Files
accounted/app/api/agent/ask/route.ts
T
ff4425d10e feat(agent): let the single-call assistant read the ledger via read-only MCP tools (#1767)
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>
2026-08-20 21:18:21 +02:00

153 lines
5.9 KiB
TypeScript

import { NextResponse } from 'next/server'
import { z } from 'zod'
import { ensureInitialized } from '@/lib/init'
import { requireAuth } from '@/lib/auth/require-auth'
import { getActiveCompanyId } from '@/lib/company/context'
import { checkAgentRateLimit, agentRateLimitResponseBody } from '@/lib/rate-limits/agent'
import { guardSandbox } from '@/lib/sandbox/guard'
import { requireCapability } from '@/lib/entitlements/has-capability'
import { CAPABILITY } from '@/lib/entitlements/keys'
import { getAiStatus } from '@/lib/ai'
import { answerAssistantQuestion } from '@/lib/agent/ask/ask-service'
import {
resolveChatConversation,
persistUserTurn,
persistAssistantTurn,
} from '@/lib/agent/ask/persist'
import { getErrorMessage as getUserErrorMessage } from '@/lib/errors/get-error-message'
// The assistant answers over the read-only MCP tools, which are registered
// into the agent tool registry by the mcp-server extension at load. Without
// this the registry is empty and the assistant falls back to snapshot-only,
// so a hosted deploy would silently lose its ledger tools.
ensureInitialized()
/**
* POST /api/agent/ask: a single-call, provider-agnostic assistant answer over a
* bounded read-only tool loop.
*
* Unlike POST /api/agent/invoke (the streaming Anthropic chat runtime, which
* is gated on `assistantAvailable` and only runs on the Anthropic family),
* this endpoint answers through getAiService().generateText, so it runs on ANY
* configured backend, including an OpenAI-compatible local model. It is
* therefore gated on `configured`, not `assistantAvailable`. The service
* attaches the read-only MCP tools so it can fetch real figures (audit Option
* A / rip): a page posts its context and a question, gets one answer back.
*/
const Schema = z.object({
question: z.string().min(1).max(4000),
context: z.string().max(24_000).optional(),
tier: z.enum(['assistant', 'heavy']).optional(),
company_id: z.string().uuid().optional(),
// Chat-console persistence (opt-in). When `persist` is true, the turn is
// written to agent_conversations/agent_messages so the /chat sidebar keeps
// working. Page-scoped one-off actions (a report page asking a question)
// omit it and stay stateless. `conversation_id` resumes an existing
// general.help thread; omitted means "create one". `context_ref` binds a
// fresh thread to a page ("report:vat:2026-07") for the context chip.
persist: z.boolean().optional(),
conversation_id: z.string().uuid().nullable().optional(),
context_ref: z.string().max(200).nullable().optional(),
})
export async function POST(request: Request): Promise<Response> {
const { user, supabase, error } = await requireAuth()
if (error) return error
const rate = await checkAgentRateLimit(supabase, user.id)
if (!rate.ok) return NextResponse.json(agentRateLimitResponseBody(rate), { status: 429 })
let body: unknown
try {
body = await request.json()
} catch {
return NextResponse.json({ error: 'Invalid JSON' }, { status: 400 })
}
const parsed = Schema.safeParse(body)
if (!parsed.success) {
return NextResponse.json({ error: 'Ogiltig fråga.', type: 'validation_error' }, { status: 400 })
}
const companyId = parsed.data.company_id ?? (await getActiveCompanyId(supabase, user.id))
if (!companyId) return NextResponse.json({ error: 'No active company' }, { status: 400 })
const { data: membership } = await supabase
.from('company_members')
.select('user_id')
.eq('company_id', companyId)
.eq('user_id', user.id)
.maybeSingle()
if (!membership) return NextResponse.json({ error: 'Forbidden' }, { status: 403 })
const blocked = await guardSandbox(supabase, companyId)
if (blocked) return blocked
const capBlocked = await requireCapability(supabase, companyId, CAPABILITY.ai)
if (capBlocked) return capBlocked
// Distinct from the paywall: no AI backend configured at all. Unlike the
// chat loop, ANY provider works here, so we gate on `configured`.
if (!getAiStatus().configured) {
return NextResponse.json(
{ error: 'Assistenten är inte konfigurerad på den här installationen.', code: 'ai_unconfigured' },
{ status: 503 },
)
}
// Stateless page-scoped ask: one answer, nothing written.
if (parsed.data.persist !== true) {
try {
const result = await answerAssistantQuestion({
supabase,
companyId,
userId: user.id,
question: parsed.data.question,
pageContext: parsed.data.context,
tier: parsed.data.tier,
})
return NextResponse.json({ data: result })
} catch (err) {
return NextResponse.json({ error: getUserErrorMessage(err) }, { status: 500 })
}
}
// Persisted chat-console turn: resolve/create the thread, write the question,
// answer once, write the answer. Resolve BEFORE the model call so a bad
// conversation id 404s without spending a request; the user turn is written
// before the answer so a mid-call failure still leaves the question in the
// thread (the user can retry), matching the streaming runtime's semantics.
try {
const resolved = await resolveChatConversation(
supabase,
user.id,
companyId,
parsed.data.conversation_id,
parsed.data.question,
parsed.data.context_ref,
)
if (!resolved.ok) {
return NextResponse.json({ error: 'Konversationen hittades inte.' }, { status: 404 })
}
const { conversationId } = resolved
await persistUserTurn(supabase, conversationId, parsed.data.question)
const result = await answerAssistantQuestion({
supabase,
companyId,
userId: user.id,
conversationId,
question: parsed.data.question,
pageContext: parsed.data.context,
tier: parsed.data.tier,
})
await persistAssistantTurn(supabase, conversationId, result.answer)
return NextResponse.json({ data: { ...result, conversation_id: conversationId } })
} catch (err) {
return NextResponse.json({ error: getUserErrorMessage(err) }, { status: 500 })
}
}