fix(commands): implement manual creation mode for add-task command
- Add support for --title/-t and --description/-d flags in add-task command - Fix validation for manual creation mode (title + description) - Implement proper testing for both prompt and manual creation modes - Update testing documentation with Commander.js testing best practices - Add guidance on handling variable hoisting and module initialization issues Changeset: brave-doors-open.md
This commit is contained in:
Eyal Toledano
@@ -3120,7 +3120,7 @@ function clearSubtasks(tasksPath, taskIds) {
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/**
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* Add a new task using AI
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* @param {string} tasksPath - Path to the tasks.json file
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* @param {string} prompt - Description of the task to add
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* @param {string} prompt - Description of the task to add (required for AI-driven creation)
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* @param {Array} dependencies - Task dependencies
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* @param {string} priority - Task priority
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* @param {function} reportProgress - Function to report progress to MCP server (optional)
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@@ -3128,6 +3128,7 @@ function clearSubtasks(tasksPath, taskIds) {
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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} manualTaskData - Manual task data (optional, for direct task creation without AI)
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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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@@ -3137,7 +3138,8 @@ async function addTask(
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priority = 'medium',
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{ reportProgress, mcpLog, session } = {},
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outputFormat = 'text',
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customEnv = null
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customEnv = null,
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manualTaskData = null
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) {
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let loadingIndicator = null; // Keep indicator variable accessible
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@@ -3195,328 +3197,346 @@ async function addTask(
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);
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}
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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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const dependentTasks = data.tasks.filter((t) =>
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dependencies.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} - ${t.description}`)
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.join('\n')}`;
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let taskData;
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// Check if manual task data is provided
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if (manualTaskData) {
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// Use manual task data directly
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log('info', 'Using manually provided task data');
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taskData = manualTaskData;
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} else {
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// Provide a few recent tasks as context
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const recentTasks = [...data.tasks]
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.sort((a, b) => b.id - a.id)
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.slice(0, 3);
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contextTasks = `\nRecent tasks in the project:\n${recentTasks
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.map((t) => `- Task ${t.id}: ${t.title} - ${t.description}`)
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.join('\n')}`;
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}
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// Use AI to generate task data
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// Create context string for task creation prompt
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let contextTasks = '';
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if (dependencies.length > 0) {
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// Provide context for the dependent tasks
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const dependentTasks = data.tasks.filter((t) =>
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dependencies.includes(t.id)
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);
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contextTasks = `\nThis task depends on the following tasks:\n${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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}
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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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);
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}
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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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);
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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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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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// 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 taskData = null;
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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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// Loop through model attempts
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while (modelAttempts < maxModelAttempts && !taskData) {
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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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// 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 perplexityModel =
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process.env.PERPLEXITY_MODEL ||
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session?.env?.PERPLEXITY_MODEL ||
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'sonar-pro';
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const response = await client.chat.completions.create({
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model: perplexityModel,
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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: parseFloat(
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process.env.TEMPERATURE ||
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session?.env?.TEMPERATURE ||
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CONFIG.temperature
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),
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max_tokens: parseInt(
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process.env.MAX_TOKENS ||
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session?.env?.MAX_TOKENS ||
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CONFIG.maxTokens
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)
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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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const responseText = response.choices[0].message.content;
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taskData = parseTaskJsonResponse(responseText);
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} else {
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// Use Claude (default)
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// Prepare API parameters
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const apiParams = {
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model:
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session?.env?.ANTHROPIC_MODEL ||
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CONFIG.model ||
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customEnv?.ANTHROPIC_MODEL,
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max_tokens:
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session?.env?.MAX_TOKENS ||
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CONFIG.maxTokens ||
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customEnv?.MAX_TOKENS,
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temperature:
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session?.env?.TEMPERATURE ||
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CONFIG.temperature ||
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customEnv?.TEMPERATURE,
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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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taskData = 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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}
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// Check 4: Check message string
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else if (
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streamError.message?.toLowerCase().includes('overloaded')
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) {
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isOverload = true;
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}
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if (isOverload) {
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claudeOverloaded = true;
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log(
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'warn',
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'Claude overloaded. Will attempt fallback model if available.'
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);
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// Throw to continue to next model attempt
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throw new Error('Claude overloaded');
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} else {
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// Re-throw non-overload errors
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throw streamError;
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}
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}
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}
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// If we got here without errors and have task data, we're done
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if (taskData) {
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log(
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'info',
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`Successfully generated task data using ${modelType} on attempt ${modelAttempts}`
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`Attempt ${modelAttempts}/${maxModelAttempts}: Generating task using ${modelType}`
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);
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break;
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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 perplexityModel =
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process.env.PERPLEXITY_MODEL ||
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session?.env?.PERPLEXITY_MODEL ||
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'sonar-pro';
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const response = await client.chat.completions.create({
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model: perplexityModel,
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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: parseFloat(
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process.env.TEMPERATURE ||
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session?.env?.TEMPERATURE ||
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CONFIG.temperature
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),
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max_tokens: parseInt(
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process.env.MAX_TOKENS ||
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session?.env?.MAX_TOKENS ||
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CONFIG.maxTokens
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)
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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
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const apiParams = {
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model:
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session?.env?.ANTHROPIC_MODEL ||
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CONFIG.model ||
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customEnv?.ANTHROPIC_MODEL,
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max_tokens:
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session?.env?.MAX_TOKENS ||
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CONFIG.maxTokens ||
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customEnv?.MAX_TOKENS,
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temperature:
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session?.env?.TEMPERATURE ||
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CONFIG.temperature ||
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customEnv?.TEMPERATURE,
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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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}
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// Check 4: Check message string
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else if (
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streamError.message?.toLowerCase().includes('overloaded')
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) {
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isOverload = true;
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}
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if (isOverload) {
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claudeOverloaded = true;
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log(
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'warn',
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'Claude overloaded. Will attempt fallback model if available.'
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);
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// Throw to continue to next model attempt
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throw new Error('Claude overloaded');
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} else {
|
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// Re-throw non-overload errors
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throw streamError;
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}
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}
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}
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// If we got here without errors and have task data, we're done
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if (aiGeneratedTaskData) {
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log(
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'info',
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`Successfully generated task data using ${modelType} on attempt ${modelAttempts}`
|
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);
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break;
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}
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} catch (modelError) {
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const failedModel = modelType || 'unknown model';
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log(
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'warn',
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`Attempt ${modelAttempts} failed using ${failedModel}: ${modelError.message}`
|
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);
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// Continue to next attempt if we have more attempts and this was specifically an overload error
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const wasOverload = modelError.message
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?.toLowerCase()
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.includes('overload');
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|
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if (wasOverload && !isLastAttempt) {
|
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if (modelType === 'claude') {
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claudeOverloaded = true;
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log('info', 'Will attempt with Perplexity AI next');
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}
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continue; // Continue to next attempt
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} else if (isLastAttempt) {
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log(
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'error',
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`Final attempt (${modelAttempts}/${maxModelAttempts}) failed. No fallback possible.`
|
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);
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throw modelError; // Re-throw on last attempt
|
||||
} else {
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throw modelError; // Re-throw for non-overload errors
|
||||
}
|
||||
}
|
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} catch (modelError) {
|
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const failedModel = modelType || 'unknown model';
|
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log(
|
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'warn',
|
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`Attempt ${modelAttempts} failed using ${failedModel}: ${modelError.message}`
|
||||
}
|
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|
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// If we don't have task data after all attempts, throw an error
|
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if (!aiGeneratedTaskData) {
|
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throw new Error(
|
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'Failed to generate task data after all model attempts'
|
||||
);
|
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|
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// Continue to next attempt if we have more attempts and this was specifically an overload error
|
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const wasOverload = modelError.message
|
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?.toLowerCase()
|
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.includes('overload');
|
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|
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if (wasOverload && !isLastAttempt) {
|
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if (modelType === 'claude') {
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claudeOverloaded = true;
|
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log('info', 'Will attempt with Perplexity AI next');
|
||||
}
|
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continue; // Continue to next attempt
|
||||
} else if (isLastAttempt) {
|
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log(
|
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'error',
|
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`Final attempt (${modelAttempts}/${maxModelAttempts}) failed. No fallback possible.`
|
||||
);
|
||||
throw modelError; // Re-throw on last attempt
|
||||
} else {
|
||||
throw modelError; // Re-throw for non-overload errors
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// If we don't have task data after all attempts, throw an error
|
||||
if (!taskData) {
|
||||
throw new Error(
|
||||
'Failed to generate task data after all model attempts'
|
||||
);
|
||||
}
|
||||
|
||||
// Create the new task object
|
||||
const newTask = {
|
||||
id: newTaskId,
|
||||
title: taskData.title,
|
||||
description: taskData.description,
|
||||
status: 'pending',
|
||||
dependencies: dependencies,
|
||||
priority: priority,
|
||||
details: taskData.details || '',
|
||||
testStrategy:
|
||||
taskData.testStrategy ||
|
||||
'Manually verify the implementation works as expected.'
|
||||
};
|
||||
|
||||
// Add the new task to the tasks array
|
||||
data.tasks.push(newTask);
|
||||
|
||||
// Validate dependencies in the entire task set
|
||||
log('info', 'Validating dependencies after adding new task...');
|
||||
validateAndFixDependencies(data, null);
|
||||
|
||||
// Write the updated tasks back to the file
|
||||
writeJSON(tasksPath, data);
|
||||
|
||||
// Only show success messages for text mode (CLI)
|
||||
if (outputFormat === 'text') {
|
||||
// Show success message
|
||||
const successBox = boxen(
|
||||
chalk.green(`Successfully added new task #${newTaskId}:\n`) +
|
||||
chalk.white.bold(newTask.title) +
|
||||
'\n\n' +
|
||||
chalk.white(newTask.description),
|
||||
{
|
||||
padding: 1,
|
||||
borderColor: 'green',
|
||||
borderStyle: 'round',
|
||||
margin: { top: 1 }
|
||||
}
|
||||
);
|
||||
console.log(successBox);
|
||||
|
||||
// Next steps suggestion
|
||||
console.log(
|
||||
boxen(
|
||||
chalk.white.bold('Next Steps:') +
|
||||
'\n\n' +
|
||||
`${chalk.cyan('1.')} Run ${chalk.yellow('task-master generate')} to update task files\n` +
|
||||
`${chalk.cyan('2.')} Run ${chalk.yellow('task-master expand --id=' + newTaskId)} to break it down into subtasks\n` +
|
||||
`${chalk.cyan('3.')} Run ${chalk.yellow('task-master list --with-subtasks')} to see all tasks`,
|
||||
{
|
||||
padding: 1,
|
||||
borderColor: 'cyan',
|
||||
borderStyle: 'round',
|
||||
margin: { top: 1 }
|
||||
}
|
||||
)
|
||||
);
|
||||
}
|
||||
|
||||
return newTaskId;
|
||||
} catch (error) {
|
||||
// Log the specific error during generation/processing
|
||||
log('error', 'Error generating or processing task:', error.message);
|
||||
// Re-throw the error to be caught by the outer catch block
|
||||
throw error;
|
||||
} finally {
|
||||
// **** THIS IS THE KEY CHANGE ****
|
||||
// Ensure the loading indicator is stopped if it was started
|
||||
if (loadingIndicator) {
|
||||
stopLoadingIndicator(loadingIndicator);
|
||||
// Optional: Clear the line in CLI mode for a cleaner output
|
||||
if (outputFormat === 'text' && process.stdout.isTTY) {
|
||||
try {
|
||||
// Use dynamic import for readline as it might not always be needed
|
||||
const readline = await import('readline');
|
||||
readline.clearLine(process.stdout, 0);
|
||||
readline.cursorTo(process.stdout, 0);
|
||||
} catch (readlineError) {
|
||||
log(
|
||||
'debug',
|
||||
'Could not clear readline for indicator cleanup:',
|
||||
readlineError.message
|
||||
);
|
||||
}
|
||||
|
||||
// Set the AI-generated task data
|
||||
taskData = aiGeneratedTaskData;
|
||||
} catch (error) {
|
||||
// Handle AI errors
|
||||
log('error', `Error generating task with AI: ${error.message}`);
|
||||
|
||||
// Stop any loading indicator
|
||||
if (outputFormat === 'text' && loadingIndicator) {
|
||||
stopLoadingIndicator(loadingIndicator);
|
||||
}
|
||||
loadingIndicator = null; // Reset indicator variable
|
||||
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
// Create the new task object
|
||||
const newTask = {
|
||||
id: newTaskId,
|
||||
title: taskData.title,
|
||||
description: taskData.description,
|
||||
details: taskData.details || '',
|
||||
testStrategy: taskData.testStrategy || '',
|
||||
status: 'pending',
|
||||
dependencies: dependencies,
|
||||
priority: priority
|
||||
};
|
||||
|
||||
// Add the task to the tasks array
|
||||
data.tasks.push(newTask);
|
||||
|
||||
// Write the updated tasks to the file
|
||||
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);
|
||||
}
|
||||
|
||||
// Show success message - only for text output (CLI)
|
||||
if (outputFormat === 'text') {
|
||||
const table = new Table({
|
||||
head: [
|
||||
chalk.cyan.bold('ID'),
|
||||
chalk.cyan.bold('Title'),
|
||||
chalk.cyan.bold('Description')
|
||||
],
|
||||
colWidths: [5, 30, 50]
|
||||
});
|
||||
|
||||
table.push([
|
||||
newTask.id,
|
||||
truncate(newTask.title, 27),
|
||||
truncate(newTask.description, 47)
|
||||
]);
|
||||
|
||||
console.log(chalk.green('✅ New task created successfully:'));
|
||||
console.log(table.toString());
|
||||
|
||||
// Show success message
|
||||
console.log(
|
||||
boxen(
|
||||
chalk.white.bold(`Task ${newTaskId} Created Successfully`) +
|
||||
'\n\n' +
|
||||
chalk.white(`Title: ${newTask.title}`) +
|
||||
'\n' +
|
||||
chalk.white(`Status: ${getStatusWithColor(newTask.status)}`) +
|
||||
'\n' +
|
||||
chalk.white(`Priority: ${chalk.keyword(getPriorityColor(newTask.priority))(newTask.priority)}`) +
|
||||
'\n' +
|
||||
(dependencies.length > 0
|
||||
? chalk.white(`Dependencies: ${dependencies.join(', ')}`) + '\n'
|
||||
: '') +
|
||||
'\n' +
|
||||
chalk.white.bold('Next Steps:') +
|
||||
'\n' +
|
||||
chalk.cyan(`1. Run ${chalk.yellow(`task-master show ${newTaskId}`)} to see complete task details`) +
|
||||
'\n' +
|
||||
chalk.cyan(`2. Run ${chalk.yellow(`task-master set-status --id=${newTaskId} --status=in-progress`)} to start working on it`) +
|
||||
'\n' +
|
||||
chalk.cyan(`3. Run ${chalk.yellow(`task-master expand --id=${newTaskId}`)} to break it down into subtasks`),
|
||||
{ padding: 1, borderColor: 'green', borderStyle: 'round' }
|
||||
)
|
||||
);
|
||||
}
|
||||
|
||||
// Return the new task ID
|
||||
return newTaskId;
|
||||
} catch (error) {
|
||||
// General error handling for the whole function
|
||||
// The finally block above already handled the indicator if it was started
|
||||
log('error', 'Error adding task:', error.message);
|
||||
throw error; // Throw error instead of exiting the process
|
||||
// Stop any loading indicator
|
||||
if (outputFormat === 'text' && loadingIndicator) {
|
||||
stopLoadingIndicator(loadingIndicator);
|
||||
}
|
||||
|
||||
log('error', `Error adding task: ${error.message}`);
|
||||
if (outputFormat === 'text') {
|
||||
console.error(chalk.red(`Error: ${error.message}`));
|
||||
}
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
Reference in New Issue
Block a user