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refactor(tasks): Align add-task with unified AI service and add research flag

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This commit is contained in:
Eyal Toledano
2025-04-24 01:59:41 -04:00
parent 90c6c1e587
commit be3f68e777
10 changed files with 351 additions and 404 deletions
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189
mcp-server/src/core/direct-functions/add-task.js
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@@ -8,15 +8,6 @@ import {
enableSilentMode,
disableSilentMode
} from '../../../../scripts/modules/utils.js';
import {
getAnthropicClientForMCP,
getModelConfig
} from '../utils/ai-client-utils.js';
import {
_buildAddTaskPrompt,
parseTaskJsonResponse,
_handleAnthropicStream
} from '../../../../scripts/modules/ai-services.js';
/**
* Direct function wrapper for adding a new task with error handling.
@@ -29,16 +20,26 @@ import {
* @param {string} [args.testStrategy] - Test strategy (for manual task creation)
* @param {string} [args.dependencies] - Comma-separated list of task IDs this task depends on
* @param {string} [args.priority='medium'] - Task priority (high, medium, low)
* @param {string} [args.file='tasks/tasks.json'] - Path to the tasks file
* @param {string} [args.projectRoot] - Project root directory
* @param {string} [args.tasksJsonPath] - Path to the tasks.json file (resolved by tool)
* @param {boolean} [args.research=false] - Whether to use research capabilities for task creation
* @param {Object} log - Logger object
* @param {Object} context - Additional context (reportProgress, session)
* @param {Object} context - Additional context (session)
* @returns {Promise<Object>} - Result object { success: boolean, data?: any, error?: { code: string, message: string } }
*/
export async function addTaskDirect(args, log, context = {}) {
// Destructure expected args
// Destructure expected args (including research)
const { tasksJsonPath, prompt, dependencies, priority, research } = args;
const { session } = context; // Destructure session from context
// Define the logger wrapper to ensure compatibility with core report function
const logWrapper = {
info: (message, ...args) => log.info(message, ...args),
warn: (message, ...args) => log.warn(message, ...args),
error: (message, ...args) => log.error(message, ...args),
debug: (message, ...args) => log.debug && log.debug(message, ...args), // Handle optional debug
success: (message, ...args) => log.info(message, ...args) // Map success to info if needed
};
try {
// Enable silent mode to prevent console logs from interfering with JSON response
enableSilentMode();
@@ -79,20 +80,17 @@ export async function addTaskDirect(args, log, context = {}) {
}
// Extract and prepare parameters
const taskPrompt = prompt;
const taskDependencies = Array.isArray(dependencies)
? dependencies
: dependencies
? dependencies // Already an array if passed directly
: dependencies // Check if dependencies exist and are a string
? String(dependencies)
.split(',')
.map((id) => parseInt(id.trim(), 10))
: [];
const taskPriority = priority || 'medium';
// Extract context parameters for advanced functionality
const { session } = context;
.map((id) => parseInt(id.trim(), 10)) // Split, trim, and parse
: []; // Default to empty array if null/undefined
const taskPriority = priority || 'medium'; // Default priority
let manualTaskData = null;
let newTaskId;
if (isManualCreation) {
// Create manual task data object
@@ -108,150 +106,61 @@ export async function addTaskDirect(args, log, context = {}) {
);
// Call the addTask function with manual task data
const newTaskId = await addTask(
newTaskId = await addTask(
tasksPath,
null, // No prompt needed for manual creation
null, // prompt is null for manual creation
taskDependencies,
priority,
taskPriority,
{
mcpLog: log,
mcpLog: logWrapper,
session
},
'json', // Use JSON output format to prevent console output
null, // No custom environment
manualTaskData // Pass the manual task data
'json', // outputFormat
manualTaskData, // Pass the manual task data
false // research flag is false for manual creation
);
// Restore normal logging
disableSilentMode();
return {
success: true,
data: {
taskId: newTaskId,
message: `Successfully added new task #${newTaskId}`
}
};
} else {
// AI-driven task creation
log.info(
`Adding new task with prompt: "${prompt}", dependencies: [${taskDependencies.join(', ')}], priority: ${priority}`
`Adding new task with prompt: "${prompt}", dependencies: [${taskDependencies.join(', ')}], priority: ${taskPriority}, research: ${research}`
);
// Initialize AI client with session environment
let localAnthropic;
try {
localAnthropic = getAnthropicClientForMCP(session, log);
} catch (error) {
log.error(`Failed to initialize Anthropic client: ${error.message}`);
disableSilentMode();
return {
success: false,
error: {
code: 'AI_CLIENT_ERROR',
message: `Cannot initialize AI client: ${error.message}`
}
};
}
// Get model configuration from session
const modelConfig = getModelConfig(session);
// Read existing tasks to provide context
let tasksData;
try {
const fs = await import('fs');
tasksData = JSON.parse(fs.readFileSync(tasksPath, 'utf8'));
} catch (error) {
log.warn(`Could not read existing tasks for context: ${error.message}`);
tasksData = { tasks: [] };
}
// Build prompts for AI
const { systemPrompt, userPrompt } = _buildAddTaskPrompt(
prompt,
tasksData.tasks
);
// Make the AI call using the streaming helper
let responseText;
try {
responseText = await _handleAnthropicStream(
localAnthropic,
{
model: modelConfig.model,
max_tokens: modelConfig.maxTokens,
temperature: modelConfig.temperature,
messages: [{ role: 'user', content: userPrompt }],
system: systemPrompt
},
{
mcpLog: log
}
);
} catch (error) {
log.error(`AI processing failed: ${error.message}`);
disableSilentMode();
return {
success: false,
error: {
code: 'AI_PROCESSING_ERROR',
message: `Failed to generate task with AI: ${error.message}`
}
};
}
// Parse the AI response
let taskDataFromAI;
try {
taskDataFromAI = parseTaskJsonResponse(responseText);
} catch (error) {
log.error(`Failed to parse AI response: ${error.message}`);
disableSilentMode();
return {
success: false,
error: {
code: 'RESPONSE_PARSING_ERROR',
message: `Failed to parse AI response: ${error.message}`
}
};
}
// Call the addTask function with 'json' outputFormat to prevent console output when called via MCP
const newTaskId = await addTask(
// Call the addTask function, passing the research flag
newTaskId = await addTask(
tasksPath,
prompt,
prompt, // Use the prompt for AI creation
taskDependencies,
priority,
taskPriority,
{
mcpLog: log,
mcpLog: logWrapper,
session
},
'json',
null,
taskDataFromAI // Pass the parsed AI result as the manual task data
'json', // outputFormat
null, // manualTaskData is null for AI creation
research // Pass the research flag
);
// Restore normal logging
disableSilentMode();
return {
success: true,
data: {
taskId: newTaskId,
message: `Successfully added new task #${newTaskId}`
}
};
}
// Restore normal logging
disableSilentMode();
return {
success: true,
data: {
taskId: newTaskId,
message: `Successfully added new task #${newTaskId}`
}
};
} catch (error) {
// Make sure to restore normal logging even if there's an error
disableSilentMode();
log.error(`Error in addTaskDirect: ${error.message}`);
// Add specific error code checks if needed
return {
success: false,
error: {
code: 'ADD_TASK_ERROR',
code: error.code || 'ADD_TASK_ERROR', // Use error code if available
message: error.message
}
};