ashim/tests/e2e-docker/full-tool-audit.mjs
Ashim 08a7ffe403 Enhance logging and error handling across tools; add full tool audit and Playwright tests
- Added model mismatch warnings in colorize, enhance-faces, and upscale routes.
- Improved error handling in colorize, enhance_faces, remove_bg, restore, and upscale scripts with detailed logging.
- Updated Dockerfile to align NCCL versions for compatibility.
- Introduced a new full tool audit script to test all tools for functionality and GPU usage.
- Created Playwright E2E tests for GPU-dependent tools to ensure proper functionality and performance.
2026-04-17 23:06:31 +08:00

248 lines
13 KiB
JavaScript

/**
* FULL TOOL AUDIT — Tests every tool in ashim on Windows/amd64.
* Verifies: (1) tool works, (2) GPU tools use GPU not CPU fallback,
* (3) no unexpected model/method downgrades.
*/
const BASE = "http://localhost:1349";
const USERNAME = "admin";
const PASSWORD = "qFIJS2KcQ0NuUfZ0";
const IMG = "C:/Users/siddh/Downloads/passport-photo-sample-correct.webp";
import { readFileSync, writeFileSync } from "fs";
const results = [];
let token = "";
function log(tool, status, detail = "") {
const icon = status === "PASS" ? "\u2713" : status === "FAIL" ? "\u2717" : "-";
const line = `${icon} [${status}] ${tool}${detail ? " -- " + detail : ""}`;
console.log(line);
results.push({ tool, status, detail });
}
async function callTool(path, settings, filename = "test.webp") {
const imageBuffer = readFileSync(IMG);
const imageBlob = new Blob([imageBuffer], { type: "image/webp" });
const formData = new FormData();
formData.append("file", new File([imageBlob], filename, { type: "image/webp" }));
formData.append("settings", JSON.stringify(settings));
const res = await fetch(`${BASE}/api/v1/tools/${path}`, {
method: "POST",
headers: { Authorization: `Bearer ${token}` },
body: formData,
});
const body = await res.json().catch(() => ({ error: `HTTP ${res.status} (non-JSON)` }));
return { status: res.status, ok: res.ok, body };
}
async function test(name, path, settings, checks = {}) {
try {
const { status, ok, body } = await callTool(path, settings);
if (!ok || body.error) {
log(name, "FAIL", body.details || body.error || `HTTP ${status}`);
return;
}
// Check expected model/method
if (checks.expectKey && checks.expectValue) {
const actual = body[checks.expectKey];
if (actual !== checks.expectValue) {
log(name, "FAIL", `Expected ${checks.expectKey}=${checks.expectValue} but got ${actual} (FALLBACK DETECTED)`);
return;
}
}
// Build detail string
const parts = [];
for (const k of ["method", "model", "engine", "format", "width", "height", "facesDetected", "steps"]) {
if (body[k] !== undefined) {
const v = Array.isArray(body[k]) ? JSON.stringify(body[k]) : body[k];
parts.push(`${k}=${v}`);
}
}
log(name, "PASS", parts.join(", "));
} catch (err) {
log(name, "FAIL", err.message.slice(0, 200));
}
}
async function main() {
console.log("=============================================================");
console.log(" ASHIM FULL TOOL AUDIT — Windows amd64 + RTX 4070");
console.log("=============================================================\n");
// Login
const loginRes = await fetch(`${BASE}/api/auth/login`, {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({ username: USERNAME, password: PASSWORD }),
});
const loginBody = await loginRes.json();
token = loginBody.token;
console.log("Authenticated.\n");
// Check GPU status
const healthRes = await fetch(`${BASE}/api/v1/admin/health`, {
headers: { Authorization: `Bearer ${token}` },
});
const health = await healthRes.json();
console.log(`GPU detected: ${health.ai?.gpu}`);
console.log(`Version: ${health.version}\n`);
// ════════════════════════════════════════════════════════════════
// SECTION 1: GPU/AI TOOLS — verify correct model, no fallbacks
// ════════════════════════════════════════════════════════════════
console.log("--- GPU/AI TOOLS (must use GPU, no CPU fallback) ---\n");
// Background removal — all models
await test("Remove BG (birefnet-general-lite)", "remove-background", { model: "birefnet-general-lite" }, { expectKey: "model", expectValue: "birefnet-general-lite" });
await test("Remove BG (birefnet-portrait)", "remove-background", { model: "birefnet-portrait" }, { expectKey: "model", expectValue: "birefnet-portrait" });
await test("Remove BG (birefnet-general)", "remove-background", { model: "birefnet-general" }, { expectKey: "model", expectValue: "birefnet-general" });
await test("Remove BG (u2net)", "remove-background", { model: "u2net" }, { expectKey: "model", expectValue: "u2net" });
await test("Remove BG (bria-rmbg)", "remove-background", { model: "bria-rmbg" }, { expectKey: "model", expectValue: "bria-rmbg" });
await test("Remove BG (isnet-general-use)", "remove-background", { model: "isnet-general-use" }, { expectKey: "model", expectValue: "isnet-general-use" });
await test("Remove BG (birefnet-matting/Ultra)", "remove-background", { model: "birefnet-matting" }, { expectKey: "model", expectValue: "birefnet-matting" });
// Upscale
await test("Upscale (realesrgan 2x)", "upscale", { scale: 2, model: "realesrgan" }, { expectKey: "method", expectValue: "realesrgan" });
await test("Upscale (realesrgan 4x)", "upscale", { scale: 4, model: "realesrgan" }, { expectKey: "method", expectValue: "realesrgan" });
await test("Upscale (lanczos 2x)", "upscale", { scale: 2, model: "lanczos" });
await test("Upscale (auto)", "upscale", { scale: 2, model: "auto" });
// Face enhancement
await test("Face Enhance (gfpgan)", "enhance-faces", { model: "gfpgan" }, { expectKey: "model", expectValue: "gfpgan" });
await test("Face Enhance (codeformer)", "enhance-faces", { model: "codeformer" });
await test("Face Enhance (auto)", "enhance-faces", { model: "auto" });
// Colorize
await test("Colorize (ddcolor)", "colorize", { model: "ddcolor" }, { expectKey: "method", expectValue: "ddcolor" });
await test("Colorize (auto)", "colorize", { model: "auto" });
// Noise removal — all tiers
await test("Noise Removal (quick)", "noise-removal", { tier: "quick" });
await test("Noise Removal (balanced)", "noise-removal", { tier: "balanced" });
await test("Noise Removal (quality/SCUNet)", "noise-removal", { tier: "quality" });
await test("Noise Removal (maximum/NAFNet)", "noise-removal", { tier: "maximum" });
// Photo restoration
await test("Photo Restoration", "restore-photo", {});
// OCR
await test("OCR (tesseract)", "ocr", { engine: "tesseract" }, { expectKey: "engine", expectValue: "tesseract" });
await test("OCR (paddleocr)", "ocr", { engine: "paddleocr" }, { expectKey: "engine", expectValue: "paddleocr-v5" });
// Face operations (MediaPipe)
await test("Face Blur", "blur-faces", { intensity: 50 });
await test("Red-Eye Removal", "red-eye-removal", {});
// Content-aware resize (caire binary)
await test("Content-Aware Resize", "content-aware-resize", { width: 800, height: 800 });
// Erase object (LaMa inpainting — needs mask, likely fails without one)
// Skipping as it needs a mask input
// Smart crop
await test("Smart Crop", "smart-crop", { width: 400, height: 400 });
// ════════════════════════════════════════════════════════════════
// SECTION 2: IMAGE PROCESSING TOOLS (Sharp-based, CPU)
// ════════════════════════════════════════════════════════════════
console.log("\n--- IMAGE PROCESSING TOOLS (Sharp-based) ---\n");
await test("Resize", "resize", { width: 512, height: 512, fit: "cover" });
await test("Crop", "crop", { left: 100, top: 100, width: 500, height: 500 });
await test("Rotate (90)", "rotate", { angle: 90 });
await test("Rotate (45 + fill)", "rotate", { angle: 45, background: "#ffffff" });
await test("Compress (webp q50)", "compress", { quality: 50 });
await test("Convert (to PNG)", "convert", { format: "png" });
await test("Convert (to JPEG)", "convert", { format: "jpg", quality: 85 });
await test("Image Enhancement (auto)", "image-enhancement", { preset: "auto" });
// color-adjustments is part of image-enhancement, not a separate tool
await test("Image Enhancement (vivid)", "image-enhancement", { preset: "vivid" });
await test("Sharpening", "sharpening", { sigma: 1.5, amount: 1.0 });
await test("Border", "border", { size: 20, color: "#ff0000" });
await test("Replace Color", "replace-color", { targetColor: "#ffffff", replacementColor: "#000000", tolerance: 30 });
// ════════════════════════════════════════════════════════════════
// SECTION 3: UTILITY TOOLS
// ════════════════════════════════════════════════════════════════
console.log("\n--- UTILITY TOOLS ---\n");
await test("Info (metadata)", "info", {});
await test("Strip Metadata", "strip-metadata", {});
await test("Image to Base64", "image-to-base64", {});
await test("Optimize for Web", "optimize-for-web", { maxWidth: 1920, quality: 80 });
// Favicon returns binary ICO, not JSON — test via status code only
try {
const imageBuffer = readFileSync(IMG);
const imageBlob = new Blob([imageBuffer], { type: "image/webp" });
const formData = new FormData();
formData.append("file", new File([imageBlob], "test.webp", { type: "image/webp" }));
formData.append("settings", JSON.stringify({}));
const res = await fetch(`${BASE}/api/v1/tools/favicon`, {
method: "POST", headers: { Authorization: `Bearer ${token}` }, body: formData,
});
log("Favicon", res.ok ? "PASS" : "FAIL", `HTTP ${res.status}, ${res.headers.get('content-type')}`);
} catch (e) { log("Favicon", "FAIL", e.message.slice(0, 100)); }
// ════════════════════════════════════════════════════════════════
// SECTION 4: MULTI-IMAGE / SPECIAL TOOLS (may need special input)
// ════════════════════════════════════════════════════════════════
console.log("\n--- SPECIAL TOOLS (may need specific inputs) ---\n");
await test("QR Generate", "qr-generate", { text: "https://ashim.app", size: 512, format: "png" });
await test("Text Overlay", "text-overlay", { text: "TEST", fontSize: 48, color: "#ff0000", position: "center" });
await test("Vectorize", "vectorize", {});
await test("SVG to Raster", "svg-to-raster", {}); // Will fail - needs SVG input
// ════════════════════════════════════════════════════════════════
// SUMMARY
// ════════════════════════════════════════════════════════════════
console.log("\n=============================================================");
console.log(" SUMMARY");
console.log("=============================================================\n");
const passed = results.filter(r => r.status === "PASS");
const failed = results.filter(r => r.status === "FAIL");
console.log(`PASSED: ${passed.length}`);
console.log(`FAILED: ${failed.length}`);
console.log(`TOTAL: ${results.length}\n`);
if (failed.length > 0) {
console.log("FAILURES:");
for (const r of failed) {
// Truncate long error messages
const detail = r.detail.length > 150 ? r.detail.slice(0, 150) + "..." : r.detail;
console.log(` \u2717 ${r.tool}: ${detail}`);
}
}
// Check GPU usage in docker logs
console.log("\n--- GPU USAGE CHECK ---\n");
const { execSync } = await import("child_process");
const logs = execSync('docker logs ashim 2>&1', { encoding: 'utf-8', maxBuffer: 1024 * 1024 });
const gpuLines = logs.split('\n').filter(l =>
l.includes('[gpu]') || l.includes('[bridge]') || l.includes('[dispatcher]') ||
l.includes('GPU') || l.includes('CUDA') || l.includes('CUDAExecution')
);
for (const line of gpuLines.slice(0, 15)) {
console.log(" " + line.trim().slice(0, 120));
}
// Check for any fallback warnings
console.log("\n--- FALLBACK/MISMATCH WARNINGS ---\n");
const warnLines = logs.split('\n').filter(l =>
l.includes('mismatch') || l.includes('fallback') || l.includes('Falling back') ||
l.includes('degraded') || l.includes('lanczos') && l.includes('warn')
);
if (warnLines.length === 0) {
console.log(" None detected - no silent fallbacks occurred.");
} else {
for (const line of warnLines) {
console.log(" WARNING: " + line.trim().slice(0, 150));
}
}
process.exit(failed.length > 0 ? 1 : 0);
}
main().catch(err => { console.error("Fatal:", err); process.exit(1); });