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feat(telemetry): Integrate AI usage telemetry into update-tasks

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This commit applies the standard telemetry pattern to the  command and its corresponding MCP tool.

Key Changes:

1.  **Core Logic ():**
    -   The call to  now includes  and .
    -   The full response  is captured.
    -    (the AI-generated text) is used for parsing the updated task JSON.
    -   If running in CLI mode (),  is called with the .
    -   The function now returns .

2.  **Direct Function ():**
    -   The call to the core  function now passes the necessary context for telemetry (, ).
    -   The successful response object now correctly extracts  and includes it in the  field returned to the MCP client.
This commit is contained in:
Eyal Toledano
2025-05-08 18:37:41 -04:00
parent 21c3cb8cda
commit c955431753
7 changed files with 255 additions and 169 deletions
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193
scripts/modules/task-manager/update-tasks.js
View File

@@ -15,7 +15,8 @@ import {
import {
getStatusWithColor,
startLoadingIndicator,
stopLoadingIndicator
stopLoadingIndicator,
displayAiUsageSummary
} from '../ui.js';
import { getDebugFlag } from '../config-manager.js';
@@ -350,26 +351,100 @@ The changes described in the prompt should be applied to ALL tasks in the list.`
const userPrompt = `Here are the tasks to update:\n${taskDataString}\n\nPlease update these tasks based on the following new context:\n${prompt}\n\nIMPORTANT: In the tasks 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 tasks as a valid JSON array.`;
// --- End Build Prompts ---
// --- AI Call ---
let loadingIndicator = null;
if (outputFormat === 'text') {
loadingIndicator = startLoadingIndicator('Updating tasks...\n');
let aiServiceResponse = null;
if (!isMCP && outputFormat === 'text') {
loadingIndicator = startLoadingIndicator('Updating tasks with AI...\n');
}
let responseText = '';
let updatedTasks;
try {
// --- Call Unified AI Service ---
const role = useResearch ? 'research' : 'main';
// Determine role based on research flag
const serviceRole = useResearch ? 'research' : 'main';
responseText = await generateTextService({
prompt: userPrompt,
// Call the unified AI service
aiServiceResponse = await generateTextService({
role: serviceRole,
session: session,
projectRoot: projectRoot,
systemPrompt: systemPrompt,
role,
session,
projectRoot
prompt: userPrompt,
commandName: 'update-tasks',
outputType: isMCP ? 'mcp' : 'cli'
});
// --- End AI Service Call ---
if (loadingIndicator)
stopLoadingIndicator(loadingIndicator, 'AI update complete.');
// Use the mainResult (text) for parsing
const parsedUpdatedTasks = parseUpdatedTasksFromText(
aiServiceResponse.mainResult,
tasksToUpdate.length,
logFn,
isMCP
);
// --- Update Tasks Data (Unchanged) ---
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
data.tasks[index] = updatedTasksMap.get(task.id);
actualUpdateCount++;
}
});
if (isMCP)
logFn.info(
`Applied updates to ${actualUpdateCount} tasks in the dataset.`
);
else
logFn(
'info',
`Applied updates to ${actualUpdateCount} tasks in the dataset.`
);
writeJSON(tasksPath, data);
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
};
} catch (error) {
if (loadingIndicator) stopLoadingIndicator(loadingIndicator);
if (isMCP) logFn.error(`Error during AI service call: ${error.message}`);
@@ -385,98 +460,10 @@ The changes described in the prompt should be applied to ALL tasks in the list.`
'Please ensure API keys are configured correctly in .env or mcp.json.'
);
}
throw error; // Re-throw error
throw error;
} finally {
if (loadingIndicator) stopLoadingIndicator(loadingIndicator);
}
// --- Parse and Validate Response ---
try {
updatedTasks = parseUpdatedTasksFromText(
responseText,
tasksToUpdate.length,
logFn,
isMCP
);
} catch (parseError) {
if (isMCP)
logFn.error(
`Failed to parse updated tasks from AI response: ${parseError.message}`
);
else
logFn(
'error',
`Failed to parse updated tasks from AI response: ${parseError.message}`
);
if (getDebugFlag(session)) {
if (isMCP) logFn.error(`Raw AI Response:\n${responseText}`);
else logFn('error', `Raw AI Response:\n${responseText}`);
}
throw new Error(
`Failed to parse valid updated tasks from AI response: ${parseError.message}`
);
}
// --- End Parse/Validate ---
// --- Update Tasks Data (Unchanged) ---
if (!Array.isArray(updatedTasks)) {
// 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 ${updatedTasks.length} updated tasks from AI.`);
else
logFn('info', `Received ${updatedTasks.length} updated tasks from AI.`);
// Create a map for efficient lookup
const updatedTasksMap = new Map(
updatedTasks.map((task) => [task.id, task])
);
// Iterate through the original data and update based on the map
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
data.tasks[index] = updatedTasksMap.get(task.id);
actualUpdateCount++;
}
});
if (isMCP)
logFn.info(
`Applied updates to ${actualUpdateCount} tasks in the dataset.`
);
else
logFn(
'info',
`Applied updates to ${actualUpdateCount} tasks in the dataset.`
);
// --- End Update Tasks Data ---
// --- Write File and Generate (Unchanged) ---
writeJSON(tasksPath, data);
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));
// --- End Write File ---
// --- Final CLI Output (Unchanged) ---
if (outputFormat === 'text') {
console.log(
boxen(chalk.green(`Successfully updated ${actualUpdateCount} tasks`), {
padding: 1,
borderColor: 'green',
borderStyle: 'round'
})
);
}
// --- End Final CLI Output ---
} catch (error) {
// --- General Error Handling (Unchanged) ---
if (isMCP) logFn.error(`Error updating tasks: ${error.message}`);