mirror of
https://github.com/tiddly-gittly/TidGi-Desktop.git
synced 2026-03-11 01:10:23 -07:00
- Added functionality to restore heartbeat timers and alarms for active agents upon service initialization. - Introduced methods to retrieve active background tasks and cancel them via the UI. - Enhanced alarm clock tool to persist alarm data in the database, ensuring alarms survive app restarts. - Updated agent instance schema to include scheduled alarm data. - Modified prompt concatenation logic to support context window size for message history. - Removed system prompt parameter from model parameters schema and related components. - Improved UI to display and manage background tasks, including heartbeat and alarm details.
641 lines
24 KiB
TypeScript
641 lines
24 KiB
TypeScript
import { After, DataTable, Given, Then, When } from '@cucumber/cucumber';
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import { AIGlobalSettings, AIProviderConfig } from '@services/externalAPI/interface';
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import type { IWorkspace } from '@services/workspaces/interface';
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import { backOff } from 'exponential-backoff';
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import fs from 'fs-extra';
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import { isEqual, omit } from 'lodash';
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import path from 'path';
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import type { ISettingFile } from '../../src/services/database/interface';
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import { MockOpenAIServer } from '../supports/mockOpenAI';
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import { getSettingsPath } from '../supports/paths';
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import { PLAYWRIGHT_SHORT_TIMEOUT } from '../supports/timeouts';
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import type { ApplicationWorld } from './application';
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// Backoff configuration for retries
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const BACKOFF_OPTIONS = {
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numOfAttempts: 10,
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startingDelay: 200,
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timeMultiple: 1.5,
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};
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/**
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* Generate deterministic embedding vector based on a semantic tag
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* This allows us to control similarity in tests without writing full 384-dim vectors
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*
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* Strategy:
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* - Similar tags (note1, note1-similar) -> similar vectors (high similarity)
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* - Different tags (note1, note2) -> different vectors (medium similarity)
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* - Unrelated tags (note1, unrelated) -> very different vectors (low similarity)
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*/
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function generateSemanticEmbedding(tag: string): number[] {
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const vector: number[] = [];
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// Parse tag to determine semantic relationship
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// Format: "note1", "note2", "query-note1", "unrelated"
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const baseTag = tag.replace(/-similar$/, '').replace(/^query-/, '');
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const isSimilar = tag.includes('-similar');
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const isQuery = tag.startsWith('query-');
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const isUnrelated = tag === 'unrelated';
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// Generate base vector from tag
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const seed = Array.from(baseTag).reduce((hash, char) => {
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return ((hash << 5) - hash) + char.charCodeAt(0);
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}, 0);
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for (let dimension = 0; dimension < 384; dimension++) {
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const x = Math.sin((seed + dimension) * 0.1) * 10000;
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let value = x - Math.floor(x);
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// Adjust vector based on semantic relationship
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if (isUnrelated) {
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// Completely different direction
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value = -value;
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} else if (isSimilar || isQuery) {
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// Very similar (>95% similarity) - add small noise
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value = value + (Math.sin(dimension * 0.01) * 0.05);
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}
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// Normalize to [-1, 1]
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vector.push(value * 2 - 1);
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}
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return vector;
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}
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// Helper function to start mock OpenAI server and update settings
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async function startMockOpenAIServerAndUpdateSettings(
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world: ApplicationWorld,
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rules: Array<{ response: string; stream?: boolean; embedding?: number[] }>,
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): Promise<void> {
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// Use dynamic port (0) to allow parallel test execution
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world.mockOpenAIServer = new MockOpenAIServer(0, rules);
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world.providerConfig = createProviderConfig();
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await world.mockOpenAIServer.start();
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// Update provider config with actual mock server URL
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world.providerConfig.baseURL = `${world.mockOpenAIServer.baseUrl}/v1`;
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// Update AI settings in settings.json with the correct baseURL
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const settingsPath = getSettingsPath(world);
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if (fs.existsSync(settingsPath)) {
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const settings = fs.readJsonSync(settingsPath) as ISettingFile;
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if (settings.aiSettings?.providers?.[0]) {
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settings.aiSettings.providers[0].baseURL = world.providerConfig.baseURL;
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fs.writeJsonSync(settingsPath, settings, { spaces: 2 });
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}
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}
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}
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// Agent-specific Given steps
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/**
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* Start mock OpenAI server without any rules.
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* Rules can be added later using "I add mock OpenAI responses" step.
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*/
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Given('I have started the mock OpenAI server without rules', function(this: ApplicationWorld, done: (error?: Error) => void) {
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startMockOpenAIServerAndUpdateSettings(this, [])
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.then(() => {
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done();
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})
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.catch((error: unknown) => {
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done(error as Error);
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});
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});
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/**
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* Start mock OpenAI server with predefined rules from dataTable.
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* This is the legacy method used when rules are known upfront.
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*/
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Given('I have started the mock OpenAI server', function(this: ApplicationWorld, dataTable: DataTable | undefined, done: (error?: Error) => void) {
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try {
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const rules: Array<{ response: string; stream?: boolean; embedding?: number[] }> = [];
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if (dataTable && typeof dataTable.raw === 'function') {
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const rows = dataTable.raw();
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// Skip header row
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for (let index = 1; index < rows.length; index++) {
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const row = rows[index];
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const response = (row[0] ?? '').trim();
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const stream = (row[1] ?? '').trim().toLowerCase() === 'true';
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const embeddingTag = (row[2] ?? '').trim();
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// Generate embedding from semantic tag if provided
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let embedding: number[] | undefined;
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if (embeddingTag) {
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embedding = generateSemanticEmbedding(embeddingTag);
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}
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// Include rules with a response OR an embedding — MockOpenAIServer separates them into chatRules vs embeddingRules internally
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if (response || embedding) rules.push({ response, stream, embedding });
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}
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}
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startMockOpenAIServerAndUpdateSettings(this, rules)
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.then(() => {
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done();
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})
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.catch((error: unknown) => {
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done(error as Error);
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});
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} catch (error) {
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done(error as Error);
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}
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});
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/**
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* Add new responses to an already-running mock OpenAI server.
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* This allows scenarios to configure server responses after the application has started.
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*/
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Given('I add mock OpenAI responses:', function(this: ApplicationWorld, dataTable: DataTable | undefined) {
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if (!this.mockOpenAIServer) {
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throw new Error('Mock OpenAI server is not running. Use "I have started the mock OpenAI server" first.');
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}
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const rules: Array<{ response: string; stream?: boolean; embedding?: number[] }> = [];
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if (dataTable && typeof dataTable.raw === 'function') {
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const rows = dataTable.raw();
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// Skip header row
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for (let index = 1; index < rows.length; index++) {
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const row = rows[index];
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const response = (row[0] ?? '').trim();
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const stream = (row[1] ?? '').trim().toLowerCase() === 'true';
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const embeddingTag = (row[2] ?? '').trim();
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// Generate embedding from semantic tag if provided
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let embedding: number[] | undefined;
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if (embeddingTag) {
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embedding = generateSemanticEmbedding(embeddingTag);
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}
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// Include rules with a response OR an embedding — MockOpenAIServer separates them into chatRules vs embeddingRules internally
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if (response || embedding) rules.push({ response, stream, embedding });
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}
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}
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this.mockOpenAIServer.addRules(rules);
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});
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// Mock OpenAI server cleanup - for scenarios using mock OpenAI
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After({ tags: '@mockOpenAI' }, async function(this: ApplicationWorld) {
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// Stop mock OpenAI server with timeout protection
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if (this.mockOpenAIServer) {
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try {
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await Promise.race([
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this.mockOpenAIServer.stop(),
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new Promise<void>((resolve) => setTimeout(resolve, 2000)),
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]);
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} catch {
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// Ignore errors during cleanup
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} finally {
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this.mockOpenAIServer = undefined;
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}
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}
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});
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// Only keep agent-specific steps that can't use generic ones
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Then('I should see {int} messages in chat history', async function(this: ApplicationWorld, expectedCount: number) {
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const currentWindow = this.currentWindow || this.mainWindow;
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if (!currentWindow) {
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throw new Error('No current window is available');
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}
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const messageSelector = '[data-testid="message-bubble"]';
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await backOff(
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async () => {
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// Wait for at least one message to exist
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await currentWindow.waitForSelector(messageSelector, { timeout: PLAYWRIGHT_SHORT_TIMEOUT });
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// Count current messages
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const messages = currentWindow.locator(messageSelector);
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const currentCount = await messages.count();
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if (currentCount === expectedCount) {
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return; // Success
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} else if (currentCount > expectedCount) {
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throw new Error(`Expected ${expectedCount} messages but found ${currentCount} (too many)`);
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} else {
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// Not enough messages yet, throw to trigger retry
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throw new Error(`Expected ${expectedCount} messages but found ${currentCount}`);
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}
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},
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BACKOFF_OPTIONS,
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).catch(async (error: unknown) => {
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// Get final count for error message
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try {
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const finalCount = await currentWindow.locator(messageSelector).count();
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throw new Error(`Could not find expected ${expectedCount} messages. Found ${finalCount}. Error: ${(error as Error).message}`);
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} catch {
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throw new Error(`Could not find expected ${expectedCount} messages. Error: ${(error as Error).message}`);
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}
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});
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});
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Then('the last AI request should contain system prompt {string}', async function(this: ApplicationWorld, expectedPrompt: string) {
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if (!this.mockOpenAIServer) {
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throw new Error('Mock OpenAI server is not running');
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}
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const lastRequest = this.mockOpenAIServer.getLastRequest();
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if (!lastRequest) {
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throw new Error('No AI request has been made yet');
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}
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// Find system message in the request
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const systemMessage = lastRequest.messages.find(message => message.role === 'system');
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if (!systemMessage) {
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throw new Error('No system message found in the AI request');
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}
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if (!systemMessage.content || !systemMessage.content.includes(expectedPrompt)) {
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throw new Error(`Expected system prompt to contain "${expectedPrompt}", but got: "${systemMessage.content}"`);
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}
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});
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Then('the last AI request system prompt should not contain {string}', async function(this: ApplicationWorld, unexpectedText: string) {
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if (!this.mockOpenAIServer) {
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throw new Error('Mock OpenAI server is not running');
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}
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const lastRequest = this.mockOpenAIServer.getLastRequest();
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if (!lastRequest) {
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throw new Error('No AI request has been made yet');
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}
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const systemMessage = lastRequest.messages.find(message => message.role === 'system');
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if (!systemMessage) {
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// No system message means it definitely doesn't contain the text
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return;
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}
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if (systemMessage.content && systemMessage.content.includes(unexpectedText)) {
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throw new Error(`Expected system prompt NOT to contain "${unexpectedText}", but it was found in: "${systemMessage.content.substring(0, 300)}..."`);
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}
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});
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Then('the last AI request should have {int} messages', async function(this: ApplicationWorld, expectedCount: number) {
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if (!this.mockOpenAIServer) {
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throw new Error('Mock OpenAI server is not running');
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}
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const lastRequest = this.mockOpenAIServer.getLastRequest();
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if (!lastRequest) {
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throw new Error('No AI request has been made yet');
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}
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const actualCount = lastRequest.messages.length;
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if (actualCount !== expectedCount) {
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throw new Error(`Expected ${expectedCount} messages in the AI request, but got ${actualCount}`);
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}
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});
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Then('the last AI request user message should contain {string}', async function(this: ApplicationWorld, expectedText: string) {
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if (!this.mockOpenAIServer) {
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throw new Error('Mock OpenAI server is not running');
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}
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const lastRequest = this.mockOpenAIServer.getLastRequest();
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if (!lastRequest) {
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throw new Error('No AI request has been made yet');
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}
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// Find the last user message in the request
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const userMessages = lastRequest.messages.filter(message => message.role === 'user');
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if (userMessages.length === 0) {
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throw new Error('No user message found in the AI request');
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}
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const lastUserMessage = userMessages[userMessages.length - 1];
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const content = lastUserMessage.content ?? '';
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const normalizedExpectedText = expectedText.replaceAll('\\n', '\n');
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const contentHasExpectedText = content.includes(expectedText) || content.includes(normalizedExpectedText);
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if (!contentHasExpectedText) {
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throw new Error(`Expected user message to contain "${expectedText}", but got: "${content}"`);
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}
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});
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Then('the last AI request user message should not contain {string}', async function(this: ApplicationWorld, unexpectedText: string) {
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if (!this.mockOpenAIServer) {
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throw new Error('Mock OpenAI server is not running');
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}
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const lastRequest = this.mockOpenAIServer.getLastRequest();
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if (!lastRequest) {
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throw new Error('No AI request has been made yet');
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}
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// Find the last user message in the request
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const userMessages = lastRequest.messages.filter(message => message.role === 'user');
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if (userMessages.length === 0) {
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throw new Error('No user message found in the AI request');
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}
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const lastUserMessage = userMessages[userMessages.length - 1];
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if (lastUserMessage.content && lastUserMessage.content.includes(unexpectedText)) {
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throw new Error(`Expected user message NOT to contain "${unexpectedText}", but it was found in: "${lastUserMessage.content.substring(0, 200)}..."`);
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}
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});
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// Factory function to create scenario-specific provider config
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// Returns a new object each time to avoid state pollution between scenarios
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function createProviderConfig(): AIProviderConfig {
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return {
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provider: 'TestProvider',
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baseURL: 'http://127.0.0.1:0/v1', // Will be updated with actual port when mock server starts
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models: [
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{ name: 'test-model', features: ['language'] },
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{ name: 'test-embedding-model', features: ['language', 'embedding'] },
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{ name: 'test-speech-model', features: ['speech'] },
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],
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providerClass: 'openAICompatible',
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isPreset: false,
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enabled: true,
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};
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}
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const desiredModelParameters = { temperature: 0.7, systemPrompt: 'You are a helpful assistant.', topP: 0.95 };
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// Step to remove AI settings for testing config errors
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Given('I remove test ai settings', function(this: ApplicationWorld) {
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const settingsPath = path.resolve(process.cwd(), 'test-artifacts', this.scenarioSlug, 'userData-test', 'settings', 'settings.json');
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if (fs.existsSync(settingsPath)) {
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const existing = fs.readJsonSync(settingsPath) as ISettingFile;
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// Remove aiSettings but keep other settings
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const { aiSettings: _removed, ...rest } = existing;
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fs.writeJsonSync(settingsPath, rest, { spaces: 2 });
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}
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});
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Given('I ensure test ai settings exists', function(this: ApplicationWorld) {
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const settingsPath = path.resolve(process.cwd(), 'test-artifacts', this.scenarioSlug, 'userData-test', 'settings', 'settings.json');
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const parsed = fs.readJsonSync(settingsPath) as Record<string, unknown>;
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const actual = (parsed.aiSettings as Record<string, unknown> | undefined) || null;
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if (!actual) {
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throw new Error('aiSettings not found in settings file');
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}
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const actualProviders = (actual.providers as Array<Record<string, unknown>>) || [];
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// If providerConfig is set (from mock server), use it; otherwise create expected config
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// and use actual baseURL from settings (for UI-configured scenarios)
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let providerConfig: AIProviderConfig;
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const providerName = 'TestProvider';
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const existingProvider = actualProviders.find(p => p.provider === providerName) as AIProviderConfig | undefined;
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if (this.providerConfig) {
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// Use the mock server's providerConfig
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providerConfig = this.providerConfig;
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} else if (existingProvider) {
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// For UI-configured scenarios: build expected config using actual baseURL
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providerConfig = createProviderConfig();
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providerConfig.baseURL = existingProvider.baseURL ?? providerConfig.baseURL;
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} else {
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providerConfig = createProviderConfig();
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}
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// Build expected aiSettings from providerConfig and compare with actual
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const modelsArray = providerConfig.models;
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const modelName = modelsArray[0]?.name;
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// Check TestProvider exists
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const testProvider = actualProviders.find(p => p.provider === providerName);
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if (!testProvider) {
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console.error('TestProvider not found in actual providers:', JSON.stringify(actualProviders, null, 2));
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throw new Error('TestProvider not found in aiSettings');
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}
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// Verify TestProvider configuration
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if (!isEqual(testProvider, providerConfig)) {
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console.error('TestProvider config mismatch. expected:', JSON.stringify(providerConfig, null, 2));
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console.error('TestProvider config actual:', JSON.stringify(testProvider, null, 2));
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throw new Error('TestProvider configuration does not match expected');
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}
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// Check ComfyUI provider exists
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const comfyuiProvider = actualProviders.find(p => p.provider === 'comfyui');
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if (!comfyuiProvider) {
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console.error('ComfyUI provider not found in actual providers:', JSON.stringify(actualProviders, null, 2));
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throw new Error('ComfyUI provider not found in aiSettings');
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}
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// Verify ComfyUI has test-flux model with workflow path
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const comfyuiModels = (comfyuiProvider.models as Array<Record<string, unknown>>) || [];
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const testFluxModel = comfyuiModels.find(m => m.name === 'test-flux');
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if (!testFluxModel) {
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console.error('test-flux model not found in ComfyUI models:', JSON.stringify(comfyuiModels, null, 2));
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throw new Error('test-flux model not found in ComfyUI provider');
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}
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// Verify workflow path
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const parameters = testFluxModel.parameters as Record<string, unknown> | undefined;
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if (!parameters || parameters.workflowPath !== 'C:/test/mock/workflow.json') {
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console.error('Workflow path mismatch. expected: C:/test/mock/workflow.json, actual:', parameters?.workflowPath);
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throw new Error('Workflow path not correctly saved');
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}
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// Verify default config
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const defaultConfig = actual.defaultConfig as Record<string, unknown>;
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const defaultModel = defaultConfig.default as Record<string, unknown>;
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if (defaultModel?.provider !== providerName || defaultModel?.model !== modelName) {
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console.error('Default config mismatch. expected provider:', providerName, 'model:', modelName);
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console.error('actual defaultModel:', JSON.stringify(defaultModel, null, 2));
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throw new Error('Default configuration does not match expected');
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}
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});
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// Version without datatable for simple cases
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Given('I add test ai settings', async function(this: ApplicationWorld) {
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const settingsPath = path.resolve(process.cwd(), 'test-artifacts', this.scenarioSlug, 'userData-test', 'settings', 'settings.json');
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let existing = {} as ISettingFile;
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if (fs.existsSync(settingsPath)) {
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existing = fs.readJsonSync(settingsPath) as ISettingFile;
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} else {
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fs.ensureDirSync(path.dirname(settingsPath));
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}
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// Initialize scenario-specific providerConfig if not set
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if (!this.providerConfig) {
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this.providerConfig = createProviderConfig();
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}
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const providerConfig = this.providerConfig;
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const modelsArray = providerConfig.models;
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const modelName = modelsArray[0]?.name;
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const embeddingModelName = modelsArray[1]?.name;
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const speechModelName = modelsArray[2]?.name;
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const newAi: AIGlobalSettings = {
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providers: [providerConfig],
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defaultConfig: {
|
|
default: {
|
|
provider: providerConfig.provider,
|
|
model: modelName,
|
|
},
|
|
embedding: {
|
|
provider: providerConfig.provider,
|
|
model: embeddingModelName,
|
|
},
|
|
speech: {
|
|
provider: providerConfig.provider,
|
|
model: speechModelName,
|
|
},
|
|
modelParameters: desiredModelParameters,
|
|
},
|
|
};
|
|
|
|
const newPreferences = existing.preferences || {};
|
|
|
|
fs.writeJsonSync(settingsPath, { ...existing, aiSettings: newAi, preferences: newPreferences } as ISettingFile, { spaces: 2 });
|
|
});
|
|
|
|
// Version with datatable for advanced configuration
|
|
Given('I add test ai settings:', async function(this: ApplicationWorld, dataTable: DataTable) {
|
|
const settingsPath = path.resolve(process.cwd(), 'test-artifacts', this.scenarioSlug, 'userData-test', 'settings', 'settings.json');
|
|
let existing = {} as ISettingFile;
|
|
if (fs.existsSync(settingsPath)) {
|
|
existing = fs.readJsonSync(settingsPath) as ISettingFile;
|
|
} else {
|
|
fs.ensureDirSync(path.dirname(settingsPath));
|
|
}
|
|
|
|
// Initialize scenario-specific providerConfig if not set
|
|
if (!this.providerConfig) {
|
|
this.providerConfig = createProviderConfig();
|
|
}
|
|
const providerConfig = this.providerConfig;
|
|
|
|
const modelsArray = providerConfig.models;
|
|
const modelName = modelsArray[0]?.name;
|
|
const embeddingModelName = modelsArray[1]?.name;
|
|
const speechModelName = modelsArray[2]?.name;
|
|
|
|
// Parse options from data table
|
|
let freeModel: string | undefined;
|
|
let aiGenerateBackupTitle: boolean | undefined;
|
|
let aiGenerateBackupTitleTimeout: number | undefined;
|
|
|
|
if (dataTable && typeof dataTable.raw === 'function') {
|
|
const rows = dataTable.raw();
|
|
// Process all rows as key-value pairs (no header row)
|
|
for (let index = 0; index < rows.length; index++) {
|
|
const row = rows[index];
|
|
const key = (row[0] ?? '').trim();
|
|
const value = (row[1] ?? '').trim();
|
|
|
|
if (key === 'freeModel') {
|
|
// If value is 'true', enable freeModel using the same model as main model
|
|
if (value === 'true') {
|
|
freeModel = modelName;
|
|
}
|
|
} else if (key === 'aiGenerateBackupTitle') {
|
|
aiGenerateBackupTitle = value === 'true';
|
|
} else if (key === 'aiGenerateBackupTitleTimeout') {
|
|
aiGenerateBackupTitleTimeout = Number.parseInt(value, 10);
|
|
}
|
|
}
|
|
}
|
|
|
|
const newAi: AIGlobalSettings = {
|
|
providers: [providerConfig],
|
|
defaultConfig: {
|
|
default: {
|
|
provider: providerConfig.provider,
|
|
model: modelName,
|
|
},
|
|
embedding: {
|
|
provider: providerConfig.provider,
|
|
model: embeddingModelName,
|
|
},
|
|
speech: {
|
|
provider: providerConfig.provider,
|
|
model: speechModelName,
|
|
},
|
|
...(freeModel
|
|
? {
|
|
free: {
|
|
provider: providerConfig.provider,
|
|
model: freeModel,
|
|
},
|
|
}
|
|
: {}),
|
|
modelParameters: desiredModelParameters,
|
|
},
|
|
};
|
|
|
|
const newPreferences = {
|
|
...(existing.preferences || {}),
|
|
...(aiGenerateBackupTitle !== undefined ? { aiGenerateBackupTitle } : {}),
|
|
...(aiGenerateBackupTitleTimeout !== undefined ? { aiGenerateBackupTitleTimeout } : {}),
|
|
};
|
|
|
|
fs.writeJsonSync(settingsPath, { ...existing, aiSettings: newAi, preferences: newPreferences } as ISettingFile, { spaces: 2 });
|
|
});
|
|
|
|
async function clearAISettings(scenarioRoot?: string) {
|
|
const root = scenarioRoot || process.cwd();
|
|
const settingsPath = path.resolve(root, 'userData-test', 'settings', 'settings.json');
|
|
if (!(await fs.pathExists(settingsPath))) return;
|
|
const parsed = await fs.readJson(settingsPath) as ISettingFile;
|
|
const cleaned = omit(parsed, ['aiSettings']);
|
|
await fs.writeJson(settingsPath, cleaned, { spaces: 2 });
|
|
}
|
|
|
|
// Step to send ask AI with selection IPC message
|
|
When('I send ask AI with selection message with text {string} and workspace {string}', async function(this: ApplicationWorld, selectionText: string, workspaceName: string) {
|
|
const currentWindow = await this.getWindow('main');
|
|
if (!currentWindow) {
|
|
throw new Error('Main window not found');
|
|
}
|
|
|
|
// Get workspace ID from workspace name
|
|
const workspaceId = await currentWindow.evaluate(async (name: string): Promise<string | undefined> => {
|
|
// Use a narrow type view of window.service to avoid coupling to preload internals.
|
|
const windowWithService = window as unknown as { service: { workspace: { getWorkspacesAsList: () => Promise<IWorkspace[]> } } };
|
|
const workspaces = await windowWithService.service.workspace.getWorkspacesAsList();
|
|
const workspace = workspaces.find((ws) => ws.name === name);
|
|
return workspace?.id;
|
|
}, workspaceName);
|
|
|
|
if (!workspaceId) {
|
|
throw new Error(`Workspace with name "${workspaceName}" not found`);
|
|
}
|
|
|
|
// Send IPC message to trigger "Talk with AI" through main process
|
|
// Use app.evaluate to access Electron main process API
|
|
if (!this.app) {
|
|
throw new Error('Electron app not found');
|
|
}
|
|
|
|
const sendResult = await this.app.evaluate(async ({ BrowserWindow }, { text, wsId }: { text: string; wsId: string }) => {
|
|
// Find main window - the first window is always the main window in TidGi
|
|
const allWindows = BrowserWindow.getAllWindows();
|
|
const mainWindow = allWindows[0]; // Main window is always the first window created
|
|
|
|
if (!mainWindow) {
|
|
return { success: false, error: 'No windows found', windowCount: allWindows.length };
|
|
}
|
|
|
|
const data = {
|
|
selectionText: text,
|
|
wikiUrl: `tidgi://${wsId}`,
|
|
workspaceId: wsId,
|
|
};
|
|
|
|
// Send IPC message to renderer
|
|
mainWindow.webContents.send('ask-ai-with-selection', data);
|
|
|
|
return { success: true };
|
|
}, { text: selectionText, wsId: workspaceId });
|
|
|
|
if (!sendResult.success) {
|
|
throw new Error(`Failed to send IPC message: ${sendResult.error || 'Unknown error'}`);
|
|
}
|
|
|
|
// Small delay to ensure IPC message is processed (cross-process communication needs time)
|
|
await new Promise(resolve => setTimeout(resolve, 200));
|
|
});
|
|
|
|
export { clearAISettings };
|