feat: Add new API endpoints and HTML pages for ML model management

- Implemented HTML pages for datasets, models, training, testing, and results.
- Created API endpoints for managing repositories, results, tests, and training sessions.
- Added functionality for streaming training progress via Server-Sent Events (SSE).
- Introduced a Dockerfile for the ML runner with necessary dependencies.
- Developed an SDK for user code execution within the runner container.
- Enhanced CSS styles for improved UI layout and navigation.
- Established a layout template for consistent HTML structure across pages.
- Added JavaScript for dynamic interactions on the models page.
- Implemented WebSocket handling for real-time communication with kiosk devices and controllers.
- Implemented model registration and management API at /api/models
- Added Gitea proxy API for repository interactions at /api/repos
- Created results API for listing and comparing training results at /api/results
- Developed training management API for enqueueing and retrieving training jobs at /api/trainings
- Introduced SSE endpoint for live training progress updates
- Added HTML pages for models, datasets, and training management
- Created a Dockerfile for the ML runner with necessary dependencies
- Developed SDK for user code execution within the runner container
- Enhanced CSS styles for improved UI/UX
- Implemented WebSocket communication for real-time device and controller interactions in the kiosk system

realtime/src/routes/rules.js

@@ -0,0 +1,57 @@
+/**
+ * Relay HTTP → WS per il push dei rulesets ai sensori.
+ * Chiamato SOLO dal servizio api (internal, x-api-key).
+ *
+ * POST /rules/push
+ *   Body: { sensors: [name, ...], type, ruleset }
+ *   -> invia msgpack { _t: 'ruleset_update', type, ruleset } ad ogni sensore
+ *      online tramite la connessione WS gia' stabilita.
+ */
+
+const router = require('express').Router();
+const { encode } = require('@msgpack/msgpack');
+const { connectedSensors } = require('../ws/handler');
+
+const INTERNAL_KEY = process.env.INTERNAL_API_KEY;
+
+function requireInternal(req, res, next) {
+    const k = req.headers['x-api-key'];
+    if (!INTERNAL_KEY || !k || k !== INTERNAL_KEY) {
+        return res.status(403).json({ error: 'forbidden' });
+    }
+    next();
+}
+
+router.post('/push', requireInternal, (req, res) => {
+    const { sensors, type, ruleset } = req.body || {};
+    if (!Array.isArray(sensors) || !sensors.length) return res.status(400).json({ error: 'sensors array required' });
+    if (!type || !ruleset) return res.status(400).json({ error: 'type and ruleset required' });
+
+    const payload = { _t: 'ruleset_update', type, ruleset };
+    let encoded;
+    try {
+        encoded = encode(payload);
+    } catch (err) {
+        return res.status(500).json({ error: `encode error: ${err.message}` });
+    }
+
+    const pushed = [], offline = [], errors = [];
+    for (const name of sensors) {
+        const ws = connectedSensors.get(name);
+        if (!ws || ws.readyState !== ws.OPEN) {
+            offline.push(name);
+            continue;
+        }
+        try {
+            ws.send(encoded);
+            pushed.push(name);
+        } catch (err) {
+            errors.push({ sensor: name, error: err.message });
+        }
+    }
+
+    console.log(`[RULES] push type=${type} v=${ruleset?.version?.str || '?'} → pushed=${pushed.length} offline=${offline.length} err=${errors.length}`);
+    res.json({ pushed, offline, errors });
+});
+
+module.exports = router;