Ralph Khreish 738ec51c04
feat: Migrate Task Master to generateObject for structured AI responses (#1262)
Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>
Co-authored-by: Ben Vargas <ben@example.com>
2025-10-02 16:23:34 +02:00

343 lines
10 KiB
JavaScript

import path from 'path';
import chalk from 'chalk';
import boxen from 'boxen';
import Table from 'cli-table3';
import {
log as consoleLog,
readJSON,
writeJSON,
truncate,
isSilentMode
} from '../utils.js';
import {
getStatusWithColor,
startLoadingIndicator,
stopLoadingIndicator,
displayAiUsageSummary
} from '../ui.js';
import { getDebugFlag, hasCodebaseAnalysis } from '../config-manager.js';
import { getPromptManager } from '../prompt-manager.js';
import generateTaskFiles from './generate-task-files.js';
import { generateObjectService } from '../ai-services-unified.js';
import { COMMAND_SCHEMAS } from '../../../src/schemas/registry.js';
import { getModelConfiguration } from './models.js';
import { ContextGatherer } from '../utils/contextGatherer.js';
import { FuzzyTaskSearch } from '../utils/fuzzyTaskSearch.js';
import { flattenTasksWithSubtasks, findProjectRoot } from '../utils.js';
/**
* Update tasks based on new context using the unified AI service.
* @param {string} tasksPath - Path to the tasks.json file
* @param {number} fromId - Task ID to start updating from
* @param {string} prompt - Prompt with new context
* @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} [context.tag] - Tag for the task
* @param {string} [outputFormat='text'] - Output format ('text' or 'json').
*/
async function updateTasks(
tasksPath,
fromId,
prompt,
useResearch = false,
context = {},
outputFormat = 'text' // Default to text for CLI
) {
const { session, mcpLog, projectRoot: providedProjectRoot, tag } = context;
// Use mcpLog if available, otherwise use the imported consoleLog function
const logFn = mcpLog || consoleLog;
// Flag to easily check which logger type we have
const isMCP = !!mcpLog;
if (isMCP)
logFn.info(`updateTasks called with context: session=${!!session}`);
else logFn('info', `updateTasks called`); // CLI log
try {
if (isMCP) logFn.info(`Updating tasks from ID ${fromId}`);
else
logFn(
'info',
`Updating tasks from ID ${fromId} with prompt: "${prompt}"`
);
// Determine project root
const projectRoot = providedProjectRoot || findProjectRoot();
if (!projectRoot) {
throw new Error('Could not determine project root directory');
}
// --- Task Loading/Filtering (Updated to pass projectRoot and tag) ---
const data = readJSON(tasksPath, projectRoot, tag);
if (!data || !data.tasks)
throw new Error(`No valid tasks found in ${tasksPath}`);
const tasksToUpdate = data.tasks.filter(
(task) => task.id >= fromId && task.status !== 'done'
);
if (tasksToUpdate.length === 0) {
if (isMCP)
logFn.info(`No tasks to update (ID >= ${fromId} and not 'done').`);
else
logFn('info', `No tasks to update (ID >= ${fromId} and not 'done').`);
if (outputFormat === 'text') console.log(/* yellow message */);
return; // Nothing to do
}
// --- End Task Loading/Filtering ---
// --- Context Gathering ---
let gatheredContext = '';
try {
const contextGatherer = new ContextGatherer(projectRoot, tag);
const allTasksFlat = flattenTasksWithSubtasks(data.tasks);
const fuzzySearch = new FuzzyTaskSearch(allTasksFlat, 'update');
const searchResults = fuzzySearch.findRelevantTasks(prompt, {
maxResults: 5,
includeSelf: true
});
const relevantTaskIds = fuzzySearch.getTaskIds(searchResults);
const tasksToUpdateIds = tasksToUpdate.map((t) => t.id.toString());
const finalTaskIds = [
...new Set([...tasksToUpdateIds, ...relevantTaskIds])
];
if (finalTaskIds.length > 0) {
const contextResult = await contextGatherer.gather({
tasks: finalTaskIds,
format: 'research'
});
gatheredContext = contextResult.context || '';
}
} catch (contextError) {
logFn(
'warn',
`Could not gather additional context: ${contextError.message}`
);
}
// --- End Context Gathering ---
// --- Display Tasks to Update (CLI Only - Unchanged) ---
if (outputFormat === 'text') {
// Show the tasks that will be updated
const table = new Table({
head: [
chalk.cyan.bold('ID'),
chalk.cyan.bold('Title'),
chalk.cyan.bold('Status')
],
colWidths: [5, 70, 20]
});
tasksToUpdate.forEach((task) => {
table.push([
task.id,
truncate(task.title, 57),
getStatusWithColor(task.status)
]);
});
console.log(
boxen(chalk.white.bold(`Updating ${tasksToUpdate.length} tasks`), {
padding: 1,
borderColor: 'blue',
borderStyle: 'round',
margin: { top: 1, bottom: 0 }
})
);
console.log(table.toString());
// Display a message about how completed subtasks are handled
console.log(
boxen(
chalk.cyan.bold('How Completed Subtasks Are Handled:') +
'\n\n' +
chalk.white(
'• Subtasks marked as "done" or "completed" will be preserved\n'
) +
chalk.white(
'• New subtasks will build upon what has already been completed\n'
) +
chalk.white(
'• If completed work needs revision, a new subtask will be created instead of modifying done items\n'
) +
chalk.white(
'• This approach maintains a clear record of completed work and new requirements'
),
{
padding: 1,
borderColor: 'blue',
borderStyle: 'round',
margin: { top: 1, bottom: 1 }
}
)
);
}
// --- End Display Tasks ---
// --- Build Prompts (Using PromptManager) ---
// Load prompts using PromptManager
const promptManager = getPromptManager();
const { systemPrompt, userPrompt } = await promptManager.loadPrompt(
'update-tasks',
{
tasks: tasksToUpdate,
updatePrompt: prompt,
useResearch,
projectContext: gatheredContext,
hasCodebaseAnalysis: hasCodebaseAnalysis(
useResearch,
projectRoot,
session
),
projectRoot: projectRoot
}
);
// --- End Build Prompts ---
// --- AI Call ---
let loadingIndicator = null;
let aiServiceResponse = null;
if (!isMCP && outputFormat === 'text') {
loadingIndicator = startLoadingIndicator('Updating tasks with AI...\n');
}
try {
// Determine role based on research flag
const serviceRole = useResearch ? 'research' : 'main';
// Call the unified AI service with generateObject
aiServiceResponse = await generateObjectService({
role: serviceRole,
session: session,
projectRoot: projectRoot,
systemPrompt: systemPrompt,
prompt: userPrompt,
schema: COMMAND_SCHEMAS['update-tasks'],
objectName: 'tasks',
commandName: 'update-tasks',
outputType: isMCP ? 'mcp' : 'cli'
});
if (loadingIndicator)
stopLoadingIndicator(loadingIndicator, 'AI update complete.');
// With generateObject, we get structured data directly
const parsedUpdatedTasks = aiServiceResponse.mainResult.tasks;
// --- Update Tasks Data (Updated writeJSON call) ---
if (!Array.isArray(parsedUpdatedTasks)) {
// Should be caught by parser, but extra check
throw new Error(
'Parsed AI response for updated tasks was not an array.'
);
}
if (isMCP)
logFn.info(
`Received ${parsedUpdatedTasks.length} updated tasks from AI.`
);
else
logFn(
'info',
`Received ${parsedUpdatedTasks.length} updated tasks from AI.`
);
// Create a map for efficient lookup
const updatedTasksMap = new Map(
parsedUpdatedTasks.map((task) => [task.id, task])
);
let actualUpdateCount = 0;
data.tasks.forEach((task, index) => {
if (updatedTasksMap.has(task.id)) {
// Only update if the task was part of the set sent to AI
const updatedTask = updatedTasksMap.get(task.id);
// Merge the updated task with the existing one to preserve fields like subtasks
data.tasks[index] = {
...task, // Keep all existing fields
...updatedTask, // Override with updated fields
// Ensure subtasks field is preserved if not provided by AI
subtasks:
updatedTask.subtasks !== undefined
? updatedTask.subtasks
: task.subtasks
};
actualUpdateCount++;
}
});
if (isMCP)
logFn.info(
`Applied updates to ${actualUpdateCount} tasks in the dataset.`
);
else
logFn(
'info',
`Applied updates to ${actualUpdateCount} tasks in the dataset.`
);
// Fix: Pass projectRoot and currentTag to writeJSON
writeJSON(tasksPath, data, projectRoot, tag);
if (isMCP)
logFn.info(
`Successfully updated ${actualUpdateCount} tasks in ${tasksPath}`
);
else
logFn(
'success',
`Successfully updated ${actualUpdateCount} tasks in ${tasksPath}`
);
// await generateTaskFiles(tasksPath, path.dirname(tasksPath));
if (outputFormat === 'text' && aiServiceResponse.telemetryData) {
displayAiUsageSummary(aiServiceResponse.telemetryData, 'cli');
}
return {
success: true,
updatedTasks: parsedUpdatedTasks,
telemetryData: aiServiceResponse.telemetryData,
tagInfo: aiServiceResponse.tagInfo
};
} catch (error) {
if (loadingIndicator) stopLoadingIndicator(loadingIndicator);
if (isMCP) logFn.error(`Error during AI service call: ${error.message}`);
else logFn('error', `Error during AI service call: ${error.message}`);
if (error.message.includes('API key')) {
if (isMCP)
logFn.error(
'Please ensure API keys are configured correctly in .env or mcp.json.'
);
else
logFn(
'error',
'Please ensure API keys are configured correctly in .env or mcp.json.'
);
}
throw error;
} finally {
if (loadingIndicator) stopLoadingIndicator(loadingIndicator);
}
} catch (error) {
// --- General Error Handling (Unchanged) ---
if (isMCP) logFn.error(`Error updating tasks: ${error.message}`);
else logFn('error', `Error updating tasks: ${error.message}`);
if (outputFormat === 'text') {
console.error(chalk.red(`Error: ${error.message}`));
if (getDebugFlag(session)) {
console.error(error);
}
process.exit(1);
} else {
throw error; // Re-throw for MCP/programmatic callers
}
// --- End General Error Handling ---
}
}
export default updateTasks;