Plugin रनटाइम सहायक

// Resolve the agent's working directoryconst agentDir = api.runtime.agent.resolveAgentDir(cfg); // Resolve agent workspaceconst workspaceDir = api.runtime.agent.resolveAgentWorkspaceDir(cfg); // Get agent identityconst identity = api.runtime.agent.resolveAgentIdentity(cfg); // Get default thinking levelconst thinking = api.runtime.agent.resolveThinkingDefault({  cfg,  provider,  model,}); // Validate a user-provided thinking level against the active provider profileconst policy = api.runtime.agent.resolveThinkingPolicy({ provider, model });const level = api.runtime.agent.normalizeThinkingLevel("extra high");if (level && policy.levels.some((entry) => entry.id === level)) {  // pass level to an embedded run} // Get agent timeoutconst timeoutMs = api.runtime.agent.resolveAgentTimeoutMs(cfg); // Ensure workspace existsawait api.runtime.agent.ensureAgentWorkspace(cfg); // Run an embedded agent turnconst result = await api.runtime.agent.runEmbeddedAgent({  sessionId: "my-plugin:task-1",  runId: crypto.randomUUID(),  workspaceDir: api.runtime.agent.resolveAgentWorkspaceDir(cfg),  prompt: "Summarize the latest changes",  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 })) {  // Iterate session rows without depending on the legacy sessions.json shape.}await api.runtime.agent.session.patchSessionEntry({  agentId,  sessionKey,  update: (entry) => ({ thinkingLevel: "high" }),});

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

const result = await api.runtime.llm.complete({  messages: [{ role: "user", content: "Summarize this transcript." }],  purpose: "my-plugin.summary",  maxTokens: 512,  temperature: 0.2,});

// Start a subagent runconst { runId } = await api.runtime.subagent.run({  sessionKey: "agent:main:subagent:search-helper",  message: "Expand this query into focused follow-up searches.",  provider: "openai", // optional override  model: "gpt-4.1-mini", // optional override  deliver: false,}); // Wait for completionconst result = await api.runtime.subagent.waitForRun({ runId, timeoutMs: 30000 }); // Read session messagesconst { messages } = await api.runtime.subagent.getSessionMessages({  sessionKey: "agent:main:subagent:search-helper",  limit: 10,}); // Delete a sessionawait 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" },});

// Standard TTSconst clip = await api.runtime.tts.textToSpeech({  text: "Hello from OpenClaw",  cfg: api.config,}); // Telephony-optimized TTSconst telephonyClip = await api.runtime.tts.textToSpeechTelephony({  text: "Hello from OpenClaw",  cfg: api.config,}); // List available voicesconst voices = await api.runtime.tts.listVoices({  provider: "elevenlabs",  cfg: api.config,});

// Describe an imageconst image = await api.runtime.mediaUnderstanding.describeImageFile({  filePath: "/tmp/inbound-photo.jpg",  cfg: api.config,  agentDir: "/tmp/agent",}); // Transcribe audioconst { text } = await api.runtime.mediaUnderstanding.transcribeAudioFile({  filePath: "/tmp/inbound-audio.ogg",  cfg: api.config,  mime: "audio/ogg", // optional, for when MIME cannot be inferred}); // Describe a videoconst video = await api.runtime.mediaUnderstanding.describeVideoFile({  filePath: "/tmp/inbound-video.mp4",  cfg: api.config,}); // Generic file analysisconst result = await api.runtime.mediaUnderstanding.runFile({  filePath: "/tmp/inbound-file.pdf",  cfg: api.config,}); // Structured image extraction through a specific provider/model.// Include at least one image; text inputs are supplemental context.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: "Prefer the printed total over handwritten notes." },  ],  instructions: "Extract vendor, total, and searchable tags.",  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" }); // Deprecated compatibility alias.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,  },});