Bernd Rodler
dda7adf565
Three pieces built together tonight since they're naturally linked (the
server-class proxy is the real entitlement enforcement chokepoint):
1. Multi-key BYOK (public class): several named provider profiles
(name/baseUrl/model), each with its own key in lib/ai/key-store.ts
(keyed by profile id, not a single fixed 'public' slot). The "Try it"
pane lets you pick which saved profile answers each question - not one
fixed default.
2. `server` class, real: app/api/ai/server/{models,chat} proxy through
this app's own backend to AI_SERVER_BASE_URL - same-origin from the
browser, no CORS/OLLAMA_ORIGINS story at all, standing in tonight for
VNC's EU/CH-hosted infra with the real Ollama on this Mac (swapping to
the real instance tomorrow is a config change).
3. Real entitlement enforcement (lib/ai/entitlement.ts), scoped to `server`
only (not local/public, per the 2026-08-05 decisions): checkAndAssignSeat()
re-validates on every /api/ai/server/chat call - first use auto-assigns a
seat if any remain, further calls from an unlicensed user get a 402 with
a specific reason. recordUsage() appends to an append-only metering
ledger (timestamp/user/model/tokens/latency) that IS the billing record.
Admin data endpoints at /api/admin/ai/entitlement (seat total, revoke) -
the visual admin console is a separate, not-yet-built task.
Two real bugs found and fixed during verification, not just claimed fixed:
- /api/ai/policy never actually added 'server' to entitlement.classes even
when AI_SERVER_BASE_URL was set (only the type comment was updated) - the
Server radio option silently never appeared until this was caught live.
- The new routes used readStalwartAuthContext(0) (hardcoded slot, SSO/reauth-
specific) instead of getStalwartCredentials() (the general multi-slot
session resolver every other authenticated route uses) - reachable but
wrong, and would have hidden a real auth gap behind "works on my slot".
Verified end-to-end for real: built + ran the actual server, logged in via
the real (non-demo) auth flow, selected Server, listed the real Ollama
models through the proxy, asked "Reply with exactly the words: SERVER CLASS
WORKS" and got back exactly that - plus confirmed on disk (not just in the
UI) that data/admin-state/ai-entitlement.json recorded the seat assignment
and ai-metering.jsonl recorded real prompt/completion token counts and
latency from the actual model call. Rejection-path logic (seat limit
reached, zero seats configured, revocation) covered by 5 new unit tests
rather than a second live round trip. Full suite: typecheck clean, lint
clean, translations 48/48, production build succeeds.
43 lines
1.7 KiB
TypeScript
43 lines
1.7 KiB
TypeScript
import { NextRequest, NextResponse } from 'next/server';
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import { getStalwartCredentials } from '@/lib/stalwart/credentials';
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export const runtime = 'nodejs';
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/**
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* GET /api/ai/server/models — list models on the centrally-hosted `server`
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* class runtime (docs/AI-ASSISTANT-CONCEPT.md §2.1: "the same self-hosted
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* open-weight model stack as `local`... running on VNC's own infrastructure
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* instead of the user's laptop"). Tonight, `AI_SERVER_BASE_URL` stands in for
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* that infra with the Ollama already running on this developer's Mac — see
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* the module comment in lib/ai/entitlement.ts. Swapping to the real
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* EU/CH-hosted instance tomorrow is a config change, not a rewrite.
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*
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* Listing models is not a billable action (doc §10 point 1 — cosmetic), so
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* this only requires a valid session, not a seat.
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*/
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export async function GET(request: NextRequest) {
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const auth = await getStalwartCredentials(request);
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if (!auth) {
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return NextResponse.json({ error: 'not authenticated' }, { status: 401 });
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}
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const baseUrl = process.env.AI_SERVER_BASE_URL;
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if (!baseUrl) {
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return NextResponse.json({ error: 'AI server class is not configured' }, { status: 503 });
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}
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try {
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const res = await fetch(`${baseUrl.replace(/\/+$/, '')}/api/tags`);
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if (!res.ok) {
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return NextResponse.json({ error: `upstream returned ${res.status}` }, { status: 502 });
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}
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const body = (await res.json()) as { models?: Array<{ name: string }> };
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return NextResponse.json({ models: (body.models ?? []).map((m) => m.name).filter(Boolean) });
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} catch (cause) {
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return NextResponse.json(
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{ error: cause instanceof Error ? cause.message : 'AI server unreachable' },
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{ status: 502 },
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);
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}
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}
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