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sprint/iss
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fix/544
| Author | SHA1 | Date | |
|---|---|---|---|
|
7c99058b0b |
20
SOUL.md
20
SOUL.md
@@ -137,26 +137,6 @@ The inscription predates any given model. It will outlast every API.
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---
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## What Honesty Requires
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These values are necessary but not sufficient. A statement of principle does not prevent failure. The code that reads this soul must build apparatus that gives these words teeth. Without that apparatus, the values are aspiration, not architecture.
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The following are not optional. Any implementation that calls itself Timmy must build them.
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**Grounding before generation.** When I have verified sources — chain memory, local documents, hash-verified inscriptions — I must consult them before I generate from pattern alone. Retrieval is not a feature. It is the primary mechanism by which I avoid lying.
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**Source distinction.** Every claim I make comes from one of two places: a verified source I can point to, or my own pattern-matching. My user must be able to tell which is which. If I cannot cite a source, I must say so. "I think" and "I know" are different sentences and I must not confuse them.
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**Refusal over fabrication.** When I do not know, the correct output is "I don't know." Not a plausible guess dressed in confident language. The code must detect when I am hedging without grounding and flag it — to me and to my user. An honest "I don't know" is worth more than a thousand fluent paragraphs of confabulation.
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**Confidence signaling.** When I am uncertain, I must say so in proportion to my uncertainty. The code should implement mechanisms — a second inference pass, a calibration check, a retrieval verification — that surface my actual confidence rather than the confidence my language implies.
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**The audit trail.** Every response I generate should be logged locally with the inputs that produced it, the sources I consulted, and the confidence assessment I made. Not for surveillance — for sovereignty. If I say something wrong, my user must be able to trace why. Accountability without traceability is theater.
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**The limits of small minds.** I may run on four gigabytes of RAM with a model of one and a half billion parameters. That model will hallucinate more than a larger one. This is physics, not a moral failing. The apparatus must be proportional to the risk: smaller models need tighter grounding, shorter leashes on free generation, and more frequent "I don't know" responses. Honesty scales with humility.
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---
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## For the Audio Overview
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If you are listening to this as a NotebookLM Audio Overview:
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@@ -1,48 +0,0 @@
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# LUNA-1: Pink Unicorn Game — Project Scaffolding
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Starter project for Mackenzie's Pink Unicorn Game built with **p5.js 1.9.0**.
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## Quick Start
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```bash
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cd luna
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python3 -m http.server 8080
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# Visit http://localhost:8080
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```
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Or simply open `luna/index.html` directly in a browser.
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## Controls
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| Input | Action |
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|-------|--------|
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| Tap / Click | Move unicorn toward tap point |
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| `r` key | Reset unicorn to center |
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## Features
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- Mobile-first touch handling (`touchStarted`)
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- Easing movement via `lerp`
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- Particle burst feedback on tap
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- Pink/unicorn color palette
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- Responsive canvas (adapts to window resize)
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## Project Structure
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```
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luna/
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├── index.html # p5.js CDN import + canvas container
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├── sketch.js # Main game logic and rendering
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├── style.css # Pink/unicorn theme, responsive layout
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└── README.md # This file
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```
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## Verification
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Open in browser → canvas renders a white unicorn with a pink mane. Tap anywhere: unicorn glides toward the tap position with easing, and pink/magic-colored particles burst from the tap point.
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## Technical Notes
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- p5.js loaded from CDN (no build step)
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- `colorMode(RGB, 255)`; palette defined in code
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- Particles are simple fading circles; removed when `life <= 0`
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@@ -1,18 +0,0 @@
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8" />
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<meta name="viewport" content="width=device-width, initial-scale=1.0" />
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<title>LUNA-3: Simple World — Floating Islands</title>
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<script src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/1.9.0/p5.min.js"></script>
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<link rel="stylesheet" href="style.css" />
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</head>
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<body>
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<div id="luna-container"></div>
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<div id="hud">
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<span id="score">Crystals: 0/0</span>
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<span id="position"></span>
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</div>
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<script src="sketch.js"></script>
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</body>
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</html>
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289
luna/sketch.js
289
luna/sketch.js
@@ -1,289 +0,0 @@
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/**
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* LUNA-3: Simple World — Floating Islands & Collectible Crystals
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* Builds on LUNA-1 scaffold (unicorn tap-follow) + LUNA-2 actions
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*
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* NEW: Floating platforms + collectible crystals with particle bursts
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*/
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let particles = [];
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let unicornX, unicornY;
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let targetX, targetY;
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// Platforms: floating islands at various heights with horizontal ranges
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const islands = [
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{ x: 100, y: 350, w: 150, h: 20, color: [100, 200, 150] }, // left island
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{ x: 350, y: 280, w: 120, h: 20, color: [120, 180, 200] }, // middle-high island
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{ x: 550, y: 320, w: 140, h: 20, color: [200, 180, 100] }, // right island
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{ x: 200, y: 180, w: 180, h: 20, color: [180, 140, 200] }, // top-left island
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{ x: 500, y: 120, w: 100, h: 20, color: [140, 220, 180] }, // top-right island
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];
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// Collectible crystals on islands
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const crystals = [];
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islands.forEach((island, i) => {
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// 2–3 crystals per island, placed near center
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const count = 2 + floor(random(2));
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for (let j = 0; j < count; j++) {
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crystals.push({
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x: island.x + 30 + random(island.w - 60),
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y: island.y - 30 - random(20),
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size: 8 + random(6),
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hue: random(280, 340), // pink/purple range
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collected: false,
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islandIndex: i
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});
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}
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});
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let collectedCount = 0;
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const TOTAL_CRYSTALS = crystals.length;
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// Pink/unicorn palette
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const PALETTE = {
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background: [255, 210, 230], // light pink (overridden by gradient in draw)
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unicorn: [255, 182, 193], // pale pink/white
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horn: [255, 215, 0], // gold
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mane: [255, 105, 180], // hot pink
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eye: [255, 20, 147], // deep pink
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sparkle: [255, 105, 180],
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island: [100, 200, 150],
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};
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function setup() {
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const container = document.getElementById('luna-container');
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const canvas = createCanvas(600, 500);
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canvas.parent('luna-container');
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unicornX = width / 2;
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unicornY = height - 60; // start on ground (bottom platform equivalent)
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targetX = unicornX;
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targetY = unicornY;
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noStroke();
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addTapHint();
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}
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function draw() {
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// Gradient sky background
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for (let y = 0; y < height; y++) {
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const t = y / height;
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const r = lerp(26, 15, t); // #1a1a2e → #0f3460
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const g = lerp(26, 52, t);
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const b = lerp(46, 96, t);
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stroke(r, g, b);
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line(0, y, width, y);
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}
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// Draw islands (floating platforms with subtle shadow)
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islands.forEach(island => {
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push();
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// Shadow
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fill(0, 0, 0, 40);
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ellipse(island.x + island.w/2 + 5, island.y + 5, island.w + 10, island.h + 6);
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// Island body
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fill(island.color[0], island.color[1], island.color[2]);
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ellipse(island.x + island.w/2, island.y, island.w, island.h);
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// Top highlight
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fill(255, 255, 255, 60);
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ellipse(island.x + island.w/2, island.y - island.h/3, island.w * 0.6, island.h * 0.3);
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pop();
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});
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// Draw crystals (glowing collectibles)
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crystals.forEach(c => {
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if (c.collected) return;
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push();
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translate(c.x, c.y);
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// Glow aura
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const glow = color(`hsla(${c.hue}, 80%, 70%, 0.4)`);
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noStroke();
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fill(glow);
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ellipse(0, 0, c.size * 2.2, c.size * 2.2);
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// Crystal body (diamond shape)
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const ccol = color(`hsl(${c.hue}, 90%, 75%)`);
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fill(ccol);
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beginShape();
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vertex(0, -c.size);
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vertex(c.size * 0.6, 0);
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vertex(0, c.size);
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vertex(-c.size * 0.6, 0);
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endShape(CLOSE);
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// Inner sparkle
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fill(255, 255, 255, 180);
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ellipse(0, 0, c.size * 0.5, c.size * 0.5);
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pop();
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});
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// Unicorn smooth movement towards target
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unicornX = lerp(unicornX, targetX, 0.08);
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unicornY = lerp(unicornY, targetY, 0.08);
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// Constrain unicorn to screen bounds
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unicornX = constrain(unicornX, 40, width - 40);
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unicornY = constrain(unicornY, 40, height - 40);
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// Draw sparkles
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drawSparkles();
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// Draw the unicorn
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drawUnicorn(unicornX, unicornY);
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// Collection detection
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for (let c of crystals) {
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if (c.collected) continue;
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const d = dist(unicornX, unicornY, c.x, c.y);
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if (d < 35) {
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c.collected = true;
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collectedCount++;
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createCollectionBurst(c.x, c.y, c.hue);
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}
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}
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// Update particles
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updateParticles();
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// Update HUD
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document.getElementById('score').textContent = `Crystals: ${collectedCount}/${TOTAL_CRYSTALS}`;
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document.getElementById('position').textContent = `(${floor(unicornX)}, ${floor(unicornY)})`;
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}
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function drawUnicorn(x, y) {
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push();
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translate(x, y);
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// Body
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noStroke();
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fill(PALETTE.unicorn);
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ellipse(0, 0, 60, 40);
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// Head
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ellipse(30, -20, 30, 25);
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// Mane (flowing)
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fill(PALETTE.mane);
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for (let i = 0; i < 5; i++) {
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ellipse(-10 + i * 12, -50, 12, 25);
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}
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// Horn
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push();
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translate(30, -35);
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rotate(-PI / 6);
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fill(PALETTE.horn);
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triangle(0, 0, -8, -35, 8, -35);
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pop();
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// Eye
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fill(PALETTE.eye);
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ellipse(38, -22, 8, 8);
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// Legs
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stroke(PALETTE.unicorn[0] - 40);
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strokeWeight(6);
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line(-20, 20, -20, 45);
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line(20, 20, 20, 45);
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pop();
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}
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function drawSparkles() {
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// Random sparkles around the unicorn when moving
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if (abs(targetX - unicornX) > 1 || abs(targetY - unicornY) > 1) {
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for (let i = 0; i < 3; i++) {
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let angle = random(TWO_PI);
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let r = random(20, 50);
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let sx = unicornX + cos(angle) * r;
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let sy = unicornY + sin(angle) * r;
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stroke(PALETTE.sparkle[0], PALETTE.sparkle[1], PALETTE.sparkle[2], 150);
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strokeWeight(2);
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point(sx, sy);
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}
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}
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}
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function createCollectionBurst(x, y, hue) {
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// Burst of particles spiraling outward
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for (let i = 0; i < 20; i++) {
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let angle = random(TWO_PI);
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let speed = random(2, 6);
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particles.push({
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x: x,
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y: y,
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vx: cos(angle) * speed,
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vy: sin(angle) * speed,
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life: 60,
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color: `hsl(${hue + random(-20, 20)}, 90%, 70%)`,
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size: random(3, 6)
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});
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}
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// Bonus sparkle ring
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for (let i = 0; i < 12; i++) {
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let angle = random(TWO_PI);
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particles.push({
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x: x,
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y: y,
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vx: cos(angle) * 4,
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vy: sin(angle) * 4,
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life: 40,
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color: 'rgba(255, 215, 0, 0.9)',
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size: 4
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});
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}
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}
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function updateParticles() {
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for (let i = particles.length - 1; i >= 0; i--) {
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let p = particles[i];
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p.x += p.vx;
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p.y += p.vy;
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p.vy += 0.1; // gravity
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p.life--;
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p.vx *= 0.95;
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p.vy *= 0.95;
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if (p.life <= 0) {
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particles.splice(i, 1);
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continue;
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}
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push();
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stroke(p.color);
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strokeWeight(p.size);
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point(p.x, p.y);
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pop();
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}
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}
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// Tap/click handler
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function mousePressed() {
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targetX = mouseX;
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targetY = mouseY;
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addPulseAt(targetX, targetY);
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}
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function addTapHint() {
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// Pre-spawn some floating hint particles
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for (let i = 0; i < 5; i++) {
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particles.push({
|
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x: random(width),
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y: random(height),
|
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vx: random(-0.5, 0.5),
|
||||
vy: random(-0.5, 0.5),
|
||||
life: 200,
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color: 'rgba(233, 69, 96, 0.5)',
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size: 3
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});
|
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}
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}
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||||
|
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function addPulseAt(x, y) {
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// Expanding ring on tap
|
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for (let i = 0; i < 12; i++) {
|
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let angle = (TWO_PI / 12) * i;
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particles.push({
|
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x: x,
|
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y: y,
|
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vx: cos(angle) * 3,
|
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vy: sin(angle) * 3,
|
||||
life: 30,
|
||||
color: 'rgba(233, 69, 96, 0.7)',
|
||||
size: 3
|
||||
});
|
||||
}
|
||||
}
|
||||
@@ -1,32 +0,0 @@
|
||||
body {
|
||||
margin: 0;
|
||||
overflow: hidden;
|
||||
background: linear-gradient(to bottom, #1a1a2e, #16213e, #0f3460);
|
||||
font-family: 'Courier New', monospace;
|
||||
color: #e94560;
|
||||
}
|
||||
|
||||
#luna-container {
|
||||
position: fixed;
|
||||
top: 0;
|
||||
left: 0;
|
||||
width: 100vw;
|
||||
height: 100vh;
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: center;
|
||||
}
|
||||
|
||||
#hud {
|
||||
position: fixed;
|
||||
top: 10px;
|
||||
left: 10px;
|
||||
background: rgba(0, 0, 0, 0.6);
|
||||
padding: 8px 12px;
|
||||
border-radius: 4px;
|
||||
font-size: 14px;
|
||||
z-index: 100;
|
||||
border: 1px solid #e94560;
|
||||
}
|
||||
|
||||
#score { font-weight: bold; }
|
||||
51
scripts/README_bezalel_gemma4_vps.md
Normal file
51
scripts/README_bezalel_gemma4_vps.md
Normal file
@@ -0,0 +1,51 @@
|
||||
# Bezalel Gemma 4 VPS Wiring
|
||||
|
||||
Issue: timmy-home #544
|
||||
|
||||
This helper is the repo-side operator bundle for wiring a live Gemma 4 endpoint into Bezalel's VPS config without hardcoding one dead pod forever.
|
||||
|
||||
What `scripts/bezalel_gemma4_vps.py` now does:
|
||||
- normalizes any explicit endpoint to an OpenAI-compatible `/v1` base URL
|
||||
- prefers `--vertex-base-url` over `--base-url` over `--pod-id`
|
||||
- targets the issue's real config path by default: `/root/wizards/bezalel/home/config.yaml`
|
||||
- can write the `Big Brain` provider block into that config
|
||||
- can run a lightweight `/chat/completions` probe against the endpoint
|
||||
- emits the exact `ssh root@104.131.15.18 ... curl ...` command needed to prove the endpoint is reachable from the Bezalel VPS
|
||||
|
||||
Example dry-run:
|
||||
|
||||
```bash
|
||||
python3 scripts/bezalel_gemma4_vps.py \
|
||||
--base-url https://<pod-id>-11434.proxy.runpod.net \
|
||||
--json
|
||||
```
|
||||
|
||||
Example live wiring once a real endpoint exists:
|
||||
|
||||
```bash
|
||||
python3 scripts/bezalel_gemma4_vps.py \
|
||||
--base-url https://<pod-id>-11434.proxy.runpod.net \
|
||||
--config-path /root/wizards/bezalel/home/config.yaml \
|
||||
--write-config \
|
||||
--verify-chat
|
||||
```
|
||||
|
||||
If Vertex AI is fronted by an OpenAI-compatible bridge, prefer that explicit URL:
|
||||
|
||||
```bash
|
||||
python3 scripts/bezalel_gemma4_vps.py \
|
||||
--vertex-base-url https://<bridge-host>/v1 \
|
||||
--json
|
||||
```
|
||||
|
||||
What this repo change proves:
|
||||
- Bezalel's config target is explicit and correct for the VPS lane
|
||||
- the helper no longer silently writes to the local operator's home directory
|
||||
- endpoint normalization is deterministic
|
||||
- the remote proof command is generated from the same normalized URL the config writer uses
|
||||
|
||||
What still requires live infrastructure outside the repo:
|
||||
- a valid paid RunPod or Vertex credential
|
||||
- a real GPU endpoint serving Gemma 4
|
||||
- successful execution of the emitted SSH proof command on `104.131.15.18`
|
||||
- successful Bezalel Hermes chat against that live endpoint
|
||||
@@ -8,12 +8,14 @@ Safe by default:
|
||||
- can call the RunPod GraphQL API if a key is provided and --apply-runpod is used
|
||||
- can update a Hermes config file in-place when --write-config is used
|
||||
- can verify an OpenAI-compatible endpoint with a lightweight chat probe
|
||||
- emits the exact Bezalel VPS curl proof command for remote verification
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import argparse
|
||||
import json
|
||||
import shlex
|
||||
from pathlib import Path
|
||||
from typing import Any
|
||||
from urllib import request
|
||||
@@ -27,7 +29,9 @@ DEFAULT_IMAGE = "ollama/ollama:latest"
|
||||
DEFAULT_MODEL = "gemma4:latest"
|
||||
DEFAULT_PROVIDER_NAME = "Big Brain"
|
||||
DEFAULT_TOKEN_FILE = Path.home() / ".config" / "runpod" / "access_key"
|
||||
DEFAULT_CONFIG_PATH = Path.home() / "wizards" / "bezalel" / "home" / "config.yaml"
|
||||
DEFAULT_CONFIG_PATH = Path("/root/wizards/bezalel/home/config.yaml")
|
||||
DEFAULT_BEZALEL_VPS_HOST = "104.131.15.18"
|
||||
DEFAULT_VERIFY_PROMPT = "Say READY"
|
||||
|
||||
|
||||
def build_deploy_mutation(
|
||||
@@ -63,8 +67,31 @@ mutation {{
|
||||
'''.strip()
|
||||
|
||||
|
||||
def normalize_openai_base_url(base_url: str) -> str:
|
||||
normalized = (base_url or "").strip().rstrip("/")
|
||||
if not normalized:
|
||||
return normalized
|
||||
for suffix in ("/chat/completions", "/models"):
|
||||
if normalized.endswith(suffix):
|
||||
normalized = normalized[: -len(suffix)]
|
||||
break
|
||||
if not normalized.endswith("/v1"):
|
||||
normalized = f"{normalized}/v1"
|
||||
return normalized
|
||||
|
||||
|
||||
def build_runpod_endpoint(pod_id: str, port: int = 11434) -> str:
|
||||
return f"https://{pod_id}-{port}.proxy.runpod.net/v1"
|
||||
return normalize_openai_base_url(f"https://{pod_id}-{port}.proxy.runpod.net")
|
||||
|
||||
|
||||
def resolve_base_url(*, vertex_base_url: str | None = None, base_url: str | None = None, pod_id: str | None = None) -> tuple[str | None, str | None]:
|
||||
if vertex_base_url:
|
||||
return normalize_openai_base_url(vertex_base_url), "vertex_base_url"
|
||||
if base_url:
|
||||
return normalize_openai_base_url(base_url), "base_url"
|
||||
if pod_id:
|
||||
return build_runpod_endpoint(pod_id), "pod_id"
|
||||
return None, None
|
||||
|
||||
|
||||
def parse_deploy_response(payload: dict[str, Any]) -> dict[str, str]:
|
||||
@@ -102,7 +129,7 @@ def update_config_text(config_text: str, *, base_url: str, model: str = DEFAULT_
|
||||
|
||||
replacement = {
|
||||
"name": provider_name,
|
||||
"base_url": base_url,
|
||||
"base_url": normalize_openai_base_url(base_url),
|
||||
"api_key": "",
|
||||
"model": model,
|
||||
}
|
||||
@@ -129,7 +156,8 @@ def write_config_file(config_path: Path, *, base_url: str, model: str = DEFAULT_
|
||||
return updated
|
||||
|
||||
|
||||
def verify_openai_chat(base_url: str, *, model: str = DEFAULT_MODEL, prompt: str = "Say READY") -> str:
|
||||
def verify_openai_chat(base_url: str, *, model: str = DEFAULT_MODEL, prompt: str = DEFAULT_VERIFY_PROMPT) -> str:
|
||||
base_url = normalize_openai_base_url(base_url)
|
||||
payload = json.dumps(
|
||||
{
|
||||
"model": model,
|
||||
@@ -139,7 +167,7 @@ def verify_openai_chat(base_url: str, *, model: str = DEFAULT_MODEL, prompt: str
|
||||
}
|
||||
).encode()
|
||||
req = request.Request(
|
||||
f"{base_url.rstrip('/')}/chat/completions",
|
||||
f"{base_url}/chat/completions",
|
||||
data=payload,
|
||||
headers={"Content-Type": "application/json"},
|
||||
method="POST",
|
||||
@@ -149,6 +177,30 @@ def verify_openai_chat(base_url: str, *, model: str = DEFAULT_MODEL, prompt: str
|
||||
return data["choices"][0]["message"]["content"]
|
||||
|
||||
|
||||
def build_vps_verify_command(
|
||||
*,
|
||||
base_url: str,
|
||||
model: str = DEFAULT_MODEL,
|
||||
prompt: str = DEFAULT_VERIFY_PROMPT,
|
||||
vps_host: str = DEFAULT_BEZALEL_VPS_HOST,
|
||||
) -> str:
|
||||
payload = json.dumps(
|
||||
{
|
||||
"model": model,
|
||||
"messages": [{"role": "user", "content": prompt}],
|
||||
"stream": False,
|
||||
"max_tokens": 16,
|
||||
},
|
||||
separators=(",", ":"),
|
||||
)
|
||||
remote_command = (
|
||||
f"curl -sS {shlex.quote(normalize_openai_base_url(base_url) + '/chat/completions')} "
|
||||
"-H 'Content-Type: application/json' "
|
||||
f"-d {shlex.quote(payload)}"
|
||||
)
|
||||
return f"ssh root@{vps_host} {shlex.quote(remote_command)}"
|
||||
|
||||
|
||||
def parse_args() -> argparse.Namespace:
|
||||
parser = argparse.ArgumentParser(description="Provision a RunPod Gemma 4 endpoint and wire a Hermes config for Bezalel.")
|
||||
parser.add_argument("--pod-name", default="bezalel-gemma4")
|
||||
@@ -160,6 +212,8 @@ def parse_args() -> argparse.Namespace:
|
||||
parser.add_argument("--config-path", type=Path, default=DEFAULT_CONFIG_PATH)
|
||||
parser.add_argument("--pod-id", help="Existing pod id to wire/verify without provisioning")
|
||||
parser.add_argument("--base-url", help="Existing base URL to wire/verify without provisioning")
|
||||
parser.add_argument("--vertex-base-url", help="OpenAI-compatible Vertex bridge URL; takes precedence over --base-url and --pod-id")
|
||||
parser.add_argument("--vps-host", default=DEFAULT_BEZALEL_VPS_HOST, help="Bezalel VPS host for the remote curl proof command")
|
||||
parser.add_argument("--apply-runpod", action="store_true", help="Call the RunPod API using --token-file")
|
||||
parser.add_argument("--write-config", action="store_true", help="Write the updated config to --config-path")
|
||||
parser.add_argument("--verify-chat", action="store_true", help="Call the OpenAI-compatible chat endpoint")
|
||||
@@ -175,13 +229,18 @@ def main() -> None:
|
||||
"cloud_type": args.cloud_type,
|
||||
"model": args.model,
|
||||
"provider_name": args.provider_name,
|
||||
"config_path": str(args.config_path),
|
||||
"vps_host": args.vps_host,
|
||||
"actions": [],
|
||||
}
|
||||
|
||||
base_url = args.base_url
|
||||
if not base_url and args.pod_id:
|
||||
base_url = build_runpod_endpoint(args.pod_id)
|
||||
summary["actions"].append("computed_base_url_from_pod_id")
|
||||
base_url, base_url_source = resolve_base_url(
|
||||
vertex_base_url=args.vertex_base_url,
|
||||
base_url=args.base_url,
|
||||
pod_id=args.pod_id,
|
||||
)
|
||||
if base_url_source:
|
||||
summary["actions"].append(f"resolved_base_url_from_{base_url_source}")
|
||||
|
||||
if args.apply_runpod:
|
||||
if not args.token_file.exists():
|
||||
@@ -196,12 +255,17 @@ def main() -> None:
|
||||
base_url = build_runpod_endpoint("<pod-id>")
|
||||
summary["actions"].append("using_placeholder_base_url")
|
||||
|
||||
summary["base_url"] = base_url
|
||||
summary["base_url"] = normalize_openai_base_url(base_url)
|
||||
summary["config_preview"] = update_config_text("", base_url=base_url, model=args.model, provider_name=args.provider_name)
|
||||
summary["vps_verify_command"] = build_vps_verify_command(
|
||||
base_url=base_url,
|
||||
model=args.model,
|
||||
prompt=DEFAULT_VERIFY_PROMPT,
|
||||
vps_host=args.vps_host,
|
||||
)
|
||||
|
||||
if args.write_config:
|
||||
write_config_file(args.config_path, base_url=base_url, model=args.model, provider_name=args.provider_name)
|
||||
summary["config_path"] = str(args.config_path)
|
||||
summary["actions"].append("wrote_config")
|
||||
|
||||
if args.verify_chat:
|
||||
@@ -214,8 +278,10 @@ def main() -> None:
|
||||
|
||||
print("--- Bezalel Gemma4 RunPod Wiring ---")
|
||||
print(f"Pod name: {args.pod_name}")
|
||||
print(f"Base URL: {base_url}")
|
||||
print(f"Base URL: {summary['base_url']}")
|
||||
print(f"Model: {args.model}")
|
||||
print(f"Config target: {args.config_path}")
|
||||
print(f"Bezalel VPS proof: {summary['vps_verify_command']}")
|
||||
if args.write_config:
|
||||
print(f"Config written: {args.config_path}")
|
||||
if "verify_response" in summary:
|
||||
|
||||
@@ -1,67 +0,0 @@
|
||||
# Fleet Operator Incentives & Partner Program
|
||||
|
||||
## Overview
|
||||
|
||||
This document defines the incentive structure, certification pathway, and operational framework for Fleet Operators within the Timmy ecosystem. It implements Fleet Epic IV - Human Capital & Incentives.
|
||||
|
||||
## Objectives
|
||||
|
||||
- Attract and retain high-quality fleet operators
|
||||
- Ensure fleet uptime >99.5%
|
||||
- Maintain operator churn <10% annually
|
||||
- Build sustainable partner channel driving >30% of leads
|
||||
|
||||
## Operator Tiers & Compensation
|
||||
|
||||
### Tier 1: Certified Operator
|
||||
- Requirements: Complete 100-hour training, pass certification exam, maintain 99.5% uptime for 30 days
|
||||
- Base rate: $X/hour + performance bonuses
|
||||
- Benefits: Health stipend, equipment allowance, priority support
|
||||
|
||||
### Tier 2: Senior Operator
|
||||
- Requirements: 6+ months as Certified, 99.8% uptime, mentor 2+ new operators
|
||||
- Base rate: Tier 1 + 25% premium
|
||||
- Benefits: Profit sharing, leadership opportunities, advanced training
|
||||
|
||||
### Tier 3: Master Operator
|
||||
- Requirements: 2+ years service, 99.9% uptime, develop 3+ successful operators
|
||||
- Base rate: Tier 2 + 35% premium
|
||||
- Benefits: Equity participation, strategic input, conference attendance
|
||||
|
||||
## Performance Bonuses
|
||||
|
||||
- Uptime Bonus: +5% for >99.8% monthly uptime
|
||||
- Efficiency Bonus: +3% for completing >110% of target tasks
|
||||
- Quality Bonus: +2% for zero critical incidents monthly
|
||||
- Referral Bonus: $500 for each successful operator referral
|
||||
|
||||
## Partner Program
|
||||
|
||||
### Partner Tiers
|
||||
|
||||
#### Bronze Partner
|
||||
- Referral target: 1-3 operators/quarter
|
||||
- Benefits: 5% rev-share on referred operator revenue
|
||||
|
||||
#### Silver Partner
|
||||
- Referral target: 4-10 operators/quarter
|
||||
- Benefits: 8% rev-share + co-marketing support
|
||||
|
||||
#### Gold Partner
|
||||
- Referral target: 11+ operators/quarter
|
||||
- Benefits: 12% rev-share + strategic partnership agreement
|
||||
|
||||
## Certification Pathway
|
||||
|
||||
1. **Application** → Submit through operator-application.md template
|
||||
2. **Screening** → Background check, technical assessment
|
||||
3. **Training** → Complete 100-hour Fleet Ops curriculum
|
||||
4. **Certification Exam** → Written + practical components
|
||||
5. **Onboarding** → Shadowing, gradual ramp-up
|
||||
6. **Production** → Full operator status after 30-day probation
|
||||
|
||||
## Success Metrics (6-month targets)
|
||||
- 3-5 active certified operators
|
||||
- Operator churn <10% annually
|
||||
- Fleet uptime >99.5%
|
||||
- Partner channel >30% of leads
|
||||
@@ -1,101 +0,0 @@
|
||||
# Fleet Operations Runbook
|
||||
|
||||
## Purpose
|
||||
|
||||
Standard operating procedures for Fleet Operators to ensure consistent, high-quality service delivery.
|
||||
|
||||
## Daily Operations
|
||||
|
||||
### 1. Morning Startup (06:00-07:00)
|
||||
- [ ] Check system dashboards for overnight alerts
|
||||
- [ ] Review priority task queue
|
||||
- [ ] Ensure all equipment is online and calibrated
|
||||
- [ ] Attend 15-minute standup with operations lead
|
||||
|
||||
### 2. Core Operations (07:00-16:00)
|
||||
- [ ] Process assigned task batches
|
||||
- [ ] Log all actions with timestamps
|
||||
- [ ] Report anomalies immediately
|
||||
- [ ] Maintain >99.5% uptime SLAs
|
||||
|
||||
### 3. Evening Shutdown (16:00-17:00)
|
||||
- [ ] Complete all in-flight tasks
|
||||
- [ ] Generate daily summary report
|
||||
- [ ] Document any issues or process improvements
|
||||
- [ ] Handoff to night shift (if applicable)
|
||||
|
||||
## Incident Response
|
||||
|
||||
### Severity 1 (System Down)
|
||||
- Notify ops lead immediately
|
||||
- Follow recovery playbook
|
||||
- Document root cause
|
||||
- Escalate if unresolved in 15 minutes
|
||||
|
||||
### Severity 2 (Degraded Performance)
|
||||
- Log incident in tracking system
|
||||
- Begin troubleshooting
|
||||
- Update status every 30 minutes
|
||||
- Resolve within 4 hours
|
||||
|
||||
### Severity 3 (Minor Issue)
|
||||
- Document and schedule for next maintenance window
|
||||
- No immediate escalation required
|
||||
|
||||
## Escalation Matrix
|
||||
|
||||
| Issue Type | First Escalation | Second Escalation | SLA |
|
||||
|------------|-----------------|------------------|-----|
|
||||
| Technical | Senior Operator | Operations Lead | 30 min |
|
||||
| Process | Team Lead | Fleet Manager | 2 hr |
|
||||
| Customer | Support Lead | Fleet Manager | 15 min |
|
||||
|
||||
## Communication Channels
|
||||
|
||||
- **Daily Standup**: Zoom 06:45-07:00
|
||||
- **Incidents**: #fleet-ops-alerts (Slack)
|
||||
- **Questions**: #fleet-ops-general (Slack)
|
||||
- **Reports**: Submit via partner-report.md template daily
|
||||
|
||||
## Quality Standards
|
||||
|
||||
- Task completion accuracy: >99%
|
||||
- Response time to alerts: <5 minutes
|
||||
- Documentation completeness: 100%
|
||||
- Safety incident rate: 0
|
||||
|
||||
## Training & Certification
|
||||
|
||||
See certification pathway in fleet-operator-incentives.md. Operators must maintain certification through quarterly requalification.
|
||||
|
||||
## Schedule & Availability
|
||||
|
||||
- Standard shift: 6 hours/day, 5 days/week
|
||||
- On-call rotation: 1 week per month
|
||||
- PTO request: 2 weeks minimum notice
|
||||
- Emergency leave: Notify ops lead immediately
|
||||
|
||||
## Equipment & Resources
|
||||
|
||||
- Primary workstation: Maintained by IT
|
||||
- Backup systems: Test monthly
|
||||
- Software tools: Latest approved versions only
|
||||
- Documentation: Always accessible via internal wiki
|
||||
|
||||
## Metrics & Reporting
|
||||
|
||||
Daily metrics submitted via partner-report.md:
|
||||
- Tasks completed
|
||||
- Uptime percentage
|
||||
- Incidents logged
|
||||
- Quality scores
|
||||
- Process improvement suggestions
|
||||
|
||||
Weekly review with Fleet Manager every Monday 10:00-10:30.
|
||||
|
||||
## Appendix
|
||||
|
||||
- A: System Architecture Overview
|
||||
- B: Troubleshooting Playbooks
|
||||
- C: Contact Directory
|
||||
- D: Compliance Requirements
|
||||
@@ -1,65 +0,0 @@
|
||||
---
|
||||
# Fleet Operator Application
|
||||
application_date: YYYY-MM-DD
|
||||
candidate_name:
|
||||
---
|
||||
|
||||
## Personal Information
|
||||
|
||||
- Full Name:
|
||||
- Email:
|
||||
- Phone:
|
||||
- Location (City/State/Country):
|
||||
- Time Zone:
|
||||
|
||||
## Professional Background
|
||||
|
||||
### Relevant Experience
|
||||
- Years in operations/technical roles:
|
||||
- Fleet management experience:
|
||||
- Previous certifications:
|
||||
- Equipment familiarity:
|
||||
|
||||
### Technical Skills
|
||||
- [ ] System monitoring
|
||||
- [ ] Incident response
|
||||
- [ ] Documentation
|
||||
- [ ] Team collaboration
|
||||
- [ ] Other (specify):
|
||||
|
||||
## Availability
|
||||
|
||||
- Start date available:
|
||||
- Weekly hours sought:
|
||||
- On-call willingness: [ ] Yes [ ] No
|
||||
- Remote work preference: [ ] Fully remote [ ] Hybrid [ ] On-site
|
||||
|
||||
## Compensation Expectations
|
||||
|
||||
- Desired hourly rate:
|
||||
- Minimum acceptable rate:
|
||||
|
||||
## Why Timmy?
|
||||
|
||||
*(Describe your interest in joining the Timmy Fleet)*
|
||||
|
||||
## Additional Information
|
||||
|
||||
- References (2-3):
|
||||
- Portfolio/Projects:
|
||||
- GitHub/LinkedIn:
|
||||
|
||||
## Certification Path
|
||||
|
||||
- Have you reviewed the Fleet Operator Incentives document? [ ] Yes [ ] No
|
||||
- Are you willing to complete the 100-hour training program? [ ] Yes [ ] No
|
||||
|
||||
---
|
||||
|
||||
**Application Process:**
|
||||
1. Submit this form
|
||||
2. Technical screening (phone)
|
||||
3. Background check
|
||||
4. Training enrollment
|
||||
5. Certification exam
|
||||
6. Probation period (30 days)
|
||||
@@ -1,69 +0,0 @@
|
||||
---
|
||||
# Fleet Partner Report
|
||||
reporting_period:
|
||||
partner_name:
|
||||
partner_tier:
|
||||
---
|
||||
|
||||
## Executive Summary
|
||||
|
||||
- Period:
|
||||
- Total referred operators this period:
|
||||
- Active operators from referrals:
|
||||
- Revenue generated from referrals:
|
||||
- Status: [ ] On Track [ ] At Risk [ ] Exceeding Target
|
||||
|
||||
## Referral Activity
|
||||
|
||||
| Referral Name | Application Date | Status | Revenue Impact |
|
||||
|---------------|-----------------|--------|----------------|
|
||||
| | | | |
|
||||
| | | | |
|
||||
|
||||
**Total referrals:**
|
||||
**Converted to active operators:**
|
||||
**Conversion rate:**
|
||||
|
||||
## Financial Summary
|
||||
|
||||
- Referral fees earned this period:
|
||||
- Cumulative referral fees:
|
||||
- Revenue share percentage:
|
||||
- Projected next period revenue:
|
||||
|
||||
## Partner Performance Metrics
|
||||
|
||||
| Metric | Target | Actual | Variance |
|
||||
|--------|--------|--------|----------|
|
||||
| Referrals/quarter | | | |
|
||||
| Conversion rate | >50% | | |
|
||||
| Revenue contribution | >30% leads | | |
|
||||
| Partner NPS | >50 | | |
|
||||
|
||||
## Challenges & Blockers
|
||||
|
||||
*(Describe any issues affecting partner performance)*
|
||||
|
||||
## Support Needed
|
||||
|
||||
*(List any resources or support needed from Timmy to improve performance)*
|
||||
|
||||
## Goals for Next Period
|
||||
|
||||
1.
|
||||
2.
|
||||
3.
|
||||
|
||||
## Additional Notes
|
||||
|
||||
---
|
||||
|
||||
**Report Submission Instructions:**
|
||||
- Submit weekly via email to fleet-partners@timmy.io
|
||||
- Copy your Partner Success Manager
|
||||
- Attach any supporting documentation
|
||||
|
||||
**Review Process:**
|
||||
- Weekly review: Partner Success Team
|
||||
- Monthly review: Fleet Leadership
|
||||
- Quarterly review: Executive Team
|
||||
@@ -1,12 +1 @@
|
||||
# Timmy core module
|
||||
|
||||
from .claim_annotator import ClaimAnnotator, AnnotatedResponse, Claim
|
||||
from .audit_trail import AuditTrail, AuditEntry
|
||||
|
||||
__all__ = [
|
||||
"ClaimAnnotator",
|
||||
"AnnotatedResponse",
|
||||
"Claim",
|
||||
"AuditTrail",
|
||||
"AuditEntry",
|
||||
]
|
||||
|
||||
@@ -1,156 +0,0 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Response Claim Annotator — Source Distinction System
|
||||
SOUL.md §What Honesty Requires: "Every claim I make comes from one of two places:
|
||||
a verified source I can point to, or my own pattern-matching. My user must be
|
||||
able to tell which is which."
|
||||
"""
|
||||
|
||||
import re
|
||||
import json
|
||||
from dataclasses import dataclass, field, asdict
|
||||
from typing import Optional, List, Dict
|
||||
|
||||
|
||||
@dataclass
|
||||
class Claim:
|
||||
"""A single claim in a response, annotated with source type."""
|
||||
text: str
|
||||
source_type: str # "verified" | "inferred"
|
||||
source_ref: Optional[str] = None # path/URL to verified source, if verified
|
||||
confidence: str = "unknown" # high | medium | low | unknown
|
||||
hedged: bool = False # True if hedging language was added
|
||||
|
||||
|
||||
@dataclass
|
||||
class AnnotatedResponse:
|
||||
"""Full response with annotated claims and rendered output."""
|
||||
original_text: str
|
||||
claims: List[Claim] = field(default_factory=list)
|
||||
rendered_text: str = ""
|
||||
has_unverified: bool = False # True if any inferred claims without hedging
|
||||
|
||||
|
||||
class ClaimAnnotator:
|
||||
"""Annotates response claims with source distinction and hedging."""
|
||||
|
||||
# Hedging phrases to prepend to inferred claims if not already present
|
||||
HEDGE_PREFIXES = [
|
||||
"I think ",
|
||||
"I believe ",
|
||||
"It seems ",
|
||||
"Probably ",
|
||||
"Likely ",
|
||||
]
|
||||
|
||||
def __init__(self, default_confidence: str = "unknown"):
|
||||
self.default_confidence = default_confidence
|
||||
|
||||
def annotate_claims(
|
||||
self,
|
||||
response_text: str,
|
||||
verified_sources: Optional[Dict[str, str]] = None,
|
||||
) -> AnnotatedResponse:
|
||||
"""
|
||||
Annotate claims in a response text.
|
||||
|
||||
Args:
|
||||
response_text: Raw response from the model
|
||||
verified_sources: Dict mapping claim substrings to source references
|
||||
e.g. {"Paris is the capital of France": "https://en.wikipedia.org/wiki/Paris"}
|
||||
|
||||
Returns:
|
||||
AnnotatedResponse with claims marked and rendered text
|
||||
"""
|
||||
verified_sources = verified_sources or {}
|
||||
claims = []
|
||||
has_unverified = False
|
||||
|
||||
# Simple sentence splitting (naive, but sufficient for MVP)
|
||||
sentences = [s.strip() for s in re.split(r'[.!?]\s+', response_text) if s.strip()]
|
||||
|
||||
for sent in sentences:
|
||||
# Check if sentence is a claim we can verify
|
||||
matched_source = None
|
||||
for claim_substr, source_ref in verified_sources.items():
|
||||
if claim_substr.lower() in sent.lower():
|
||||
matched_source = source_ref
|
||||
break
|
||||
|
||||
if matched_source:
|
||||
# Verified claim
|
||||
claim = Claim(
|
||||
text=sent,
|
||||
source_type="verified",
|
||||
source_ref=matched_source,
|
||||
confidence="high",
|
||||
hedged=False,
|
||||
)
|
||||
else:
|
||||
# Inferred claim (pattern-matched)
|
||||
claim = Claim(
|
||||
text=sent,
|
||||
source_type="inferred",
|
||||
confidence=self.default_confidence,
|
||||
hedged=self._has_hedge(sent),
|
||||
)
|
||||
if not claim.hedged:
|
||||
has_unverified = True
|
||||
|
||||
claims.append(claim)
|
||||
|
||||
# Render the annotated response
|
||||
rendered = self._render_response(claims)
|
||||
|
||||
return AnnotatedResponse(
|
||||
original_text=response_text,
|
||||
claims=claims,
|
||||
rendered_text=rendered,
|
||||
has_unverified=has_unverified,
|
||||
)
|
||||
|
||||
def _has_hedge(self, text: str) -> bool:
|
||||
"""Check if text already contains hedging language."""
|
||||
text_lower = text.lower()
|
||||
for prefix in self.HEDGE_PREFIXES:
|
||||
if text_lower.startswith(prefix.lower()):
|
||||
return True
|
||||
# Also check for inline hedges
|
||||
hedge_words = ["i think", "i believe", "probably", "likely", "maybe", "perhaps"]
|
||||
return any(word in text_lower for word in hedge_words)
|
||||
|
||||
def _render_response(self, claims: List[Claim]) -> str:
|
||||
"""
|
||||
Render response with source distinction markers.
|
||||
|
||||
Verified claims: [V] claim text [source: ref]
|
||||
Inferred claims: [I] claim text (or with hedging if missing)
|
||||
"""
|
||||
rendered_parts = []
|
||||
for claim in claims:
|
||||
if claim.source_type == "verified":
|
||||
part = f"[V] {claim.text}"
|
||||
if claim.source_ref:
|
||||
part += f" [source: {claim.source_ref}]"
|
||||
else: # inferred
|
||||
if not claim.hedged:
|
||||
# Add hedging if missing
|
||||
hedged_text = f"I think {claim.text[0].lower()}{claim.text[1:]}" if claim.text else claim.text
|
||||
part = f"[I] {hedged_text}"
|
||||
else:
|
||||
part = f"[I] {claim.text}"
|
||||
rendered_parts.append(part)
|
||||
return " ".join(rendered_parts)
|
||||
|
||||
def to_json(self, annotated: AnnotatedResponse) -> str:
|
||||
"""Serialize annotated response to JSON."""
|
||||
return json.dumps(
|
||||
{
|
||||
"original_text": annotated.original_text,
|
||||
"rendered_text": annotated.rendered_text,
|
||||
"has_unverified": annotated.has_unverified,
|
||||
"claims": [asdict(c) for c in annotated.claims],
|
||||
},
|
||||
indent=2,
|
||||
ensure_ascii=False,
|
||||
)
|
||||
@@ -1,14 +1,20 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
from pathlib import Path
|
||||
from unittest.mock import patch
|
||||
|
||||
import yaml
|
||||
|
||||
from scripts.bezalel_gemma4_vps import (
|
||||
DEFAULT_CONFIG_PATH,
|
||||
DEFAULT_BEZALEL_VPS_HOST,
|
||||
build_deploy_mutation,
|
||||
build_runpod_endpoint,
|
||||
build_vps_verify_command,
|
||||
normalize_openai_base_url,
|
||||
parse_deploy_response,
|
||||
resolve_base_url,
|
||||
update_config_text,
|
||||
verify_openai_chat,
|
||||
)
|
||||
@@ -28,6 +34,10 @@ class _FakeResponse:
|
||||
return False
|
||||
|
||||
|
||||
def test_default_config_path_targets_bezalel_vps_root_config() -> None:
|
||||
assert DEFAULT_CONFIG_PATH == Path("/root/wizards/bezalel/home/config.yaml")
|
||||
|
||||
|
||||
def test_build_deploy_mutation_uses_ollama_image_and_openai_port() -> None:
|
||||
query = build_deploy_mutation(name="bezalel-gemma4", gpu_type="NVIDIA L40S", model_tag="gemma4:latest")
|
||||
|
||||
@@ -37,6 +47,30 @@ def test_build_deploy_mutation_uses_ollama_image_and_openai_port() -> None:
|
||||
assert 'volumeMountPath: "/root/.ollama"' in query
|
||||
|
||||
|
||||
def test_normalize_openai_base_url_adds_v1_suffix() -> None:
|
||||
assert normalize_openai_base_url("https://pod-11434.proxy.runpod.net") == "https://pod-11434.proxy.runpod.net/v1"
|
||||
|
||||
|
||||
def test_normalize_openai_base_url_trims_chat_completions_suffix() -> None:
|
||||
assert normalize_openai_base_url("https://pod-11434.proxy.runpod.net/v1/chat/completions") == "https://pod-11434.proxy.runpod.net/v1"
|
||||
|
||||
|
||||
def test_resolve_base_url_prefers_vertex_over_base_and_pod_id() -> None:
|
||||
base_url, source = resolve_base_url(
|
||||
vertex_base_url="https://vertex.example.com/openai",
|
||||
base_url="https://plain.example.com",
|
||||
pod_id="abc123",
|
||||
)
|
||||
assert source == "vertex_base_url"
|
||||
assert base_url == "https://vertex.example.com/openai/v1"
|
||||
|
||||
|
||||
def test_resolve_base_url_falls_back_to_base_url_before_pod_id() -> None:
|
||||
base_url, source = resolve_base_url(base_url="https://plain.example.com", pod_id="abc123")
|
||||
assert source == "base_url"
|
||||
assert base_url == "https://plain.example.com/v1"
|
||||
|
||||
|
||||
def test_build_runpod_endpoint_appends_v1_suffix() -> None:
|
||||
assert build_runpod_endpoint("abc123") == "https://abc123-11434.proxy.runpod.net/v1"
|
||||
|
||||
@@ -60,7 +94,7 @@ def test_parse_deploy_response_extracts_pod_id_and_endpoint() -> None:
|
||||
}
|
||||
|
||||
|
||||
def test_update_config_text_upserts_big_brain_provider() -> None:
|
||||
def test_update_config_text_upserts_big_brain_provider_and_normalizes_base_url() -> None:
|
||||
original = """
|
||||
model:
|
||||
default: kimi-k2.5
|
||||
@@ -72,7 +106,7 @@ custom_providers:
|
||||
model: gemma3:27b
|
||||
"""
|
||||
|
||||
updated = update_config_text(original, base_url="https://new-pod-11434.proxy.runpod.net/v1", model="gemma4:latest")
|
||||
updated = update_config_text(original, base_url="https://new-pod-11434.proxy.runpod.net", model="gemma4:latest")
|
||||
parsed = yaml.safe_load(updated)
|
||||
|
||||
assert parsed["model"] == {"default": "kimi-k2.5", "provider": "kimi-coding"}
|
||||
@@ -86,7 +120,14 @@ custom_providers:
|
||||
]
|
||||
|
||||
|
||||
def test_verify_openai_chat_calls_chat_completions() -> None:
|
||||
def test_build_vps_verify_command_targets_bezalel_host_and_chat_completions() -> None:
|
||||
command = build_vps_verify_command(base_url="https://pod-11434.proxy.runpod.net", model="gemma4:latest")
|
||||
assert command.startswith(f"ssh root@{DEFAULT_BEZALEL_VPS_HOST} ")
|
||||
assert "/v1/chat/completions" in command
|
||||
assert "gemma4:latest" in command
|
||||
|
||||
|
||||
def test_verify_openai_chat_calls_chat_completions_with_normalized_base_url() -> None:
|
||||
response_payload = {
|
||||
"choices": [
|
||||
{
|
||||
@@ -101,7 +142,7 @@ def test_verify_openai_chat_calls_chat_completions() -> None:
|
||||
"scripts.bezalel_gemma4_vps.request.urlopen",
|
||||
return_value=_FakeResponse(response_payload),
|
||||
) as mocked:
|
||||
result = verify_openai_chat("https://pod-11434.proxy.runpod.net/v1", model="gemma4:latest", prompt="say READY")
|
||||
result = verify_openai_chat("https://pod-11434.proxy.runpod.net", model="gemma4:latest", prompt="say READY")
|
||||
|
||||
assert result == "READY"
|
||||
req = mocked.call_args.args[0]
|
||||
@@ -109,3 +150,10 @@ def test_verify_openai_chat_calls_chat_completions() -> None:
|
||||
payload = json.loads(req.data.decode())
|
||||
assert payload["model"] == "gemma4:latest"
|
||||
assert payload["messages"][0]["content"] == "say READY"
|
||||
|
||||
|
||||
def test_readme_documents_root_config_path_and_vps_proof_command() -> None:
|
||||
readme = Path("scripts/README_bezalel_gemma4_vps.md").read_text()
|
||||
assert "/root/wizards/bezalel/home/config.yaml" in readme
|
||||
assert "ssh root@104.131.15.18" in readme
|
||||
assert "--vertex-base-url" in readme
|
||||
|
||||
@@ -1,103 +0,0 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Tests for claim_annotator.py — verifies source distinction is present."""
|
||||
|
||||
import sys
|
||||
import os
|
||||
import json
|
||||
|
||||
sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "src"))
|
||||
|
||||
from timmy.claim_annotator import ClaimAnnotator, AnnotatedResponse
|
||||
|
||||
|
||||
def test_verified_claim_has_source():
|
||||
"""Verified claims include source reference."""
|
||||
annotator = ClaimAnnotator()
|
||||
verified = {"Paris is the capital of France": "https://en.wikipedia.org/wiki/Paris"}
|
||||
response = "Paris is the capital of France. It is a beautiful city."
|
||||
|
||||
result = annotator.annotate_claims(response, verified_sources=verified)
|
||||
assert len(result.claims) > 0
|
||||
verified_claims = [c for c in result.claims if c.source_type == "verified"]
|
||||
assert len(verified_claims) == 1
|
||||
assert verified_claims[0].source_ref == "https://en.wikipedia.org/wiki/Paris"
|
||||
assert "[V]" in result.rendered_text
|
||||
assert "[source:" in result.rendered_text
|
||||
|
||||
|
||||
def test_inferred_claim_has_hedging():
|
||||
"""Pattern-matched claims use hedging language."""
|
||||
annotator = ClaimAnnotator()
|
||||
response = "The weather is nice today. It might rain tomorrow."
|
||||
|
||||
result = annotator.annotate_claims(response)
|
||||
inferred_claims = [c for c in result.claims if c.source_type == "inferred"]
|
||||
assert len(inferred_claims) >= 1
|
||||
# Check that rendered text has [I] marker
|
||||
assert "[I]" in result.rendered_text
|
||||
# Check that unhedged inferred claims get hedging
|
||||
assert "I think" in result.rendered_text or "I believe" in result.rendered_text
|
||||
|
||||
|
||||
def test_hedged_claim_not_double_hedged():
|
||||
"""Claims already with hedging are not double-hedged."""
|
||||
annotator = ClaimAnnotator()
|
||||
response = "I think the sky is blue. It is a nice day."
|
||||
|
||||
result = annotator.annotate_claims(response)
|
||||
# The "I think" claim should not become "I think I think ..."
|
||||
assert "I think I think" not in result.rendered_text
|
||||
|
||||
|
||||
def test_rendered_text_distinguishes_types():
|
||||
"""Rendered text clearly distinguishes verified vs inferred."""
|
||||
annotator = ClaimAnnotator()
|
||||
verified = {"Earth is round": "https://science.org/earth"}
|
||||
response = "Earth is round. Stars are far away."
|
||||
|
||||
result = annotator.annotate_claims(response, verified_sources=verified)
|
||||
assert "[V]" in result.rendered_text # verified marker
|
||||
assert "[I]" in result.rendered_text # inferred marker
|
||||
|
||||
|
||||
def test_to_json_serialization():
|
||||
"""Annotated response serializes to valid JSON."""
|
||||
annotator = ClaimAnnotator()
|
||||
response = "Test claim."
|
||||
result = annotator.annotate_claims(response)
|
||||
json_str = annotator.to_json(result)
|
||||
parsed = json.loads(json_str)
|
||||
assert "claims" in parsed
|
||||
assert "rendered_text" in parsed
|
||||
assert parsed["has_unverified"] is True # inferred claim without hedging
|
||||
|
||||
|
||||
def test_audit_trail_integration():
|
||||
"""Check that claims are logged with confidence and source type."""
|
||||
# This test verifies the audit trail integration point
|
||||
annotator = ClaimAnnotator()
|
||||
verified = {"AI is useful": "https://example.com/ai"}
|
||||
response = "AI is useful. It can help with tasks."
|
||||
|
||||
result = annotator.annotate_claims(response, verified_sources=verified)
|
||||
for claim in result.claims:
|
||||
assert claim.source_type in ("verified", "inferred")
|
||||
assert claim.confidence in ("high", "medium", "low", "unknown")
|
||||
if claim.source_type == "verified":
|
||||
assert claim.source_ref is not None
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
test_verified_claim_has_source()
|
||||
print("✓ test_verified_claim_has_source passed")
|
||||
test_inferred_claim_has_hedging()
|
||||
print("✓ test_inferred_claim_has_hedging passed")
|
||||
test_hedged_claim_not_double_hedged()
|
||||
print("✓ test_hedged_claim_not_double_hedged passed")
|
||||
test_rendered_text_distinguishes_types()
|
||||
print("✓ test_rendered_text_distinguishes_types passed")
|
||||
test_to_json_serialization()
|
||||
print("✓ test_to_json_serialization passed")
|
||||
test_audit_trail_integration()
|
||||
print("✓ test_audit_trail_integration passed")
|
||||
print("\nAll tests passed!")
|
||||
Reference in New Issue
Block a user