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Adjusts claude calls using message to use stream instead.

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This commit is contained in:
Eyal Toledano
2025-03-24 17:22:48 -04:00
parent 9a8bdcf8ea
commit 193d07d580
3 changed files with 169 additions and 63 deletions
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155
scripts/modules/ai-services.js
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@@ -123,9 +123,11 @@ Important: Your response must be valid JSON only, with no additional explanation
async function handleStreamingRequest(prdContent, prdPath, numTasks, maxTokens, systemPrompt) {
const loadingIndicator = startLoadingIndicator('Generating tasks from PRD...');
let responseText = '';
let streamingInterval = null;
try {
const message = await anthropic.messages.create({
// Use streaming for handling large responses
const stream = await anthropic.messages.create({
model: CONFIG.model,
max_tokens: maxTokens,
temperature: CONFIG.temperature,
@@ -135,14 +137,34 @@ async function handleStreamingRequest(prdContent, prdPath, numTasks, maxTokens,
role: 'user',
content: `Here's the Product Requirements Document (PRD) to break down into ${numTasks} tasks:\n\n${prdContent}`
}
]
],
stream: true
});
responseText = message.content[0].text;
// Update loading indicator to show streaming progress
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);
// Process the stream
for await (const chunk of stream) {
if (chunk.type === 'content_block_delta' && chunk.delta.text) {
responseText += chunk.delta.text;
}
}
if (streamingInterval) clearInterval(streamingInterval);
stopLoadingIndicator(loadingIndicator);
log('info', "Completed streaming response from Claude API!");
return processClaudeResponse(responseText, numTasks, 0, prdContent, prdPath);
} catch (error) {
if (streamingInterval) clearInterval(streamingInterval);
stopLoadingIndicator(loadingIndicator);
throw error;
}
@@ -224,6 +246,8 @@ async function generateSubtasks(task, numSubtasks, nextSubtaskId, additionalCont
log('info', `Generating ${numSubtasks} subtasks for task ${task.id}: ${task.title}`);
const loadingIndicator = startLoadingIndicator(`Generating subtasks for task ${task.id}...`);
let streamingInterval = null;
let responseText = '';
const systemPrompt = `You are an AI assistant helping with task breakdown for software development.
You need to break down a high-level task into ${numSubtasks} specific subtasks that can be implemented one by one.
@@ -269,22 +293,49 @@ Return exactly ${numSubtasks} subtasks with the following JSON structure:
Note on dependencies: Subtasks can depend on other subtasks with lower IDs. Use an empty array if there are no dependencies.`;
const message = await anthropic.messages.create({
model: CONFIG.model,
max_tokens: CONFIG.maxTokens,
temperature: CONFIG.temperature,
system: systemPrompt,
messages: [
{
role: 'user',
content: userPrompt
try {
// Update loading indicator to show streaming progress
let dotCount = 0;
const readline = await import('readline');
streamingInterval = setInterval(() => {
readline.cursorTo(process.stdout, 0);
process.stdout.write(`Generating subtasks for task ${task.id}${'.'.repeat(dotCount)}`);
dotCount = (dotCount + 1) % 4;
}, 500);
// Use streaming API call
const stream = await anthropic.messages.create({
model: CONFIG.model,
max_tokens: CONFIG.maxTokens,
temperature: CONFIG.temperature,
system: systemPrompt,
messages: [
{
role: 'user',
content: userPrompt
}
],
stream: true
});
// Process the stream
for await (const chunk of stream) {
if (chunk.type === 'content_block_delta' && chunk.delta.text) {
responseText += chunk.delta.text;
}
]
});
stopLoadingIndicator(loadingIndicator);
return parseSubtasksFromText(message.content[0].text, nextSubtaskId, numSubtasks, task.id);
}
if (streamingInterval) clearInterval(streamingInterval);
stopLoadingIndicator(loadingIndicator);
log('info', `Completed generating subtasks for task ${task.id}`);
return parseSubtasksFromText(responseText, nextSubtaskId, numSubtasks, task.id);
} catch (error) {
if (streamingInterval) clearInterval(streamingInterval);
stopLoadingIndicator(loadingIndicator);
throw error;
}
} catch (error) {
log('error', `Error generating subtasks: ${error.message}`);
throw error;
@@ -339,6 +390,8 @@ ${additionalContext || "No additional context provided."}
// Now generate subtasks with Claude
const loadingIndicator = startLoadingIndicator(`Generating research-backed subtasks for task ${task.id}...`);
let streamingInterval = null;
let responseText = '';
const systemPrompt = `You are an AI assistant helping with task breakdown for software development.
You need to break down a high-level task into ${numSubtasks} specific subtasks that can be implemented one by one.
@@ -350,7 +403,7 @@ Subtasks should:
1. Be specific and actionable implementation steps
2. Follow a logical sequence
3. Each handle a distinct part of the parent task
4. Include clear guidance on implementation approach, referencing the research where relevant
4. Include clear guidance on implementation approach
5. Have appropriate dependency chains between subtasks
6. Collectively cover all aspects of the parent task
@@ -362,8 +415,7 @@ For each subtask, provide:
Each subtask should be implementable in a focused coding session.`;
const userPrompt = `Please break down this task into ${numSubtasks} specific, actionable subtasks,
using the research findings to inform your breakdown:
const userPrompt = `Please break down this task into ${numSubtasks} specific, well-researched, actionable subtasks:
Task ID: ${task.id}
Title: ${task.title}
@@ -377,31 +429,58 @@ Return exactly ${numSubtasks} subtasks with the following JSON structure:
{
"id": ${nextSubtaskId},
"title": "First subtask title",
"description": "Detailed description",
"description": "Detailed description incorporating research",
"dependencies": [],
"details": "Implementation details"
"details": "Implementation details with best practices"
},
...more subtasks...
]
Note on dependencies: Subtasks can depend on other subtasks with lower IDs. Use an empty array if there are no dependencies.`;
const message = await anthropic.messages.create({
model: CONFIG.model,
max_tokens: CONFIG.maxTokens,
temperature: CONFIG.temperature,
system: systemPrompt,
messages: [
{
role: 'user',
content: userPrompt
try {
// Update loading indicator to show streaming progress
let dotCount = 0;
const readline = await import('readline');
streamingInterval = setInterval(() => {
readline.cursorTo(process.stdout, 0);
process.stdout.write(`Generating research-backed subtasks for task ${task.id}${'.'.repeat(dotCount)}`);
dotCount = (dotCount + 1) % 4;
}, 500);
// Use streaming API call
const stream = await anthropic.messages.create({
model: CONFIG.model,
max_tokens: CONFIG.maxTokens,
temperature: CONFIG.temperature,
system: systemPrompt,
messages: [
{
role: 'user',
content: userPrompt
}
],
stream: true
});
// Process the stream
for await (const chunk of stream) {
if (chunk.type === 'content_block_delta' && chunk.delta.text) {
responseText += chunk.delta.text;
}
]
});
stopLoadingIndicator(loadingIndicator);
return parseSubtasksFromText(message.content[0].text, nextSubtaskId, numSubtasks, task.id);
}
if (streamingInterval) clearInterval(streamingInterval);
stopLoadingIndicator(loadingIndicator);
log('info', `Completed generating research-backed subtasks for task ${task.id}`);
return parseSubtasksFromText(responseText, nextSubtaskId, numSubtasks, task.id);
} catch (error) {
if (streamingInterval) clearInterval(streamingInterval);
stopLoadingIndicator(loadingIndicator);
throw error;
}
} catch (error) {
log('error', `Error generating research-backed subtasks: ${error.message}`);
throw error;