phase 3

2026-03-23 14:42:36 -03:00
parent 71fd0510de
commit 5ed876d694
17 changed files with 767 additions and 137 deletions
--- a/tests/detect/manual/push_logs.py
+++ b/tests/detect/manual/push_logs.py
@@ -0,0 +1,98 @@
+#!/usr/bin/env python3
+"""
+Push a stream of log events to Redis for UI testing.
+
+Usage:
+    python tests/detect/manual/push_logs.py [--job JOB_ID] [--port PORT] [--count N] [--delay SECS]
+
+Opens: http://mpr.local.ar/detection/?job=<JOB_ID>
+"""
+
+import argparse
+import json
+import random
+import time
+from datetime import datetime, timezone
+
+import redis
+
+STAGES = ["FrameExtractor", "SceneFilter", "YOLODetector", "OCRStage", "BrandResolver", "VLMLocal", "Aggregator"]
+LEVELS = ["INFO", "INFO", "INFO", "INFO", "WARNING", "DEBUG", "ERROR"]  # weighted toward INFO
+MESSAGES = {
+    "FrameExtractor": [
+        "Starting extraction: sample.mp4 (120.0s, 1920x1080, fps=2)",
+        "Extracted 240 frames",
+        "Frame extraction complete",
+    ],
+    "SceneFilter": [
+        "Filtering duplicate scenes (hamming_threshold=8)",
+        "Removed 180 duplicate frames",
+        "Kept 60 unique frames (75% reduction)",
+    ],
+    "YOLODetector": [
+        "Loading yolov8n.pt (fp16)",
+        "Processing batch 1/3 (20 frames)",
+        "Processing batch 2/3 (20 frames)",
+        "Processing batch 3/3 (20 frames)",
+        "Detected 45 regions across 60 frames",
+    ],
+    "OCRStage": [
+        "Running PaddleOCR on 45 regions",
+        "Extracted text from 32 regions",
+        "Resolved 28 brands via OCR",
+    ],
+    "BrandResolver": [
+        "Matching against brand dictionary (12 brands)",
+        "Exact matches: 20, Fuzzy matches: 8",
+        "Unresolved: 4 regions → escalating to VLM",
+    ],
+    "VLMLocal": [
+        "Loading moondream2 (int4, 2.1GB VRAM)",
+        "Processing 4 unresolved crops",
+        "Resolved 3/4 crops, 1 → cloud escalation",
+    ],
+    "Aggregator": [
+        "Compiling detection report",
+        "Found 6 unique brands, 31 total appearances",
+        "Report complete",
+    ],
+}
+
+
+def main():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--job", default="manual-test")
+    parser.add_argument("--port", type=int, default=6382)
+    parser.add_argument("--count", type=int, default=50)
+    parser.add_argument("--delay", type=float, default=0.2)
+    args = parser.parse_args()
+
+    r = redis.Redis(port=args.port, decode_responses=True)
+    key = f"detect_events:{args.job}"
+
+    print(f"Pushing {args.count} log events to {key} (redis port {args.port})")
+    print(f"Open: http://mpr.local.ar/detection/?job={args.job}")
+    print()
+
+    for i in range(args.count):
+        stage = random.choice(STAGES)
+        level = random.choice(LEVELS)
+        msg = random.choice(MESSAGES[stage])
+
+        event = {
+            "event": "log",
+            "level": level,
+            "stage": stage,
+            "msg": f"[{i+1}/{args.count}] {msg}",
+            "ts": datetime.now(timezone.utc).isoformat(),
+        }
+
+        r.rpush(key, json.dumps(event))
+        print(f"  {level:7s} {stage:16s} {msg[:60]}")
+        time.sleep(args.delay)
+
+    print(f"\nDone. {args.count} events pushed.")
+
+
+if __name__ == "__main__":
+    main()