feat(api): port remaining 12 modules to unified API server

Complete consolidation of all 15 app servers into one Hono/Bun process.

Modules added: chat, context, picture, storage, todo, planta, nutriphi,
guides, moodlit, news, traces, presi

Total: 15 modules, one server, one port (3050), ~2400 LOC.

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

apps/api/src/modules/planta/routes.ts

@@ -0,0 +1,89 @@
+/**
+ * Planta module — Photo upload + AI plant analysis
+ * Ported from apps/planta/apps/server
+ *
+ * CRUD for plants, photos, watering handled by mana-sync.
+ * This module handles S3 uploads and Gemini Vision analysis.
+ */
+
+import { Hono } from 'hono';
+
+const LLM_URL = process.env.MANA_LLM_URL || 'http://localhost:3025';
+
+const routes = new Hono();
+
+// ─── Photo Upload (server-only: S3 storage) ─────────────────
+
+routes.post('/photos/upload', async (c) => {
+	const userId = c.get('userId');
+	const formData = await c.req.formData();
+	const file = formData.get('file') as File | null;
+	const plantId = formData.get('plantId') as string | null;
+
+	if (!file) return c.json({ error: 'No file provided' }, 400);
+	if (file.size > 10 * 1024 * 1024) return c.json({ error: 'File too large (max 10MB)' }, 400);
+
+	try {
+		const { createPlantaStorage, generateUserFileKey, getContentType } = await import(
+			'@manacore/shared-storage'
+		);
+		const storage = createPlantaStorage();
+		const key = generateUserFileKey(userId, file.name);
+		const buffer = Buffer.from(await file.arrayBuffer());
+
+		const result = await storage.upload(key, buffer, {
+			contentType: getContentType(file.name),
+			public: true,
+		});
+
+		return c.json({ storagePath: key, publicUrl: result.url, plantId }, 201);
+	} catch (err) {
+		console.error('Upload failed:', err);
+		return c.json({ error: 'Upload failed' }, 500);
+	}
+});
+
+// ─── AI Analysis (server-only: Gemini Vision) ───────────────
+
+routes.post('/analysis/identify', async (c) => {
+	const { photoUrl } = await c.req.json();
+	if (!photoUrl) return c.json({ error: 'photoUrl 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:
+							'Du bist ein Pflanzenexperte. Analysiere das Bild und gib JSON zurück: {scientificName, commonNames[], confidence, healthAssessment, wateringAdvice, lightAdvice, generalTips[]}',
+					},
+					{
+						role: 'user',
+						content: [
+							{ type: 'text', text: 'Analysiere diese Pflanze.' },
+							{ type: 'image_url', image_url: { url: photoUrl } },
+						],
+					},
+				],
+				model: process.env.VISION_MODEL || 'gemini-2.0-flash',
+				response_format: { type: 'json_object' },
+			}),
+		});
+
+		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('Analysis failed:', err);
+		return c.json({ error: 'Analysis failed' }, 500);
+	}
+});
+
+export { routes as plantaRoutes };