refactor(config): Standardize env var access and config getters
This commit focuses on standardizing configuration and API key access patterns across key modules as part of subtask 61.34. Key changes include: - Refactored `ai-services.js` to remove global AI clients and use `resolveEnvVariable` for API key checks. Client instantiation now relies on `getAnthropicClient`/`getPerplexityClient` accepting a session object. - Refactored `task-manager.js` (`analyzeTaskComplexity` function) to use the unified `generateTextService` from `ai-services-unified.js`, removing direct AI client calls. - Replaced direct `process.env` access for model parameters and other configurations (`PERPLEXITY_MODEL`, `CONFIG.*`) in `task-manager.js` with calls to the appropriate getters from `config-manager.js` (e.g., `getResearchModelId(session)`, `getMainMaxTokens(session)`). - Ensured `utils.js` (`resolveEnvVariable`) correctly handles potentially undefined session objects. - Updated function signatures where necessary to propagate the `session` object for correct context-aware configuration/key retrieval. This moves towards the goal of using `ai-client-factory.js` and `ai-services-unified.js` as the standard pattern for AI interactions and centralizing configuration management through `config-manager.js`.
This commit is contained in:
Eyal Toledano
261
scripts/modules/task-manager/expand-task.js
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261
scripts/modules/task-manager/expand-task.js
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import fs from 'fs';
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import path from 'path';
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import { log, readJSON, writeJSON, isSilentMode } from '../utils.js';
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import { startLoadingIndicator, stopLoadingIndicator } from '../ui.js';
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import {
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generateSubtasksWithPerplexity,
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_handleAnthropicStream,
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getConfiguredAnthropicClient,
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parseSubtasksFromText
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} from '../ai-services.js';
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import { getDefaultSubtasks } from '../config-manager.js';
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import generateTaskFiles from './generate-task-files.js';
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/**
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* Expand a task into subtasks
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* @param {string} tasksPath - Path to the tasks.json file
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* @param {number} taskId - Task ID to expand
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* @param {number} numSubtasks - Number of subtasks to generate
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* @param {boolean} useResearch - Whether to use research with Perplexity
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* @param {string} additionalContext - Additional context
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* @param {Object} options - Options for expanding tasks
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* @param {function} options.reportProgress - Function to report progress
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* @param {Object} options.mcpLog - MCP logger object
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* @param {Object} options.session - Session object from MCP
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* @returns {Promise<Object>} Expanded task
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*/
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async function expandTask(
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tasksPath,
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taskId,
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numSubtasks,
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useResearch = false,
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additionalContext = '',
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{ reportProgress, mcpLog, session } = {}
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) {
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// Determine output format based on mcpLog presence (simplification)
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const outputFormat = mcpLog ? 'json' : 'text';
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// Create custom reporter that checks for MCP log and silent mode
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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 (!isSilentMode() && outputFormat === 'text') {
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// Only log to console if not in silent mode and outputFormat is 'text'
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log(level, message);
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}
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};
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// Keep the mcpLog check for specific MCP context logging
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if (mcpLog) {
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mcpLog.info(
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`expandTask - reportProgress available: ${!!reportProgress}, session available: ${!!session}`
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);
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}
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try {
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// Read the tasks.json file
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const data = readJSON(tasksPath);
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if (!data || !data.tasks) {
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throw new Error('Invalid or missing tasks.json');
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}
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// Find the task
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const task = data.tasks.find((t) => t.id === parseInt(taskId, 10));
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if (!task) {
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throw new Error(`Task with ID ${taskId} not found`);
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}
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report(`Expanding task ${taskId}: ${task.title}`);
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// If the task already has subtasks and force flag is not set, return the existing subtasks
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if (task.subtasks && task.subtasks.length > 0) {
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report(`Task ${taskId} already has ${task.subtasks.length} subtasks`);
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return task;
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}
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// Determine the number of subtasks to generate
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let subtaskCount = parseInt(numSubtasks, 10) || getDefaultSubtasks(); // Use getter
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// Check if we have a complexity analysis for this task
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let taskAnalysis = null;
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try {
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const reportPath = 'scripts/task-complexity-report.json';
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if (fs.existsSync(reportPath)) {
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const report = readJSON(reportPath);
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if (report && report.complexityAnalysis) {
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taskAnalysis = report.complexityAnalysis.find(
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(a) => a.taskId === task.id
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);
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}
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}
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} catch (error) {
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report(`Could not read complexity analysis: ${error.message}`, 'warn');
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}
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// Use recommended subtask count if available
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if (taskAnalysis) {
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report(
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`Found complexity analysis for task ${taskId}: Score ${taskAnalysis.complexityScore}/10`
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);
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// Use recommended number of subtasks if available
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if (
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taskAnalysis.recommendedSubtasks &&
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subtaskCount === getDefaultSubtasks() // Use getter
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) {
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subtaskCount = taskAnalysis.recommendedSubtasks;
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report(`Using recommended number of subtasks: ${subtaskCount}`);
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}
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// Use the expansion prompt from analysis as additional context
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if (taskAnalysis.expansionPrompt && !additionalContext) {
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additionalContext = taskAnalysis.expansionPrompt;
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report(`Using expansion prompt from complexity analysis`);
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}
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}
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// Generate subtasks with AI
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let generatedSubtasks = [];
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// Only create loading indicator if not in silent mode and no mcpLog (CLI mode)
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let loadingIndicator = null;
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if (!isSilentMode() && !mcpLog) {
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loadingIndicator = startLoadingIndicator(
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useResearch
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? 'Generating research-backed subtasks...'
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: 'Generating subtasks...'
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);
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}
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try {
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// Determine the next subtask ID
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const nextSubtaskId = 1;
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if (useResearch) {
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// Use Perplexity for research-backed subtasks
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if (!perplexity) {
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report(
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'Perplexity AI is not available. Falling back to Claude AI.',
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'warn'
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);
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useResearch = false;
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} else {
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report('Using Perplexity for research-backed subtasks');
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generatedSubtasks = await generateSubtasksWithPerplexity(
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task,
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subtaskCount,
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nextSubtaskId,
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additionalContext,
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{ reportProgress, mcpLog, silentMode: isSilentMode(), session }
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);
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}
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}
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if (!useResearch) {
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report('Using regular Claude for generating subtasks');
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// Use our getConfiguredAnthropicClient function instead of getAnthropicClient
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const client = getConfiguredAnthropicClient(session);
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// Build the system prompt
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const systemPrompt = `You are an AI assistant helping with task breakdown for software development.
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You need to break down a high-level task into ${subtaskCount} specific subtasks that can be implemented one by one.
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Subtasks should:
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1. Be specific and actionable implementation steps
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2. Follow a logical sequence
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3. Each handle a distinct part of the parent task
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4. Include clear guidance on implementation approach
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5. Have appropriate dependency chains between subtasks
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6. Collectively cover all aspects of the parent task
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For each subtask, provide:
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- A clear, specific title
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- Detailed implementation steps
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- Dependencies on previous subtasks
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- Testing approach
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Each subtask should be implementable in a focused coding session.`;
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const contextPrompt = additionalContext
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? `\n\nAdditional context to consider: ${additionalContext}`
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: '';
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const userPrompt = `Please break down this task into ${subtaskCount} specific, actionable subtasks:
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Task ID: ${task.id}
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Title: ${task.title}
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Description: ${task.description}
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Current details: ${task.details || 'None provided'}
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${contextPrompt}
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Return exactly ${subtaskCount} subtasks with the following JSON structure:
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[
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{
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"id": ${nextSubtaskId},
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"title": "First subtask title",
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"description": "Detailed description",
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"dependencies": [],
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"details": "Implementation details"
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},
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...more subtasks...
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]
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Note on dependencies: Subtasks can depend on other subtasks with lower IDs. Use an empty array if there are no dependencies.`;
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// Prepare API parameters
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const apiParams = {
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model: session?.env?.ANTHROPIC_MODEL || CONFIG.model,
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max_tokens: session?.env?.MAX_TOKENS || CONFIG.maxTokens,
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temperature: session?.env?.TEMPERATURE || CONFIG.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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const responseText = await _handleAnthropicStream(
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client,
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apiParams,
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{ reportProgress, mcpLog, silentMode: isSilentMode() }, // Pass isSilentMode() directly
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!isSilentMode() // Only use CLI mode if not in silent mode
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);
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// Parse the subtasks from the response
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generatedSubtasks = parseSubtasksFromText(
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responseText,
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nextSubtaskId,
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subtaskCount,
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task.id
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);
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}
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// Add the generated subtasks to the task
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task.subtasks = generatedSubtasks;
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// Write the updated tasks back to the file
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writeJSON(tasksPath, data);
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// Generate the individual task files
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await generateTaskFiles(tasksPath, path.dirname(tasksPath));
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return task;
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} catch (error) {
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report(`Error expanding task: ${error.message}`, 'error');
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throw error;
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} finally {
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// Always stop the loading indicator if we created one
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if (loadingIndicator) {
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stopLoadingIndicator(loadingIndicator);
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}
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}
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} catch (error) {
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report(`Error expanding task: ${error.message}`, 'error');
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throw error;
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}
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}
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export default expandTask;
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