feat(apps): create Hono compute servers for Traces, Planta, NutriPhi

Add lightweight Hono + Bun servers for server-only compute endpoints.
CRUD is handled by mana-sync, these handle AI + file upload only.

Traces: AI guide generation, location sync (Port 3026)
Planta: Photo upload (S3), AI plant analysis (Port 3022)
NutriPhi: AI meal analysis (photo+text), recommendations (Port 3023)

Each uses @manacore/shared-hono for auth/health/errors. ~100-200 LOC.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

apps/nutriphi/apps/server/package.json

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+{
+	"name": "@nutriphi/server",
+	"version": "0.1.0",
+	"private": true,
+	"type": "module",
+	"scripts": {
+		"dev": "bun run --watch src/index.ts",
+		"start": "bun run src/index.ts"
+	},
+	"dependencies": {
+		"@manacore/shared-hono": "workspace:*",
+		"hono": "^4.7.0"
+	},
+	"devDependencies": {
+		"typescript": "^5.9.3"
+	}
+}

apps/nutriphi/apps/server/src/index.ts

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+/**
+ * NutriPhi Hono Server — Compute-only endpoints
+ *
+ * Server-side logic:
+ * - AI meal analysis (photo + text) via mana-llm (Gemini)
+ * - Nutritional recommendations engine
+ *
+ * CRUD for meals, goals, favorites handled by mana-sync.
+ */
+
+import { Hono } from 'hono';
+import { cors } from 'hono/cors';
+import { authMiddleware, healthRoute, errorHandler, notFoundHandler } from '@manacore/shared-hono';
+
+const PORT = parseInt(process.env.PORT || '3023', 10);
+const LLM_URL = process.env.MANA_LLM_URL || 'http://localhost:3025';
+const CORS_ORIGINS = (process.env.CORS_ORIGINS || 'http://localhost:5180').split(',');
+
+const ANALYSIS_PROMPT = `Du bist ein Ernährungsexperte. Analysiere die Mahlzeit und gib ein JSON zurück mit:
+{
+  "foods": [{"name": "...", "quantity": "...", "calories": 0}],
+  "totalNutrition": {"calories": 0, "protein": 0, "carbohydrates": 0, "fat": 0, "fiber": 0, "sugar": 0},
+  "description": "Kurze Beschreibung der Mahlzeit",
+  "confidence": 0.0-1.0,
+  "warnings": [],
+  "suggestions": []
+}`;
+
+const app = new Hono();
+
+app.onError(errorHandler);
+app.notFound(notFoundHandler);
+app.use('*', cors({ origin: CORS_ORIGINS, credentials: true }));
+app.route('/health', healthRoute('nutriphi-server'));
+app.use('/api/*', authMiddleware());
+
+// ─── Photo Analysis (server-only: Gemini Vision) ────────────
+
+app.post('/api/v1/analysis/photo', async (c) => {
+	const { imageBase64, mimeType } = await c.req.json();
+	if (!imageBase64) return c.json({ error: 'imageBase64 required' }, 400);
+
+	try {
+		const res = await fetch(`${LLM_URL}/api/v1/chat/completions`, {
+			method: 'POST',
+			headers: { 'Content-Type': 'application/json' },
+			body: JSON.stringify({
+				messages: [
+					{ role: 'system', content: ANALYSIS_PROMPT },
+					{
+						role: 'user',
+						content: [
+							{ type: 'text', text: 'Analysiere diese Mahlzeit.' },
+							{
+								type: 'image_url',
+								image_url: { url: `data:${mimeType || 'image/jpeg'};base64,${imageBase64}` },
+							},
+						],
+					},
+				],
+				model: process.env.GEMINI_MODEL || 'gemini-2.0-flash',
+				response_format: { type: 'json_object' },
+				temperature: 0.3,
+			}),
+		});
+
+		if (!res.ok) return c.json({ error: 'AI analysis failed' }, 502);
+
+		const data = await res.json();
+		const content = data.choices?.[0]?.message?.content;
+		const analysis = typeof content === 'string' ? JSON.parse(content) : content;
+
+		return c.json(analysis);
+	} catch (err) {
+		console.error('Photo analysis failed:', err);
+		return c.json({ error: 'Analysis failed' }, 500);
+	}
+});
+
+// ─── Text Analysis (server-only: Gemini) ─────────────────────
+
+app.post('/api/v1/analysis/text', async (c) => {
+	const { description } = await c.req.json();
+	if (!description) return c.json({ error: 'description required' }, 400);
+
+	try {
+		const res = await fetch(`${LLM_URL}/api/v1/chat/completions`, {
+			method: 'POST',
+			headers: { 'Content-Type': 'application/json' },
+			body: JSON.stringify({
+				messages: [
+					{ role: 'system', content: ANALYSIS_PROMPT },
+					{ role: 'user', content: `Analysiere diese Mahlzeit: ${description}` },
+				],
+				model: process.env.GEMINI_MODEL || 'gemini-2.0-flash',
+				response_format: { type: 'json_object' },
+				temperature: 0.3,
+			}),
+		});
+
+		if (!res.ok) return c.json({ error: 'AI analysis failed' }, 502);
+
+		const data = await res.json();
+		const content = data.choices?.[0]?.message?.content;
+		const analysis = typeof content === 'string' ? JSON.parse(content) : content;
+
+		return c.json(analysis);
+	} catch (err) {
+		console.error('Text analysis failed:', err);
+		return c.json({ error: 'Analysis failed' }, 500);
+	}
+});
+
+// ─── Recommendations (server-only: rule engine) ──────────────
+
+app.post('/api/v1/recommendations/generate', async (c) => {
+	const { dailyNutrition } = await c.req.json();
+	const hints: Array<{ type: string; priority: string; message: string; nutrient?: string }> = [];
+
+	if (dailyNutrition) {
+		if (dailyNutrition.protein < 25) {
+			hints.push({
+				type: 'hint',
+				priority: 'medium',
+				message:
+					'Deine Proteinzufuhr ist niedrig. Versuche Hülsenfrüchte, Eier oder Joghurt einzubauen.',
+				nutrient: 'protein',
+			});
+		}
+		if (dailyNutrition.fiber < 10) {
+			hints.push({
+				type: 'hint',
+				priority: 'medium',
+				message: 'Mehr Ballaststoffe! Vollkornprodukte, Gemüse und Obst helfen.',
+				nutrient: 'fiber',
+			});
+		}
+		if (dailyNutrition.sugar > 50) {
+			hints.push({
+				type: 'hint',
+				priority: 'high',
+				message:
+					'Dein Zuckerkonsum ist hoch. Achte auf versteckten Zucker in Getränken und Fertigprodukten.',
+				nutrient: 'sugar',
+			});
+		}
+	}
+
+	return c.json({ recommendations: hints });
+});
+
+console.log(`nutriphi-server starting on port ${PORT}...`);
+
+export default { port: PORT, fetch: app.fetch };

apps/nutriphi/apps/server/tsconfig.json

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+{
+	"compilerOptions": {
+		"target": "ESNext",
+		"module": "ESNext",
+		"moduleResolution": "bundler",
+		"strict": true,
+		"esModuleInterop": true,
+		"skipLibCheck": true
+	},
+	"include": ["src/**/*.ts"]
+}