The /chat assistant (audit Option A / rip) shipped in #1759 reading only the company name + entity type, so it answered "jag har ingen bokföringsdata" to every figures question ("vad är min största utgiftspost?"). It now behaves like an MCP client: it answers over a bounded, READ-only tool loop across the same MCP read tools the old streaming assistant had, plus an always-on company snapshot as the backstop. Provider-agnostic by construction, so it still runs on a local model: - lib/ai generateText gains optional `tools` + `maxSteps`. The OpenAI-compatible service forwards them to the Vercel AI SDK (stopWhen: stepCountIs), which runs the loop; the Anthropic-family service hand-rolls a small loop against messages.create. Kept on the raw Anthropic SDK: no new deps, and the no-tools path is byte-identical, so hosted extraction/composer/etc. are unchanged. - lib/agent/ask/ledger-tools.ts: the read slice of general.help's whitelist (income statement, VAT, ledgers, query_journal, reskontror, lists…) from agentToolRegistry, dispatched with the agent_chat actor run-turn uses. Write/ staging + memory-write tools are excluded; readOnlyHint/destructiveHint are re-checked. Empty in a core-only build → snapshot-only, graceful. - lib/agent/ask/snapshot.ts: a compact company_settings + deadlines block so a model that can't/won't call tools still answers status questions. Never carries figures (those come from the live tools). - ask-service attaches tools + snapshot when a userId is present and uses a tool-aware system prompt; the route calls ensureInitialized() so the registry is populated and threads userId/conversationId through. Works on Bedrock and on any local model with function-calling (Qwen). Tests: the anthropic hand-rolled loop (tool call → result → answer, is_error handling, step-budget forced answer), openai tool forwarding, the read-only adapter filter, the snapshot format, and the ask-service wiring. 457 agent+ai tests green, lint/guards clean. Co-authored-by: Jakob Wennberg <311770904+jakobwennberg-oss@users.noreply.github.com> Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
153 lines
5.9 KiB
TypeScript
153 lines
5.9 KiB
TypeScript
import { NextResponse } from 'next/server'
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import { z } from 'zod'
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import { ensureInitialized } from '@/lib/init'
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import { requireAuth } from '@/lib/auth/require-auth'
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import { getActiveCompanyId } from '@/lib/company/context'
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import { checkAgentRateLimit, agentRateLimitResponseBody } from '@/lib/rate-limits/agent'
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import { guardSandbox } from '@/lib/sandbox/guard'
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import { requireCapability } from '@/lib/entitlements/has-capability'
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import { CAPABILITY } from '@/lib/entitlements/keys'
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import { getAiStatus } from '@/lib/ai'
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import { answerAssistantQuestion } from '@/lib/agent/ask/ask-service'
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import {
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resolveChatConversation,
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persistUserTurn,
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persistAssistantTurn,
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} from '@/lib/agent/ask/persist'
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import { getErrorMessage as getUserErrorMessage } from '@/lib/errors/get-error-message'
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// The assistant answers over the read-only MCP tools, which are registered
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// into the agent tool registry by the mcp-server extension at load. Without
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// this the registry is empty and the assistant falls back to snapshot-only,
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// so a hosted deploy would silently lose its ledger tools.
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ensureInitialized()
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/**
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* POST /api/agent/ask: a single-call, provider-agnostic assistant answer over a
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* bounded read-only tool loop.
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*
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* Unlike POST /api/agent/invoke (the streaming Anthropic chat runtime, which
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* is gated on `assistantAvailable` and only runs on the Anthropic family),
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* this endpoint answers through getAiService().generateText, so it runs on ANY
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* configured backend, including an OpenAI-compatible local model. It is
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* therefore gated on `configured`, not `assistantAvailable`. The service
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* attaches the read-only MCP tools so it can fetch real figures (audit Option
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* A / rip): a page posts its context and a question, gets one answer back.
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*/
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const Schema = z.object({
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question: z.string().min(1).max(4000),
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context: z.string().max(24_000).optional(),
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tier: z.enum(['assistant', 'heavy']).optional(),
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company_id: z.string().uuid().optional(),
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// Chat-console persistence (opt-in). When `persist` is true, the turn is
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// written to agent_conversations/agent_messages so the /chat sidebar keeps
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// working. Page-scoped one-off actions (a report page asking a question)
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// omit it and stay stateless. `conversation_id` resumes an existing
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// general.help thread; omitted means "create one". `context_ref` binds a
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// fresh thread to a page ("report:vat:2026-07") for the context chip.
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persist: z.boolean().optional(),
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conversation_id: z.string().uuid().nullable().optional(),
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context_ref: z.string().max(200).nullable().optional(),
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})
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export async function POST(request: Request): Promise<Response> {
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const { user, supabase, error } = await requireAuth()
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if (error) return error
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const rate = await checkAgentRateLimit(supabase, user.id)
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if (!rate.ok) return NextResponse.json(agentRateLimitResponseBody(rate), { status: 429 })
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let body: unknown
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try {
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body = await request.json()
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} catch {
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return NextResponse.json({ error: 'Invalid JSON' }, { status: 400 })
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}
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const parsed = Schema.safeParse(body)
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if (!parsed.success) {
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return NextResponse.json({ error: 'Ogiltig fråga.', type: 'validation_error' }, { status: 400 })
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}
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const companyId = parsed.data.company_id ?? (await getActiveCompanyId(supabase, user.id))
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if (!companyId) return NextResponse.json({ error: 'No active company' }, { status: 400 })
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const { data: membership } = await supabase
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.from('company_members')
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.select('user_id')
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.eq('company_id', companyId)
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.eq('user_id', user.id)
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.maybeSingle()
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if (!membership) return NextResponse.json({ error: 'Forbidden' }, { status: 403 })
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const blocked = await guardSandbox(supabase, companyId)
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if (blocked) return blocked
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const capBlocked = await requireCapability(supabase, companyId, CAPABILITY.ai)
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if (capBlocked) return capBlocked
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// Distinct from the paywall: no AI backend configured at all. Unlike the
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// chat loop, ANY provider works here, so we gate on `configured`.
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if (!getAiStatus().configured) {
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return NextResponse.json(
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{ error: 'Assistenten är inte konfigurerad på den här installationen.', code: 'ai_unconfigured' },
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{ status: 503 },
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)
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}
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// Stateless page-scoped ask: one answer, nothing written.
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if (parsed.data.persist !== true) {
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try {
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const result = await answerAssistantQuestion({
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supabase,
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companyId,
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userId: user.id,
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question: parsed.data.question,
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pageContext: parsed.data.context,
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tier: parsed.data.tier,
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})
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return NextResponse.json({ data: result })
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} catch (err) {
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return NextResponse.json({ error: getUserErrorMessage(err) }, { status: 500 })
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}
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}
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// Persisted chat-console turn: resolve/create the thread, write the question,
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// answer once, write the answer. Resolve BEFORE the model call so a bad
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// conversation id 404s without spending a request; the user turn is written
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// before the answer so a mid-call failure still leaves the question in the
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// thread (the user can retry), matching the streaming runtime's semantics.
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try {
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const resolved = await resolveChatConversation(
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supabase,
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user.id,
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companyId,
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parsed.data.conversation_id,
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parsed.data.question,
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parsed.data.context_ref,
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)
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if (!resolved.ok) {
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return NextResponse.json({ error: 'Konversationen hittades inte.' }, { status: 404 })
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}
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const { conversationId } = resolved
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await persistUserTurn(supabase, conversationId, parsed.data.question)
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const result = await answerAssistantQuestion({
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supabase,
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companyId,
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userId: user.id,
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conversationId,
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question: parsed.data.question,
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pageContext: parsed.data.context,
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tier: parsed.data.tier,
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})
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await persistAssistantTurn(supabase, conversationId, result.answer)
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return NextResponse.json({ data: { ...result, conversation_id: conversationId } })
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} catch (err) {
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return NextResponse.json({ error: getUserErrorMessage(err) }, { status: 500 })
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}
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}
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