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/chat/routes.ts

@@ -0,0 +1,128 @@
+/**
+ * Chat module — LLM completions (sync + streaming SSE)
+ * Ported from apps/chat/apps/server
+ *
+ * CRUD for conversations/messages handled by mana-sync.
+ * This module handles AI completions via mana-llm or OpenRouter.
+ */
+
+import { Hono } from 'hono';
+import { streamSSE } from 'hono/streaming';
+import { consumeCredits, validateCredits } from '@manacore/shared-hono/credits';
+
+const LLM_URL = process.env.MANA_LLM_URL || 'http://localhost:3025';
+
+const routes = new Hono();
+
+// ─── Chat Completion (sync) ──────────────────────────────────
+
+routes.post('/completions', async (c) => {
+	const userId = c.get('userId');
+	const { messages, model, temperature, maxTokens } = await c.req.json();
+
+	if (!messages?.length) return c.json({ error: 'messages required' }, 400);
+
+	const isLocal = !model || model.startsWith('ollama/') || model.startsWith('local/');
+	const cost = isLocal ? 0.1 : 5;
+
+	const validation = await validateCredits(userId, 'AI_CHAT', cost);
+	if (!validation.hasCredits) {
+		return c.json({ error: 'Insufficient credits', required: cost }, 402);
+	}
+
+	try {
+		const llmRes = await fetch(`${LLM_URL}/api/v1/chat/completions`, {
+			method: 'POST',
+			headers: { 'Content-Type': 'application/json' },
+			body: JSON.stringify({
+				messages,
+				model: model || 'gemma3:4b',
+				temperature: temperature || 0.7,
+				max_tokens: maxTokens || 2000,
+			}),
+		});
+
+		if (!llmRes.ok) return c.json({ error: 'LLM request failed' }, 502);
+
+		const data = await llmRes.json();
+		await consumeCredits(userId, 'AI_CHAT', cost, `Chat: ${model || 'gemma3:4b'}`);
+
+		return c.json(data);
+	} catch (_err) {
+		return c.json({ error: 'Chat completion failed' }, 500);
+	}
+});
+
+// ─── Chat Completion (streaming SSE) ─────────────────────────
+
+routes.post('/completions/stream', async (c) => {
+	const userId = c.get('userId');
+	const { messages, model, temperature, maxTokens } = await c.req.json();
+
+	if (!messages?.length) return c.json({ error: 'messages required' }, 400);
+
+	const isLocal = !model || model.startsWith('ollama/') || model.startsWith('local/');
+	const cost = isLocal ? 0.1 : 5;
+
+	const validation = await validateCredits(userId, 'AI_CHAT', cost);
+	if (!validation.hasCredits) {
+		return c.json({ error: 'Insufficient credits' }, 402);
+	}
+
+	return streamSSE(c, async (stream) => {
+		try {
+			const llmRes = await fetch(`${LLM_URL}/api/v1/chat/completions`, {
+				method: 'POST',
+				headers: { 'Content-Type': 'application/json' },
+				body: JSON.stringify({
+					messages,
+					model: model || 'gemma3:4b',
+					temperature: temperature || 0.7,
+					max_tokens: maxTokens || 2000,
+					stream: true,
+				}),
+			});
+
+			if (!llmRes.ok || !llmRes.body) {
+				await stream.writeSSE({ data: JSON.stringify({ error: 'LLM failed' }) });
+				return;
+			}
+
+			const reader = llmRes.body.getReader();
+			const decoder = new TextDecoder();
+
+			while (true) {
+				const { done, value } = await reader.read();
+				if (done) break;
+				const chunk = decoder.decode(value, { stream: true });
+				// Forward SSE chunks directly
+				for (const line of chunk.split('\n')) {
+					if (line.startsWith('data: ')) {
+						await stream.writeSSE({ data: line.slice(6) });
+					}
+				}
+			}
+
+			await stream.writeSSE({ data: '[DONE]' });
+			consumeCredits(userId, 'AI_CHAT', cost, `Chat stream: ${model || 'gemma3:4b'}`).catch(
+				() => {}
+			);
+		} catch (_err) {
+			await stream.writeSSE({ data: JSON.stringify({ error: 'Stream failed' }) });
+		}
+	});
+});
+
+// ─── Models List ─────────────────────────────────────────────
+
+routes.get('/models', async (c) => {
+	try {
+		const res = await fetch(`${LLM_URL}/api/v1/models`);
+		if (res.ok) return c.json(await res.json());
+	} catch {
+		// Fallback
+	}
+	return c.json({ models: [] });
+});
+
+export { routes as chatRoutes };