Implements phase 1 of AI_PIPELINE_HARDENING_PLAN.md. Every Anthropic call now goes through one module that owns retry, timeout, abort, structured- output parsing, schema validation, and best-effort call telemetry. * src/lib/llm.js — single callLLM entry point. Resolves model per tier (fast / standard / reasoning) with admin:model legacy fallback for the standard tier; 60s default timeout via AbortController; balanced-brace JSON extraction; LLMHttpError, LLMTruncatedError, LLMOutputError, and LLMValidationError surface clearly distinct failure modes. * src/lib/llmRetry.js — exponential backoff with full jitter, retries only on transient HTTP statuses, honours Retry-After up to 60s, never retries on AbortError. * src/lib/llmSchemas.js — Zod schemas for every structured task plus normalizeHandbookResult (collapses legacy "executes" relations into the canonical "executed_by" vocabulary). * src/lib/api.js — thin shim over callLLM so existing callers (extraction pipeline, learning, quiz, R42, knowledge graph) keep working unchanged. * src/lib/__tests__/ — 32 Vitest cases covering parse paths, error surfaces, simulation mode, model resolution, and schema validation. * src/pages/Admin/index.jsx — three model inputs (fast / standard / reasoning) replacing the single legacy field; legacy value falls back for the standard tier so existing overrides survive. Adds Zod and Vitest, plus an "npm run test" script. Also cleans up the pre-existing repo-wide ESLint failures so phase 1's "npm run lint passes" acceptance criterion can be checked: drops unused React imports across the JSX tree (React 19 JSX runtime auto-imports), attaches cause to rethrown errors in the service modules, ignores pb_migrations in the ESLint config (PocketBase JSVM globals), and removes one dead handleCreateCustom function in Leren.jsx. A real behaviour bug surfaced in Testen.jsx — the quiz timer captured a stale finishQuiz via setInterval closure; now updated via finishQuizRef so the timer always invokes the latest callback. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
233 lines
7.8 KiB
JavaScript
233 lines
7.8 KiB
JavaScript
import { afterEach, describe, expect, it, vi } from 'vitest';
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import { z } from 'zod';
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vi.mock('../storage', () => ({
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storage: {
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_data: new Map(),
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get(key, fallback = null) {
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return this._data.has(key) ? this._data.get(key) : fallback;
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},
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set(key, value) { this._data.set(key, value); },
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remove(key) { this._data.delete(key); },
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getKeysByPrefix() { return []; },
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},
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}));
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vi.mock('../pb', () => ({
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pb: { collection: () => ({ create: () => ({ catch: () => {} }) }) },
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}));
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import {
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callLLM,
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LLMHttpError,
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LLMOutputError,
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LLMTruncatedError,
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LLMValidationError,
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parseStructuredText,
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resolveModel,
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} from '../llm';
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import { storage } from '../storage';
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const originalFetch = globalThis.fetch;
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afterEach(() => {
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globalThis.fetch = originalFetch;
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storage._data.clear();
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});
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describe('parseStructuredText', () => {
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it('extracts an object from raw JSON', () => {
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expect(parseStructuredText('{"a":1}')).toEqual({ a: 1 });
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});
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it('extracts an object from a json-fenced block', () => {
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const fenced = '```json\n{"hello":"world"}\n```';
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expect(parseStructuredText(fenced)).toEqual({ hello: 'world' });
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});
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it('extracts an object surrounded by prose', () => {
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const messy = 'Sure! Here you go:\n{"id":"x","label":"X"}\nLet me know if you want changes.';
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expect(parseStructuredText(messy)).toEqual({ id: 'x', label: 'X' });
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});
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it('extracts an array when it is the top-level value', () => {
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expect(parseStructuredText('[1,2,3]')).toEqual([1, 2, 3]);
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});
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it('ignores braces inside string literals', () => {
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const tricky = '{"text":"this { is not } a brace"}';
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expect(parseStructuredText(tricky)).toEqual({ text: 'this { is not } a brace' });
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});
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it('throws LLMOutputError when no balanced JSON is present', () => {
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expect(() => parseStructuredText('no json here, just words')).toThrow(LLMOutputError);
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});
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});
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describe('resolveModel', () => {
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it('falls back to tier defaults when no override is set', () => {
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expect(resolveModel('fast')).toBe('claude-haiku-4-5-20251001');
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expect(resolveModel('standard')).toBe('claude-sonnet-4-6');
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expect(resolveModel('reasoning')).toBe('claude-opus-4-7');
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});
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it('honours an explicit tier override', () => {
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storage.set('admin:model:reasoning', 'claude-opus-9-future');
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expect(resolveModel('reasoning')).toBe('claude-opus-9-future');
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});
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it('uses the legacy admin:model setting as a standard-tier fallback', () => {
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storage.set('admin:model', 'claude-some-legacy-id');
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expect(resolveModel('standard')).toBe('claude-some-legacy-id');
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});
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it('prefers the tier-specific override over the legacy fallback', () => {
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storage.set('admin:model', 'claude-legacy');
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storage.set('admin:model:standard', 'claude-new');
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expect(resolveModel('standard')).toBe('claude-new');
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});
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});
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function mockJsonResponse(body, { status = 200, headers = {} } = {}) {
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const h = new Headers({ 'content-type': 'application/json', ...headers });
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return new Response(JSON.stringify(body), { status, headers: h });
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}
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describe('callLLM happy path', () => {
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it('returns parsed tool input when toolChoice forces a tool', async () => {
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globalThis.fetch = vi.fn(async () =>
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mockJsonResponse({
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id: 'msg_1',
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model: 'claude-sonnet-4-6',
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stop_reason: 'tool_use',
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usage: { input_tokens: 10, output_tokens: 20 },
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content: [
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{
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type: 'tool_use',
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name: 'emit_custom_topic',
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input: { label: 'Pair Programming', type: 'process', description: 'Two engineers, one keyboard.' },
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},
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],
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}),
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);
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const result = await callLLM({
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task: 'learning.custom_topic',
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tier: 'standard',
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user: 'Pair programming',
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tools: [{ name: 'emit_custom_topic', description: 'x', input_schema: { type: 'object' } }],
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toolChoice: { type: 'tool', name: 'emit_custom_topic' },
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});
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expect(result.toolUses).toHaveLength(1);
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expect(result.toolUses[0].input.label).toBe('Pair Programming');
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});
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it('parses and validates plain text against a Zod schema', async () => {
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globalThis.fetch = vi.fn(async () =>
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mockJsonResponse({
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id: 'msg_2',
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model: 'claude-sonnet-4-6',
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stop_reason: 'end_turn',
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usage: { input_tokens: 5, output_tokens: 7 },
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content: [{ type: 'text', text: '```json\n{"value":42}\n```' }],
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}),
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);
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const schema = z.object({ value: z.number() });
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const result = await callLLM({
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task: 'demo.json',
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user: 'give me a number',
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schema,
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});
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expect(result.parsed).toEqual({ value: 42 });
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});
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});
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describe('callLLM error paths', () => {
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it('throws LLMTruncatedError when stop_reason is max_tokens and a tool was requested', async () => {
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globalThis.fetch = vi.fn(async () =>
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mockJsonResponse({
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stop_reason: 'max_tokens',
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usage: { input_tokens: 1, output_tokens: 1 },
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content: [],
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}),
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);
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await expect(
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callLLM({
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task: 'extract.source',
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user: 'x',
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tools: [{ name: 'emit_knowledge_graph', description: 'x', input_schema: { type: 'object' } }],
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toolChoice: { type: 'tool', name: 'emit_knowledge_graph' },
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}),
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).rejects.toBeInstanceOf(LLMTruncatedError);
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});
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it('throws LLMTruncatedError when stop_reason is max_tokens and a schema was requested', async () => {
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globalThis.fetch = vi.fn(async () =>
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mockJsonResponse({
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stop_reason: 'max_tokens',
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usage: { input_tokens: 1, output_tokens: 1 },
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content: [{ type: 'text', text: 'partial...' }],
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}),
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);
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const schema = z.object({ value: z.number() });
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await expect(
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callLLM({ task: 'demo.json', user: 'x', schema }),
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).rejects.toBeInstanceOf(LLMTruncatedError);
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});
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it('throws LLMValidationError when tool input fails schema validation', async () => {
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globalThis.fetch = vi.fn(async () =>
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mockJsonResponse({
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stop_reason: 'tool_use',
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usage: {},
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content: [
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{ type: 'tool_use', name: 'emit_custom_topic', input: { label: 'X', type: 'concept' } },
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],
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}),
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);
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await expect(
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callLLM({
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task: 'learning.custom_topic',
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user: 'x',
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tools: [{ name: 'emit_custom_topic', description: 'x', input_schema: { type: 'object' } }],
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toolChoice: { type: 'tool', name: 'emit_custom_topic' },
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}),
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).rejects.toBeInstanceOf(LLMValidationError);
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});
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it('surfaces a non-retryable HTTP error as LLMHttpError', async () => {
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globalThis.fetch = vi.fn(async () =>
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new Response(JSON.stringify({ error: 'bad request' }), {
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status: 400,
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headers: { 'content-type': 'application/json' },
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}),
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);
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await expect(callLLM({ task: 'demo', user: 'x' })).rejects.toBeInstanceOf(LLMHttpError);
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});
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it('detects an auth portal HTML response and raises a clear message', async () => {
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globalThis.fetch = vi.fn(async () =>
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new Response('<html>login</html>', { status: 200, headers: { 'content-type': 'text/html' } }),
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);
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await expect(callLLM({ task: 'demo', user: 'x' })).rejects.toThrow(/session has expired/i);
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});
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});
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describe('callLLM simulation mode', () => {
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it('returns the chat stub when admin:use_simulation is true and task is chat-like', async () => {
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storage.set('admin:use_simulation', true);
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const result = await callLLM({ task: 'chat.r42', user: 'hello' });
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expect(result.stopReason).toBe('end_turn');
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expect(result.text).toMatch(/Simulatiemodus/);
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});
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it('returns the extraction stub for other tasks in simulation mode', async () => {
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storage.set('admin:use_simulation', true);
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const result = await callLLM({ task: 'extract.source', user: 'doc' });
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expect(() => JSON.parse(result.text)).not.toThrow();
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expect(JSON.parse(result.text)).toHaveProperty('topics');
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});
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});
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