API reference

import { query, createOpenAIClient, LocalSandbox } from 'anyclaude-sdk'

const q = query({
  prompt: 'List the files and summarize the project.',
  workspace: new LocalSandbox({ cwd: process.cwd() }),
  llm: createOpenAIClient({ baseUrl: 'https://api.openai.com/v1', model: 'gpt-4o', apiKey: process.env.OPENAI_API_KEY }),
  model: 'gpt-4o',
})

for await (const msg of q) {
  if (msg.type === 'assistant') console.log(msg.message.content)
  if (msg.type === 'result') console.log('done', msg.usage)
}
// q.interrupt()  // abort the in-flight run from elsewhere

// 1. system / init — first message: model, tools, cwd, mcp status, permissionMode
{ type: 'system', subtype: 'init', tools: string[], model: string, cwd: string, … }

// 2. assistant — a model turn: text + tool_use blocks
{ type: 'assistant', message: { role: 'assistant', content: ContentBlock[] } }

// 3. stream_event — partial deltas (only when includePartialMessages: true)
{ type: 'stream_event', event: { type: 'content_block_delta', delta: { type: 'text_delta', text } } }

// 4. user — synthetic tool results (isSynthetic: true) or queued user turns
{ type: 'user', message: { role: 'user', content: ContentBlock[] }, isSynthetic?: boolean }

// 5. system / local_command_output — output of a slash command
{ type: 'system', subtype: 'local_command_output', content: string }

// 6. system / compact_boundary — emitted when the transcript was compacted
{ type: 'system', subtype: 'compact_boundary', compact_metadata: { trigger, pre_tokens } }

// 7. system / paused — survivor hit maxDurationMs; transcript persisted, resume with continueRun
{ type: 'system', subtype: 'paused', sessionId: string }

// 8. system / client_tool_request — a clientTools call; run pauses, resume with clientToolResults
{ type: 'system', subtype: 'client_tool_request', requests: { id, name, input }[] }

// 9. result — terminal: success or error, with usage + cost
{ type: 'result', subtype: 'success' | 'error_max_turns' | 'error_during_execution',
  result?: string, usage: { input_tokens, output_tokens, … }, total_cost_usd: number,
  duration_ms: number, num_turns: number }

import { query, PromptStream } from 'anyclaude-sdk'

const prompts = new PromptStream()
const q = query({ prompt: prompts, workspace, llm, model })

;(async () => { for await (const m of q) render(m) })()

prompts.push('first message')
prompts.push('follow-up')   // each push is a new user turn
// prompts.end()             // close the conversation