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>
303 lines
12 KiB
TypeScript
303 lines
12 KiB
TypeScript
import { describe, it, expect, vi, beforeEach, afterEach } from 'vitest'
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// Drive the service against a fake Bedrock client: the point of these tests
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// is the REQUEST SHAPE. Hosted stays byte-identical only if the service sends
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// exactly the literals the call sites sent before the abstraction existed.
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const mockCreate = vi.fn()
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vi.mock('@anthropic-ai/bedrock-sdk', () => {
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class FakeBedrock {
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messages = { create: mockCreate }
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}
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return { default: FakeBedrock }
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})
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import { readAiConfig } from '../config'
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import { createAnthropicFamilyService, buildAnthropicDocumentContent } from '../services/anthropic-family'
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const ENV = ['AWS_ACCESS_KEY_ID', 'AWS_SECRET_ACCESS_KEY', 'ANTHROPIC_API_KEY', 'AI_PROVIDER', 'AI_BASE_URL', 'AI_API_KEY', 'BEDROCK_MODEL_ID', 'AI_EXTRACTION_MODEL', 'AI_MODEL'] as const
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let saved: Record<string, string | undefined> = {}
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beforeEach(() => {
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vi.clearAllMocks()
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saved = {}
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for (const k of ENV) {
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saved[k] = process.env[k]
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delete process.env[k]
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}
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process.env.AWS_ACCESS_KEY_ID = 'AKIAEXAMPLE'
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process.env.AWS_SECRET_ACCESS_KEY = 'secret'
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mockCreate.mockResolvedValue({
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content: [{ type: 'text', text: '{"ok":true}' }],
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usage: { input_tokens: 10, output_tokens: 5, cache_read_input_tokens: 7, cache_creation_input_tokens: 0 },
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})
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})
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afterEach(() => {
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for (const k of ENV) {
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if (saved[k] === undefined) delete process.env[k]
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else process.env[k] = saved[k]
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}
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})
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const SYSTEM = 'You extract fields.'
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const INSTRUCTION = 'Extract the fields per the schema. JSON only.'
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describe('extractFromDocument request shape (hosted regression net)', () => {
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it('sends a PDF exactly as the inbox extractor did: cached system block, document part, instruction', async () => {
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const svc = createAnthropicFamilyService(readAiConfig())
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const pdf = Buffer.from('%PDF-1.4')
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const result = await svc.extractFromDocument({
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document: { kind: 'pdf', data: pdf, fileName: 'faktura.pdf' },
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system: SYSTEM,
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instruction: INSTRUCTION,
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maxTokens: 8192,
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})
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expect(result.ok).toBe(true)
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expect(mockCreate).toHaveBeenCalledTimes(1)
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expect(mockCreate.mock.calls[0][0]).toEqual({
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model: 'eu.anthropic.claude-sonnet-5',
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max_tokens: 8192,
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system: [{ type: 'text', text: SYSTEM, cache_control: { type: 'ephemeral' } }],
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messages: [
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{
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role: 'user',
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content: [
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{
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type: 'document',
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source: { type: 'base64', media_type: 'application/pdf', data: pdf.toString('base64') },
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},
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{ type: 'text', text: INSTRUCTION },
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],
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},
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],
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})
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})
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it('sends an image as a base64 image block with its media type', async () => {
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const svc = createAnthropicFamilyService(readAiConfig())
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const jpeg = Buffer.from('JPEG')
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await svc.extractFromDocument({
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document: { kind: 'image', data: jpeg, mediaType: 'image/jpeg' },
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system: SYSTEM,
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instruction: INSTRUCTION,
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maxTokens: 8192,
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})
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expect(mockCreate.mock.calls[0][0].messages[0].content).toEqual([
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{ type: 'image', source: { type: 'base64', media_type: 'image/jpeg', data: jpeg.toString('base64') } },
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{ type: 'text', text: INSTRUCTION },
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])
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})
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it('sends converted HTML as two text blocks', async () => {
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const svc = createAnthropicFamilyService(readAiConfig())
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await svc.extractFromDocument({
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document: { kind: 'text', text: 'The document is an HTML email invoice, converted to plain text:\n\nTotal 100' },
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system: SYSTEM,
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instruction: INSTRUCTION,
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maxTokens: 8192,
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})
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expect(mockCreate.mock.calls[0][0].messages[0].content).toEqual([
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{ type: 'text', text: 'The document is an HTML email invoice, converted to plain text:\n\nTotal 100' },
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{ type: 'text', text: INSTRUCTION },
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])
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})
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it('returns the text, model and usage', async () => {
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const svc = createAnthropicFamilyService(readAiConfig())
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const result = await svc.extractFromDocument({
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document: { kind: 'text', text: 'x' },
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system: SYSTEM,
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instruction: INSTRUCTION,
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maxTokens: 100,
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})
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expect(result).toEqual({
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ok: true,
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text: '{"ok":true}',
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model: 'eu.anthropic.claude-sonnet-5',
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usage: { inputTokens: 10, outputTokens: 5, cacheCreationInputTokens: 0, cacheReadInputTokens: 7 },
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})
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})
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it('honours the extraction tier override (legacy BEDROCK_MODEL_ID)', async () => {
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process.env.BEDROCK_MODEL_ID = 'claude-sonnet-4-6'
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const svc = createAnthropicFamilyService(readAiConfig())
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await svc.extractFromDocument({ document: { kind: 'text', text: 'x' }, system: SYSTEM, instruction: INSTRUCTION, maxTokens: 1 })
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expect(mockCreate.mock.calls[0][0].model).toBe('eu.anthropic.claude-sonnet-4-6')
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})
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it('skips without a call when the deployment has no credentials', async () => {
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delete process.env.AWS_ACCESS_KEY_ID
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delete process.env.AWS_SECRET_ACCESS_KEY
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const svc = createAnthropicFamilyService(readAiConfig())
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const result = await svc.extractFromDocument({ document: { kind: 'text', text: 'x' }, system: SYSTEM, instruction: INSTRUCTION, maxTokens: 1 })
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expect(result).toEqual({ ok: false, skipped: 'ai_unconfigured' })
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expect(mockCreate).not.toHaveBeenCalled()
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})
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})
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describe('generateText / generateStructured', () => {
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it('generateText sends a plain user message with an optional system string', async () => {
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const svc = createAnthropicFamilyService(readAiConfig())
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const result = await svc.generateText({ tier: 'assistant', system: 'S', prompt: 'Hej', maxTokens: 50 })
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expect(mockCreate.mock.calls[0][0]).toEqual({
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model: 'eu.anthropic.claude-sonnet-5',
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max_tokens: 50,
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system: 'S',
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messages: [{ role: 'user', content: 'Hej' }],
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})
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expect(result.text).toBe('{"ok":true}')
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})
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it('generateStructured forces one named tool and returns its input', async () => {
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mockCreate.mockResolvedValueOnce({
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content: [{ type: 'tool_use', id: 't1', name: 'verdict', input: { paired: true } }],
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usage: { input_tokens: 1, output_tokens: 1 },
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})
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const svc = createAnthropicFamilyService(readAiConfig())
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const schema = { type: 'object', properties: { paired: { type: 'boolean' } }, required: ['paired'] }
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const result = await svc.generateStructured({
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tier: 'heavy',
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prompt: 'Decide',
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maxTokens: 200,
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schema: { name: 'verdict', description: 'd', jsonSchema: schema },
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})
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expect(mockCreate.mock.calls[0][0]).toEqual({
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model: 'eu.anthropic.claude-sonnet-5',
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max_tokens: 200,
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tools: [{ name: 'verdict', description: 'd', input_schema: schema }],
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tool_choice: { type: 'tool', name: 'verdict' },
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messages: [{ role: 'user', content: 'Decide' }],
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})
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expect(result.value).toEqual({ paired: true })
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})
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it('generateStructured throws when the model ignored the forced tool', async () => {
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mockCreate.mockResolvedValueOnce({ content: [{ type: 'text', text: 'nope' }], usage: {} })
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const svc = createAnthropicFamilyService(readAiConfig())
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await expect(
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svc.generateStructured({ tier: 'assistant', prompt: 'x', maxTokens: 10, schema: { name: 'v', jsonSchema: {} } })
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).rejects.toThrow(/forced tool/)
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})
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})
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describe('buildAnthropicDocumentContent', () => {
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it('is a pure function of the document and instruction', () => {
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expect(buildAnthropicDocumentContent({ kind: 'text', text: 'a' }, 'b')).toEqual([
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{ type: 'text', text: 'a' },
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{ type: 'text', text: 'b' },
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])
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})
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})
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describe('generateText read-only tool loop', () => {
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it('calls a tool, feeds the JSON result back, and returns the final answer with summed usage', async () => {
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const execute = vi.fn().mockResolvedValue({ largest: '5010', amount: 12345 })
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const svc = createAnthropicFamilyService(readAiConfig())
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// Turn 1: the model asks for a report.
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mockCreate.mockResolvedValueOnce({
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stop_reason: 'tool_use',
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content: [
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{ type: 'text', text: 'Kollar.' },
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{ type: 'tool_use', id: 'tu_1', name: 'gnubok_get_income_statement', input: { period: '2026-07' } },
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],
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usage: { input_tokens: 10, output_tokens: 5 },
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})
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// Turn 2: the model answers with the figure.
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mockCreate.mockResolvedValueOnce({
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stop_reason: 'end_turn',
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content: [{ type: 'text', text: 'Din största utgift är 12 345 kr (konto 5010).' }],
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usage: { input_tokens: 20, output_tokens: 8 },
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})
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const result = await svc.generateText({
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tier: 'assistant',
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system: 'S',
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prompt: 'Vad är min största utgift?',
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maxTokens: 500,
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tools: [
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{ name: 'gnubok_get_income_statement', description: 'd', jsonSchema: { type: 'object' }, execute },
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],
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maxSteps: 4,
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})
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expect(execute).toHaveBeenCalledWith({ period: '2026-07' })
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expect(result.text).toBe('Din största utgift är 12 345 kr (konto 5010).')
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expect(mockCreate).toHaveBeenCalledTimes(2)
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// First turn carries the tools; second turn carries the tool_result.
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expect(mockCreate.mock.calls[0][0].tools[0].name).toBe('gnubok_get_income_statement')
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const secondMessages = mockCreate.mock.calls[1][0].messages
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expect(secondMessages).toHaveLength(3) // user, assistant(tool_use), user(tool_result)
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const toolResult = secondMessages[2].content[0]
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expect(toolResult.type).toBe('tool_result')
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expect(toolResult.tool_use_id).toBe('tu_1')
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expect(JSON.parse(toolResult.content)).toEqual({ largest: '5010', amount: 12345 })
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// Usage summed across both turns.
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expect(result.usage.inputTokens).toBe(30)
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expect(result.usage.outputTokens).toBe(13)
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})
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it('surfaces a tool failure as an is_error result rather than throwing', async () => {
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const execute = vi.fn().mockRejectedValue(new Error('report timeout'))
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const svc = createAnthropicFamilyService(readAiConfig())
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mockCreate.mockResolvedValueOnce({
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stop_reason: 'tool_use',
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content: [{ type: 'tool_use', id: 'tu', name: 'gnubok_get_vat_report', input: {} }],
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usage: { input_tokens: 1, output_tokens: 1 },
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})
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mockCreate.mockResolvedValueOnce({
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stop_reason: 'end_turn',
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content: [{ type: 'text', text: 'Kunde inte hämta momsrapporten just nu.' }],
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usage: { input_tokens: 1, output_tokens: 1 },
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})
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const result = await svc.generateText({
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tier: 'assistant',
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prompt: 'Momsen?',
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maxTokens: 100,
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tools: [{ name: 'gnubok_get_vat_report', description: 'd', jsonSchema: {}, execute }],
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})
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const toolResult = mockCreate.mock.calls[1][0].messages[2].content[0]
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expect(toolResult.is_error).toBe(true)
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expect(JSON.parse(toolResult.content).error).toContain('report timeout')
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expect(result.text).toBe('Kunde inte hämta momsrapporten just nu.')
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})
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it('forces a final tools-off answer when the step budget is exhausted', async () => {
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const execute = vi.fn().mockResolvedValue({ ok: true })
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const svc = createAnthropicFamilyService(readAiConfig())
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// Every turn keeps asking for the tool → never terminates on its own.
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mockCreate.mockResolvedValue({
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stop_reason: 'tool_use',
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content: [{ type: 'tool_use', id: 'tu', name: 't', input: {} }],
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usage: { input_tokens: 1, output_tokens: 1 },
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})
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// The forced final turn (index 2) returns real text.
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mockCreate.mockResolvedValueOnce({
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stop_reason: 'tool_use',
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content: [{ type: 'tool_use', id: 'tu', name: 't', input: {} }],
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usage: { input_tokens: 1, output_tokens: 1 },
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})
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mockCreate.mockResolvedValueOnce({
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stop_reason: 'tool_use',
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content: [{ type: 'tool_use', id: 'tu', name: 't', input: {} }],
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usage: { input_tokens: 1, output_tokens: 1 },
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})
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mockCreate.mockResolvedValueOnce({
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stop_reason: 'end_turn',
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content: [{ type: 'text', text: 'Sammanfattning utan fler verktygsanrop.' }],
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usage: { input_tokens: 1, output_tokens: 1 },
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})
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const result = await svc.generateText({
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tier: 'assistant',
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prompt: 'x',
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maxTokens: 100,
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tools: [{ name: 't', description: 'd', jsonSchema: {}, execute }],
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maxSteps: 2,
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})
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// 2 loop turns + 1 forced final = 3 calls; the final call omits tools.
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expect(mockCreate).toHaveBeenCalledTimes(3)
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expect(mockCreate.mock.calls[2][0].tools).toBeUndefined()
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expect(result.text).toBe('Sammanfattning utan fler verktygsanrop.')
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})
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})
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