插件运行时辅助工具

// 解析 agent 的工作目录
const agentDir = api.runtime.agent.resolveAgentDir(cfg);

// 解析 agent 工作区
const workspaceDir = api.runtime.agent.resolveAgentWorkspaceDir(cfg);

// 获取 agent 身份
const identity = api.runtime.agent.resolveAgentIdentity(cfg);

// 获取默认思考级别
const thinking = api.runtime.agent.resolveThinkingDefault({
  cfg,
  provider,
  model,
});

// 根据当前 provider profile 验证用户提供的思考级别
const policy = api.runtime.agent.resolveThinkingPolicy({ provider, model });
const level = api.runtime.agent.normalizeThinkingLevel("extra high");
if (level && policy.levels.some((entry) => entry.id === level)) {
  // 将 level 传递给嵌入式运行
}

// 获取 agent 超时
const timeoutMs = api.runtime.agent.resolveAgentTimeoutMs(cfg);

// 确保工作区存在
await api.runtime.agent.ensureAgentWorkspace(cfg);

// 运行一次嵌入式 agent 回合
const agentDir = api.runtime.agent.resolveAgentDir(cfg);
const result = await api.runtime.agent.runEmbeddedAgent({
  sessionId: "my-plugin:task-1",
  runId: crypto.randomUUID(),
  sessionFile: path.join(agentDir, "sessions", "my-plugin-task-1.jsonl"),
  workspaceDir: api.runtime.agent.resolveAgentWorkspaceDir(cfg),
  prompt: "总结最新更改",
  timeoutMs: api.runtime.agent.resolveAgentTimeoutMs(cfg),
});

const entry = api.runtime.agent.session.getSessionEntry({ agentId, sessionKey });
for (const { sessionKey, entry } of api.runtime.agent.session.listSessionEntries({ agentId })) {
  // 在不依赖旧版 sessions.json 形状的情况下遍历会话行。
}
await api.runtime.agent.session.patchSessionEntry({
  agentId,
  sessionKey,
  update: (entry) => ({ thinkingLevel: "high" }),
});

const model = api.runtime.agent.defaults.model; // 例如 "anthropic/claude-sonnet-4-6"
const provider = api.runtime.agent.defaults.provider; // 例如 "anthropic"

const result = await api.runtime.llm.complete({
  messages: [{ role: "user", content: "总结这段转录内容。" }],
  purpose: "my-plugin.summary",
  maxTokens: 512,
  temperature: 0.2,
});

// 开始一个 subagent 运行
const { runId } = await api.runtime.subagent.run({
  sessionKey: "agent:main:subagent:search-helper",
  message: "把这个查询扩展为聚焦的后续搜索。",
  provider: "openai", // 可选覆盖
  model: "gpt-4.1-mini", // 可选覆盖
  deliver: false,
});

// 等待完成
const result = await api.runtime.subagent.waitForRun({ runId, timeoutMs: 30000 });

// 读取会话消息
const { messages } = await api.runtime.subagent.getSessionMessages({
  sessionKey: "agent:main:subagent:search-helper",
  limit: 10,
});

// 删除会话
await api.runtime.subagent.deleteSession({
  sessionKey: "agent:main:subagent:search-helper",
});

const { nodes } = await api.runtime.nodes.list({ connected: true });

const result = await api.runtime.nodes.invoke({
  nodeId: "mac-studio",
  command: "my-plugin.command",
  params: { action: "start" },
  timeoutMs: 30000,
});

const taskFlow = api.runtime.tasks.managedFlows.fromToolContext(ctx);

const created = taskFlow.createManaged({
  controllerId: "my-plugin/review-batch",
  goal: "Review new pull requests",
});

const child = taskFlow.runTask({
  flowId: created.flowId,
  runtime: "acp",
  childSessionKey: "agent:main:subagent:reviewer",
  task: "Review PR #123",
  status: "running",
  startedAt: Date.now(),
});

const waiting = taskFlow.setWaiting({
  flowId: created.flowId,
  expectedRevision: created.revision,
  currentStep: "await-human-reply",
  waitJson: { kind: "reply", channel: "telegram" },
});

// 标准 TTS
const clip = await api.runtime.tts.textToSpeech({
  text: "Hello from OpenClaw",
  cfg: api.config,
});

// 面向电话优化的 TTS
const telephonyClip = await api.runtime.tts.textToSpeechTelephony({
  text: "Hello from OpenClaw",
  cfg: api.config,
});

// 列出可用语音
const voices = await api.runtime.tts.listVoices({
  provider: "elevenlabs",
  cfg: api.config,
});

// 描述一张图片
const image = await api.runtime.mediaUnderstanding.describeImageFile({
  filePath: "/tmp/inbound-photo.jpg",
  cfg: api.config,
  agentDir: "/tmp/agent",
});

// 转写音频
const { text } = await api.runtime.mediaUnderstanding.transcribeAudioFile({
  filePath: "/tmp/inbound-audio.ogg",
  cfg: api.config,
  mime: "audio/ogg", // 可选，当无法推断 MIME 时使用
});

// 描述一个视频
const video = await api.runtime.mediaUnderstanding.describeVideoFile({
  filePath: "/tmp/inbound-video.mp4",
  cfg: api.config,
});

// 通用文件分析
const result = await api.runtime.mediaUnderstanding.runFile({
  filePath: "/tmp/inbound-file.pdf",
  cfg: api.config,
});

// 通过特定 provider/model 进行结构化图像提取。
// 至少包含一张图片；文本输入作为补充上下文。
const evidence = await api.runtime.mediaUnderstanding.extractStructuredWithModel({
  provider: "codex",
  model: "gpt-5.5",
  input: [
    {
      type: "image",
      buffer: receiptImageBuffer,
      fileName: "receipt.png",
      mime: "image/png",
    },
    { type: "text", text: "优先使用打印出来的总计，而不是手写备注。" },
  ],
  instructions: "提取供应商、总额和可搜索标签。",
  schemaName: "receipt.evidence",
  jsonSchema: {
    type: "object",
    properties: {
      vendor: { type: "string" },
      total: { type: "number" },
      tags: { type: "array", items: { type: "string" } },
    },
    required: ["vendor", "total"],
  },
  cfg: api.config,
});

const result = await api.runtime.imageGeneration.generate({
  prompt: "A robot painting a sunset",
  cfg: api.config,
});

const providers = api.runtime.imageGeneration.listProviders({ cfg: api.config });

const providers = api.runtime.webSearch.listProviders({ config: api.config });

const result = await api.runtime.webSearch.search({
  config: api.config,
  args: { query: "OpenClaw plugin SDK", count: 5 },
});

const webMedia = await api.runtime.media.loadWebMedia(url);
const mime = await api.runtime.media.detectMime(buffer);
const kind = api.runtime.media.mediaKindFromMime("image/jpeg"); // "image"
const isVoice = api.runtime.media.isVoiceCompatibleAudio(filePath);
const metadata = await api.runtime.media.getImageMetadata(filePath);
const resized = await api.runtime.media.resizeToJpeg(buffer, { maxWidth: 800 });
const terminalQr = await api.runtime.media.renderQrTerminal("https://openclaw.ai");
const pngQr = await api.runtime.media.renderQrPngBase64("https://openclaw.ai", {
  scale: 6, // 1-12
  marginModules: 4, // 0-16
});
const pngQrDataUrl = await api.runtime.media.renderQrPngDataUrl("https://openclaw.ai");
const tmpRoot = resolvePreferredOpenClawTmpDir();
const pngQrFile = await api.runtime.media.writeQrPngTempFile("https://openclaw.ai", {
  tmpRoot,
  dirPrefix: "my-plugin-qr-",
  fileName: "qr.png",
});

const cfg = api.runtime.config.current();
await api.runtime.config.mutateConfigFile({
  afterWrite: { mode: "auto" },
  mutate(draft) {
    draft.plugins ??= {};
  },
});

await api.runtime.system.enqueueSystemEvent(event);
api.runtime.system.requestHeartbeat({
  source: "other",
  intent: "event",
  reason: "plugin-event",
});
api.runtime.system.requestHeartbeatNow({ reason: "plugin-event" }); // 已弃用的兼容别名。
const output = await api.runtime.system.runCommandWithTimeout(cmd, args, opts);
const hint = api.runtime.system.formatNativeDependencyHint(pkg);

api.runtime.events.onAgentEvent((event) => {
  /* ... */
});
api.runtime.events.onSessionTranscriptUpdate((update) => {
  /* ... */
});

const verbose = api.runtime.logging.shouldLogVerbose();
const childLogger = api.runtime.logging.getChildLogger({ plugin: "my-plugin" }, { level: "debug" });

const auth = await api.runtime.modelAuth.getApiKeyForModel({ model, cfg });
const providerAuth = await api.runtime.modelAuth.resolveApiKeyForProvider({
  provider: "openai",
  cfg,
});

const stateDir = api.runtime.state.resolveStateDir(process.env);
const store = api.runtime.state.openKeyedStore<MyRecord>({
  namespace: "my-feature",
  maxEntries: 200,
  defaultTtlMs: 15 * 60_000,
});

await store.register("key-1", { value: "hello" });
const claimed = await store.registerIfAbsent("dedupe-key", { value: "first" });
const value = await store.lookup("key-1");
await store.consume("key-1");
await store.clear();

const getTool = api.runtime.tools.createMemoryGetTool(/* ... */);
const searchTool = api.runtime.tools.createMemorySearchTool(/* ... */);
api.runtime.tools.registerMemoryCli(/* ... */);

const saved = await api.runtime.channel.media.saveRemoteMedia({
  url,
  subdir: "inbound",
  maxBytes,
  filePathHint: fileName,
});

const mentionMatch = api.runtime.channel.mentions.matchesMentionWithExplicit(text, {
  mentionRegexes,
  mentionPatterns,
});

const decision = api.runtime.channel.mentions.resolveInboundMentionDecision({
  facts: {
    canDetectMention: true,
    wasMentioned: mentionMatch.matched,
    implicitMentionKinds: api.runtime.channel.mentions.implicitMentionKindWhen(
      "reply_to_bot",
      isReplyToBot,
    ),
  },
  policy: {
    isGroup,
    requireMention,
    allowTextCommands,
    hasControlCommand,
    commandAuthorized,
  },
});