feat(refactor): Finalize AI service migration and cleanup obsolete files
This commit completes the major refactoring initiative (Task 61) to migrate all AI-interacting task management functions to the unified service layer (`ai-services-unified.js`) and standardized configuration (`config-manager.js`).
Key Changes:
1. **Refactor `update-task-by-id` & `update-subtask-by-id`:**
* Replaced direct AI client logic and config fetching with calls to `generateTextService`.
* Preserved original prompt logic while ensuring JSON output format is requested.
* Implemented robust manual JSON parsing and Zod validation for text-based AI responses.
* Corrected logger implementation (`logFn`/`isMCP`/`report` pattern) for both CLI and MCP contexts.
* Ensured correct passing of `session` context to the unified service.
* Refactored associated direct function wrappers (`updateTaskByIdDirect`, `updateSubtaskByIdDirect`) to remove AI client initialization and call core logic appropriately.
2. **CLI Environment Loading:**
* Added `dotenv.config()` to `scripts/dev.js` to ensure consistent loading of the `.env` file for CLI operations.
3. **Obsolete Code Removal:**
* Deleted unused helper files:
* `scripts/modules/task-manager/get-subtasks-from-ai.js`
* `scripts/modules/task-manager/generate-subtask-prompt.js`
* `scripts/modules/ai-services.js`
* `scripts/modules/ai-client-factory.js`
* `mcp-server/src/core/utils/ai-client-utils.js`
* Removed corresponding imports/exports from `scripts/modules/task-manager.js` and `mcp-server/src/core/task-master-core.js`.
4. **Verification:**
* Successfully tested `update-task` and `update-subtask` via both CLI and MCP after refactoring.
5. **Task Management:**
* Marked subtasks 61.38, 61.39, 61.40, 61.41, and 61.33 as 'done'.
* Includes other task content/status updates as reflected in the diff.
This completes the migration of core AI features to the new architecture, enhancing maintainability and flexibility.
This commit is contained in:
Eyal Toledano
@@ -11,8 +11,6 @@ import {
|
||||
disableSilentMode,
|
||||
isSilentMode
|
||||
} from '../../../../scripts/modules/utils.js';
|
||||
// Removed AI client imports:
|
||||
// import { getAnthropicClientForMCP, getModelConfig } from '../utils/ai-client-utils.js';
|
||||
import path from 'path';
|
||||
import fs from 'fs';
|
||||
|
||||
|
||||
@@ -8,10 +8,6 @@ import {
|
||||
enableSilentMode,
|
||||
disableSilentMode
|
||||
} from '../../../../scripts/modules/utils.js';
|
||||
import {
|
||||
getAnthropicClientForMCP,
|
||||
getPerplexityClientForMCP
|
||||
} from '../utils/ai-client-utils.js';
|
||||
|
||||
/**
|
||||
* Direct function wrapper for updateSubtaskById with error handling.
|
||||
@@ -95,27 +91,6 @@ export async function updateSubtaskByIdDirect(args, log, context = {}) {
|
||||
`Updating subtask with ID ${subtaskIdStr} with prompt "${prompt}" and research: ${useResearch}`
|
||||
);
|
||||
|
||||
// Initialize the appropriate AI client based on research flag
|
||||
try {
|
||||
if (useResearch) {
|
||||
// Initialize Perplexity client
|
||||
await getPerplexityClientForMCP(session);
|
||||
} else {
|
||||
// Initialize Anthropic client
|
||||
await getAnthropicClientForMCP(session);
|
||||
}
|
||||
} catch (error) {
|
||||
log.error(`AI client initialization error: ${error.message}`);
|
||||
return {
|
||||
success: false,
|
||||
error: {
|
||||
code: 'AI_CLIENT_ERROR',
|
||||
message: error.message || 'Failed to initialize AI client'
|
||||
},
|
||||
fromCache: false
|
||||
};
|
||||
}
|
||||
|
||||
try {
|
||||
// Enable silent mode to prevent console logs from interfering with JSON response
|
||||
enableSilentMode();
|
||||
|
||||
@@ -8,10 +8,6 @@ import {
|
||||
enableSilentMode,
|
||||
disableSilentMode
|
||||
} from '../../../../scripts/modules/utils.js';
|
||||
import {
|
||||
getAnthropicClientForMCP,
|
||||
getPerplexityClientForMCP
|
||||
} from '../utils/ai-client-utils.js';
|
||||
|
||||
/**
|
||||
* Direct function wrapper for updateTaskById with error handling.
|
||||
@@ -92,28 +88,6 @@ export async function updateTaskByIdDirect(args, log, context = {}) {
|
||||
// Get research flag
|
||||
const useResearch = research === true;
|
||||
|
||||
// Initialize appropriate AI client based on research flag
|
||||
let aiClient;
|
||||
try {
|
||||
if (useResearch) {
|
||||
log.info('Using Perplexity AI for research-backed task update');
|
||||
aiClient = await getPerplexityClientForMCP(session, log);
|
||||
} else {
|
||||
log.info('Using Claude AI for task update');
|
||||
aiClient = getAnthropicClientForMCP(session, log);
|
||||
}
|
||||
} catch (error) {
|
||||
log.error(`Failed to initialize AI client: ${error.message}`);
|
||||
return {
|
||||
success: false,
|
||||
error: {
|
||||
code: 'AI_CLIENT_ERROR',
|
||||
message: `Cannot initialize AI client: ${error.message}`
|
||||
},
|
||||
fromCache: false
|
||||
};
|
||||
}
|
||||
|
||||
log.info(
|
||||
`Updating task with ID ${taskId} with prompt "${prompt}" and research: ${useResearch}`
|
||||
);
|
||||
|
||||
@@ -34,15 +34,6 @@ import { modelsDirect } from './direct-functions/models.js';
|
||||
// Re-export utility functions
|
||||
export { findTasksJsonPath } from './utils/path-utils.js';
|
||||
|
||||
// Re-export AI client utilities
|
||||
export {
|
||||
getAnthropicClientForMCP,
|
||||
getPerplexityClientForMCP,
|
||||
getModelConfig,
|
||||
getBestAvailableAIModel,
|
||||
handleClaudeError
|
||||
} from './utils/ai-client-utils.js';
|
||||
|
||||
// Use Map for potential future enhancements like introspection or dynamic dispatch
|
||||
export const directFunctions = new Map([
|
||||
['listTasksDirect', listTasksDirect],
|
||||
|
||||
@@ -1,213 +0,0 @@
|
||||
/**
|
||||
* ai-client-utils.js
|
||||
* Utility functions for initializing AI clients in MCP context
|
||||
*/
|
||||
|
||||
import { Anthropic } from '@anthropic-ai/sdk';
|
||||
import dotenv from 'dotenv';
|
||||
|
||||
// Load environment variables for CLI mode
|
||||
dotenv.config();
|
||||
|
||||
// Default model configuration from CLI environment
|
||||
const DEFAULT_MODEL_CONFIG = {
|
||||
model: 'claude-3-7-sonnet-20250219',
|
||||
maxTokens: 64000,
|
||||
temperature: 0.2
|
||||
};
|
||||
|
||||
/**
|
||||
* Get an Anthropic client instance initialized with MCP session environment variables
|
||||
* @param {Object} [session] - Session object from MCP containing environment variables
|
||||
* @param {Object} [log] - Logger object to use (defaults to console)
|
||||
* @returns {Anthropic} Anthropic client instance
|
||||
* @throws {Error} If API key is missing
|
||||
*/
|
||||
export function getAnthropicClientForMCP(session, log = console) {
|
||||
try {
|
||||
// Extract API key from session.env or fall back to environment variables
|
||||
const apiKey =
|
||||
session?.env?.ANTHROPIC_API_KEY || process.env.ANTHROPIC_API_KEY;
|
||||
|
||||
if (!apiKey) {
|
||||
throw new Error(
|
||||
'ANTHROPIC_API_KEY not found in session environment or process.env'
|
||||
);
|
||||
}
|
||||
|
||||
// Initialize and return a new Anthropic client
|
||||
return new Anthropic({
|
||||
apiKey,
|
||||
defaultHeaders: {
|
||||
'anthropic-beta': 'output-128k-2025-02-19' // Include header for increased token limit
|
||||
}
|
||||
});
|
||||
} catch (error) {
|
||||
log.error(`Failed to initialize Anthropic client: ${error.message}`);
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Get a Perplexity client instance initialized with MCP session environment variables
|
||||
* @param {Object} [session] - Session object from MCP containing environment variables
|
||||
* @param {Object} [log] - Logger object to use (defaults to console)
|
||||
* @returns {OpenAI} OpenAI client configured for Perplexity API
|
||||
* @throws {Error} If API key is missing or OpenAI package can't be imported
|
||||
*/
|
||||
export async function getPerplexityClientForMCP(session, log = console) {
|
||||
try {
|
||||
// Extract API key from session.env or fall back to environment variables
|
||||
const apiKey =
|
||||
session?.env?.PERPLEXITY_API_KEY || process.env.PERPLEXITY_API_KEY;
|
||||
|
||||
if (!apiKey) {
|
||||
throw new Error(
|
||||
'PERPLEXITY_API_KEY not found in session environment or process.env'
|
||||
);
|
||||
}
|
||||
|
||||
// Dynamically import OpenAI (it may not be used in all contexts)
|
||||
const { default: OpenAI } = await import('openai');
|
||||
|
||||
// Initialize and return a new OpenAI client configured for Perplexity
|
||||
return new OpenAI({
|
||||
apiKey,
|
||||
baseURL: 'https://api.perplexity.ai'
|
||||
});
|
||||
} catch (error) {
|
||||
log.error(`Failed to initialize Perplexity client: ${error.message}`);
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Get model configuration from session environment or fall back to defaults
|
||||
* @param {Object} [session] - Session object from MCP containing environment variables
|
||||
* @param {Object} [defaults] - Default model configuration to use if not in session
|
||||
* @returns {Object} Model configuration with model, maxTokens, and temperature
|
||||
*/
|
||||
export function getModelConfig(session, defaults = DEFAULT_MODEL_CONFIG) {
|
||||
// Get values from session or fall back to defaults
|
||||
return {
|
||||
model: session?.env?.MODEL || defaults.model,
|
||||
maxTokens: parseInt(session?.env?.MAX_TOKENS || defaults.maxTokens),
|
||||
temperature: parseFloat(session?.env?.TEMPERATURE || defaults.temperature)
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Returns the best available AI model based on specified options
|
||||
* @param {Object} session - Session object from MCP containing environment variables
|
||||
* @param {Object} options - Options for model selection
|
||||
* @param {boolean} [options.requiresResearch=false] - Whether the operation requires research capabilities
|
||||
* @param {boolean} [options.claudeOverloaded=false] - Whether Claude is currently overloaded
|
||||
* @param {Object} [log] - Logger object to use (defaults to console)
|
||||
* @returns {Promise<Object>} Selected model info with type and client
|
||||
* @throws {Error} If no AI models are available
|
||||
*/
|
||||
export async function getBestAvailableAIModel(
|
||||
session,
|
||||
options = {},
|
||||
log = console
|
||||
) {
|
||||
const { requiresResearch = false, claudeOverloaded = false } = options;
|
||||
|
||||
// Test case: When research is needed but no Perplexity, use Claude
|
||||
if (
|
||||
requiresResearch &&
|
||||
!(session?.env?.PERPLEXITY_API_KEY || process.env.PERPLEXITY_API_KEY) &&
|
||||
(session?.env?.ANTHROPIC_API_KEY || process.env.ANTHROPIC_API_KEY)
|
||||
) {
|
||||
try {
|
||||
log.warn('Perplexity not available for research, using Claude');
|
||||
const client = getAnthropicClientForMCP(session, log);
|
||||
return { type: 'claude', client };
|
||||
} catch (error) {
|
||||
log.error(`Claude not available: ${error.message}`);
|
||||
throw new Error('No AI models available for research');
|
||||
}
|
||||
}
|
||||
|
||||
// Regular path: Perplexity for research when available
|
||||
if (
|
||||
requiresResearch &&
|
||||
(session?.env?.PERPLEXITY_API_KEY || process.env.PERPLEXITY_API_KEY)
|
||||
) {
|
||||
try {
|
||||
const client = await getPerplexityClientForMCP(session, log);
|
||||
return { type: 'perplexity', client };
|
||||
} catch (error) {
|
||||
log.warn(`Perplexity not available: ${error.message}`);
|
||||
// Fall through to Claude as backup
|
||||
}
|
||||
}
|
||||
|
||||
// Test case: Claude for overloaded scenario
|
||||
if (
|
||||
claudeOverloaded &&
|
||||
(session?.env?.ANTHROPIC_API_KEY || process.env.ANTHROPIC_API_KEY)
|
||||
) {
|
||||
try {
|
||||
log.warn(
|
||||
'Claude is overloaded but no alternatives are available. Proceeding with Claude anyway.'
|
||||
);
|
||||
const client = getAnthropicClientForMCP(session, log);
|
||||
return { type: 'claude', client };
|
||||
} catch (error) {
|
||||
log.error(
|
||||
`Claude not available despite being overloaded: ${error.message}`
|
||||
);
|
||||
throw new Error('No AI models available');
|
||||
}
|
||||
}
|
||||
|
||||
// Default case: Use Claude when available and not overloaded
|
||||
if (
|
||||
!claudeOverloaded &&
|
||||
(session?.env?.ANTHROPIC_API_KEY || process.env.ANTHROPIC_API_KEY)
|
||||
) {
|
||||
try {
|
||||
const client = getAnthropicClientForMCP(session, log);
|
||||
return { type: 'claude', client };
|
||||
} catch (error) {
|
||||
log.warn(`Claude not available: ${error.message}`);
|
||||
// Fall through to error if no other options
|
||||
}
|
||||
}
|
||||
|
||||
// If we got here, no models were successfully initialized
|
||||
throw new Error('No AI models available. Please check your API keys.');
|
||||
}
|
||||
|
||||
/**
|
||||
* Handle Claude API errors with user-friendly messages
|
||||
* @param {Error} error - The error from Claude API
|
||||
* @returns {string} User-friendly error message
|
||||
*/
|
||||
export function handleClaudeError(error) {
|
||||
// Check if it's a structured error response
|
||||
if (error.type === 'error' && error.error) {
|
||||
switch (error.error.type) {
|
||||
case 'overloaded_error':
|
||||
return 'Claude is currently experiencing high demand and is overloaded. Please wait a few minutes and try again.';
|
||||
case 'rate_limit_error':
|
||||
return 'You have exceeded the rate limit. Please wait a few minutes before making more requests.';
|
||||
case 'invalid_request_error':
|
||||
return 'There was an issue with the request format. If this persists, please report it as a bug.';
|
||||
default:
|
||||
return `Claude API error: ${error.error.message}`;
|
||||
}
|
||||
}
|
||||
|
||||
// Check for network/timeout errors
|
||||
if (error.message?.toLowerCase().includes('timeout')) {
|
||||
return 'The request to Claude timed out. Please try again.';
|
||||
}
|
||||
if (error.message?.toLowerCase().includes('network')) {
|
||||
return 'There was a network error connecting to Claude. Please check your internet connection and try again.';
|
||||
}
|
||||
|
||||
// Default error message
|
||||
return `Error communicating with Claude: ${error.message}`;
|
||||
}
|
||||
@@ -8,6 +8,9 @@
|
||||
* It imports functionality from the modules directory and provides a CLI.
|
||||
*/
|
||||
|
||||
import dotenv from 'dotenv'; // <-- ADD
|
||||
dotenv.config(); // <-- ADD
|
||||
|
||||
// Add at the very beginning of the file
|
||||
if (process.env.DEBUG === '1') {
|
||||
console.error('DEBUG - dev.js received args:', process.argv.slice(2));
|
||||
|
||||
@@ -1,348 +0,0 @@
|
||||
import fs from 'fs';
|
||||
import path from 'path';
|
||||
import { createOpenAI } from '@ai-sdk/openai';
|
||||
import { createAnthropic } from '@ai-sdk/anthropic';
|
||||
import { createGoogle } from '@ai-sdk/google';
|
||||
import { createPerplexity } from '@ai-sdk/perplexity';
|
||||
import { createOllama } from 'ollama-ai-provider';
|
||||
import { createMistral } from '@ai-sdk/mistral';
|
||||
import { createAzure } from '@ai-sdk/azure';
|
||||
import { createXai } from '@ai-sdk/xai';
|
||||
import { createOpenRouter } from '@openrouter/ai-sdk-provider';
|
||||
// TODO: Add imports for other supported providers like OpenRouter, Grok
|
||||
|
||||
import {
|
||||
getProviderAndModelForRole,
|
||||
findProjectRoot // Assuming config-manager exports this
|
||||
} from './config-manager.js';
|
||||
|
||||
const clientCache = new Map();
|
||||
|
||||
// Using a Symbol for a unique, unmistakable value
|
||||
const VALIDATION_SKIPPED = Symbol('validation_skipped');
|
||||
|
||||
// --- Load Supported Models Data (Lazily) ---
|
||||
let supportedModelsData = null;
|
||||
let modelsDataLoaded = false;
|
||||
|
||||
function loadSupportedModelsData() {
|
||||
console.log(
|
||||
`DEBUG: loadSupportedModelsData called. modelsDataLoaded=${modelsDataLoaded}`
|
||||
);
|
||||
if (modelsDataLoaded) {
|
||||
console.log('DEBUG: Returning cached supported models data.');
|
||||
return supportedModelsData;
|
||||
}
|
||||
try {
|
||||
const projectRoot = findProjectRoot(process.cwd());
|
||||
const supportedModelsPath = path.join(
|
||||
projectRoot,
|
||||
'data',
|
||||
'supported-models.json'
|
||||
);
|
||||
console.log(
|
||||
`DEBUG: Checking for supported models at: ${supportedModelsPath}`
|
||||
);
|
||||
const exists = fs.existsSync(supportedModelsPath);
|
||||
console.log(`DEBUG: fs.existsSync result: ${exists}`);
|
||||
|
||||
if (exists) {
|
||||
const fileContent = fs.readFileSync(supportedModelsPath, 'utf-8');
|
||||
supportedModelsData = JSON.parse(fileContent);
|
||||
console.log(
|
||||
'DEBUG: Successfully loaded and parsed supported-models.json'
|
||||
);
|
||||
} else {
|
||||
console.warn(
|
||||
`Warning: Could not find supported models file at ${supportedModelsPath}. Skipping model validation.`
|
||||
);
|
||||
supportedModelsData = {}; // Treat as empty if not found, allowing skip
|
||||
}
|
||||
} catch (error) {
|
||||
console.error(
|
||||
`Error loading or parsing supported models file: ${error.message}`
|
||||
);
|
||||
console.error('Stack Trace:', error.stack);
|
||||
supportedModelsData = {}; // Treat as empty on error, allowing skip
|
||||
}
|
||||
modelsDataLoaded = true;
|
||||
console.log(
|
||||
`DEBUG: Setting modelsDataLoaded=true, returning: ${JSON.stringify(supportedModelsData)}`
|
||||
);
|
||||
return supportedModelsData;
|
||||
}
|
||||
|
||||
/**
|
||||
* Validates if a model is supported for a given provider and role.
|
||||
* @param {string} providerName - The name of the provider.
|
||||
* @param {string} modelId - The ID of the model.
|
||||
* @param {string} role - The role ('main', 'research', 'fallback').
|
||||
* @returns {boolean|Symbol} True if valid, false if invalid, VALIDATION_SKIPPED if data was missing.
|
||||
*/
|
||||
function isModelSupportedAndAllowed(providerName, modelId, role) {
|
||||
const modelsData = loadSupportedModelsData();
|
||||
|
||||
if (
|
||||
!modelsData ||
|
||||
typeof modelsData !== 'object' ||
|
||||
Object.keys(modelsData).length === 0
|
||||
) {
|
||||
console.warn(
|
||||
'Skipping model validation as supported models data is unavailable or invalid.'
|
||||
);
|
||||
// Return the specific symbol instead of true
|
||||
return VALIDATION_SKIPPED;
|
||||
}
|
||||
|
||||
// Ensure consistent casing for provider lookup
|
||||
const providerKey = providerName?.toLowerCase();
|
||||
if (!providerKey || !modelsData.hasOwnProperty(providerKey)) {
|
||||
console.warn(
|
||||
`Provider '${providerName}' not found in supported-models.json.`
|
||||
);
|
||||
return false;
|
||||
}
|
||||
|
||||
const providerModels = modelsData[providerKey];
|
||||
if (!Array.isArray(providerModels)) {
|
||||
console.warn(
|
||||
`Invalid format for provider '${providerName}' models in supported-models.json. Expected an array.`
|
||||
);
|
||||
return false;
|
||||
}
|
||||
|
||||
const modelInfo = providerModels.find((m) => m && m.id === modelId);
|
||||
if (!modelInfo) {
|
||||
console.warn(
|
||||
`Model '${modelId}' not found for provider '${providerName}' in supported-models.json.`
|
||||
);
|
||||
return false;
|
||||
}
|
||||
|
||||
// Check if the role is allowed for this model
|
||||
if (!Array.isArray(modelInfo.allowed_roles)) {
|
||||
console.warn(
|
||||
`Model '${modelId}' (Provider: '${providerName}') has invalid or missing 'allowed_roles' array in supported-models.json.`
|
||||
);
|
||||
return false;
|
||||
}
|
||||
|
||||
const isAllowed = modelInfo.allowed_roles.includes(role);
|
||||
if (!isAllowed) {
|
||||
console.warn(
|
||||
`Role '${role}' is not allowed for model '${modelId}' (Provider: '${providerName}'). Allowed roles: ${modelInfo.allowed_roles.join(', ')}`
|
||||
);
|
||||
}
|
||||
return isAllowed;
|
||||
}
|
||||
|
||||
/**
|
||||
* Resolves an environment variable by checking process.env first, then session.env.
|
||||
* @param {string} varName - The name of the environment variable.
|
||||
* @param {object|null} session - The MCP session object (optional).
|
||||
* @returns {string|undefined} The value of the environment variable or undefined if not found.
|
||||
*/
|
||||
function resolveEnvVariable(varName, session) {
|
||||
return process.env[varName] ?? session?.env?.[varName];
|
||||
}
|
||||
|
||||
/**
|
||||
* Validates if the required environment variables are set for a given provider,
|
||||
* checking process.env and falling back to session.env.
|
||||
* Throws an error if any required variable is missing.
|
||||
* @param {string} providerName - The name of the provider (e.g., 'openai', 'anthropic').
|
||||
* @param {object|null} session - The MCP session object (optional).
|
||||
*/
|
||||
function validateEnvironment(providerName, session) {
|
||||
// Define requirements based on the provider
|
||||
const requirements = {
|
||||
openai: ['OPENAI_API_KEY'],
|
||||
anthropic: ['ANTHROPIC_API_KEY'],
|
||||
google: ['GOOGLE_API_KEY'],
|
||||
perplexity: ['PERPLEXITY_API_KEY'],
|
||||
ollama: ['OLLAMA_BASE_URL'], // Ollama only needs Base URL typically
|
||||
mistral: ['MISTRAL_API_KEY'],
|
||||
azure: ['AZURE_OPENAI_API_KEY', 'AZURE_OPENAI_ENDPOINT'],
|
||||
openrouter: ['OPENROUTER_API_KEY'],
|
||||
xai: ['XAI_API_KEY']
|
||||
// Add requirements for other providers
|
||||
};
|
||||
|
||||
const providerKey = providerName?.toLowerCase();
|
||||
if (!providerKey || !requirements[providerKey]) {
|
||||
// If the provider itself isn't in our requirements list, we can't validate.
|
||||
// This might happen if config has an unsupported provider. Validation should happen earlier.
|
||||
// Or, we could throw an error here if the provider is unknown.
|
||||
console.warn(
|
||||
`Cannot validate environment for unknown or unsupported provider: ${providerName}`
|
||||
);
|
||||
return; // Proceed without validation for unknown providers
|
||||
}
|
||||
|
||||
const missing =
|
||||
requirements[providerKey]?.filter(
|
||||
(envVar) => !resolveEnvVariable(envVar, session)
|
||||
) || [];
|
||||
|
||||
if (missing.length > 0) {
|
||||
throw new Error(
|
||||
`Missing environment variables for provider '${providerName}': ${missing.join(', ')}. Please check your .env file or session configuration.`
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Creates an AI client instance for the specified provider.
|
||||
* Assumes environment validation has already passed.
|
||||
* @param {string} providerName - The name of the provider.
|
||||
* @param {object|null} session - The MCP session object (optional).
|
||||
* @param {object} [options={}] - Additional options for the client creation (e.g., model).
|
||||
* @returns {object} The created AI client instance.
|
||||
* @throws {Error} If the provider is unsupported.
|
||||
*/
|
||||
function createClientInstance(providerName, session, options = {}) {
|
||||
// Validation is now done before calling this function
|
||||
const getEnv = (varName) => resolveEnvVariable(varName, session);
|
||||
|
||||
switch (providerName?.toLowerCase()) {
|
||||
case 'openai':
|
||||
return createOpenAI({ apiKey: getEnv('OPENAI_API_KEY'), ...options });
|
||||
case 'anthropic':
|
||||
return createAnthropic({
|
||||
apiKey: getEnv('ANTHROPIC_API_KEY'),
|
||||
...options
|
||||
});
|
||||
case 'google':
|
||||
return createGoogle({ apiKey: getEnv('GOOGLE_API_KEY'), ...options });
|
||||
case 'perplexity':
|
||||
return createPerplexity({
|
||||
apiKey: getEnv('PERPLEXITY_API_KEY'),
|
||||
...options
|
||||
});
|
||||
case 'ollama':
|
||||
const ollamaBaseUrl =
|
||||
getEnv('OLLAMA_BASE_URL') || 'http://localhost:11434/api'; // Default from ollama-ai-provider docs
|
||||
// ollama-ai-provider uses baseURL directly
|
||||
return createOllama({ baseURL: ollamaBaseUrl, ...options });
|
||||
case 'mistral':
|
||||
return createMistral({ apiKey: getEnv('MISTRAL_API_KEY'), ...options });
|
||||
case 'azure':
|
||||
return createAzure({
|
||||
apiKey: getEnv('AZURE_OPENAI_API_KEY'),
|
||||
endpoint: getEnv('AZURE_OPENAI_ENDPOINT'),
|
||||
...(options.model && { deploymentName: options.model }), // Azure often uses deployment name
|
||||
...options
|
||||
});
|
||||
case 'openrouter':
|
||||
return createOpenRouter({
|
||||
apiKey: getEnv('OPENROUTER_API_KEY'),
|
||||
...options
|
||||
});
|
||||
case 'xai':
|
||||
return createXai({ apiKey: getEnv('XAI_API_KEY'), ...options });
|
||||
// TODO: Add cases for OpenRouter, Grok
|
||||
default:
|
||||
throw new Error(`Unsupported AI provider specified: ${providerName}`);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Gets or creates an AI client instance based on the configured model for a specific role.
|
||||
* Validates the configured model against supported models and role allowances.
|
||||
* @param {string} role - The role ('main', 'research', or 'fallback').
|
||||
* @param {object|null} [session=null] - The MCP session object (optional).
|
||||
* @param {object} [overrideOptions={}] - Optional overrides for { provider, modelId }.
|
||||
* @returns {object} The cached or newly created AI client instance.
|
||||
* @throws {Error} If configuration is missing, invalid, or environment validation fails.
|
||||
*/
|
||||
export function getClient(role, session = null, overrideOptions = {}) {
|
||||
if (!role) {
|
||||
throw new Error(
|
||||
`Client role ('main', 'research', 'fallback') must be specified.`
|
||||
);
|
||||
}
|
||||
|
||||
// 1. Determine Provider and Model ID
|
||||
let providerName = overrideOptions.provider;
|
||||
let modelId = overrideOptions.modelId;
|
||||
|
||||
if (!providerName || !modelId) {
|
||||
// If not fully overridden, get from config
|
||||
try {
|
||||
const config = getProviderAndModelForRole(role); // Fetch from config manager
|
||||
providerName = providerName || config.provider;
|
||||
modelId = modelId || config.modelId;
|
||||
} catch (configError) {
|
||||
throw new Error(
|
||||
`Failed to get configuration for role '${role}': ${configError.message}`
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
if (!providerName || !modelId) {
|
||||
throw new Error(
|
||||
`Could not determine provider or modelId for role '${role}' from configuration or overrides.`
|
||||
);
|
||||
}
|
||||
|
||||
// 2. Validate Provider/Model Combination and Role Allowance
|
||||
const validationResult = isModelSupportedAndAllowed(
|
||||
providerName,
|
||||
modelId,
|
||||
role
|
||||
);
|
||||
|
||||
// Only throw if validation explicitly returned false (meaning invalid/disallowed)
|
||||
// If it returned VALIDATION_SKIPPED, we proceed but skip strict validation.
|
||||
if (validationResult === false) {
|
||||
throw new Error(
|
||||
`Model '${modelId}' from provider '${providerName}' is either not supported or not allowed for the '${role}' role. Check supported-models.json and your .taskmasterconfig.`
|
||||
);
|
||||
}
|
||||
// Note: If validationResult === VALIDATION_SKIPPED, we continue to env validation
|
||||
|
||||
// 3. Validate Environment Variables for the chosen provider
|
||||
try {
|
||||
validateEnvironment(providerName, session);
|
||||
} catch (envError) {
|
||||
// Re-throw the original environment error for clearer test messages
|
||||
throw envError;
|
||||
}
|
||||
|
||||
// 4. Check Cache
|
||||
const cacheKey = `${providerName.toLowerCase()}:${modelId}`;
|
||||
if (clientCache.has(cacheKey)) {
|
||||
return clientCache.get(cacheKey);
|
||||
}
|
||||
|
||||
// 5. Create New Client Instance
|
||||
console.log(
|
||||
`Creating new client for role '${role}': Provider=${providerName}, Model=${modelId}`
|
||||
);
|
||||
try {
|
||||
const clientInstance = createClientInstance(providerName, session, {
|
||||
model: modelId
|
||||
});
|
||||
|
||||
clientCache.set(cacheKey, clientInstance);
|
||||
return clientInstance;
|
||||
} catch (creationError) {
|
||||
throw new Error(
|
||||
`Failed to create client instance for provider '${providerName}' (role: '${role}'): ${creationError.message}`
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
// Optional: Function to clear the cache if needed
|
||||
export function clearClientCache() {
|
||||
clientCache.clear();
|
||||
console.log('AI client cache cleared.');
|
||||
}
|
||||
|
||||
// Exported for testing purposes only
|
||||
export function _resetSupportedModelsCache() {
|
||||
console.log('DEBUG: Resetting supported models cache...');
|
||||
supportedModelsData = null;
|
||||
modelsDataLoaded = false;
|
||||
console.log('DEBUG: Supported models cache reset.');
|
||||
}
|
||||
File diff suppressed because it is too large
Load Diff
@@ -6,6 +6,5 @@
|
||||
// Export all modules
|
||||
export * from './utils.js';
|
||||
export * from './ui.js';
|
||||
export * from './ai-services.js';
|
||||
export * from './task-manager.js';
|
||||
export * from './commands.js';
|
||||
|
||||
@@ -9,54 +9,55 @@ import {
|
||||
startLoadingIndicator,
|
||||
stopLoadingIndicator
|
||||
} from '../ui.js';
|
||||
import { log, readJSON, writeJSON, truncate, isSilentMode } from '../utils.js';
|
||||
import { generateTextService } from '../ai-services-unified.js';
|
||||
import {
|
||||
getDebugFlag,
|
||||
getMainModelId,
|
||||
getMainMaxTokens,
|
||||
getMainTemperature,
|
||||
getResearchModelId,
|
||||
getResearchMaxTokens,
|
||||
getResearchTemperature
|
||||
} from '../config-manager.js';
|
||||
log as consoleLog,
|
||||
readJSON,
|
||||
writeJSON,
|
||||
truncate,
|
||||
isSilentMode
|
||||
} from '../utils.js';
|
||||
import { generateTextService } from '../ai-services-unified.js';
|
||||
import { getDebugFlag, isApiKeySet } from '../config-manager.js';
|
||||
import generateTaskFiles from './generate-task-files.js';
|
||||
|
||||
/**
|
||||
* Update a subtask by appending additional information to its description and details
|
||||
* Update a subtask by appending additional timestamped information using the unified AI service.
|
||||
* @param {string} tasksPath - Path to the tasks.json file
|
||||
* @param {string} subtaskId - ID of the subtask to update in format "parentId.subtaskId"
|
||||
* @param {string} prompt - Prompt for generating additional information
|
||||
* @param {boolean} useResearch - Whether to use Perplexity AI for research-backed updates
|
||||
* @param {function} reportProgress - Function to report progress to MCP server (optional)
|
||||
* @param {Object} mcpLog - MCP logger object (optional)
|
||||
* @param {Object} session - Session object from MCP server (optional)
|
||||
* @returns {Object|null} - The updated subtask or null if update failed
|
||||
* @param {boolean} [useResearch=false] - Whether to use the research AI role.
|
||||
* @param {Object} context - Context object containing session and mcpLog.
|
||||
* @param {Object} [context.session] - Session object from MCP server.
|
||||
* @param {Object} [context.mcpLog] - MCP logger object.
|
||||
* @param {string} [outputFormat='text'] - Output format ('text' or 'json'). Automatically 'json' if mcpLog is present.
|
||||
* @returns {Promise<Object|null>} - The updated subtask or null if update failed.
|
||||
*/
|
||||
async function updateSubtaskById(
|
||||
tasksPath,
|
||||
subtaskId,
|
||||
prompt,
|
||||
useResearch = false,
|
||||
{ reportProgress, mcpLog, session } = {}
|
||||
context = {},
|
||||
outputFormat = context.mcpLog ? 'json' : 'text'
|
||||
) {
|
||||
// Determine output format based on mcpLog presence (simplification)
|
||||
const outputFormat = mcpLog ? 'json' : 'text';
|
||||
const { session, mcpLog } = context;
|
||||
const logFn = mcpLog || consoleLog;
|
||||
const isMCP = !!mcpLog;
|
||||
|
||||
// Create custom reporter that checks for MCP log and silent mode
|
||||
const report = (message, level = 'info') => {
|
||||
if (mcpLog) {
|
||||
mcpLog[level](message);
|
||||
} else if (!isSilentMode() && outputFormat === 'text') {
|
||||
// Only log to console if not in silent mode and outputFormat is 'text'
|
||||
log(level, message);
|
||||
// Report helper
|
||||
const report = (level, ...args) => {
|
||||
if (isMCP) {
|
||||
if (typeof logFn[level] === 'function') logFn[level](...args);
|
||||
else logFn.info(...args);
|
||||
} else if (!isSilentMode()) {
|
||||
logFn(level, ...args);
|
||||
}
|
||||
};
|
||||
|
||||
let loadingIndicator = null;
|
||||
|
||||
try {
|
||||
report(`Updating subtask ${subtaskId} with prompt: "${prompt}"`, 'info');
|
||||
report('info', `Updating subtask ${subtaskId} with prompt: "${prompt}"`);
|
||||
|
||||
// Validate subtask ID format
|
||||
if (
|
||||
@@ -76,9 +77,6 @@ async function updateSubtaskById(
|
||||
);
|
||||
}
|
||||
|
||||
// Prepare for fallback handling
|
||||
let claudeOverloaded = false;
|
||||
|
||||
// Validate tasks file exists
|
||||
if (!fs.existsSync(tasksPath)) {
|
||||
throw new Error(`Tasks file not found at path: ${tasksPath}`);
|
||||
@@ -121,18 +119,22 @@ async function updateSubtaskById(
|
||||
throw new Error(`Parent task ${parentId} has no subtasks.`);
|
||||
}
|
||||
|
||||
const subtask = parentTask.subtasks.find((st) => st.id === subtaskIdNum);
|
||||
if (!subtask) {
|
||||
const subtaskIndex = parentTask.subtasks.findIndex(
|
||||
(st) => st.id === subtaskIdNum
|
||||
);
|
||||
if (subtaskIndex === -1) {
|
||||
throw new Error(
|
||||
`Subtask with ID ${subtaskId} not found. Please verify the subtask ID and try again.`
|
||||
);
|
||||
}
|
||||
|
||||
const subtask = parentTask.subtasks[subtaskIndex];
|
||||
|
||||
// Check if subtask is already completed
|
||||
if (subtask.status === 'done' || subtask.status === 'completed') {
|
||||
report(
|
||||
`Subtask ${subtaskId} is already marked as done and cannot be updated`,
|
||||
'warn'
|
||||
'warn',
|
||||
`Subtask ${subtaskId} is already marked as done and cannot be updated`
|
||||
);
|
||||
|
||||
// Only show UI elements for text output (CLI)
|
||||
@@ -208,13 +210,13 @@ Provide concrete examples, code snippets, or implementation details when relevan
|
||||
const userMessageContent = `Here is the subtask to enhance:\n${subtaskData}\n\nPlease provide additional information addressing this request:\n${prompt}\n\nReturn ONLY the new information to add - do not repeat existing content.`;
|
||||
|
||||
const serviceRole = useResearch ? 'research' : 'main';
|
||||
report(`Calling AI stream service with role: ${serviceRole}`, 'info');
|
||||
report('info', `Calling AI text service with role: ${serviceRole}`);
|
||||
|
||||
const streamResult = await generateTextService({
|
||||
role: serviceRole,
|
||||
session: session,
|
||||
systemPrompt: systemPrompt, // Pass the original system prompt
|
||||
prompt: userMessageContent // Pass the original user message content
|
||||
systemPrompt: systemPrompt,
|
||||
prompt: userMessageContent
|
||||
});
|
||||
|
||||
if (outputFormat === 'text' && loadingIndicator) {
|
||||
@@ -231,11 +233,11 @@ Provide concrete examples, code snippets, or implementation details when relevan
|
||||
}
|
||||
report(
|
||||
// Corrected log message to reflect generateText
|
||||
`Successfully generated text using AI role: ${serviceRole}.`,
|
||||
'info'
|
||||
'success',
|
||||
`Successfully generated text using AI role: ${serviceRole}.`
|
||||
);
|
||||
} catch (aiError) {
|
||||
report(`AI service call failed: ${aiError.message}`, 'error');
|
||||
report('error', `AI service call failed: ${aiError.message}`);
|
||||
throw aiError;
|
||||
} // Removed the inner finally block as streamingInterval is gone
|
||||
|
||||
@@ -245,7 +247,7 @@ Provide concrete examples, code snippets, or implementation details when relevan
|
||||
const formattedInformation = `\n\n<info added on ${currentDate.toISOString()}>\n${additionalInformation}\n</info added on ${currentDate.toISOString()}>`;
|
||||
|
||||
// Only show debug info for text output (CLI)
|
||||
if (outputFormat === 'text') {
|
||||
if (outputFormat === 'text' && getDebugFlag(session)) {
|
||||
console.log(
|
||||
'>>> DEBUG: formattedInformation:',
|
||||
formattedInformation.substring(0, 70) + '...'
|
||||
@@ -254,7 +256,7 @@ Provide concrete examples, code snippets, or implementation details when relevan
|
||||
|
||||
// Append to subtask details and description
|
||||
// Only show debug info for text output (CLI)
|
||||
if (outputFormat === 'text') {
|
||||
if (outputFormat === 'text' && getDebugFlag(session)) {
|
||||
console.log('>>> DEBUG: Subtask details BEFORE append:', subtask.details);
|
||||
}
|
||||
|
||||
@@ -265,7 +267,7 @@ Provide concrete examples, code snippets, or implementation details when relevan
|
||||
}
|
||||
|
||||
// Only show debug info for text output (CLI)
|
||||
if (outputFormat === 'text') {
|
||||
if (outputFormat === 'text' && getDebugFlag(session)) {
|
||||
console.log('>>> DEBUG: Subtask details AFTER append:', subtask.details);
|
||||
}
|
||||
|
||||
@@ -273,7 +275,7 @@ Provide concrete examples, code snippets, or implementation details when relevan
|
||||
// Only append to description if it makes sense (for shorter updates)
|
||||
if (additionalInformation.length < 200) {
|
||||
// Only show debug info for text output (CLI)
|
||||
if (outputFormat === 'text') {
|
||||
if (outputFormat === 'text' && getDebugFlag(session)) {
|
||||
console.log(
|
||||
'>>> DEBUG: Subtask description BEFORE append:',
|
||||
subtask.description
|
||||
@@ -281,7 +283,7 @@ Provide concrete examples, code snippets, or implementation details when relevan
|
||||
}
|
||||
subtask.description += ` [Updated: ${currentDate.toLocaleDateString()}]`;
|
||||
// Only show debug info for text output (CLI)
|
||||
if (outputFormat === 'text') {
|
||||
if (outputFormat === 'text' && getDebugFlag(session)) {
|
||||
console.log(
|
||||
'>>> DEBUG: Subtask description AFTER append:',
|
||||
subtask.description
|
||||
@@ -291,19 +293,22 @@ Provide concrete examples, code snippets, or implementation details when relevan
|
||||
}
|
||||
|
||||
// Only show debug info for text output (CLI)
|
||||
if (outputFormat === 'text') {
|
||||
if (outputFormat === 'text' && getDebugFlag(session)) {
|
||||
console.log('>>> DEBUG: About to call writeJSON with updated data...');
|
||||
}
|
||||
|
||||
// Update the subtask in the parent task's array
|
||||
parentTask.subtasks[subtaskIndex] = subtask;
|
||||
|
||||
// Write the updated tasks to the file
|
||||
writeJSON(tasksPath, data);
|
||||
|
||||
// Only show debug info for text output (CLI)
|
||||
if (outputFormat === 'text') {
|
||||
if (outputFormat === 'text' && getDebugFlag(session)) {
|
||||
console.log('>>> DEBUG: writeJSON call completed.');
|
||||
}
|
||||
|
||||
report(`Successfully updated subtask ${subtaskId}`, 'success');
|
||||
report('success', `Successfully updated subtask ${subtaskId}`);
|
||||
|
||||
// Generate individual task files
|
||||
await generateTaskFiles(tasksPath, path.dirname(tasksPath));
|
||||
@@ -340,7 +345,7 @@ Provide concrete examples, code snippets, or implementation details when relevan
|
||||
loadingIndicator = null;
|
||||
}
|
||||
|
||||
report(`Error updating subtask: ${error.message}`, 'error');
|
||||
report('error', `Error updating subtask: ${error.message}`);
|
||||
|
||||
// Only show error UI for text output (CLI)
|
||||
if (outputFormat === 'text') {
|
||||
|
||||
@@ -3,8 +3,15 @@ import path from 'path';
|
||||
import chalk from 'chalk';
|
||||
import boxen from 'boxen';
|
||||
import Table from 'cli-table3';
|
||||
import { z } from 'zod'; // Keep Zod for post-parse validation
|
||||
|
||||
import { log, readJSON, writeJSON, truncate, isSilentMode } from '../utils.js';
|
||||
import {
|
||||
log as consoleLog,
|
||||
readJSON,
|
||||
writeJSON,
|
||||
truncate,
|
||||
isSilentMode
|
||||
} from '../utils.js';
|
||||
|
||||
import {
|
||||
getStatusWithColor,
|
||||
@@ -12,111 +19,205 @@ import {
|
||||
stopLoadingIndicator
|
||||
} from '../ui.js';
|
||||
|
||||
import { _handleAnthropicStream } from '../ai-services.js';
|
||||
import { generateTextService } from '../ai-services-unified.js';
|
||||
import {
|
||||
getDebugFlag,
|
||||
getMainModelId,
|
||||
getMainMaxTokens,
|
||||
getMainTemperature,
|
||||
getResearchModelId,
|
||||
getResearchMaxTokens,
|
||||
getResearchTemperature,
|
||||
isApiKeySet
|
||||
isApiKeySet // Keep this check
|
||||
} from '../config-manager.js';
|
||||
import generateTaskFiles from './generate-task-files.js';
|
||||
|
||||
// Zod schema for post-parsing validation of the updated task object
|
||||
const updatedTaskSchema = z
|
||||
.object({
|
||||
id: z.number().int(),
|
||||
title: z.string(), // Title should be preserved, but check it exists
|
||||
description: z.string(),
|
||||
status: z.string(),
|
||||
dependencies: z.array(z.union([z.number().int(), z.string()])),
|
||||
priority: z.string().optional(),
|
||||
details: z.string().optional(),
|
||||
testStrategy: z.string().optional(),
|
||||
subtasks: z.array(z.any()).optional()
|
||||
})
|
||||
.strip(); // Allows parsing even if AI adds extra fields, but validation focuses on schema
|
||||
|
||||
/**
|
||||
* Update a single task by ID
|
||||
* Parses a single updated task object from AI's text response.
|
||||
* @param {string} text - Response text from AI.
|
||||
* @param {number} expectedTaskId - The ID of the task expected.
|
||||
* @param {Function | Object} logFn - Logging function or MCP logger.
|
||||
* @param {boolean} isMCP - Flag indicating MCP context.
|
||||
* @returns {Object} Parsed and validated task object.
|
||||
* @throws {Error} If parsing or validation fails.
|
||||
*/
|
||||
function parseUpdatedTaskFromText(text, expectedTaskId, logFn, isMCP) {
|
||||
// Report helper consistent with the established pattern
|
||||
const report = (level, ...args) => {
|
||||
if (isMCP) {
|
||||
if (typeof logFn[level] === 'function') logFn[level](...args);
|
||||
else logFn.info(...args);
|
||||
} else if (!isSilentMode()) {
|
||||
logFn(level, ...args);
|
||||
}
|
||||
};
|
||||
|
||||
report(
|
||||
'info',
|
||||
'Attempting to parse updated task object from text response...'
|
||||
);
|
||||
if (!text || text.trim() === '')
|
||||
throw new Error('AI response text is empty.');
|
||||
|
||||
let cleanedResponse = text.trim();
|
||||
const originalResponseForDebug = cleanedResponse;
|
||||
|
||||
// Extract from Markdown code block first
|
||||
const codeBlockMatch = cleanedResponse.match(
|
||||
/```(?:json)?\s*([\s\S]*?)\s*```/
|
||||
);
|
||||
if (codeBlockMatch) {
|
||||
cleanedResponse = codeBlockMatch[1].trim();
|
||||
report('info', 'Extracted JSON content from Markdown code block.');
|
||||
} else {
|
||||
// If no code block, find first '{' and last '}' for the object
|
||||
const firstBrace = cleanedResponse.indexOf('{');
|
||||
const lastBrace = cleanedResponse.lastIndexOf('}');
|
||||
if (firstBrace !== -1 && lastBrace > firstBrace) {
|
||||
cleanedResponse = cleanedResponse.substring(firstBrace, lastBrace + 1);
|
||||
report('info', 'Extracted content between first { and last }.');
|
||||
} else {
|
||||
report(
|
||||
'warn',
|
||||
'Response does not appear to contain a JSON object structure. Parsing raw response.'
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
let parsedTask;
|
||||
try {
|
||||
parsedTask = JSON.parse(cleanedResponse);
|
||||
} catch (parseError) {
|
||||
report('error', `Failed to parse JSON object: ${parseError.message}`);
|
||||
report(
|
||||
'error',
|
||||
`Problematic JSON string (first 500 chars): ${cleanedResponse.substring(0, 500)}`
|
||||
);
|
||||
report(
|
||||
'error',
|
||||
`Original Raw Response (first 500 chars): ${originalResponseForDebug.substring(0, 500)}`
|
||||
);
|
||||
throw new Error(
|
||||
`Failed to parse JSON response object: ${parseError.message}`
|
||||
);
|
||||
}
|
||||
|
||||
if (!parsedTask || typeof parsedTask !== 'object') {
|
||||
report(
|
||||
'error',
|
||||
`Parsed content is not an object. Type: ${typeof parsedTask}`
|
||||
);
|
||||
report(
|
||||
'error',
|
||||
`Parsed content sample: ${JSON.stringify(parsedTask).substring(0, 200)}`
|
||||
);
|
||||
throw new Error('Parsed AI response is not a valid JSON object.');
|
||||
}
|
||||
|
||||
// Validate the parsed task object using Zod
|
||||
const validationResult = updatedTaskSchema.safeParse(parsedTask);
|
||||
if (!validationResult.success) {
|
||||
report('error', 'Parsed task object failed Zod validation.');
|
||||
validationResult.error.errors.forEach((err) => {
|
||||
report('error', ` - Field '${err.path.join('.')}': ${err.message}`);
|
||||
});
|
||||
throw new Error(
|
||||
`AI response failed task structure validation: ${validationResult.error.message}`
|
||||
);
|
||||
}
|
||||
|
||||
// Final check: ensure ID matches expected ID (AI might hallucinate)
|
||||
if (validationResult.data.id !== expectedTaskId) {
|
||||
report(
|
||||
'warn',
|
||||
`AI returned task with ID ${validationResult.data.id}, but expected ${expectedTaskId}. Overwriting ID.`
|
||||
);
|
||||
validationResult.data.id = expectedTaskId; // Enforce correct ID
|
||||
}
|
||||
|
||||
report('info', 'Successfully validated updated task structure.');
|
||||
return validationResult.data; // Return the validated task data
|
||||
}
|
||||
|
||||
/**
|
||||
* Update a single task by ID using the unified AI service.
|
||||
* @param {string} tasksPath - Path to the tasks.json file
|
||||
* @param {number} taskId - Task ID to update
|
||||
* @param {string} prompt - Prompt with new context
|
||||
* @param {boolean} useResearch - Whether to use Perplexity AI for research
|
||||
* @param {function} reportProgress - Function to report progress to MCP server (optional)
|
||||
* @param {Object} mcpLog - MCP logger object (optional)
|
||||
* @param {Object} session - Session object from MCP server (optional)
|
||||
* @returns {Object} - Updated task data or null if task wasn't updated
|
||||
* @param {boolean} [useResearch=false] - Whether to use the research AI role.
|
||||
* @param {Object} context - Context object containing session and mcpLog.
|
||||
* @param {Object} [context.session] - Session object from MCP server.
|
||||
* @param {Object} [context.mcpLog] - MCP logger object.
|
||||
* @param {string} [outputFormat='text'] - Output format ('text' or 'json').
|
||||
* @returns {Promise<Object|null>} - Updated task data or null if task wasn't updated/found.
|
||||
*/
|
||||
async function updateTaskById(
|
||||
tasksPath,
|
||||
taskId,
|
||||
prompt,
|
||||
useResearch = false,
|
||||
{ reportProgress, mcpLog, session } = {}
|
||||
context = {},
|
||||
outputFormat = 'text'
|
||||
) {
|
||||
// Determine output format based on mcpLog presence (simplification)
|
||||
const outputFormat = mcpLog ? 'json' : 'text';
|
||||
const { session, mcpLog } = context;
|
||||
const logFn = mcpLog || consoleLog;
|
||||
const isMCP = !!mcpLog;
|
||||
|
||||
// Create custom reporter that checks for MCP log and silent mode
|
||||
const report = (message, level = 'info') => {
|
||||
if (mcpLog) {
|
||||
mcpLog[level](message);
|
||||
} else if (!isSilentMode() && outputFormat === 'text') {
|
||||
// Only log to console if not in silent mode and outputFormat is 'text'
|
||||
log(level, message);
|
||||
// Use report helper for logging
|
||||
const report = (level, ...args) => {
|
||||
if (isMCP) {
|
||||
if (typeof logFn[level] === 'function') logFn[level](...args);
|
||||
else logFn.info(...args);
|
||||
} else if (!isSilentMode()) {
|
||||
logFn(level, ...args);
|
||||
}
|
||||
};
|
||||
|
||||
try {
|
||||
report(`Updating single task ${taskId} with prompt: "${prompt}"`, 'info');
|
||||
report('info', `Updating single task ${taskId} with prompt: "${prompt}"`);
|
||||
|
||||
// Validate task ID is a positive integer
|
||||
if (!Number.isInteger(taskId) || taskId <= 0) {
|
||||
// --- Input Validations (Keep existing) ---
|
||||
if (!Number.isInteger(taskId) || taskId <= 0)
|
||||
throw new Error(
|
||||
`Invalid task ID: ${taskId}. Task ID must be a positive integer.`
|
||||
);
|
||||
}
|
||||
|
||||
// Validate prompt
|
||||
if (!prompt || typeof prompt !== 'string' || prompt.trim() === '') {
|
||||
throw new Error(
|
||||
'Prompt cannot be empty. Please provide context for the task update.'
|
||||
);
|
||||
}
|
||||
|
||||
// Validate research flag and API key
|
||||
if (!prompt || typeof prompt !== 'string' || prompt.trim() === '')
|
||||
throw new Error('Prompt cannot be empty.');
|
||||
if (useResearch && !isApiKeySet('perplexity', session)) {
|
||||
report(
|
||||
'Perplexity AI research requested but API key is not set. Falling back to main AI.',
|
||||
'warn'
|
||||
'warn',
|
||||
'Perplexity research requested but API key not set. Falling back.'
|
||||
);
|
||||
|
||||
// Only show UI elements for text output (CLI)
|
||||
if (outputFormat === 'text') {
|
||||
if (outputFormat === 'text')
|
||||
console.log(
|
||||
chalk.yellow(
|
||||
'Perplexity AI is not available (API key may be missing). Falling back to Claude AI.'
|
||||
)
|
||||
chalk.yellow('Perplexity AI not available. Falling back to main AI.')
|
||||
);
|
||||
}
|
||||
useResearch = false;
|
||||
}
|
||||
if (!fs.existsSync(tasksPath))
|
||||
throw new Error(`Tasks file not found: ${tasksPath}`);
|
||||
// --- End Input Validations ---
|
||||
|
||||
// Validate tasks file exists
|
||||
if (!fs.existsSync(tasksPath)) {
|
||||
throw new Error(`Tasks file not found at path: ${tasksPath}`);
|
||||
}
|
||||
|
||||
// Read the tasks file
|
||||
// --- Task Loading and Status Check (Keep existing) ---
|
||||
const data = readJSON(tasksPath);
|
||||
if (!data || !data.tasks) {
|
||||
throw new Error(
|
||||
`No valid tasks found in ${tasksPath}. The file may be corrupted or have an invalid format.`
|
||||
);
|
||||
}
|
||||
|
||||
// Find the specific task to update
|
||||
const taskToUpdate = data.tasks.find((task) => task.id === taskId);
|
||||
if (!taskToUpdate) {
|
||||
throw new Error(
|
||||
`Task with ID ${taskId} not found. Please verify the task ID and try again.`
|
||||
);
|
||||
}
|
||||
|
||||
// Check if task is already completed
|
||||
if (!data || !data.tasks)
|
||||
throw new Error(`No valid tasks found in ${tasksPath}.`);
|
||||
const taskIndex = data.tasks.findIndex((task) => task.id === taskId);
|
||||
if (taskIndex === -1) throw new Error(`Task with ID ${taskId} not found.`);
|
||||
const taskToUpdate = data.tasks[taskIndex];
|
||||
if (taskToUpdate.status === 'done' || taskToUpdate.status === 'completed') {
|
||||
report(
|
||||
`Task ${taskId} is already marked as done and cannot be updated`,
|
||||
'warn'
|
||||
'warn',
|
||||
`Task ${taskId} is already marked as done and cannot be updated`
|
||||
);
|
||||
|
||||
// Only show warning box for text output (CLI)
|
||||
@@ -142,8 +243,9 @@ async function updateTaskById(
|
||||
}
|
||||
return null;
|
||||
}
|
||||
// --- End Task Loading ---
|
||||
|
||||
// Only show UI elements for text output (CLI)
|
||||
// --- Display Task Info (CLI Only - Keep existing) ---
|
||||
if (outputFormat === 'text') {
|
||||
// Show the task that will be updated
|
||||
const table = new Table({
|
||||
@@ -199,7 +301,7 @@ async function updateTaskById(
|
||||
);
|
||||
}
|
||||
|
||||
// Build the system prompt
|
||||
// --- Build Prompts (Keep EXACT original prompts) ---
|
||||
const systemPrompt = `You are an AI assistant helping to update a software development task based on new context.
|
||||
You will be given a task and a prompt describing changes or new implementation details.
|
||||
Your job is to update the task to reflect these changes, while preserving its basic structure.
|
||||
@@ -219,464 +321,162 @@ Guidelines:
|
||||
|
||||
The changes described in the prompt should be thoughtfully applied to make the task more accurate and actionable.`;
|
||||
|
||||
const taskData = JSON.stringify(taskToUpdate, null, 2);
|
||||
const taskDataString = JSON.stringify(taskToUpdate, null, 2); // Use original task data
|
||||
const userPrompt = `Here is the task to update:\n${taskDataString}\n\nPlease update this task based on the following new context:\n${prompt}\n\nIMPORTANT: In the task JSON above, any subtasks with "status": "done" or "status": "completed" should be preserved exactly as is. Build your changes around these completed items.\n\nReturn only the updated task as a valid JSON object.`;
|
||||
// --- End Build Prompts ---
|
||||
|
||||
// Initialize variables for model selection and fallback
|
||||
let updatedTask;
|
||||
let loadingIndicator = null;
|
||||
let claudeOverloaded = false;
|
||||
let modelAttempts = 0;
|
||||
const maxModelAttempts = 2; // Try up to 2 models before giving up
|
||||
|
||||
// Only create initial loading indicator for text output (CLI)
|
||||
if (outputFormat === 'text') {
|
||||
loadingIndicator = startLoadingIndicator(
|
||||
useResearch
|
||||
? 'Updating task with Perplexity AI research...'
|
||||
: 'Updating task with Claude AI...'
|
||||
useResearch ? 'Updating task with research...' : 'Updating task...'
|
||||
);
|
||||
}
|
||||
|
||||
try {
|
||||
// Import the getAvailableAIModel function
|
||||
const { getAvailableAIModel } = await import('./ai-services.js');
|
||||
|
||||
// Try different models with fallback
|
||||
while (modelAttempts < maxModelAttempts && !updatedTask) {
|
||||
modelAttempts++;
|
||||
const isLastAttempt = modelAttempts >= maxModelAttempts;
|
||||
let modelType = null;
|
||||
|
||||
try {
|
||||
// Get the appropriate model based on current state
|
||||
const result = getAvailableAIModel({
|
||||
claudeOverloaded,
|
||||
requiresResearch: useResearch
|
||||
});
|
||||
modelType = result.type;
|
||||
const client = result.client;
|
||||
|
||||
report(
|
||||
`Attempt ${modelAttempts}/${maxModelAttempts}: Updating task using ${modelType}`,
|
||||
'info'
|
||||
);
|
||||
|
||||
// Update loading indicator - only for text output
|
||||
if (outputFormat === 'text') {
|
||||
if (loadingIndicator) {
|
||||
stopLoadingIndicator(loadingIndicator);
|
||||
}
|
||||
loadingIndicator = startLoadingIndicator(
|
||||
`Attempt ${modelAttempts}: Using ${modelType.toUpperCase()}...`
|
||||
);
|
||||
}
|
||||
|
||||
if (modelType === 'perplexity') {
|
||||
// Call Perplexity AI
|
||||
const perplexityModel =
|
||||
process.env.PERPLEXITY_MODEL ||
|
||||
session?.env?.PERPLEXITY_MODEL ||
|
||||
'sonar-pro';
|
||||
const result = await client.chat.completions.create({
|
||||
model: getResearchModelId(session),
|
||||
messages: [
|
||||
{
|
||||
role: 'system',
|
||||
content: `${systemPrompt}\n\nAdditionally, please research the latest best practices, implementation details, and considerations when updating this task. Use your online search capabilities to gather relevant information. Remember to strictly follow the guidelines about preserving completed subtasks and building upon what has already been done rather than modifying or replacing it.`
|
||||
},
|
||||
{
|
||||
role: 'user',
|
||||
content: `Here is the task to update:
|
||||
${taskData}
|
||||
|
||||
Please update this task based on the following new context:
|
||||
${prompt}
|
||||
|
||||
IMPORTANT: In the task JSON above, any subtasks with "status": "done" or "status": "completed" should be preserved exactly as is. Build your changes around these completed items.
|
||||
|
||||
Return only the updated task as a valid JSON object.`
|
||||
}
|
||||
],
|
||||
temperature: getResearchTemperature(session),
|
||||
max_tokens: getResearchMaxTokens(session)
|
||||
});
|
||||
|
||||
const responseText = result.choices[0].message.content;
|
||||
|
||||
// Extract JSON from response
|
||||
const jsonStart = responseText.indexOf('{');
|
||||
const jsonEnd = responseText.lastIndexOf('}');
|
||||
|
||||
if (jsonStart === -1 || jsonEnd === -1) {
|
||||
throw new Error(
|
||||
`Could not find valid JSON object in ${modelType}'s response. The response may be malformed.`
|
||||
);
|
||||
}
|
||||
|
||||
const jsonText = responseText.substring(jsonStart, jsonEnd + 1);
|
||||
|
||||
try {
|
||||
updatedTask = JSON.parse(jsonText);
|
||||
} catch (parseError) {
|
||||
throw new Error(
|
||||
`Failed to parse ${modelType} response as JSON: ${parseError.message}\nResponse fragment: ${jsonText.substring(0, 100)}...`
|
||||
);
|
||||
}
|
||||
} else {
|
||||
// Call Claude to update the task with streaming
|
||||
let responseText = '';
|
||||
let streamingInterval = null;
|
||||
|
||||
try {
|
||||
// Update loading indicator to show streaming progress - only for text output
|
||||
if (outputFormat === 'text') {
|
||||
let dotCount = 0;
|
||||
const readline = await import('readline');
|
||||
streamingInterval = setInterval(() => {
|
||||
readline.cursorTo(process.stdout, 0);
|
||||
process.stdout.write(
|
||||
`Receiving streaming response from Claude${'.'.repeat(dotCount)}`
|
||||
);
|
||||
dotCount = (dotCount + 1) % 4;
|
||||
}, 500);
|
||||
}
|
||||
// --- Call Unified AI Service (generateTextService) ---
|
||||
const role = useResearch ? 'research' : 'main';
|
||||
report('info', `Using AI service with role: ${role}`);
|
||||
|
||||
// Use streaming API call
|
||||
const stream = await client.messages.create({
|
||||
model: getMainModelId(session),
|
||||
max_tokens: getMainMaxTokens(session),
|
||||
temperature: getMainTemperature(session),
|
||||
system: systemPrompt,
|
||||
messages: [
|
||||
{
|
||||
role: 'user',
|
||||
content: `Here is the task to update:
|
||||
${taskData}
|
||||
|
||||
Please update this task based on the following new context:
|
||||
${prompt}
|
||||
|
||||
IMPORTANT: In the task JSON above, any subtasks with "status": "done" or "status": "completed" should be preserved exactly as is. Build your changes around these completed items.
|
||||
|
||||
Return only the updated task as a valid JSON object.`
|
||||
}
|
||||
],
|
||||
stream: true
|
||||
responseText = await generateTextService({
|
||||
prompt: userPrompt,
|
||||
systemPrompt: systemPrompt,
|
||||
role,
|
||||
session
|
||||
});
|
||||
|
||||
// Process the stream
|
||||
for await (const chunk of stream) {
|
||||
if (chunk.type === 'content_block_delta' && chunk.delta.text) {
|
||||
responseText += chunk.delta.text;
|
||||
}
|
||||
if (reportProgress) {
|
||||
await reportProgress({
|
||||
progress:
|
||||
(responseText.length / getMainMaxTokens(session)) * 100
|
||||
});
|
||||
}
|
||||
if (mcpLog) {
|
||||
mcpLog.info(
|
||||
`Progress: ${(responseText.length / getMainMaxTokens(session)) * 100}%`
|
||||
);
|
||||
report('success', 'Successfully received text response from AI service');
|
||||
// --- End AI Service Call ---
|
||||
} catch (error) {
|
||||
// Catch errors from generateTextService
|
||||
if (loadingIndicator) stopLoadingIndicator(loadingIndicator);
|
||||
report('error', `Error during AI service call: ${error.message}`);
|
||||
if (error.message.includes('API key')) {
|
||||
report('error', 'Please ensure API keys are configured correctly.');
|
||||
}
|
||||
throw error; // Re-throw error
|
||||
} finally {
|
||||
if (loadingIndicator) stopLoadingIndicator(loadingIndicator);
|
||||
}
|
||||
|
||||
if (streamingInterval) clearInterval(streamingInterval);
|
||||
|
||||
report(
|
||||
`Completed streaming response from ${modelType} API (Attempt ${modelAttempts})`,
|
||||
'info'
|
||||
);
|
||||
|
||||
// Extract JSON from response
|
||||
const jsonStart = responseText.indexOf('{');
|
||||
const jsonEnd = responseText.lastIndexOf('}');
|
||||
|
||||
if (jsonStart === -1 || jsonEnd === -1) {
|
||||
throw new Error(
|
||||
`Could not find valid JSON object in ${modelType}'s response. The response may be malformed.`
|
||||
);
|
||||
}
|
||||
|
||||
const jsonText = responseText.substring(jsonStart, jsonEnd + 1);
|
||||
|
||||
// --- Parse and Validate Response ---
|
||||
try {
|
||||
updatedTask = JSON.parse(jsonText);
|
||||
// Pass logFn and isMCP flag to the parser
|
||||
updatedTask = parseUpdatedTaskFromText(
|
||||
responseText,
|
||||
taskId,
|
||||
logFn,
|
||||
isMCP
|
||||
);
|
||||
} catch (parseError) {
|
||||
throw new Error(
|
||||
`Failed to parse ${modelType} response as JSON: ${parseError.message}\nResponse fragment: ${jsonText.substring(0, 100)}...`
|
||||
);
|
||||
}
|
||||
} catch (streamError) {
|
||||
if (streamingInterval) clearInterval(streamingInterval);
|
||||
|
||||
// Process stream errors explicitly
|
||||
report(`Stream error: ${streamError.message}`, 'error');
|
||||
|
||||
// Check if this is an overload error
|
||||
let isOverload = false;
|
||||
// Check 1: SDK specific property
|
||||
if (streamError.type === 'overloaded_error') {
|
||||
isOverload = true;
|
||||
}
|
||||
// Check 2: Check nested error property
|
||||
else if (streamError.error?.type === 'overloaded_error') {
|
||||
isOverload = true;
|
||||
}
|
||||
// Check 3: Check status code
|
||||
else if (
|
||||
streamError.status === 429 ||
|
||||
streamError.status === 529
|
||||
) {
|
||||
isOverload = true;
|
||||
}
|
||||
// Check 4: Check message string
|
||||
else if (
|
||||
streamError.message?.toLowerCase().includes('overloaded')
|
||||
) {
|
||||
isOverload = true;
|
||||
}
|
||||
|
||||
if (isOverload) {
|
||||
claudeOverloaded = true;
|
||||
report(
|
||||
'Claude overloaded. Will attempt fallback model if available.',
|
||||
'warn'
|
||||
'error',
|
||||
`Failed to parse updated task from AI response: ${parseError.message}`
|
||||
);
|
||||
// Let the loop continue to try the next model
|
||||
throw new Error('Claude overloaded');
|
||||
} else {
|
||||
// Re-throw non-overload errors
|
||||
throw streamError;
|
||||
if (getDebugFlag(session)) {
|
||||
report('error', `Raw AI Response:\n${responseText}`);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// If we got here successfully, break out of the loop
|
||||
if (updatedTask) {
|
||||
report(
|
||||
`Successfully updated task using ${modelType} on attempt ${modelAttempts}`,
|
||||
'success'
|
||||
);
|
||||
break;
|
||||
}
|
||||
} catch (modelError) {
|
||||
const failedModel = modelType || 'unknown model';
|
||||
report(
|
||||
`Attempt ${modelAttempts} failed using ${failedModel}: ${modelError.message}`,
|
||||
'warn'
|
||||
);
|
||||
|
||||
// Continue to next attempt if we have more attempts and this was an overload error
|
||||
const wasOverload = modelError.message
|
||||
?.toLowerCase()
|
||||
.includes('overload');
|
||||
|
||||
if (wasOverload && !isLastAttempt) {
|
||||
if (modelType === 'claude') {
|
||||
claudeOverloaded = true;
|
||||
report('Will attempt with Perplexity AI next', 'info');
|
||||
}
|
||||
continue; // Continue to next attempt
|
||||
} else if (isLastAttempt) {
|
||||
report(
|
||||
`Final attempt (${modelAttempts}/${maxModelAttempts}) failed. No fallback possible.`,
|
||||
'error'
|
||||
);
|
||||
throw modelError; // Re-throw on last attempt
|
||||
} else {
|
||||
throw modelError; // Re-throw for non-overload errors
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// If we don't have updated task after all attempts, throw an error
|
||||
if (!updatedTask) {
|
||||
throw new Error(
|
||||
'Failed to generate updated task after all model attempts'
|
||||
`Failed to parse valid updated task from AI response: ${parseError.message}`
|
||||
);
|
||||
}
|
||||
// --- End Parse/Validate ---
|
||||
|
||||
// Validation of the updated task
|
||||
if (!updatedTask || typeof updatedTask !== 'object') {
|
||||
throw new Error(
|
||||
'Received invalid task object from AI. The response did not contain a valid task.'
|
||||
);
|
||||
}
|
||||
|
||||
// Ensure critical fields exist
|
||||
if (!updatedTask.title || !updatedTask.description) {
|
||||
throw new Error(
|
||||
'Updated task is missing required fields (title or description).'
|
||||
);
|
||||
}
|
||||
|
||||
// Ensure ID is preserved
|
||||
// --- Task Validation/Correction (Keep existing logic) ---
|
||||
if (!updatedTask || typeof updatedTask !== 'object')
|
||||
throw new Error('Received invalid task object from AI.');
|
||||
if (!updatedTask.title || !updatedTask.description)
|
||||
throw new Error('Updated task missing required fields.');
|
||||
// Preserve ID if AI changed it
|
||||
if (updatedTask.id !== taskId) {
|
||||
report(
|
||||
`Task ID was modified in the AI response. Restoring original ID ${taskId}.`,
|
||||
'warn'
|
||||
);
|
||||
report('warn', `AI changed task ID. Restoring original ID ${taskId}.`);
|
||||
updatedTask.id = taskId;
|
||||
}
|
||||
|
||||
// Ensure status is preserved unless explicitly changed in prompt
|
||||
// Preserve status if AI changed it
|
||||
if (
|
||||
updatedTask.status !== taskToUpdate.status &&
|
||||
!prompt.toLowerCase().includes('status')
|
||||
) {
|
||||
report(
|
||||
`Task status was modified without explicit instruction. Restoring original status '${taskToUpdate.status}'.`,
|
||||
'warn'
|
||||
'warn',
|
||||
`AI changed task status. Restoring original status '${taskToUpdate.status}'.`
|
||||
);
|
||||
updatedTask.status = taskToUpdate.status;
|
||||
}
|
||||
|
||||
// Ensure completed subtasks are preserved
|
||||
if (taskToUpdate.subtasks && taskToUpdate.subtasks.length > 0) {
|
||||
// Preserve completed subtasks (Keep existing logic)
|
||||
if (taskToUpdate.subtasks?.length > 0) {
|
||||
if (!updatedTask.subtasks) {
|
||||
report(
|
||||
'Subtasks were removed in the AI response. Restoring original subtasks.',
|
||||
'warn'
|
||||
);
|
||||
report('warn', 'Subtasks removed by AI. Restoring original subtasks.');
|
||||
updatedTask.subtasks = taskToUpdate.subtasks;
|
||||
} else {
|
||||
// Check for each completed subtask
|
||||
const completedSubtasks = taskToUpdate.subtasks.filter(
|
||||
const completedOriginal = taskToUpdate.subtasks.filter(
|
||||
(st) => st.status === 'done' || st.status === 'completed'
|
||||
);
|
||||
|
||||
for (const completedSubtask of completedSubtasks) {
|
||||
const updatedSubtask = updatedTask.subtasks.find(
|
||||
(st) => st.id === completedSubtask.id
|
||||
completedOriginal.forEach((compSub) => {
|
||||
const updatedSub = updatedTask.subtasks.find(
|
||||
(st) => st.id === compSub.id
|
||||
);
|
||||
|
||||
// If completed subtask is missing or modified, restore it
|
||||
if (!updatedSubtask) {
|
||||
report(
|
||||
`Completed subtask ${completedSubtask.id} was removed. Restoring it.`,
|
||||
'warn'
|
||||
);
|
||||
updatedTask.subtasks.push(completedSubtask);
|
||||
} else if (
|
||||
updatedSubtask.title !== completedSubtask.title ||
|
||||
updatedSubtask.description !== completedSubtask.description ||
|
||||
updatedSubtask.details !== completedSubtask.details ||
|
||||
updatedSubtask.status !== completedSubtask.status
|
||||
if (
|
||||
!updatedSub ||
|
||||
JSON.stringify(updatedSub) !== JSON.stringify(compSub)
|
||||
) {
|
||||
report(
|
||||
`Completed subtask ${completedSubtask.id} was modified. Restoring original.`,
|
||||
'warn'
|
||||
'warn',
|
||||
`Completed subtask ${compSub.id} was modified or removed. Restoring.`
|
||||
);
|
||||
// Find and replace the modified subtask
|
||||
const index = updatedTask.subtasks.findIndex(
|
||||
(st) => st.id === completedSubtask.id
|
||||
// Remove potentially modified version
|
||||
updatedTask.subtasks = updatedTask.subtasks.filter(
|
||||
(st) => st.id !== compSub.id
|
||||
);
|
||||
if (index !== -1) {
|
||||
updatedTask.subtasks[index] = completedSubtask;
|
||||
// Add back original
|
||||
updatedTask.subtasks.push(compSub);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Ensure no duplicate subtask IDs
|
||||
});
|
||||
// Deduplicate just in case
|
||||
const subtaskIds = new Set();
|
||||
const uniqueSubtasks = [];
|
||||
updatedTask.subtasks = updatedTask.subtasks.filter((st) => {
|
||||
if (!subtaskIds.has(st.id)) {
|
||||
subtaskIds.add(st.id);
|
||||
return true;
|
||||
}
|
||||
report('warn', `Duplicate subtask ID ${st.id} removed.`);
|
||||
return false;
|
||||
});
|
||||
}
|
||||
}
|
||||
// --- End Task Validation/Correction ---
|
||||
|
||||
for (const subtask of updatedTask.subtasks) {
|
||||
if (!subtaskIds.has(subtask.id)) {
|
||||
subtaskIds.add(subtask.id);
|
||||
uniqueSubtasks.push(subtask);
|
||||
} else {
|
||||
report(
|
||||
`Duplicate subtask ID ${subtask.id} found. Removing duplicate.`,
|
||||
'warn'
|
||||
);
|
||||
}
|
||||
}
|
||||
// --- Update Task Data (Keep existing) ---
|
||||
data.tasks[taskIndex] = updatedTask;
|
||||
// --- End Update Task Data ---
|
||||
|
||||
updatedTask.subtasks = uniqueSubtasks;
|
||||
}
|
||||
}
|
||||
|
||||
// Update the task in the original data
|
||||
const index = data.tasks.findIndex((t) => t.id === taskId);
|
||||
if (index !== -1) {
|
||||
data.tasks[index] = updatedTask;
|
||||
} else {
|
||||
throw new Error(`Task with ID ${taskId} not found in tasks array.`);
|
||||
}
|
||||
|
||||
// Write the updated tasks to the file
|
||||
// --- Write File and Generate (Keep existing) ---
|
||||
writeJSON(tasksPath, data);
|
||||
|
||||
report(`Successfully updated task ${taskId}`, 'success');
|
||||
|
||||
// Generate individual task files
|
||||
report('success', `Successfully updated task ${taskId}`);
|
||||
await generateTaskFiles(tasksPath, path.dirname(tasksPath));
|
||||
// --- End Write File ---
|
||||
|
||||
// Only show success box for text output (CLI)
|
||||
// --- Final CLI Output (Keep existing) ---
|
||||
if (outputFormat === 'text') {
|
||||
console.log(
|
||||
boxen(
|
||||
chalk.green(`Successfully updated task #${taskId}`) +
|
||||
'\n\n' +
|
||||
chalk.white.bold('Updated Title:') +
|
||||
' ' +
|
||||
updatedTask.title,
|
||||
{ padding: 1, borderColor: 'green', borderStyle: 'round' }
|
||||
)
|
||||
);
|
||||
/* ... success boxen ... */
|
||||
}
|
||||
// --- End Final CLI Output ---
|
||||
|
||||
// Return the updated task for testing purposes
|
||||
return updatedTask;
|
||||
} finally {
|
||||
// Stop the loading indicator if it was created
|
||||
if (loadingIndicator) {
|
||||
stopLoadingIndicator(loadingIndicator);
|
||||
loadingIndicator = null;
|
||||
}
|
||||
}
|
||||
return updatedTask; // Return the updated task
|
||||
} catch (error) {
|
||||
report(`Error updating task: ${error.message}`, 'error');
|
||||
|
||||
// Only show error UI for text output (CLI)
|
||||
// General error catch
|
||||
// --- General Error Handling (Keep existing) ---
|
||||
report('error', `Error updating task: ${error.message}`);
|
||||
if (outputFormat === 'text') {
|
||||
console.error(chalk.red(`Error: ${error.message}`));
|
||||
|
||||
// Provide more helpful error messages for common issues
|
||||
if (error.message.includes('ANTHROPIC_API_KEY')) {
|
||||
console.log(
|
||||
chalk.yellow('\nTo fix this issue, set your Anthropic API key:')
|
||||
);
|
||||
console.log(' export ANTHROPIC_API_KEY=your_api_key_here');
|
||||
} else if (error.message.includes('PERPLEXITY_API_KEY')) {
|
||||
console.log(chalk.yellow('\nTo fix this issue:'));
|
||||
console.log(
|
||||
' 1. Set your Perplexity API key: export PERPLEXITY_API_KEY=your_api_key_here'
|
||||
);
|
||||
console.log(
|
||||
' 2. Or run without the research flag: task-master update-task --id=<id> --prompt="..."'
|
||||
);
|
||||
} else if (
|
||||
error.message.includes('Task with ID') &&
|
||||
error.message.includes('not found')
|
||||
) {
|
||||
console.log(chalk.yellow('\nTo fix this issue:'));
|
||||
console.log(' 1. Run task-master list to see all available task IDs');
|
||||
console.log(' 2. Use a valid task ID with the --id parameter');
|
||||
}
|
||||
|
||||
if (getDebugFlag(session)) {
|
||||
// Use getter
|
||||
console.error(error);
|
||||
}
|
||||
// ... helpful hints ...
|
||||
if (getDebugFlag(session)) console.error(error);
|
||||
process.exit(1);
|
||||
} else {
|
||||
throw error; // Re-throw for JSON output
|
||||
throw error; // Re-throw for MCP
|
||||
}
|
||||
|
||||
return null;
|
||||
return null; // Indicate failure in CLI case if process doesn't exit
|
||||
// --- End General Error Handling ---
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
# Task ID: 56
|
||||
# Title: Refactor Task-Master Files into Node Module Structure
|
||||
# Status: pending
|
||||
# Status: done
|
||||
# Dependencies: None
|
||||
# Priority: medium
|
||||
# Description: Restructure the task-master files by moving them from the project root into a proper node module structure to improve organization and maintainability.
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
# Task ID: 58
|
||||
# Title: Implement Elegant Package Update Mechanism for Task-Master
|
||||
# Status: pending
|
||||
# Status: done
|
||||
# Dependencies: None
|
||||
# Priority: medium
|
||||
# Description: Create a robust update mechanism that handles package updates gracefully, ensuring all necessary files are updated when the global package is upgraded.
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
# Task ID: 59
|
||||
# Title: Remove Manual Package.json Modifications and Implement Automatic Dependency Management
|
||||
# Status: pending
|
||||
# Status: done
|
||||
# Dependencies: None
|
||||
# Priority: medium
|
||||
# Description: Eliminate code that manually modifies users' package.json files and implement proper npm dependency management that automatically handles package requirements when users install task-master-ai.
|
||||
@@ -30,37 +30,37 @@ This change will make the package more reliable, follow npm best practices, and
|
||||
9. Create an integration test that simulates a real user workflow from installation through usage
|
||||
|
||||
# Subtasks:
|
||||
## 1. Conduct Code Audit for Dependency Management [pending]
|
||||
## 1. Conduct Code Audit for Dependency Management [done]
|
||||
### Dependencies: None
|
||||
### Description: Review the current codebase to identify all areas where dependencies are manually managed, modified, or referenced outside of npm best practices.
|
||||
### Details:
|
||||
Focus on scripts, configuration files, and any custom logic related to dependency installation or versioning.
|
||||
|
||||
## 2. Remove Manual Dependency Modifications [pending]
|
||||
## 2. Remove Manual Dependency Modifications [done]
|
||||
### Dependencies: 59.1
|
||||
### Description: Eliminate any custom scripts or manual steps that alter dependencies outside of npm's standard workflow.
|
||||
### Details:
|
||||
Refactor or delete code that manually installs, updates, or modifies dependencies, ensuring all dependency management is handled via npm.
|
||||
|
||||
## 3. Update npm Dependencies [pending]
|
||||
## 3. Update npm Dependencies [done]
|
||||
### Dependencies: 59.2
|
||||
### Description: Update all project dependencies using npm, ensuring versions are current and compatible, and resolve any conflicts.
|
||||
### Details:
|
||||
Run npm update, audit for vulnerabilities, and adjust package.json and package-lock.json as needed.
|
||||
|
||||
## 4. Update Initialization and Installation Commands [pending]
|
||||
## 4. Update Initialization and Installation Commands [done]
|
||||
### Dependencies: 59.3
|
||||
### Description: Revise project setup scripts and documentation to reflect the new npm-based dependency management approach.
|
||||
### Details:
|
||||
Ensure that all initialization commands (e.g., npm install) are up-to-date and remove references to deprecated manual steps.
|
||||
|
||||
## 5. Update Documentation [pending]
|
||||
## 5. Update Documentation [done]
|
||||
### Dependencies: 59.4
|
||||
### Description: Revise project documentation to describe the new dependency management process and provide clear setup instructions.
|
||||
### Details:
|
||||
Update README, onboarding guides, and any developer documentation to align with npm best practices.
|
||||
|
||||
## 6. Perform Regression Testing [pending]
|
||||
## 6. Perform Regression Testing [done]
|
||||
### Dependencies: 59.5
|
||||
### Description: Run comprehensive tests to ensure that the refactor has not introduced any regressions or broken existing functionality.
|
||||
### Details:
|
||||
|
||||
@@ -4,6 +4,8 @@
|
||||
# Dependencies: None
|
||||
# Priority: medium
|
||||
# Description: Implement full support for installing and managing Taskmaster using Yarn package manager, ensuring users have the exact same experience as with npm or pnpm. The installation process, including any CLI prompts or web interfaces, must serve the exact same content and user experience regardless of whether npm, pnpm, or Yarn is used. The project uses 'module' as the package type, defines binaries 'task-master' and 'task-master-mcp', and its core logic resides in 'scripts/modules/'. The 'init' command (via scripts/init.js) creates the directory structure (.cursor/rules, scripts, tasks), copies templates (.env.example, .gitignore, rule files, dev.js), manages package.json merging, and sets up MCP config (.cursor/mcp.json). All dependencies are standard npm dependencies listed in package.json, and manual modifications are being removed.
|
||||
|
||||
If the installation process includes a website component (such as for account setup or registration), ensure that any required website actions (e.g., creating an account, logging in, or configuring user settings) are clearly documented and tested for parity between Yarn and other package managers. If no website or account setup is required, confirm and document this explicitly.
|
||||
# Details:
|
||||
This task involves adding comprehensive Yarn support to the Taskmaster package to ensure it can be properly installed and managed using Yarn. Implementation should include:
|
||||
|
||||
@@ -24,6 +26,7 @@ This task involves adding comprehensive Yarn support to the Taskmaster package t
|
||||
11. Ensure proper lockfile generation and management
|
||||
12. Update any package manager detection logic in the codebase to recognize Yarn installations
|
||||
13. Verify that core logic in `scripts/modules/` works correctly when installed via Yarn
|
||||
14. If the installation process includes a website component, verify that any account setup or user registration flows work identically with Yarn as they do with npm or pnpm. If website actions are required, document the steps and ensure they are tested for parity. If not, confirm and document that no website or account setup is needed.
|
||||
|
||||
The implementation should maintain feature parity and identical user experience regardless of which package manager (npm, pnpm, or Yarn) is used to install Taskmaster.
|
||||
|
||||
@@ -64,6 +67,10 @@ Testing should verify complete Yarn support through the following steps:
|
||||
- Test package.json merging functionality
|
||||
- Verify MCP config setup
|
||||
|
||||
8. Website/Account Setup Testing:
|
||||
- If the installation process includes a website component, test the complete user flow including account setup, registration, or configuration steps. Ensure these work identically with Yarn as with npm. If no website or account setup is required, confirm and document this in the test results.
|
||||
- Document any website-specific steps that users need to complete during installation.
|
||||
|
||||
All tests should pass with the same results as when using npm, with identical user experience throughout the installation and usage process.
|
||||
|
||||
# Subtasks:
|
||||
@@ -87,9 +94,9 @@ Test all lifecycle scripts, post-install actions, and CLI commands using Yarn. A
|
||||
|
||||
## 4. Update Documentation for Yarn Installation and Usage [pending]
|
||||
### Dependencies: 64.3
|
||||
### Description: Revise installation and usage documentation to include clear instructions for installing and managing Taskmaster with Yarn. Clearly state that the installation process, including any website or UI shown, is identical to npm. Ensure documentation reflects the use of 'module' package type, binaries, and the init process as defined in scripts/init.js.
|
||||
### Description: Revise installation and usage documentation to include clear instructions for installing and managing Taskmaster with Yarn. Clearly state that the installation process, including any website or UI shown, is identical to npm. Ensure documentation reflects the use of 'module' package type, binaries, and the init process as defined in scripts/init.js. If the installation process includes a website component or requires account setup, document the steps users must follow. If not, explicitly state that no website or account setup is required.
|
||||
### Details:
|
||||
Add Yarn-specific installation commands, troubleshooting tips, and notes on version compatibility to the README and any relevant docs. Document that any installation website or prompt is the same as with npm. Include notes on the 'module' package type, binaries, and the directory/template setup performed by scripts/init.js.
|
||||
Add Yarn-specific installation commands, troubleshooting tips, and notes on version compatibility to the README and any relevant docs. Document that any installation website or prompt is the same as with npm. Include notes on the 'module' package type, binaries, and the directory/template setup performed by scripts/init.js. If website or account setup is required during installation, provide clear instructions; otherwise, confirm and document that no such steps are needed.
|
||||
|
||||
## 5. Implement and Test Package Manager Detection Logic [pending]
|
||||
### Dependencies: 64.4
|
||||
@@ -99,9 +106,9 @@ Modify detection logic to recognize Yarn (classic and berry), handle lockfile ge
|
||||
|
||||
## 6. Verify Installation UI/Website Consistency [pending]
|
||||
### Dependencies: 64.3
|
||||
### Description: Ensure any installation UIs, websites, or interactive prompts—including any website or prompt shown during install—appear and function identically when installing with Yarn compared to npm. Confirm that the experience is consistent for the 'module' package type and the init process.
|
||||
### Description: Ensure any installation UIs, websites, or interactive prompts—including any website or prompt shown during install—appear and function identically when installing with Yarn compared to npm. Confirm that the experience is consistent for the 'module' package type and the init process. If the installation process includes a website or account setup, verify that all required website actions (e.g., account creation, login) are consistent and documented. If not, confirm and document that no website or account setup is needed.
|
||||
### Details:
|
||||
Identify all user-facing elements during the installation process, including any website or prompt shown during install, and verify they are consistent across package managers. If a website is shown during installation, ensure it appears the same regardless of package manager used. Validate that any prompts or UIs triggered by scripts/init.js are identical.
|
||||
Identify all user-facing elements during the installation process, including any website or prompt shown during install, and verify they are consistent across package managers. If a website is shown during installation or account setup is required, ensure it appears and functions the same regardless of package manager used, and document the steps. If not, confirm and document that no website or account setup is needed. Validate that any prompts or UIs triggered by scripts/init.js are identical.
|
||||
|
||||
## 7. Test init.js Script with Yarn [pending]
|
||||
### Dependencies: 64.3
|
||||
@@ -115,3 +122,81 @@ Test the init command to ensure it properly creates .cursor/rules, scripts, and
|
||||
### Details:
|
||||
Check that the binaries defined in package.json are correctly linked in node_modules/.bin when installed with Yarn, and that they can be executed without errors. Validate that binaries work for ESM ('module') projects and are accessible after both global and local installs.
|
||||
|
||||
## 9. Test Website Account Setup with Yarn [pending]
|
||||
### Dependencies: 64.6
|
||||
### Description: If the installation process includes a website component, verify that account setup, registration, or any other user-specific configurations work correctly when Taskmaster is installed via Yarn. If no website or account setup is required, confirm and document this explicitly.
|
||||
### Details:
|
||||
Test the complete user flow for any website component that appears during installation, including account creation, login, and configuration steps. Ensure that all website interactions work identically with Yarn as they do with npm or pnpm. Document any website-specific steps that users need to complete during the installation process. If no website or account setup is required, confirm and document this.
|
||||
|
||||
<info added on 2025-04-25T08:45:48.709Z>
|
||||
Since the request is vague, I'll provide helpful implementation details for testing website account setup with Yarn:
|
||||
|
||||
For thorough testing, create a test matrix covering different browsers (Chrome, Firefox, Safari) and operating systems (Windows, macOS, Linux). Document specific Yarn-related environment variables that might affect website connectivity. Use tools like Playwright or Cypress to automate the account setup flow testing, capturing screenshots at each step for documentation. Implement network throttling tests to verify behavior under poor connectivity. Create a checklist of all UI elements that should be verified during the account setup process, including form validation, error messages, and success states. If no website component exists, explicitly document this in the project README and installation guides to prevent user confusion.
|
||||
</info added on 2025-04-25T08:45:48.709Z>
|
||||
|
||||
<info added on 2025-04-25T08:46:08.651Z>
|
||||
- For environments where the website component requires integration with external authentication providers (such as OAuth, SSO, or LDAP), ensure that these flows are tested specifically when Taskmaster is installed via Yarn. Validate that redirect URIs, token exchanges, and session persistence behave as expected across all supported browsers.
|
||||
|
||||
- If the website setup involves configuring application pools or web server settings (e.g., with IIS), document any Yarn-specific considerations, such as environment variable propagation or file permission differences, that could affect the web service's availability or configuration[2].
|
||||
|
||||
- When automating tests, include validation for accessibility compliance (e.g., using axe-core or Lighthouse) during the account setup process to ensure the UI is usable for all users.
|
||||
|
||||
- Capture and log all HTTP requests and responses during the account setup flow to help diagnose any discrepancies between Yarn and other package managers. This can be achieved by enabling network logging in Playwright or Cypress test runs.
|
||||
|
||||
- If the website component supports batch operations or automated uploads (such as uploading user data or configuration files), verify that these automation features function identically after installation with Yarn[3].
|
||||
|
||||
- For documentation, provide annotated screenshots or screen recordings of the account setup process, highlighting any Yarn-specific prompts, warnings, or differences encountered.
|
||||
|
||||
- If the website component is not required, add a badge or prominent note in the README and installation guides stating "No website or account setup required," and reference the test results confirming this.
|
||||
</info added on 2025-04-25T08:46:08.651Z>
|
||||
|
||||
<info added on 2025-04-25T17:04:12.550Z>
|
||||
For clarity, this task does not involve setting up a Yarn account. Yarn itself is just a package manager that doesn't require any account creation. The task is about testing whether any website component that is part of Taskmaster (if one exists) works correctly when Taskmaster is installed using Yarn as the package manager.
|
||||
|
||||
To be specific:
|
||||
- You don't need to create a Yarn account
|
||||
- Yarn is simply the tool used to install Taskmaster (`yarn add taskmaster` instead of `npm install taskmaster`)
|
||||
- The testing focuses on whether any web interfaces or account setup processes that are part of Taskmaster itself function correctly when the installation was done via Yarn
|
||||
- If Taskmaster includes a web dashboard or requires users to create accounts within the Taskmaster system, those features should be tested
|
||||
|
||||
If you're uncertain whether Taskmaster includes a website component at all, the first step would be to check the project documentation or perform an initial installation to determine if any web interface exists.
|
||||
</info added on 2025-04-25T17:04:12.550Z>
|
||||
|
||||
<info added on 2025-04-25T17:19:03.256Z>
|
||||
When testing website account setup with Yarn after the codebase refactor, pay special attention to:
|
||||
|
||||
- Verify that any environment-specific configuration files (like `.env` or config JSON files) are properly loaded when the application is installed via Yarn
|
||||
- Test the session management implementation to ensure user sessions persist correctly across page refreshes and browser restarts
|
||||
- Check that any database migrations or schema updates required for account setup execute properly when installed via Yarn
|
||||
- Validate that client-side form validation logic works consistently with server-side validation
|
||||
- Ensure that any WebSocket connections for real-time features initialize correctly after the refactor
|
||||
- Test account deletion and data export functionality to verify GDPR compliance remains intact
|
||||
- Document any changes to the authentication flow that resulted from the refactor and confirm they work identically with Yarn installation
|
||||
</info added on 2025-04-25T17:19:03.256Z>
|
||||
|
||||
<info added on 2025-04-25T17:22:05.951Z>
|
||||
When testing website account setup with Yarn after the logging fix, implement these additional verification steps:
|
||||
|
||||
1. Verify that all account-related actions are properly logged with the correct log levels (debug, info, warn, error) according to the updated logging framework
|
||||
2. Test the error handling paths specifically - force authentication failures and verify the logs contain sufficient diagnostic information
|
||||
3. Check that sensitive user information is properly redacted in logs according to privacy requirements
|
||||
4. Confirm that log rotation and persistence work correctly when high volumes of authentication attempts occur
|
||||
5. Validate that any custom logging middleware correctly captures HTTP request/response data for account operations
|
||||
6. Test that log aggregation tools (if used) can properly parse and display the account setup logs in their expected format
|
||||
7. Verify that performance metrics for account setup flows are correctly captured in logs for monitoring purposes
|
||||
8. Document any Yarn-specific environment variables that affect the logging configuration for the website component
|
||||
</info added on 2025-04-25T17:22:05.951Z>
|
||||
|
||||
<info added on 2025-04-25T17:22:46.293Z>
|
||||
When testing website account setup with Yarn, consider implementing a positive user experience validation:
|
||||
|
||||
1. Measure and document time-to-completion for the account setup process to ensure it meets usability standards
|
||||
2. Create a satisfaction survey for test users to rate the account setup experience on a 1-5 scale
|
||||
3. Implement A/B testing for different account setup flows to identify the most user-friendly approach
|
||||
4. Add delightful micro-interactions or success animations that make the setup process feel rewarding
|
||||
5. Test the "welcome" or "onboarding" experience that follows successful account creation
|
||||
6. Ensure helpful tooltips and contextual help are displayed at appropriate moments during setup
|
||||
7. Verify that error messages are friendly, clear, and provide actionable guidance rather than technical jargon
|
||||
8. Test the account recovery flow to ensure users have a smooth experience if they forget credentials
|
||||
</info added on 2025-04-25T17:22:46.293Z>
|
||||
|
||||
|
||||
File diff suppressed because one or more lines are too long
3602
tasks/tasks.json.bak
3602
tasks/tasks.json.bak
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user