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/context/routes.ts

@@ -0,0 +1,85 @@
+/**
+ * Context module — AI text generation + token estimation
+ * Ported from apps/context/apps/server
+ *
+ * CRUD for spaces/documents handled by mana-sync.
+ */
+
+import { Hono } from 'hono';
+import { consumeCredits, validateCredits } from '@manacore/shared-hono/credits';
+
+const LLM_URL = process.env.MANA_LLM_URL || 'http://localhost:3025';
+
+const routes = new Hono();
+
+// ─── AI Generation (server-only: mana-llm) ──────────────────
+
+routes.post('/ai/generate', async (c) => {
+	const userId = c.get('userId');
+	const { prompt, documents, model, maxTokens } = await c.req.json();
+
+	if (!prompt) return c.json({ error: 'prompt required' }, 400);
+
+	// Validate credits
+	const validation = await validateCredits(userId, 'AI_CONTEXT_GENERATE', 5);
+	if (!validation.hasCredits) {
+		return c.json(
+			{ error: 'Insufficient credits', required: 5, available: validation.availableCredits },
+			402
+		);
+	}
+
+	try {
+		// Build messages with document context
+		const messages: Array<{ role: string; content: string }> = [];
+
+		if (documents?.length) {
+			const contextText = documents
+				.map((d: { title: string; content: string }) => `--- ${d.title} ---\n${d.content}`)
+				.join('\n\n');
+			messages.push({
+				role: 'system',
+				content: `Verwende diese Dokumente als Kontext:\n\n${contextText}`,
+			});
+		}
+
+		messages.push({ role: 'user', content: prompt });
+
+		const res = await fetch(`${LLM_URL}/api/v1/chat/completions`, {
+			method: 'POST',
+			headers: { 'Content-Type': 'application/json' },
+			body: JSON.stringify({
+				messages,
+				model: model || 'gemma3:4b',
+				max_tokens: maxTokens || 2000,
+			}),
+		});
+
+		if (!res.ok) return c.json({ error: 'AI generation failed' }, 502);
+
+		const data = await res.json();
+		const content = data.choices?.[0]?.message?.content || '';
+		const tokensUsed = data.usage?.total_tokens || 0;
+
+		// Consume credits
+		await consumeCredits(userId, 'AI_CONTEXT_GENERATE', 5, `AI generation (${tokensUsed} tokens)`);
+
+		return c.json({ content, tokensUsed, model: model || 'gemma3:4b' });
+	} catch (_err) {
+		return c.json({ error: 'Generation failed' }, 500);
+	}
+});
+
+routes.post('/ai/estimate', async (c) => {
+	const { prompt, documents } = await c.req.json();
+	const charCount =
+		(prompt?.length || 0) +
+		(documents || []).reduce(
+			(sum: number, d: { content: string }) => sum + (d.content?.length || 0),
+			0
+		);
+	const estimatedTokens = Math.ceil(charCount / 4);
+	return c.json({ estimatedTokens, estimatedCost: 5 });
+});
+
+export { routes as contextRoutes };