feat(ask): air ask "<task>" — interactive AI task execution
New `air ask` command: - Accepts task description from CLI - Auto-initializes project if needed - MainAgent classifies → LLM generates → tools execute → results - Supports Chinese keywords (创建/写/开发/实现 etc.) - Tool call parser supports ```json and ```tool blocks - Executes tools first, then checks DONE (fixes race condition) - Strips GLM </think> reasoning tags from output Usage: air ask "创建一个C++程序打印Hello World" Tested end-to-end with glm-5.1 on new API endpoint. Files correctly created: 13/13 E2E gates pass. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
AirCoding
266
packages/cli/src/commands/ask.ts
Executable file
266
packages/cli/src/commands/ask.ts
Executable file
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/**
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* AskCommand - Direct AI task execution
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* air ask "task description" → MainAgent → LLM → tools → result
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*
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* @module packages/cli/src/commands/ask
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*/
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import { loadConfig } from '../bootstrap/loadConfig.js'
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import { createRuntime } from '../bootstrap/createRuntime.js'
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import { initCommand } from './init.js'
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import { existsSync } from 'fs'
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import { join } from 'path'
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import { ProviderManager, createAnthropicAdapter, OpenAICompatibleAdapter } from '@aircoding/llm'
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import { MainAgent } from '@aircoding/runtime'
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import type { ProviderAdapter } from '@aircoding/contracts'
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export async function askCommand(prompt: string, opts?: { model?: string; maxTurns?: number }): Promise<void> {
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if (!prompt) {
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console.log('Usage: air ask "<task description>"')
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console.log('Example: air ask "create a C++ program that prints hello world"')
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process.exit(1)
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}
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const config = loadConfig()
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const projectRoot = config.project_root || process.cwd()
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// Auto-init if not already initialized
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if (!existsSync(join(projectRoot, '.air', 'shared', 'project.json'))) {
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console.log('Project not initialized. Running air init first...\n')
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await initCommand(projectRoot)
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}
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const model = opts?.model || process.env.AIRCODING_MODEL || 'glm-5.1'
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const maxTurns = opts?.maxTurns || 10
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console.log('══════════════════════════════════════════════')
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console.log(' AirCoding v1.0.0-alpha')
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console.log(' Project:', projectRoot)
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console.log(' Model:', model)
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console.log('══════════════════════════════════════════════\n')
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// Create ProviderManager with available adapter
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const provider = createProvider(model)
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// Create runtime
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const runtime = await createRuntime(config)
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await runtime.start()
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const app = runtime.app
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// Create MainAgent with regex classifier (中文 support added)
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const agent = new MainAgent({
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session_id: 'ask-session',
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project_id: 'ask-project',
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classify_mode: 'regex',
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provider_manager: provider as any,
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classify_model: model
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})
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console.log('Task:', prompt)
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console.log('')
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// Classify intent
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const classification = await agent.handle_user_message(prompt)
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console.log(`[${classification.action}] ${agent.state}`)
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// Execute based on action
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if (classification.action === 'delegate') {
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await execute_task(prompt, provider, app.tool_registry, app.context_assembler, model, projectRoot, maxTurns)
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} else if (classification.action === 'answer') {
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console.log('\n' + (classification.response || 'No response'))
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} else {
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console.log('Direct mode not yet supported for ask. Use implementation requests.')
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}
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await runtime.shutdown()
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}
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async function execute_task(
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task: string,
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provider: any,
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toolRegistry: any,
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contextAssembler: any,
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model: string,
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projectRoot: string,
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maxTurns: number
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): Promise<void> {
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const ctx = {
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session_id: 'ask-session',
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project_id: 'ask-project',
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agent_id: 'ask-agent',
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permission_template: 'main_direct' as const,
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cwd: projectRoot
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}
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const systemPrompt = `You are an AI coding assistant. Help the user by reading files, writing code, and running commands.
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Available tools:
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- fs.read(path) — Read a file
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- fs.write(path, content) — Write/create a file
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- fs.edit(path, old_str, new_str) — Edit a file
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- fs.list(path, depth?) — List directory contents
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- fs.stat(path) — Get file info
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- shell.run(command, timeout?) — Run a shell command
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- git.status() — Show git status
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- project.scan(root) — Scan project for source files
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- cpp.detect() — Detect C++ project
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- cpp.build(target?) — Build C++ project
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- cpp.test(filter?) — Run C++ tests
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To use a tool, output EXACTLY:
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\`\`\`json
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{"tool": "fs.read", "args": {"path": "file.cpp"}}
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\`\`\`
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When you are done, output:
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DONE: <summary of what was done>`
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const messages: any[] = [
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{ role: 'system', content: systemPrompt },
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{ role: 'user', content: task }
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]
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let turn = 0
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const changedFiles: string[] = []
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while (turn < maxTurns) {
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turn++
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console.log(`─ Turn ${turn}/${maxTurns} ─`)
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// Call LLM
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const result = await provider.complete_text(messages, { model, max_tokens: 4096 })
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let text = result.content || ''
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// Strip GLM reasoning tags if present
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text = text.replace(/<\/?think>/g, '')
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// Show LLM response summary
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const preview = text.slice(0, 100).replace(/\n/g, ' ')
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console.log(` LLM: ${preview}...`)
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// Parse tool calls FIRST (before DONE check — LLM may emit both)
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const tools = parseToolCalls(text)
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if (tools.length > 0) {
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console.log(` Tools: ${tools.map(t => t.name).join(', ')}`)
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// Add assistant message
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messages.push({ role: 'assistant', content: text })
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// Execute each tool call
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for (const tool of tools) {
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try {
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const toolResult = await toolRegistry.call(
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{ call_id: `ask-${Date.now()}`, name: tool.name, arguments: tool.args },
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ctx
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)
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const output = toolResult.status === 'ok'
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? JSON.stringify(toolResult.output).slice(0, 500)
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: `Error: ${JSON.stringify(toolResult.error)}`
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console.log(` ✓ ${tool.name}: ${output.slice(0, 100)}`)
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if (tool.name === 'fs.write' || tool.name === 'fs.edit') {
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changedFiles.push(String(tool.args.path || 'unknown'))
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}
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messages.push({
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role: 'user',
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content: `Tool ${tool.name} result: ${output}`
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})
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} catch (e: any) {
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messages.push({
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role: 'user',
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content: `Tool ${tool.name} error: ${e.message}`
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})
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}
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}
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// After executing tools, check for DONE
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if (text.includes('DONE:')) {
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const summary = text.split('DONE:')[1]?.trim() || 'Task completed'
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console.log(`\n✅ ${summary}`)
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break
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}
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// Ask LLM to continue with remaining work
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messages.push({
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role: 'user',
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content: 'Tools executed successfully. If the task is complete, respond with DONE: <summary>. Otherwise continue with more tool calls.'
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})
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continue
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}
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// No tool calls — LLM is just talking
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// Check for DONE (no tools to execute)
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if (text.includes('DONE:')) {
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const summary = text.split('DONE:')[1]?.trim() || 'Task completed'
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console.log(`\n✅ ${summary}`)
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break
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}
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}
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if (turn >= maxTurns) {
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console.log(`\n⚠️ Reached max ${maxTurns} turns. Task may be incomplete.`)
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}
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if (changedFiles.length > 0) {
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console.log(`\nChanged files: ${changedFiles.join(', ')}`)
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}
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}
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function parseToolCalls(text: string): Array<{ name: string; args: Record<string, unknown> }> {
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const calls: Array<{ name: string; args: Record<string, unknown> }> = []
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// Pattern 1: ```tool or ```json code blocks
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const blockRe = /```(?:tool|json)\s*\n?([\s\S]*?)```/g
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for (const match of text.matchAll(blockRe)) {
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try {
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const parsed = JSON.parse(match[1].trim())
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if (parsed.tool) calls.push({ name: parsed.tool, args: parsed.args || {} })
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} catch { /* skip */ }
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}
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// Pattern 2: {"tool": "..."} inline JSON anywhere in text
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const jsonRe = /\{\s*"tool"\s*:\s*"([^"]+)"\s*,\s*"args"\s*:\s*(\{[^}]+\})\s*\}/g
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for (const match of text.matchAll(jsonRe)) {
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try {
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const name = match[1]
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const args = JSON.parse(match[2])
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if (!calls.some(c => c.name === name)) {
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calls.push({ name, args })
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}
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} catch { /* skip */ }
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}
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return calls
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}
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function createProvider(model: string): any {
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const apiKey = process.env.AIRCODING_API_KEY || process.env.OPENAI_API_KEY || ''
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const apiUrl = process.env.AIRCODING_API_URL || process.env.OPENAI_BASE_URL || 'https://api.openai.com/v1'
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if (!apiKey) {
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console.log('⚠️ No API key found. Set AIRCODING_API_KEY or OPENAI_API_KEY.')
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console.log(' Export: export AIRCODING_API_KEY="your-key"')
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process.exit(1)
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}
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const adapter = new OpenAICompatibleAdapter({
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base_url: apiUrl,
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api_key: apiKey,
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model
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})
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// Wrap adapter in a simple provider interface
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return {
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adapters: new Map([['openai-compatible', adapter]]),
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current_adapter: adapter,
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current_model: model,
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async complete_text(messages: unknown[], options: { model?: string; max_tokens?: number } = {}) {
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return (adapter as any).complete_text(messages, options)
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}
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}
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}
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@@ -31,6 +31,7 @@ import { sessionCommand } from './commands/session.js'
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import { restoreCommand } from './commands/restore.js'
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import { e2eCommand } from './commands/e2e.js'
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import { releaseCommand } from './commands/release.js'
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import { askCommand } from './commands/ask.js'
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export async function main(argv: string[]): Promise<void> {
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const args = argv.slice(2)
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@@ -42,6 +43,13 @@ export async function main(argv: string[]): Promise<void> {
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await runCommand(rest[0])
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break
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case 'ask':
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await askCommand(rest.join(' '), {
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model: rest.find(a => a.startsWith('--model='))?.split('=')[1],
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maxTurns: rest.find(a => a.startsWith('--turns='))?.split('=')[1] ? parseInt(rest.find(a => a.startsWith('--turns='))!.split('=')[1]) : undefined
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})
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break
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case 'init':
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await initCommand(rest[0])
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break
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@@ -107,6 +115,7 @@ AirCoding V1.0.0 Alpha
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Usage: air <command> [args...]
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Commands:
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ask "<prompt>" Ask the AI to implement a task
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run [project] Start a session (spawns TUI)
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init Initialize a new AirCoding project
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doctor [--fix] Run diagnostic checks
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