2116
+
2117
+ function setupFigureNavigation() {
2118
+ window.addEventListener("message", (event) => {
2119
+ const data = event.data;
2120
+ if (!data || data.type !== "trackio-logbook:navigate") return;
2121
+ // Only accept messages from one of this logbook's sandboxed figure
2122
+ // iframes, rather than from an arbitrary same-origin page.
2123
+ const isFigureFrame = Array.from(
2124
+ document.querySelectorAll("iframe.figure-frame")
2125
+ ).some((frame) => frame.contentWindow === event.source);
2126
+ if (!isFigureFrame) return;
2127
+ navigateToLogbookSlug(data.target);
2128
+ });
2129
+ }
2130
+
2131
+ let SCROLL_FRAME = 0;
2132
+ function updateActiveSection() {
2133
+ cancelAnimationFrame(SCROLL_FRAME);
2134
+ SCROLL_FRAME = requestAnimationFrame(() => {
2135
+ const sections = Array.from(document.querySelectorAll(".page-section"));
2136
+ if (!sections.length) return;
2137
+ const marker = Math.min(window.innerHeight * 0.28, 180);
2138
+ let active = sections[0];
2139
+ sections.forEach((section) => {
2140
+ if (section.getBoundingClientRect().top <= marker) active = section;
2141
+ });
2142
+ if (
2143
+ window.innerHeight + window.scrollY >=
2144
+ document.documentElement.scrollHeight - 2
2145
+ ) {
2146
+ active = sections[sections.length - 1];
2147
+ }
2148
+ highlight(active.dataset.slug);
2149
+ });
2150
+ }
2151
+
2152
+ function startLiveReload() {
2153
+ if (!isLocalPreview()) return;
2154
+ setInterval(async () => {
2155
+ try {
2156
+ const next = await fetchManifest();
2157
+ if (!next || next.revision === MANIFEST.revision) return;
2158
+ MANIFEST = next;
2159
+ clearPageCache();
2160
+ document.title = MANIFEST.title + " · Trackio Logbook";
2161
+ document.getElementById("book-title").textContent = MANIFEST.title;
2162
+ document.getElementById("book-head").setAttribute("aria-label", MANIFEST.title);
2163
+ buildTree();
2164
+ renderLogbook({ preserveScroll: true });
2165
+ } catch (e) {}
2166
+ }, LIVE_RELOAD_MS);
2167
+ }
2168
+
2169
+ function setupConnect() {
2170
+ const space = MANIFEST.space_id;
2171
+ if (!space) return;
2172
+ const steps = [
2173
+ { t: "Install Trackio, if you don't have it yet.", c: "uv tool install trackio" },
2174
+ { t: "Add the Trackio skill for your agent, then reload it.", c: "trackio skills add" },
2175
+ { t: "Connect to this logbook.", c: `trackio logbook open ${space}` },
2176
+ ];
2177
+ const ol = document.getElementById("connect-steps");
2178
+ steps.forEach((s, i) => {
2179
+ const li = document.createElement("li");
2180
+ const title = document.createElement("div");
2181
+ title.className = "step-title";
2182
+ title.textContent = `${i + 1}. ${s.t}`;
2183
+ const block = document.createElement("div");
2184
+ block.className = "codeblock";
2185
+ const code = document.createElement("code");
2186
+ code.textContent = s.c;
2187
+ const copy = document.createElement("button");
2188
+ copy.className = "copy";
2189
+ copy.type = "button";
2190
+ copy.title = "Copy";
2191
+ copy.textContent = "⧉";
2192
+ copy.addEventListener("click", () => copyText(s.c, copy, "⧉"));
2193
+ block.appendChild(code);
2194
+ block.appendChild(copy);
2195
+ li.appendChild(title);
2196
+ li.appendChild(block);
2197
+ ol.appendChild(li);
2198
+ });
2199
+
2200
+ const agentPrompt =
2201
+ `Read and help maintain this Trackio experiment logbook ("${MANIFEST.title}").\n\n` +
2202
+ "1. If you don't have Trackio, install it: uv tool install trackio\n" +
2203
+ "2. Add the Trackio skill for your agent: trackio skills add (then reload)\n" +
2204
+ `3. Connect to this logbook: trackio logbook open ${space}\n\n` +
2205
+ "Start with `trackio logbook read`; use `trackio logbook read page \"...\"` " +
2206
+ "for a page-level view, then fetch relevant details with " +
2207
+ "`trackio logbook read cell cell_<id>`. If I've given you " +
2208
+ 'write access to the Space, add findings with `trackio logbook cell markdown "..." ' +
2209
+ '--page "..."` and they will sync back automatically.';
2210
+
2211
+ const foot = document.getElementById("sidebar-foot");
2212
+ foot.hidden = false;
2213
+ const modal = document.getElementById("modal");
2214
+ const open = () => (modal.hidden = false);
2215
+ const close = () => (modal.hidden = true);
2216
+ document.getElementById("connect-btn").addEventListener("click", open);
2217
+ document.getElementById("modal-close").addEventListener("click", close);
2218
+ modal.querySelector(".modal-backdrop").addEventListener("click", close);
2219
+ document.addEventListener("keydown", (e) => {
2220
+ if (e.key === "Escape") close();
2221
+ });
2222
+ const agentBtn = document.getElementById("copy-agent");
2223
+ agentBtn.addEventListener("click", () =>
2224
+ copyText(agentPrompt, agentBtn, "Copy for agent")
2225
+ );
2226
+ }
2227
+
2228
+ function copyText(text, btn, restore) {
2229
+ const done = () => {
2230
+ const prev = btn.textContent;
2231
+ btn.textContent = restore === "⧉" ? "✓" : "Copied!";
2232
+ btn.classList.add("copied");
2233
+ setTimeout(() => {
2234
+ btn.textContent = restore;
2235
+ btn.classList.remove("copied");
2236
+ }, 1400);
2237
+ void prev;
2238
+ };
2239
+ if (navigator.clipboard && navigator.clipboard.writeText) {
2240
+ navigator.clipboard.writeText(text).then(done, done);
2241
+ } else {
2242
+ const ta = document.createElement("textarea");
2243
+ ta.value = text;
2244
+ document.body.appendChild(ta);
2245
+ ta.select();
2246
+ try {
2247
+ document.execCommand("copy");
2248
+ } catch (e) {}
2249
+ document.body.removeChild(ta);
2250
+ done();
2251
+ }
2252
+ }
2253
+
2254
+ async function init() {
2255
+ MANIFEST = await fetchManifest();
2256
+ document.title = MANIFEST.title + " · Trackio Logbook";
2257
+ document.getElementById("book-title").textContent = MANIFEST.title;
2258
+ document.getElementById("book-head").setAttribute("aria-label", MANIFEST.title);
2259
+ document.getElementById("book-head").addEventListener("click", () => {
2260
+ const target = "#/" + MANIFEST.root.slug;
2261
+ if (location.hash === target) scrollToHash();
2262
+ else location.hash = target;
2263
+ });
2264
+ buildTree();
2265
+ setupConnect();
2266
+ setupResourceHover();
2267
+ setupFigureNavigation();
2268
+ window.addEventListener("hashchange", () => scrollToHash());
2269
+ window.addEventListener("scroll", updateActiveSection, { passive: true });
2270
+ await renderLogbook();
2271
+ startLiveReload();
2272
+ }
2273
+
2274
+ init();
2275
+ })();
logbook.json ADDED
@@ -0,0 +1,61 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "schema_version": 1,
3
+ "title": "Repro - The Optimal Sample Complexity of Linear Contracts",
4
+ "emoji": "🎯",
5
+ "space_id": "DineshAI/ry5HitnXzc",
6
+ "paper": {
7
+ "openreview_id": "ry5HitnXzc",
8
+ "arxiv_id": "2601.01496",
9
+ "title": "The Optimal Sample Complexity of Linear Contracts"
10
+ },
11
+ "tags": [
12
+ "icml2026-repro",
13
+ "paper-ry5HitnXzc"
14
+ ],
15
+ "updated_at": "2026-07-17T16:43:25+00:00",
16
+ "root": {
17
+ "slug": "index",
18
+ "title": "Repro - The Optimal Sample Complexity of Linear Contracts",
19
+ "file": "pages/index.md",
20
+ "children": [
21
+ {
22
+ "slug": "overview",
23
+ "title": "Overview",
24
+ "file": "pages/overview/page.md",
25
+ "children": []
26
+ },
27
+ {
28
+ "slug": "claim-1",
29
+ "title": "Claim 1",
30
+ "file": "pages/claim-1/page.md",
31
+ "children": []
32
+ },
33
+ {
34
+ "slug": "claim-2",
35
+ "title": "Claim 2",
36
+ "file": "pages/claim-2/page.md",
37
+ "children": []
38
+ },
39
+ {
40
+ "slug": "methods",
41
+ "title": "Methods",
42
+ "file": "pages/methods/page.md",
43
+ "children": []
44
+ },
45
+ {
46
+ "slug": "negative-controls",
47
+ "title": "Negative controls",
48
+ "file": "pages/negative-controls/page.md",
49
+ "children": []
50
+ },
51
+ {
52
+ "slug": "conclusion",
53
+ "title": "Conclusion",
54
+ "file": "pages/conclusion/page.md",
55
+ "children": []
56
+ }
57
+ ]
58
+ },
59
+ "agent_view_tokens": 1830,
60
+ "revision": "1784306605130028180"
61
+ }
pages/claim-1/page.md ADDED
@@ -0,0 +1,450 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Claim 1
2
+
3
+
4
+ ---
5
+ <!-- trackio-cell
6
+ {"type": "markdown", "id": "cell_bc4b47d78769", "created_at": "2026-07-17T05:27:33+00:00", "title": "Uniform-convergence certificate"}
7
+ -->
8
+ ## Theorem 1.1 at its stated sample bound
9
+
10
+ For epsilon=0.1 and delta=0.05, the paper bound is s=1,514,429. The binary i.i.d. model has exactly s+1 sufficient statistics, all represented by the exact binomial tail calculation. Across 3, 16, 128, and 1,024 actions, expected reward is monotone over every action switch and the largest failure log probability is below base-10 exponent -18,528.87.
11
+
12
+
13
+ ---
14
+ <!-- trackio-cell
15
+ {"type": "code", "id": "cell_bb08528907fb", "created_at": "2026-07-17T05:27:48+00:00", "title": "Full-bound exact certificate", "command": ["python", "repro/src/run_contracts.py", "--config", "repro/configs/full.json", "--output-dir", "outputs"], "exit_code": 0, "duration_s": 2.709}
16
+ -->
17
+ ````bash
18
+ $ python repro/src/run_contracts.py --config repro/configs/full.json --output-dir outputs
19
+ ````
20
+
21
+ exit 0 · 2.7s
22
+
23
+
24
+ ````python title=run_contracts.py
25
+ #!/usr/bin/env python3
26
+ """Exact finite-support certificates for arXiv:2601.01496 / ry5HitnXzc.
27
+
28
+ The paper's high-probability statements are universal theorems. This program
29
+ does not purport to prove them empirically. Instead it evaluates the stated
30
+ sample sizes exactly on a nontrivial two-type contract model. A binary i.i.d.
31
+ sample is fully characterized by its type-A count, so all s + 1 sample
32
+ outcomes are accounted for with binomial tail identities; the EUM result also
33
+ enumerates every count and runs the prescribed epsilon/4 grid.
34
+ """
35
+
36
+ from __future__ import annotations
37
+
38
+ import argparse
39
+ import csv
40
+ import json
41
+ import math
42
+ from functools import lru_cache
43
+ from dataclasses import dataclass
44
+ from pathlib import Path
45
+
46
+ import numpy as np
47
+ from scipy.stats import binom
48
+ from scipy.special import logsumexp
49
+
50
+ ROOT = Path(__file__).resolve().parents[2]
51
+
52
+
53
+ @dataclass(frozen=True)
54
+ class AgentType:
55
+ """Finite-agent type represented by expected reward and action cost."""
56
+
57
+ reward: np.ndarray
58
+ cost: np.ndarray
59
+
60
+
61
+ def make_types(action_count: int) -> tuple[AgentType, AgentType]:
62
+ """Paper-faithful finite types with principal-favoring tie breaking.
63
+
64
+ There are two outcomes with reward vector (0, 1). Action i produces the
65
+ positive outcome with probability reward[i]. Type A always selects its
66
+ productive action. Type B switches 0 -> 1/2 -> 1 at alpha=0.4 and 0.8.
67
+ Additional actions are strictly dominated; varying their count checks the
68
+ paper's action-count-independent sample bound without changing the model.
69
+ """
70
+ if action_count < 3:
71
+ raise ValueError("need outside option plus two productive actions")
72
+ reward_a = np.zeros(action_count)
73
+ cost_a = np.ones(action_count)
74
+ reward_b = np.zeros(action_count)
75
+ cost_b = np.ones(action_count)
76
+
77
+ # Outside option: zero reward, zero cost.
78
+ cost_a[0] = cost_b[0] = 0.0
79
+ # Type A: high-reward action is available at zero cost.
80
+ reward_a[1], cost_a[1] = 1.0, 0.0
81
+ # Type B: the two productive actions induce the stated breakpoints.
82
+ reward_b[1], cost_b[1] = 0.5, 0.2
83
+ reward_b[2], cost_b[2] = 1.0, 0.6
84
+ return AgentType(reward_a, cost_a), AgentType(reward_b, cost_b)
85
+
86
+
87
+ def chosen_action(agent: AgentType, alpha: float) -> int:
88
+ """Agent maximization with the paper's principal-favoring tie convention."""
89
+ agent_utility = alpha * agent.reward - agent.cost
90
+ maximizers = np.flatnonzero(np.isclose(agent_utility, agent_utility.max(), atol=1e-12))
91
+ principal_utility = (1.0 - alpha) * agent.reward[maximizers]
92
+ return int(maximizers[np.argmax(principal_utility)])
93
+
94
+
95
+ def principal_utility(agent: AgentType, alpha: float) -> float:
96
+ return float((1.0 - alpha) * agent.reward[chosen_action(agent, alpha)])
97
+
98
+
99
+ def selected_reward(agent: AgentType, alpha: float) -> float:
100
+ return float(agent.reward[chosen_action(agent, alpha)])
101
+
102
+
103
+ def breakpoints(agent: AgentType) -> set[float]:
104
+ points = {0.0, 1.0}
105
+ for i in range(len(agent.reward)):
106
+ for j in range(i):
107
+ denominator = agent.reward[i] - agent.reward[j]
108
+ if abs(denominator) < 1e-14:
109
+ continue
110
+ alpha = (agent.cost[i] - agent.cost[j]) / denominator
111
+ if -1e-12 <= alpha <= 1.0 + 1e-12:
112
+ points.add(float(min(1.0, max(0.0, alpha))))
113
+ return points
114
+
115
+
116
+ def evaluation_points(*agents: AgentType) -> np.ndarray:
117
+ """Both sides of every action switch, sufficient for piecewise-linear u_p."""
118
+ raw = set().union(*(breakpoints(agent) for agent in agents))
119
+ points = set(raw)
120
+ for alpha in raw:
121
+ if alpha > 0.0:
122
+ points.add(float(np.nextafter(alpha, 0.0)))
123
+ return np.array(sorted(points), dtype=float)
124
+
125
+
126
+ def utilities(agent: AgentType, alphas: np.ndarray) -> np.ndarray:
127
+ return np.array([principal_utility(agent, float(alpha)) for alpha in alphas])
128
+
129
+
130
+ def rewards(agent: AgentType, alphas: np.ndarray) -> np.ndarray:
131
+ return np.array([selected_reward(agent, float(alpha)) for alpha in alphas])
132
+
133
+
134
+ def direct_profile(agent_a: AgentType, agent_b: AgentType) -> dict[str, object]:
135
+ points = evaluation_points(agent_a, agent_b)
136
+ utility_a, utility_b = utilities(agent_a, points), utilities(agent_b, points)
137
+ reward_a, reward_b = rewards(agent_a, points), rewards(agent_b, points)
138
+ return {
139
+ "points": points,
140
+ "utility_a": utility_a,
141
+ "utility_b": utility_b,
142
+ "reward_a": reward_a,
143
+ "reward_b": reward_b,
144
+ "max_type_difference": float(np.max(np.abs(utility_a - utility_b))),
145
+ "reward_monotone_a": bool(np.all(np.diff(reward_a) >= -1e-12)),
146
+ "reward_monotone_b": bool(np.all(np.diff(reward_b) >= -1e-12)),
147
+ }
148
+
149
+
150
+ def theorem_samples(constant: int, epsilon: float, delta: float) -> int:
151
+ return int(math.ceil(constant * math.log(4.0 / delta) / (epsilon * epsilon)))
152
+
153
+
154
+ def logdiffexp(log_x: float, log_y: float) -> float:
155
+ """log(exp(log_x) - exp(log_y)) for log_x >= log_y."""
156
+ if math.isinf(log_y) and log_y < 0:
157
+ return log_x
158
+ if log_y >= log_x:
159
+ return -math.inf
160
+ return log_x + math.log1p(-math.exp(log_y - log_x))
161
+
162
+
163
+ @lru_cache(maxsize=None)
164
+ def log_interval_probability(n: int, probability: float, low: int, high: int) -> float:
165
+ """Stable exact binomial mass over inclusive integer interval [low, high]."""
166
+ low, high = max(0, low), min(n, high)
167
+ if low > high:
168
+ return -math.inf
169
+ if low > n * probability:
170
+ value = logdiffexp(float(binom.logsf(low - 1, n, probability)), float(binom.logsf(high, n, probability)))
171
+ else:
172
+ log_high = float(binom.logcdf(high, n, probability))
173
+ log_before = -math.inf if low == 0 else float(binom.logcdf(low - 1, n, probability))
174
+ value = logdiffexp(log_high, log_before)
175
+ if math.isfinite(value):
176
+ return value
177
+ # scipy's survival/CDF interface deliberately saturates for astronomically
178
+ # small tails. Sum the exact log-PMF terms instead, keeping the reported
179
+ # probability auditable even at the paper's multi-million-sample bound.
180
+ counts = np.arange(low, high + 1, dtype=np.int64)
181
+ return float(logsumexp(binom.logpmf(counts, n, probability)))
182
+
183
+
184
+ def logsum(values: list[float]) -> float:
185
+ result = -math.inf
186
+ for value in values:
187
+ result = float(np.logaddexp(result, value))
188
+ return result
189
+
190
+
191
+ def as_probability(log_probability: float) -> float:
192
+ return 0.0 if log_probability < math.log(np.finfo(float).tiny) else float(math.exp(log_probability))
193
+
194
+
195
+ def exact_uniform_failure(n: int, p_type_a: float, epsilon: float, max_difference: float) -> dict[str, float | int]:
196
+ """Exact probability of sup_alpha |u(S,alpha)-u(D,alpha)| > epsilon."""
197
+ tolerance = epsilon / max_difference
198
+ logs: list[float] = []
199
+ lower_max = math.ceil(n * (p_type_a - tolerance)) - 1
200
+ upper_min = math.floor(n * (p_type_a + tolerance)) + 1
201
+ if lower_max >= 0:
202
+ logs.append(log_interval_probability(n, p_type_a, 0, lower_max))
203
+ if upper_min <= n:
204
+ logs.append(log_interval_probability(n, p_type_a, upper_min, n))
205
+ log_failure = logsum(logs)
206
+ return {
207
+ "lower_max_count": lower_max,
208
+ "upper_min_count": upper_min,
209
+ "log_failure_probability": log_failure,
210
+ "log10_failure_probability": log_failure / math.log(10.0),
211
+ "failure_probability": as_probability(log_failure),
212
+ }
213
+
214
+
215
+ def eum_grid(epsilon: float) -> np.ndarray:
216
+ step = epsilon / 4.0
217
+ values = np.arange(math.floor(4.0 / epsilon) + 1, dtype=float) * step
218
+ return np.unique(np.append(values, 1.0))
219
+
220
+
221
+ def mask_ranges(mask: np.ndarray, offset: int, previous: list[tuple[int, int]]) -> list[tuple[int, int]]:
222
+ transitions = np.where(np.diff(np.r_[False, mask, False].astype(int)) != 0)[0]
223
+ for begin, end in transitions.reshape(-1, 2):
224
+ low, high = offset + int(begin), offset + int(end) - 1
225
+ if previous and low == previous[-1][1] + 1:
226
+ previous[-1] = (previous[-1][0], high)
227
+ else:
228
+ previous.append((low, high))
229
+ return previous
230
+
231
+
232
+ def exact_eum_failure(
233
+ n: int,
234
+ p_type_a: float,
235
+ epsilon: float,
236
+ agent_a: AgentType,
237
+ agent_b: AgentType,
238
+ chunk_size: int,
239
+ ) -> dict[str, object]:
240
+ """Enumerate every binomial count and execute Algorithm 1's exact grid."""
241
+ grid = eum_grid(epsilon)
242
+ utility_a_grid, utility_b_grid = utilities(agent_a, grid), utilities(agent_b, grid)
243
+ profile = direct_profile(agent_a, agent_b)
244
+ population_values = p_type_a * profile["utility_a"] + (1.0 - p_type_a) * profile["utility_b"]
245
+ population_optimum = float(np.max(population_values))
246
+ population_grid = p_type_a * utility_a_grid + (1.0 - p_type_a) * utility_b_grid
247
+ ranges: list[tuple[int, int]] = []
248
+ for start in range(0, n + 1, chunk_size):
249
+ counts = np.arange(start, min(n + 1, start + chunk_size), dtype=float)
250
+ frequencies = counts / n
251
+ empirical = frequencies[:, None] * utility_a_grid + (1.0 - frequencies[:, None]) * utility_b_grid
252
+ selected = np.argmax(empirical, axis=1)
253
+ failure = population_grid[selected] < population_optimum - epsilon - 1e-12
254
+ mask_ranges(failure, start, ranges)
255
+ log_failure = logsum([log_interval_probability(n, p_type_a, low, high) for low, high in ranges])
256
+ return {
257
+ "grid_size": int(len(grid)),
258
+ "oracle_queries": int(len(grid)),
259
+ "population_optimum": population_optimum,
260
+ "failure_ranges": ranges,
261
+ "sufficient_statistics_enumerated": n + 1,
262
+ "log_failure_probability": log_failure,
263
+ "log10_failure_probability": log_failure / math.log(10.0),
264
+ "failure_probability": as_probability(log_failure),
265
+ }
266
+
267
+
268
+ def run(config: Path, output_dir: Path) -> dict[str, object]:
269
+ cfg = json.loads(config.read_text())
270
+ epsilon, delta, p = cfg["epsilon"], cfg["delta"], cfg["type_a_probability"]
271
+ output_dir.mkdir(parents=True, exist_ok=True)
272
+ uniform_n = theorem_samples(3456, epsilon, delta)
273
+ eum_n = theorem_samples(6912, epsilon, delta)
274
+
275
+ uniform_rows = []
276
+ profiles: dict[int, tuple[AgentType, AgentType, dict[str, object]]] = {}
277
+ for action_count in cfg["action_counts"]:
278
+ agent_a, agent_b = make_types(action_count)
279
+ profile = direct_profile(agent_a, agent_b)
280
+ profiles[action_count] = (agent_a, agent_b, profile)
281
+ exact = exact_uniform_failure(uniform_n, p, epsilon, float(profile["max_type_difference"]))
282
+ uniform_rows.append({
283
+ "action_count": action_count,
284
+ "sample_count": uniform_n,
285
+ "sufficient_statistics": uniform_n + 1,
286
+ "max_type_difference": profile["max_type_difference"],
287
+ "reward_monotone_a": profile["reward_monotone_a"],
288
+ "reward_monotone_b": profile["reward_monotone_b"],
289
+ **exact,
290
+ })
291
+
292
+ largest = max(cfg["action_counts"])
293
+ agent_a, agent_b, profile = profiles[largest]
294
+ eum = exact_eum_failure(eum_n, p, epsilon, agent_a, agent_b, cfg["eum_chunk_size"])
295
+ eum_row = {
296
+ "action_count": largest,
297
+ "sample_count": eum_n,
298
+ "epsilon": epsilon,
299
+ "delta": delta,
300
+ **eum,
301
+ }
302
+
303
+ dmax = float(profile["max_type_difference"])
304
+ correlated_error_a, correlated_error_b = (1.0 - p) * dmax, p * dmax
305
+ # Under the negative control all draws share one latent type, so no concentration occurs.
306
+ correlated_uniform_failure = float(
307
+ p * (correlated_error_a > epsilon) + (1.0 - p) * (correlated_error_b > epsilon)
308
+ )
309
+ grid = eum_grid(epsilon)
310
+ pop_values = p * utilities(agent_a, profile["points"]) + (1.0 - p) * utilities(agent_b, profile["points"])
311
+ optimum = float(np.max(pop_values))
312
+ all_a_choice = int(np.argmax(utilities(agent_a, grid)))
313
+ all_b_choice = int(np.argmax(utilities(agent_b, grid)))
314
+ pop_grid = p * utilities(agent_a, grid) + (1.0 - p) * utilities(agent_b, grid)
315
+ correlated_eum_failure = float(
316
+ p * (pop_grid[all_a_choice] < optimum - epsilon) + (1.0 - p) * (pop_grid[all_b_choice] < optimum - epsilon)
317
+ )
318
+ negative_row = {
319
+ "sample_count": eum_n,
320
+ "type_a_shared_sample_error": correlated_error_a,
321
+ "type_b_shared_sample_error": correlated_error_b,
322
+ "uniform_failure_probability": correlated_uniform_failure,
323
+ "eum_failure_probability": correlated_eum_failure,
324
+ "assumption_rejected": "i.i.d. sampling",
325
+ }
326
+
327
+ with (output_dir / "uniform_convergence.csv").open("w", newline="") as handle:
328
+ writer = csv.DictWriter(handle, fieldnames=uniform_rows[0].keys(), lineterminator="\n")
329
+ writer.writeheader()
330
+ writer.writerows(uniform_rows)
331
+ with (output_dir / "eum.csv").open("w", newline="") as handle:
332
+ writer = csv.DictWriter(handle, fieldnames=eum_row.keys(), lineterminator="\n")
333
+ writer.writeheader()
334
+ writer.writerow(eum_row)
335
+ with (output_dir / "negative_control.csv").open("w", newline="") as handle:
336
+ writer = csv.DictWriter(handle, fieldnames=negative_row.keys(), lineterminator="\n")
337
+ writer.writeheader()
338
+ writer.writerow(negative_row)
339
+
340
+ summary = {
341
+ "paper": "ry5HitnXzc",
342
+ "arxiv": "2601.01496",
343
+ "claim1_uniform_convergence": {
344
+ "paper_sample_bound": uniform_n,
345
+ "action_counts": cfg["action_counts"],
346
+ "sufficient_statistics_per_configuration": uniform_n + 1,
347
+ "max_exact_failure_probability": max(row["failure_probability"] for row in uniform_rows),
348
+ "max_log10_failure_probability": max(row["log10_failure_probability"] for row in uniform_rows),
349
+ "all_reward_sequences_monotone": all(row["reward_monotone_a"] and row["reward_monotone_b"] for row in uniform_rows),
350
+ },
351
+ "claim2_eum": {
352
+ "paper_sample_bound": eum_n,
353
+ "epsilon_over_4_grid_size": eum["grid_size"],
354
+ "oracle_queries": eum["oracle_queries"],
355
+ "sufficient_statistics_enumerated": eum["sufficient_statistics_enumerated"],
356
+ "exact_failure_probability": eum["failure_probability"],
357
+ "log10_failure_probability": eum["log10_failure_probability"],
358
+ },
359
+ "negative_control": negative_row,
360
+ }
361
+ (output_dir / "summary.json").write_text(json.dumps(summary, indent=2) + "\n")
362
+ print(json.dumps(summary, indent=2))
363
+ return summary
364
+
365
+
366
+ if __name__ == "__main__":
367
+ parser = argparse.ArgumentParser()
368
+ parser.add_argument("--config", type=Path, default=ROOT / "repro/configs/full.json")
369
+ parser.add_argument("--output-dir", type=Path, default=ROOT / "outputs")
370
+ args = parser.parse_args()
371
+ run(args.config, args.output_dir)
372
+
373
+ ````
374
+
375
+
376
+ ````json title=full.json
377
+ {
378
+ "epsilon": 0.1,
379
+ "delta": 0.05,
380
+ "type_a_probability": 0.2,
381
+ "action_counts": [3, 16, 128, 1024],
382
+ "eum_chunk_size": 25000
383
+ }
384
+
385
+ ````
386
+
387
+
388
+ ````output
389
+ {
390
+ "paper": "ry5HitnXzc",
391
+ "arxiv": "2601.01496",
392
+ "claim1_uniform_convergence": {
393
+ "paper_sample_bound": 1514429,
394
+ "action_counts": [
395
+ 3,
396
+ 16,
397
+ 128,
398
+ 1024
399
+ ],
400
+ "sufficient_statistics_per_configuration": 1514430,
401
+ "max_exact_failure_probability": 0.0,
402
+ "max_log10_failure_probability": -18528.872762083196,
403
+ "all_reward_sequences_monotone": true
404
+ },
405
+ "claim2_eum": {
406
+ "paper_sample_bound": 3028857,
407
+ "epsilon_over_4_grid_size": 41,
408
+ "oracle_queries": 41,
409
+ "sufficient_statistics_enumerated": 3028858,
410
+ "exact_failure_probability": 0.0,
411
+ "log10_failure_probability": -176744.7469399194
412
+ },
413
+ "negative_control": {
414
+ "sample_count": 3028857,
415
+ "type_a_shared_sample_error": 0.8,
416
+ "type_b_shared_sample_error": 0.2,
417
+ "uniform_failure_probability": 1.0,
418
+ "eum_failure_probability": 0.2,
419
+ "assumption_rejected": "i.i.d. sampling"
420
+ }
421
+ }
422
+
423
+ ````
424
+
425
+
426
+ ---
427
+ <!-- trackio-cell
428
+ {"type": "artifact", "id": "cell_065b371a4118", "created_at": "2026-07-17T05:27:48+00:00", "title": "Artifact: uniform_convergence.csv", "path": "outputs/uniform_convergence.csv", "size": 568, "artifact_type": "dataset", "auto": true}
429
+ -->
430
+ **📦 Artifact** `outputs/uniform_convergence.csv` · dataset · 568 B
431
+
432
+ trackio-local-path://outputs/uniform_convergence.csv
433
+
434
+
435
+ ---
436
+ <!-- trackio-cell
437
+ {"type": "artifact", "id": "cell_805b09cf91b1", "created_at": "2026-07-17T05:27:48+00:00", "title": "Artifact: eum.csv", "path": "outputs/eum.csv", "size": 323, "artifact_type": "dataset", "auto": true}
438
+ -->
439
+ **📦 Artifact** `outputs/eum.csv` · dataset · 323 B
440
+
441
+ trackio-local-path://outputs/eum.csv
442
+
443
+
444
+ ---
445
+ <!-- trackio-cell
446
+ {"type": "artifact", "id": "cell_ff9d346d96a1", "created_at": "2026-07-17T05:27:48+00:00", "title": "Artifact: negative_control.csv", "path": "outputs/negative_control.csv", "size": 179, "artifact_type": "dataset", "auto": true}
447
+ -->
448
+ **📦 Artifact** `outputs/negative_control.csv` · dataset · 179 B
449
+
450
+ trackio-local-path://outputs/negative_control.csv
pages/claim-2/page.md ADDED
@@ -0,0 +1,450 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Claim 2
2
+
3
+
4
+ ---
5
+ <!-- trackio-cell
6
+ {"type": "markdown", "id": "cell_205515aaa598", "created_at": "2026-07-17T05:27:34+00:00", "title": "EUM certificate"}
7
+ -->
8
+ ## Corollary 1.2 and Algorithm 1
9
+
10
+ For the same epsilon and delta, the paper bound is s=3,028,857. The evaluator streams every count K=0 through s, runs the exact epsilon/4 grid of 41 unique contracts, and tests the population utility of the selected contract. The exact failure log probability is below base-10 exponent -176,744.75.
11
+
12
+
13
+ ---
14
+ <!-- trackio-cell
15
+ {"type": "code", "id": "cell_e69cca81ee90", "created_at": "2026-07-17T05:27:56+00:00", "title": "Full-bound Algorithm 1 certificate", "command": ["python", "repro/src/run_contracts.py", "--config", "repro/configs/full.json", "--output-dir", "outputs"], "exit_code": 0, "duration_s": 2.914}
16
+ -->
17
+ ````bash
18
+ $ python repro/src/run_contracts.py --config repro/configs/full.json --output-dir outputs
19
+ ````
20
+
21
+ exit 0 · 2.9s
22
+
23
+
24
+ ````python title=run_contracts.py
25
+ #!/usr/bin/env python3
26
+ """Exact finite-support certificates for arXiv:2601.01496 / ry5HitnXzc.
27
+
28
+ The paper's high-probability statements are universal theorems. This program
29
+ does not purport to prove them empirically. Instead it evaluates the stated
30
+ sample sizes exactly on a nontrivial two-type contract model. A binary i.i.d.
31
+ sample is fully characterized by its type-A count, so all s + 1 sample
32
+ outcomes are accounted for with binomial tail identities; the EUM result also
33
+ enumerates every count and runs the prescribed epsilon/4 grid.
34
+ """
35
+
36
+ from __future__ import annotations
37
+
38
+ import argparse
39
+ import csv
40
+ import json
41
+ import math
42
+ from functools import lru_cache
43
+ from dataclasses import dataclass
44
+ from pathlib import Path
45
+
46
+ import numpy as np
47
+ from scipy.stats import binom
48
+ from scipy.special import logsumexp
49
+
50
+ ROOT = Path(__file__).resolve().parents[2]
51
+
52
+
53
+ @dataclass(frozen=True)
54
+ class AgentType:
55
+ """Finite-agent type represented by expected reward and action cost."""
56
+
57
+ reward: np.ndarray
58
+ cost: np.ndarray
59
+
60
+
61
+ def make_types(action_count: int) -> tuple[AgentType, AgentType]:
62
+ """Paper-faithful finite types with principal-favoring tie breaking.
63
+
64
+ There are two outcomes with reward vector (0, 1). Action i produces the
65
+ positive outcome with probability reward[i]. Type A always selects its
66
+ productive action. Type B switches 0 -> 1/2 -> 1 at alpha=0.4 and 0.8.
67
+ Additional actions are strictly dominated; varying their count checks the
68
+ paper's action-count-independent sample bound without changing the model.
69
+ """
70
+ if action_count < 3:
71
+ raise ValueError("need outside option plus two productive actions")
72
+ reward_a = np.zeros(action_count)
73
+ cost_a = np.ones(action_count)
74
+ reward_b = np.zeros(action_count)
75
+ cost_b = np.ones(action_count)
76
+
77
+ # Outside option: zero reward, zero cost.
78
+ cost_a[0] = cost_b[0] = 0.0
79
+ # Type A: high-reward action is available at zero cost.
80
+ reward_a[1], cost_a[1] = 1.0, 0.0
81
+ # Type B: the two productive actions induce the stated breakpoints.
82
+ reward_b[1], cost_b[1] = 0.5, 0.2
83
+ reward_b[2], cost_b[2] = 1.0, 0.6
84
+ return AgentType(reward_a, cost_a), AgentType(reward_b, cost_b)
85
+
86
+
87
+ def chosen_action(agent: AgentType, alpha: float) -> int:
88
+ """Agent maximization with the paper's principal-favoring tie convention."""
89
+ agent_utility = alpha * agent.reward - agent.cost
90
+ maximizers = np.flatnonzero(np.isclose(agent_utility, agent_utility.max(), atol=1e-12))
91
+ principal_utility = (1.0 - alpha) * agent.reward[maximizers]
92
+ return int(maximizers[np.argmax(principal_utility)])
93
+
94
+
95
+ def principal_utility(agent: AgentType, alpha: float) -> float:
96
+ return float((1.0 - alpha) * agent.reward[chosen_action(agent, alpha)])
97
+
98
+
99
+ def selected_reward(agent: AgentType, alpha: float) -> float:
100
+ return float(agent.reward[chosen_action(agent, alpha)])
101
+
102
+
103
+ def breakpoints(agent: AgentType) -> set[float]:
104
+ points = {0.0, 1.0}
105
+ for i in range(len(agent.reward)):
106
+ for j in range(i):
107
+ denominator = agent.reward[i] - agent.reward[j]
108
+ if abs(denominator) < 1e-14:
109
+ continue
110
+ alpha = (agent.cost[i] - agent.cost[j]) / denominator
111
+ if -1e-12 <= alpha <= 1.0 + 1e-12:
112
+ points.add(float(min(1.0, max(0.0, alpha))))
113
+ return points
114
+
115
+
116
+ def evaluation_points(*agents: AgentType) -> np.ndarray:
117
+ """Both sides of every action switch, sufficient for piecewise-linear u_p."""
118
+ raw = set().union(*(breakpoints(agent) for agent in agents))
119
+ points = set(raw)
120
+ for alpha in raw:
121
+ if alpha > 0.0:
122
+ points.add(float(np.nextafter(alpha, 0.0)))
123
+ return np.array(sorted(points), dtype=float)
124
+
125
+
126
+ def utilities(agent: AgentType, alphas: np.ndarray) -> np.ndarray:
127
+ return np.array([principal_utility(agent, float(alpha)) for alpha in alphas])
128
+
129
+
130
+ def rewards(agent: AgentType, alphas: np.ndarray) -> np.ndarray:
131
+ return np.array([selected_reward(agent, float(alpha)) for alpha in alphas])
132
+
133
+
134
+ def direct_profile(agent_a: AgentType, agent_b: AgentType) -> dict[str, object]:
135
+ points = evaluation_points(agent_a, agent_b)
136
+ utility_a, utility_b = utilities(agent_a, points), utilities(agent_b, points)
137
+ reward_a, reward_b = rewards(agent_a, points), rewards(agent_b, points)
138
+ return {
139
+ "points": points,
140
+ "utility_a": utility_a,
141
+ "utility_b": utility_b,
142
+ "reward_a": reward_a,
143
+ "reward_b": reward_b,
144
+ "max_type_difference": float(np.max(np.abs(utility_a - utility_b))),
145
+ "reward_monotone_a": bool(np.all(np.diff(reward_a) >= -1e-12)),
146
+ "reward_monotone_b": bool(np.all(np.diff(reward_b) >= -1e-12)),
147
+ }
148
+
149
+
150
+ def theorem_samples(constant: int, epsilon: float, delta: float) -> int:
151
+ return int(math.ceil(constant * math.log(4.0 / delta) / (epsilon * epsilon)))
152
+
153
+
154
+ def logdiffexp(log_x: float, log_y: float) -> float:
155
+ """log(exp(log_x) - exp(log_y)) for log_x >= log_y."""
156
+ if math.isinf(log_y) and log_y < 0:
157
+ return log_x
158
+ if log_y >= log_x:
159
+ return -math.inf
160
+ return log_x + math.log1p(-math.exp(log_y - log_x))
161
+
162
+
163
+ @lru_cache(maxsize=None)
164
+ def log_interval_probability(n: int, probability: float, low: int, high: int) -> float:
165
+ """Stable exact binomial mass over inclusive integer interval [low, high]."""
166
+ low, high = max(0, low), min(n, high)
167
+ if low > high:
168
+ return -math.inf
169
+ if low > n * probability:
170
+ value = logdiffexp(float(binom.logsf(low - 1, n, probability)), float(binom.logsf(high, n, probability)))
171
+ else:
172
+ log_high = float(binom.logcdf(high, n, probability))
173
+ log_before = -math.inf if low == 0 else float(binom.logcdf(low - 1, n, probability))
174
+ value = logdiffexp(log_high, log_before)
175
+ if math.isfinite(value):
176
+ return value
177
+ # scipy's survival/CDF interface deliberately saturates for astronomically
178
+ # small tails. Sum the exact log-PMF terms instead, keeping the reported
179
+ # probability auditable even at the paper's multi-million-sample bound.
180
+ counts = np.arange(low, high + 1, dtype=np.int64)
181
+ return float(logsumexp(binom.logpmf(counts, n, probability)))
182
+
183
+
184
+ def logsum(values: list[float]) -> float:
185
+ result = -math.inf
186
+ for value in values:
187
+ result = float(np.logaddexp(result, value))
188
+ return result
189
+
190
+
191
+ def as_probability(log_probability: float) -> float:
192
+ return 0.0 if log_probability < math.log(np.finfo(float).tiny) else float(math.exp(log_probability))
193
+
194
+
195
+ def exact_uniform_failure(n: int, p_type_a: float, epsilon: float, max_difference: float) -> dict[str, float | int]:
196
+ """Exact probability of sup_alpha |u(S,alpha)-u(D,alpha)| > epsilon."""
197
+ tolerance = epsilon / max_difference
198
+ logs: list[float] = []
199
+ lower_max = math.ceil(n * (p_type_a - tolerance)) - 1
200
+ upper_min = math.floor(n * (p_type_a + tolerance)) + 1
201
+ if lower_max >= 0:
202
+ logs.append(log_interval_probability(n, p_type_a, 0, lower_max))
203
+ if upper_min <= n:
204
+ logs.append(log_interval_probability(n, p_type_a, upper_min, n))
205
+ log_failure = logsum(logs)
206
+ return {
207
+ "lower_max_count": lower_max,
208
+ "upper_min_count": upper_min,
209
+ "log_failure_probability": log_failure,
210
+ "log10_failure_probability": log_failure / math.log(10.0),
211
+ "failure_probability": as_probability(log_failure),
212
+ }
213
+
214
+
215
+ def eum_grid(epsilon: float) -> np.ndarray:
216
+ step = epsilon / 4.0
217
+ values = np.arange(math.floor(4.0 / epsilon) + 1, dtype=float) * step
218
+ return np.unique(np.append(values, 1.0))
219
+
220
+
221
+ def mask_ranges(mask: np.ndarray, offset: int, previous: list[tuple[int, int]]) -> list[tuple[int, int]]:
222
+ transitions = np.where(np.diff(np.r_[False, mask, False].astype(int)) != 0)[0]
223
+ for begin, end in transitions.reshape(-1, 2):
224
+ low, high = offset + int(begin), offset + int(end) - 1
225
+ if previous and low == previous[-1][1] + 1:
226
+ previous[-1] = (previous[-1][0], high)
227
+ else:
228
+ previous.append((low, high))
229
+ return previous
230
+
231
+
232
+ def exact_eum_failure(
233
+ n: int,
234
+ p_type_a: float,
235
+ epsilon: float,
236
+ agent_a: AgentType,
237
+ agent_b: AgentType,
238
+ chunk_size: int,
239
+ ) -> dict[str, object]:
240
+ """Enumerate every binomial count and execute Algorithm 1's exact grid."""
241
+ grid = eum_grid(epsilon)
242
+ utility_a_grid, utility_b_grid = utilities(agent_a, grid), utilities(agent_b, grid)
243
+ profile = direct_profile(agent_a, agent_b)
244
+ population_values = p_type_a * profile["utility_a"] + (1.0 - p_type_a) * profile["utility_b"]
245
+ population_optimum = float(np.max(population_values))
246
+ population_grid = p_type_a * utility_a_grid + (1.0 - p_type_a) * utility_b_grid
247
+ ranges: list[tuple[int, int]] = []
248
+ for start in range(0, n + 1, chunk_size):
249
+ counts = np.arange(start, min(n + 1, start + chunk_size), dtype=float)
250
+ frequencies = counts / n
251
+ empirical = frequencies[:, None] * utility_a_grid + (1.0 - frequencies[:, None]) * utility_b_grid
252
+ selected = np.argmax(empirical, axis=1)
253
+ failure = population_grid[selected] < population_optimum - epsilon - 1e-12
254
+ mask_ranges(failure, start, ranges)
255
+ log_failure = logsum([log_interval_probability(n, p_type_a, low, high) for low, high in ranges])
256
+ return {
257
+ "grid_size": int(len(grid)),
258
+ "oracle_queries": int(len(grid)),
259
+ "population_optimum": population_optimum,
260
+ "failure_ranges": ranges,
261
+ "sufficient_statistics_enumerated": n + 1,
262
+ "log_failure_probability": log_failure,
263
+ "log10_failure_probability": log_failure / math.log(10.0),
264
+ "failure_probability": as_probability(log_failure),
265
+ }
266
+
267
+
268
+ def run(config: Path, output_dir: Path) -> dict[str, object]:
269
+ cfg = json.loads(config.read_text())
270
+ epsilon, delta, p = cfg["epsilon"], cfg["delta"], cfg["type_a_probability"]
271
+ output_dir.mkdir(parents=True, exist_ok=True)
272
+ uniform_n = theorem_samples(3456, epsilon, delta)
273
+ eum_n = theorem_samples(6912, epsilon, delta)
274
+
275
+ uniform_rows = []
276
+ profiles: dict[int, tuple[AgentType, AgentType, dict[str, object]]] = {}
277
+ for action_count in cfg["action_counts"]:
278
+ agent_a, agent_b = make_types(action_count)
279
+ profile = direct_profile(agent_a, agent_b)
280
+ profiles[action_count] = (agent_a, agent_b, profile)
281
+ exact = exact_uniform_failure(uniform_n, p, epsilon, float(profile["max_type_difference"]))
282
+ uniform_rows.append({
283
+ "action_count": action_count,
284
+ "sample_count": uniform_n,
285
+ "sufficient_statistics": uniform_n + 1,
286
+ "max_type_difference": profile["max_type_difference"],
287
+ "reward_monotone_a": profile["reward_monotone_a"],
288
+ "reward_monotone_b": profile["reward_monotone_b"],
289
+ **exact,
290
+ })
291
+
292
+ largest = max(cfg["action_counts"])
293
+ agent_a, agent_b, profile = profiles[largest]
294
+ eum = exact_eum_failure(eum_n, p, epsilon, agent_a, agent_b, cfg["eum_chunk_size"])
295
+ eum_row = {
296
+ "action_count": largest,
297
+ "sample_count": eum_n,
298
+ "epsilon": epsilon,
299
+ "delta": delta,
300
+ **eum,
301
+ }
302
+
303
+ dmax = float(profile["max_type_difference"])
304
+ correlated_error_a, correlated_error_b = (1.0 - p) * dmax, p * dmax
305
+ # Under the negative control all draws share one latent type, so no concentration occurs.
306
+ correlated_uniform_failure = float(
307
+ p * (correlated_error_a > epsilon) + (1.0 - p) * (correlated_error_b > epsilon)
308
+ )
309
+ grid = eum_grid(epsilon)
310
+ pop_values = p * utilities(agent_a, profile["points"]) + (1.0 - p) * utilities(agent_b, profile["points"])
311
+ optimum = float(np.max(pop_values))
312
+ all_a_choice = int(np.argmax(utilities(agent_a, grid)))
313
+ all_b_choice = int(np.argmax(utilities(agent_b, grid)))
314
+ pop_grid = p * utilities(agent_a, grid) + (1.0 - p) * utilities(agent_b, grid)
315
+ correlated_eum_failure = float(
316
+ p * (pop_grid[all_a_choice] < optimum - epsilon) + (1.0 - p) * (pop_grid[all_b_choice] < optimum - epsilon)
317
+ )
318
+ negative_row = {
319
+ "sample_count": eum_n,
320
+ "type_a_shared_sample_error": correlated_error_a,
321
+ "type_b_shared_sample_error": correlated_error_b,
322
+ "uniform_failure_probability": correlated_uniform_failure,
323
+ "eum_failure_probability": correlated_eum_failure,
324
+ "assumption_rejected": "i.i.d. sampling",
325
+ }
326
+
327
+ with (output_dir / "uniform_convergence.csv").open("w", newline="") as handle:
328
+ writer = csv.DictWriter(handle, fieldnames=uniform_rows[0].keys(), lineterminator="\n")
329
+ writer.writeheader()
330
+ writer.writerows(uniform_rows)
331
+ with (output_dir / "eum.csv").open("w", newline="") as handle:
332
+ writer = csv.DictWriter(handle, fieldnames=eum_row.keys(), lineterminator="\n")
333
+ writer.writeheader()
334
+ writer.writerow(eum_row)
335
+ with (output_dir / "negative_control.csv").open("w", newline="") as handle:
336
+ writer = csv.DictWriter(handle, fieldnames=negative_row.keys(), lineterminator="\n")
337
+ writer.writeheader()
338
+ writer.writerow(negative_row)
339
+
340
+ summary = {
341
+ "paper": "ry5HitnXzc",
342
+ "arxiv": "2601.01496",
343
+ "claim1_uniform_convergence": {
344
+ "paper_sample_bound": uniform_n,
345
+ "action_counts": cfg["action_counts"],
346
+ "sufficient_statistics_per_configuration": uniform_n + 1,
347
+ "max_exact_failure_probability": max(row["failure_probability"] for row in uniform_rows),
348
+ "max_log10_failure_probability": max(row["log10_failure_probability"] for row in uniform_rows),
349
+ "all_reward_sequences_monotone": all(row["reward_monotone_a"] and row["reward_monotone_b"] for row in uniform_rows),
350
+ },
351
+ "claim2_eum": {
352
+ "paper_sample_bound": eum_n,
353
+ "epsilon_over_4_grid_size": eum["grid_size"],
354
+ "oracle_queries": eum["oracle_queries"],
355
+ "sufficient_statistics_enumerated": eum["sufficient_statistics_enumerated"],
356
+ "exact_failure_probability": eum["failure_probability"],
357
+ "log10_failure_probability": eum["log10_failure_probability"],
358
+ },
359
+ "negative_control": negative_row,
360
+ }
361
+ (output_dir / "summary.json").write_text(json.dumps(summary, indent=2) + "\n")
362
+ print(json.dumps(summary, indent=2))
363
+ return summary
364
+
365
+
366
+ if __name__ == "__main__":
367
+ parser = argparse.ArgumentParser()
368
+ parser.add_argument("--config", type=Path, default=ROOT / "repro/configs/full.json")
369
+ parser.add_argument("--output-dir", type=Path, default=ROOT / "outputs")
370
+ args = parser.parse_args()
371
+ run(args.config, args.output_dir)
372
+
373
+ ````
374
+
375
+
376
+ ````json title=full.json
377
+ {
378
+ "epsilon": 0.1,
379
+ "delta": 0.05,
380
+ "type_a_probability": 0.2,
381
+ "action_counts": [3, 16, 128, 1024],
382
+ "eum_chunk_size": 25000
383
+ }
384
+
385
+ ````
386
+
387
+
388
+ ````output
389
+ {
390
+ "paper": "ry5HitnXzc",
391
+ "arxiv": "2601.01496",
392
+ "claim1_uniform_convergence": {
393
+ "paper_sample_bound": 1514429,
394
+ "action_counts": [
395
+ 3,
396
+ 16,
397
+ 128,
398
+ 1024
399
+ ],
400
+ "sufficient_statistics_per_configuration": 1514430,
401
+ "max_exact_failure_probability": 0.0,
402
+ "max_log10_failure_probability": -18528.872762083196,
403
+ "all_reward_sequences_monotone": true
404
+ },
405
+ "claim2_eum": {
406
+ "paper_sample_bound": 3028857,
407
+ "epsilon_over_4_grid_size": 41,
408
+ "oracle_queries": 41,
409
+ "sufficient_statistics_enumerated": 3028858,
410
+ "exact_failure_probability": 0.0,
411
+ "log10_failure_probability": -176744.7469399194
412
+ },
413
+ "negative_control": {
414
+ "sample_count": 3028857,
415
+ "type_a_shared_sample_error": 0.8,
416
+ "type_b_shared_sample_error": 0.2,
417
+ "uniform_failure_probability": 1.0,
418
+ "eum_failure_probability": 0.2,
419
+ "assumption_rejected": "i.i.d. sampling"
420
+ }
421
+ }
422
+
423
+ ````
424
+
425
+
426
+ ---
427
+ <!-- trackio-cell
428
+ {"type": "artifact", "id": "cell_44068b110c03", "created_at": "2026-07-17T05:27:56+00:00", "title": "Artifact: uniform_convergence.csv", "path": "outputs/uniform_convergence.csv", "size": 568, "artifact_type": "dataset", "auto": true}
429
+ -->
430
+ **📦 Artifact** `outputs/uniform_convergence.csv` · dataset · 568 B
431
+
432
+ trackio-local-path://outputs/uniform_convergence.csv
433
+
434
+
435
+ ---
436
+ <!-- trackio-cell
437
+ {"type": "artifact", "id": "cell_8221e985e34e", "created_at": "2026-07-17T05:27:56+00:00", "title": "Artifact: eum.csv", "path": "outputs/eum.csv", "size": 323, "artifact_type": "dataset", "auto": true}
438
+ -->
439
+ **📦 Artifact** `outputs/eum.csv` · dataset · 323 B
440
+
441
+ trackio-local-path://outputs/eum.csv
442
+
443
+
444
+ ---
445
+ <!-- trackio-cell
446
+ {"type": "artifact", "id": "cell_3c7c02d5ba0c", "created_at": "2026-07-17T05:27:56+00:00", "title": "Artifact: negative_control.csv", "path": "outputs/negative_control.csv", "size": 179, "artifact_type": "dataset", "auto": true}
447
+ -->
448
+ **📦 Artifact** `outputs/negative_control.csv` · dataset · 179 B
449
+
450
+ trackio-local-path://outputs/negative_control.csv
pages/conclusion/page.md ADDED
@@ -0,0 +1,20 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Conclusion
2
+
3
+
4
+ ---
5
+ <!-- trackio-cell
6
+ {"type": "markdown", "id": "cell_6dd9baac06f7", "created_at": "2026-07-17T05:27:38+00:00", "title": "Executive summary", "pinned": true, "pinned_at": "2026-07-17T05:27:39+00:00"}
7
+ -->
8
+ # Executive summary
9
+
10
+ The stated sample constants and EUM grid behave as claimed in an exact finite contract model at the literal multi-million-sample bounds. The artifact independently checks all type-count outcomes and rejects a correlated-sample control. It does not represent a finite experiment as a proof of the paper distribution-free theorems.
11
+
12
+ ## Scope & cost
13
+
14
+ | Dimension | This reproduction | Full replication |
15
+ | --- | --- | --- |
16
+ | Scope | Exact finite agent/type certificate at paper constants | Distribution-free proof over all agent-type distributions |
17
+ | Hardware | CPU, 4 vCPU | Mathematical proof verification; no training hardware prescribed |
18
+ | Time | Seconds per full certificate | Proof-level review beyond empirical testing |
19
+ | Cost | Local CPU only | Research/proof effort |
20
+ | Outcome | Mechanism, constants, grid, and i.i.d. boundary verified | Not claimed by this artifact |
pages/index.md ADDED
@@ -0,0 +1,12 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Repro - The Optimal Sample Complexity of Linear Contracts
2
+
3
+ ## Pages
4
+
5
+ | Page |
6
+ | --- |
7
+ | [Overview](#/overview) |
8
+ | [Claim 1](#/claim-1) |
9
+ | [Claim 2](#/claim-2) |
10
+ | [Methods](#/methods) |
11
+ | [Negative controls](#/negative-controls) |
12
+ | [Conclusion](#/conclusion) |
pages/methods/page.md ADDED
@@ -0,0 +1,10 @@
 
 
 
 
 
 
 
 
 
 
 
1
+ # Methods
2
+
3
+
4
+ ---
5
+ <!-- trackio-cell
6
+ {"type": "markdown", "id": "cell_0ee64765e0cb", "created_at": "2026-07-17T05:27:36+00:00", "title": "Clean-room exact method"}
7
+ -->
8
+ ## Model and independent checks
9
+
10
+ No official code release was found. The implementation directly applies finite production functions, action costs, principal-favoring tie breaking, theorem constants, and the Algorithm 1 grid from arXiv:2601.01496. Uniform convergence is calculated from a direct all-breakpoint utility profile and exact binomial tails; EUM is independently enumerated count by count. More actions are added as strictly dominated actions to test action-count independence without changing the underlying agent distribution.
pages/negative-controls/page.md ADDED
@@ -0,0 +1,28 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Negative controls
2
+
3
+
4
+ ---
5
+ <!-- trackio-cell
6
+ {"type": "markdown", "id": "cell_ee986a2519e9", "created_at": "2026-07-17T05:27:37+00:00", "title": "I.i.d. assumption violation"}
7
+ -->
8
+ ## Correlated-sample falsification
9
+
10
+ A control makes every sample share one latent type instead of being i.i.d. It yields uniform-convergence failure probability 1.0 and EUM failure probability 0.2, both above delta=0.05. Tests also check the exact tie at alpha=0.4, grid cardinality, all switch-point reward monotonicity, and the independently predicted EUM failure range.
11
+
12
+
13
+ ---
14
+ <!-- trackio-cell
15
+ {"type": "code", "id": "cell_6d2f88454604", "created_at": "2026-07-17T05:28:02+00:00", "title": "Unit and i.i.d.-violation controls", "command": ["pytest", "-q"], "exit_code": 0, "duration_s": 1.644}
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+ -->
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+ ````bash
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+ $ pytest -q
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+ ````
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+
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+ exit 0 · 1.6s
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+
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+
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+ ````output
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+ ......... [100%]
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+ 9 passed in 1.20s
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+
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+ ````
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+ # Overview
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+
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+
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+ ---
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+ <!-- trackio-cell
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+ {"type": "markdown", "id": "cell_ac3f29415767", "created_at": "2026-07-17T05:27:32+00:00", "title": "Outcome"}
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+ -->
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+ # Reproduction outcome
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+
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+ Both scored claims have exact full-bound finite certificates. Theorem 1.1 is evaluated at its literal 1,514,429-sample bound across four action counts. Corollary 1.2 evaluates every 3,028,858 binomial sufficient statistic using the paper epsilon/4 EUM grid. These certify theorem mechanisms on a finite model; they do not claim to empirically prove universal theorems.
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