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@@ -2,6 +2,7 @@ import path from 'path';
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import chalk from 'chalk';
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import boxen from 'boxen';
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import Table from 'cli-table3';
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import { z } from 'zod';
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import {
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displayBanner,
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@@ -10,16 +11,23 @@ import {
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stopLoadingIndicator
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} from '../ui.js';
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import { log, readJSON, writeJSON, truncate } from '../utils.js';
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import { _handleAnthropicStream } from '../ai-services.js';
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import {
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getDefaultPriority,
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getResearchModelId,
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getResearchTemperature,
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getResearchMaxTokens,
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getMainModelId,
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getMainTemperature,
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getMainMaxTokens
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} from '../config-manager.js';
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import { generateObjectService } from '../ai-services-unified.js';
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import { getDefaultPriority } from '../config-manager.js';
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import generateTaskFiles from './generate-task-files.js';
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// Define Zod schema for the expected AI output object
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const AiTaskDataSchema = z.object({
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title: z.string().describe('Clear, concise title for the task'),
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description: z
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.string()
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.describe('A one or two sentence description of the task'),
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details: z
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.string()
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.describe('In-depth implementation details, considerations, and guidance'),
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testStrategy: z
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.string()
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.describe('Detailed approach for verifying task completion')
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});
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/**
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* Add a new task using AI
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@@ -31,21 +39,32 @@ import {
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* @param {Object} mcpLog - MCP logger object (optional)
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* @param {Object} session - Session object from MCP server (optional)
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* @param {string} outputFormat - Output format (text or json)
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* @param {Object} customEnv - Custom environment variables (optional)
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* @param {Object} customEnv - Custom environment variables (optional) - Note: AI params override deprecated
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* @param {Object} manualTaskData - Manual task data (optional, for direct task creation without AI)
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* @param {boolean} useResearch - Whether to use the research model (passed to unified service)
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* @returns {number} The new task ID
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*/
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async function addTask(
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tasksPath,
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prompt,
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dependencies = [],
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priority = getDefaultPriority(), // Use getter
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priority = getDefaultPriority(), // Keep getter for default priority
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{ reportProgress, mcpLog, session } = {},
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outputFormat = 'text',
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customEnv = null,
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manualTaskData = null
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// customEnv = null, // Removed as AI param overrides are deprecated
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manualTaskData = null,
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useResearch = false // <-- Add useResearch parameter
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) {
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let loadingIndicator = null; // Keep indicator variable accessible
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let loadingIndicator = null;
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// Create custom reporter that checks for MCP log
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const report = (message, level = 'info') => {
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if (mcpLog) {
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mcpLog[level](message);
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} else if (outputFormat === 'text') {
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log(level, message);
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}
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};
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try {
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// Only display banner and UI elements for text output (CLI)
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@@ -65,12 +84,13 @@ async function addTask(
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// Read the existing tasks
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const data = readJSON(tasksPath);
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if (!data || !data.tasks) {
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log('error', 'Invalid or missing tasks.json.');
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report('Invalid or missing tasks.json.', 'error');
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throw new Error('Invalid or missing tasks.json.');
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}
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// Find the highest task ID to determine the next ID
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const highestId = Math.max(...data.tasks.map((t) => t.id));
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const highestId =
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data.tasks.length > 0 ? Math.max(...data.tasks.map((t) => t.id)) : 0;
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const newTaskId = highestId + 1;
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// Only show UI box for CLI mode
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@@ -87,251 +107,119 @@ async function addTask(
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// Validate dependencies before proceeding
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const invalidDeps = dependencies.filter((depId) => {
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return !data.tasks.some((t) => t.id === depId);
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// Ensure depId is parsed as a number for comparison
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const numDepId = parseInt(depId, 10);
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return isNaN(numDepId) || !data.tasks.some((t) => t.id === numDepId);
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});
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if (invalidDeps.length > 0) {
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log(
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'warn',
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`The following dependencies do not exist: ${invalidDeps.join(', ')}`
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report(
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`The following dependencies do not exist or are invalid: ${invalidDeps.join(', ')}`,
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'warn'
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);
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log('info', 'Removing invalid dependencies...');
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report('Removing invalid dependencies...', 'info');
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dependencies = dependencies.filter(
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(depId) => !invalidDeps.includes(depId)
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);
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}
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// Ensure dependencies are numbers
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const numericDependencies = dependencies.map((dep) => parseInt(dep, 10));
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let taskData;
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// Check if manual task data is provided
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if (manualTaskData) {
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// Use manual task data directly
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log('info', 'Using manually provided task data');
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report('Using manually provided task data', 'info');
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taskData = manualTaskData;
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// Basic validation for manual data
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if (
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!taskData.title ||
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typeof taskData.title !== 'string' ||
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!taskData.description ||
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typeof taskData.description !== 'string'
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) {
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throw new Error(
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'Manual task data must include at least a title and description.'
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);
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}
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} else {
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// Use AI to generate task data
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// --- Refactored AI Interaction ---
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report('Generating task data with AI...', 'info');
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// Create context string for task creation prompt
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let contextTasks = '';
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if (dependencies.length > 0) {
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// Provide context for the dependent tasks
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if (numericDependencies.length > 0) {
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const dependentTasks = data.tasks.filter((t) =>
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dependencies.includes(t.id)
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numericDependencies.includes(t.id)
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);
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contextTasks = `\nThis task depends on the following tasks:\n${dependentTasks
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.map((t) => `- Task ${t.id}: ${t.title} - ${t.description}`)
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.join('\n')}`;
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} else {
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// Provide a few recent tasks as context
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const recentTasks = [...data.tasks]
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.sort((a, b) => b.id - a.id)
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.slice(0, 3);
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contextTasks = `\nRecent tasks in the project:\n${recentTasks
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.map((t) => `- Task ${t.id}: ${t.title} - ${t.description}`)
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.join('\n')}`;
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if (recentTasks.length > 0) {
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contextTasks = `\nRecent tasks in the project:\n${recentTasks
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.map((t) => `- Task ${t.id}: ${t.title} - ${t.description}`)
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.join('\n')}`;
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}
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}
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// System Prompt
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const systemPrompt =
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"You are a helpful assistant that creates well-structured tasks for a software development project. Generate a single new task based on the user's description, adhering strictly to the provided JSON schema.";
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// Task Structure Description (for user prompt)
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const taskStructureDesc = `
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{
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"title": "Task title goes here",
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"description": "A concise one or two sentence description of what the task involves",
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"details": "In-depth implementation details, considerations, and guidance.",
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"testStrategy": "Detailed approach for verifying task completion."
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}`;
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// User Prompt
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const userPrompt = `Create a comprehensive new task (Task #${newTaskId}) for a software development project based on this description: "${prompt}"
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${contextTasks}
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Return your answer as a single JSON object matching the schema precisely.
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Make sure the details and test strategy are thorough and specific.`;
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// Start the loading indicator - only for text mode
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if (outputFormat === 'text') {
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loadingIndicator = startLoadingIndicator(
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'Generating new task with Claude AI...'
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`Generating new task with ${useResearch ? 'Research' : 'Main'} AI...`
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);
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}
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try {
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// Import the AI services - explicitly importing here to avoid circular dependencies
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const {
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_handleAnthropicStream,
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_buildAddTaskPrompt,
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parseTaskJsonResponse,
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getAvailableAIModel
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} = await import('./ai-services.js');
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// Determine the service role based on the useResearch flag
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const serviceRole = useResearch ? 'research' : 'main';
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// Initialize model state variables
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let claudeOverloaded = false;
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let modelAttempts = 0;
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const maxModelAttempts = 2; // Try up to 2 models before giving up
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let aiGeneratedTaskData = null;
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// Call the unified AI service
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const aiGeneratedTaskData = await generateObjectService({
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role: serviceRole, // <-- Use the determined role
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session: session, // Pass session for API key resolution
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schema: AiTaskDataSchema, // Pass the Zod schema
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objectName: 'newTaskData', // Name for the object
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systemPrompt: systemPrompt,
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prompt: userPrompt,
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reportProgress // Pass progress reporter if available
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});
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// Loop through model attempts
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while (modelAttempts < maxModelAttempts && !aiGeneratedTaskData) {
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modelAttempts++; // Increment attempt counter
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const isLastAttempt = modelAttempts >= maxModelAttempts;
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let modelType = null; // Track which model we're using
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try {
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// Get the best available model based on our current state
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const result = getAvailableAIModel({
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claudeOverloaded,
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requiresResearch: false // We're not using the research flag here
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});
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modelType = result.type;
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const client = result.client;
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log(
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'info',
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`Attempt ${modelAttempts}/${maxModelAttempts}: Generating task using ${modelType}`
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);
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// Update loading indicator text - only for text output
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if (outputFormat === 'text') {
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if (loadingIndicator) {
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stopLoadingIndicator(loadingIndicator); // Stop previous indicator
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}
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loadingIndicator = startLoadingIndicator(
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`Attempt ${modelAttempts}: Using ${modelType.toUpperCase()}...`
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);
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}
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// Build the prompts using the helper
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const { systemPrompt, userPrompt } = _buildAddTaskPrompt(
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prompt,
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contextTasks,
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{ newTaskId }
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);
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if (modelType === 'perplexity') {
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// Use Perplexity AI
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const response = await client.chat.completions.create({
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model: getResearchModelId(session),
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messages: [
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{ role: 'system', content: systemPrompt },
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{ role: 'user', content: userPrompt }
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],
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temperature: getResearchTemperature(session),
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max_tokens: getResearchMaxTokens(session)
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});
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const responseText = response.choices[0].message.content;
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aiGeneratedTaskData = parseTaskJsonResponse(responseText);
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} else {
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// Use Claude (default)
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// Prepare API parameters using getters, preserving customEnv override
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const apiParams = {
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model: customEnv?.ANTHROPIC_MODEL || getMainModelId(session),
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max_tokens: customEnv?.MAX_TOKENS || getMainMaxTokens(session),
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temperature:
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customEnv?.TEMPERATURE || getMainTemperature(session),
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system: systemPrompt,
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messages: [{ role: 'user', content: userPrompt }]
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};
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// Call the streaming API using our helper
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try {
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const fullResponse = await _handleAnthropicStream(
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client,
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apiParams,
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{ reportProgress, mcpLog },
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outputFormat === 'text' // CLI mode flag
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);
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log(
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'debug',
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`Streaming response length: ${fullResponse.length} characters`
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);
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// Parse the response using our helper
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aiGeneratedTaskData = parseTaskJsonResponse(fullResponse);
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} catch (streamError) {
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// Process stream errors explicitly
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log('error', `Stream error: ${streamError.message}`);
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// Check if this is an overload error
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let isOverload = false;
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// Check 1: SDK specific property
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if (streamError.type === 'overloaded_error') {
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isOverload = true;
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}
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// Check 2: Check nested error property
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else if (streamError.error?.type === 'overloaded_error') {
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isOverload = true;
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}
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// Check 3: Check status code
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else if (
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streamError.status === 429 ||
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streamError.status === 529
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) {
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isOverload = true;
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}
|
|
|
|
|
// Check 4: Check message string
|
|
|
|
|
else if (
|
|
|
|
|
streamError.message?.toLowerCase().includes('overloaded')
|
|
|
|
|
) {
|
|
|
|
|
isOverload = true;
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
if (isOverload) {
|
|
|
|
|
claudeOverloaded = true;
|
|
|
|
|
log(
|
|
|
|
|
'warn',
|
|
|
|
|
'Claude overloaded. Will attempt fallback model if available.'
|
|
|
|
|
);
|
|
|
|
|
// Throw to continue to next model attempt
|
|
|
|
|
throw new Error('Claude overloaded');
|
|
|
|
|
} else {
|
|
|
|
|
// Re-throw non-overload errors
|
|
|
|
|
throw streamError;
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
// If we got here without errors and have task data, we're done
|
|
|
|
|
if (aiGeneratedTaskData) {
|
|
|
|
|
log(
|
|
|
|
|
'info',
|
|
|
|
|
`Successfully generated task data using ${modelType} on attempt ${modelAttempts}`
|
|
|
|
|
);
|
|
|
|
|
break;
|
|
|
|
|
}
|
|
|
|
|
} catch (modelError) {
|
|
|
|
|
const failedModel = modelType || 'unknown model';
|
|
|
|
|
log(
|
|
|
|
|
'warn',
|
|
|
|
|
`Attempt ${modelAttempts} failed using ${failedModel}: ${modelError.message}`
|
|
|
|
|
);
|
|
|
|
|
|
|
|
|
|
// Continue to next attempt if we have more attempts and this was specifically an overload error
|
|
|
|
|
const wasOverload = modelError.message
|
|
|
|
|
?.toLowerCase()
|
|
|
|
|
.includes('overload');
|
|
|
|
|
|
|
|
|
|
if (wasOverload && !isLastAttempt) {
|
|
|
|
|
if (modelType === 'claude') {
|
|
|
|
|
claudeOverloaded = true;
|
|
|
|
|
log('info', 'Will attempt with Perplexity AI next');
|
|
|
|
|
}
|
|
|
|
|
continue; // Continue to next attempt
|
|
|
|
|
} else if (isLastAttempt) {
|
|
|
|
|
log(
|
|
|
|
|
'error',
|
|
|
|
|
`Final attempt (${modelAttempts}/${maxModelAttempts}) failed. No fallback possible.`
|
|
|
|
|
);
|
|
|
|
|
throw modelError; // Re-throw on last attempt
|
|
|
|
|
} else {
|
|
|
|
|
throw modelError; // Re-throw for non-overload errors
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
// If we don't have task data after all attempts, throw an error
|
|
|
|
|
if (!aiGeneratedTaskData) {
|
|
|
|
|
throw new Error(
|
|
|
|
|
'Failed to generate task data after all model attempts'
|
|
|
|
|
);
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
// Set the AI-generated task data
|
|
|
|
|
taskData = aiGeneratedTaskData;
|
|
|
|
|
report('Successfully generated task data from AI.', 'success');
|
|
|
|
|
taskData = aiGeneratedTaskData; // Assign the validated object
|
|
|
|
|
} catch (error) {
|
|
|
|
|
// Handle AI errors
|
|
|
|
|
log('error', `Error generating task with AI: ${error.message}`);
|
|
|
|
|
|
|
|
|
|
// Stop any loading indicator
|
|
|
|
|
if (outputFormat === 'text' && loadingIndicator) {
|
|
|
|
|
stopLoadingIndicator(loadingIndicator);
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
throw error;
|
|
|
|
|
report(`Error generating task with AI: ${error.message}`, 'error');
|
|
|
|
|
if (loadingIndicator) stopLoadingIndicator(loadingIndicator);
|
|
|
|
|
throw error; // Re-throw error after logging
|
|
|
|
|
} finally {
|
|
|
|
|
if (loadingIndicator) stopLoadingIndicator(loadingIndicator); // Ensure indicator stops
|
|
|
|
|
}
|
|
|
|
|
// --- End Refactored AI Interaction ---
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
// Create the new task object
|
|
|
|
|
@@ -342,8 +230,9 @@ async function addTask(
|
|
|
|
|
details: taskData.details || '',
|
|
|
|
|
testStrategy: taskData.testStrategy || '',
|
|
|
|
|
status: 'pending',
|
|
|
|
|
dependencies: dependencies,
|
|
|
|
|
priority: priority
|
|
|
|
|
dependencies: numericDependencies, // Use validated numeric dependencies
|
|
|
|
|
priority: priority,
|
|
|
|
|
subtasks: [] // Initialize with empty subtasks array
|
|
|
|
|
};
|
|
|
|
|
|
|
|
|
|
// Add the task to the tasks array
|
|
|
|
|
@@ -353,13 +242,9 @@ async function addTask(
|
|
|
|
|
writeJSON(tasksPath, data);
|
|
|
|
|
|
|
|
|
|
// Generate markdown task files
|
|
|
|
|
log('info', 'Generating task files...');
|
|
|
|
|
await generateTaskFiles(tasksPath, path.dirname(tasksPath));
|
|
|
|
|
|
|
|
|
|
// Stop the loading indicator if it's still running
|
|
|
|
|
if (outputFormat === 'text' && loadingIndicator) {
|
|
|
|
|
stopLoadingIndicator(loadingIndicator);
|
|
|
|
|
}
|
|
|
|
|
report('Generating task files...', 'info');
|
|
|
|
|
// Pass mcpLog if available to generateTaskFiles
|
|
|
|
|
await generateTaskFiles(tasksPath, path.dirname(tasksPath), { mcpLog });
|
|
|
|
|
|
|
|
|
|
// Show success message - only for text output (CLI)
|
|
|
|
|
if (outputFormat === 'text') {
|
|
|
|
|
@@ -369,7 +254,7 @@ async function addTask(
|
|
|
|
|
chalk.cyan.bold('Title'),
|
|
|
|
|
chalk.cyan.bold('Description')
|
|
|
|
|
],
|
|
|
|
|
colWidths: [5, 30, 50]
|
|
|
|
|
colWidths: [5, 30, 50] // Adjust widths as needed
|
|
|
|
|
});
|
|
|
|
|
|
|
|
|
|
table.push([
|
|
|
|
|
@@ -381,7 +266,20 @@ async function addTask(
|
|
|
|
|
console.log(chalk.green('✅ New task created successfully:'));
|
|
|
|
|
console.log(table.toString());
|
|
|
|
|
|
|
|
|
|
// Show success message
|
|
|
|
|
// Helper to get priority color
|
|
|
|
|
const getPriorityColor = (p) => {
|
|
|
|
|
switch (p?.toLowerCase()) {
|
|
|
|
|
case 'high':
|
|
|
|
|
return 'red';
|
|
|
|
|
case 'low':
|
|
|
|
|
return 'gray';
|
|
|
|
|
case 'medium':
|
|
|
|
|
default:
|
|
|
|
|
return 'yellow';
|
|
|
|
|
}
|
|
|
|
|
};
|
|
|
|
|
|
|
|
|
|
// Show success message box
|
|
|
|
|
console.log(
|
|
|
|
|
boxen(
|
|
|
|
|
chalk.white.bold(`Task ${newTaskId} Created Successfully`) +
|
|
|
|
|
@@ -394,8 +292,9 @@ async function addTask(
|
|
|
|
|
`Priority: ${chalk.keyword(getPriorityColor(newTask.priority))(newTask.priority)}`
|
|
|
|
|
) +
|
|
|
|
|
'\n' +
|
|
|
|
|
(dependencies.length > 0
|
|
|
|
|
? chalk.white(`Dependencies: ${dependencies.join(', ')}`) + '\n'
|
|
|
|
|
(numericDependencies.length > 0
|
|
|
|
|
? chalk.white(`Dependencies: ${numericDependencies.join(', ')}`) +
|
|
|
|
|
'\n'
|
|
|
|
|
: '') +
|
|
|
|
|
'\n' +
|
|
|
|
|
chalk.white.bold('Next Steps:') +
|
|
|
|
|
@@ -419,15 +318,16 @@ async function addTask(
|
|
|
|
|
// Return the new task ID
|
|
|
|
|
return newTaskId;
|
|
|
|
|
} catch (error) {
|
|
|
|
|
// Stop any loading indicator
|
|
|
|
|
if (outputFormat === 'text' && loadingIndicator) {
|
|
|
|
|
// Stop any loading indicator on error
|
|
|
|
|
if (loadingIndicator) {
|
|
|
|
|
stopLoadingIndicator(loadingIndicator);
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
log('error', `Error adding task: ${error.message}`);
|
|
|
|
|
report(`Error adding task: ${error.message}`, 'error');
|
|
|
|
|
if (outputFormat === 'text') {
|
|
|
|
|
console.error(chalk.red(`Error: ${error.message}`));
|
|
|
|
|
}
|
|
|
|
|
// In MCP mode, we let the direct function handler catch and format
|
|
|
|
|
throw error;
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|