feat: add optional llm-task JSON-only tool (#1498)
* feat(llm-task): add optional JSON-only LLM task tool * fix(llm-task): fix invalid package.json * fix(llm-task): fix invalid plugin manifest JSON * fix(llm-task): fix index.ts import quoting * fix(llm-task): load embedded runner from src or bundled dist
This commit is contained in:
86
extensions/llm-task/README.md
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86
extensions/llm-task/README.md
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# LLM Task (plugin)
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Adds an **optional** agent tool `llm-task` for running **JSON-only** LLM tasks (drafting, summarizing, classifying) with optional JSON Schema validation.
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This is designed to be called from workflow engines (e.g. Lobster via `clawd.invoke --each`) without adding new Clawdbot code per workflow.
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## Enable
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1) Enable the plugin:
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```json
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{
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"plugins": {
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"entries": {
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"llm-task": { "enabled": true }
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}
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}
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}
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```
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2) Allowlist the tool (it is registered with `optional: true`):
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```json
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{
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"agents": {
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"list": [
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{
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"id": "main",
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"tools": { "allow": ["llm-task"] }
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}
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]
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}
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}
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```
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## Config (optional)
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```json
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{
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"plugins": {
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"entries": {
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"llm-task": {
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"enabled": true,
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"config": {
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"defaultProvider": "openai-codex",
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"defaultModel": "gpt-5.2",
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"allowedModels": ["openai-codex/gpt-5.2"],
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"maxTokens": 800,
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"timeoutMs": 30000
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}
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}
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}
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}
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}
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```
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`allowedModels` is an allowlist of `provider/model` strings. If set, any request outside the list is rejected.
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## Tool API
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### Parameters
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- `prompt` (string, required)
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- `input` (any, optional)
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- `schema` (object, optional JSON Schema)
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- `provider` (string, optional)
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- `model` (string, optional)
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- `authProfileId` (string, optional)
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- `temperature` (number, optional)
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- `maxTokens` (number, optional)
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- `timeoutMs` (number, optional)
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### Output
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Returns `details.json` containing the parsed JSON (and validates against `schema` when provided).
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## Notes
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- The tool is **JSON-only** and instructs the model to output only JSON (no code fences, no commentary).
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- Side effects should be handled outside this tool (e.g. approvals in Lobster) before calling tools that send messages/emails.
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## Bundled extension note
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This extension depends on Clawdbot internal modules (the embedded agent runner). It is intended to ship as a **bundled** Clawdbot extension (like `lobster`) and be enabled via `plugins.entries` + tool allowlists.
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It is **not** currently designed to be copied into `~/.clawdbot/extensions` as a standalone plugin directory.
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21
extensions/llm-task/clawdbot.plugin.json
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21
extensions/llm-task/clawdbot.plugin.json
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{
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"id": "llm-task",
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"name": "LLM Task",
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"description": "Generic JSON-only LLM tool for structured tasks callable from workflows.",
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"configSchema": {
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"type": "object",
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"additionalProperties": false,
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"properties": {
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"defaultProvider": { "type": "string" },
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"defaultModel": { "type": "string" },
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"defaultAuthProfileId": { "type": "string" },
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"allowedModels": {
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"type": "array",
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"items": { "type": "string" },
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"description": "Allowlist of provider/model keys like openai-codex/gpt-5.2."
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},
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"maxTokens": { "type": "number" },
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"timeoutMs": { "type": "number" }
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}
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}
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}
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5
extensions/llm-task/index.ts
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5
extensions/llm-task/index.ts
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import { createLlmTaskTool } from "./src/llm-task-tool.js";
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export default function (api: any) {
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api.registerTool(createLlmTaskTool(api), { optional: true });
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}
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7
extensions/llm-task/package.json
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7
extensions/llm-task/package.json
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{
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"name": "@clawdbot/llm-task",
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"private": true,
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"type": "module",
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"main": "index.ts",
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"version": "0.0.0"
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}
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96
extensions/llm-task/src/llm-task-tool.test.ts
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extensions/llm-task/src/llm-task-tool.test.ts
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import { describe, it, expect, vi, beforeEach } from "vitest";
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vi.mock("../../../src/agents/pi-embedded-runner.js", () => {
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return {
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runEmbeddedPiAgent: vi.fn(async () => ({
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meta: { startedAt: Date.now() },
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payloads: [{ text: "{}" }],
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})),
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};
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});
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import { runEmbeddedPiAgent } from "../../../src/agents/pi-embedded-runner.js";
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import { createLlmTaskTool } from "./llm-task-tool.js";
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function fakeApi(overrides: any = {}) {
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return {
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id: "llm-task",
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name: "llm-task",
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source: "test",
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config: { agents: { defaults: { workspace: "/tmp", model: { primary: "openai-codex/gpt-5.2" } } } },
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pluginConfig: {},
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runtime: { version: "test" },
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logger: { debug() {}, info() {}, warn() {}, error() {} },
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registerTool() {},
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...overrides,
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};
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}
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describe("llm-task tool (json-only)", () => {
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beforeEach(() => vi.clearAllMocks());
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it("returns parsed json", async () => {
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(runEmbeddedPiAgent as any).mockResolvedValueOnce({
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meta: {},
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payloads: [{ text: JSON.stringify({ foo: "bar" }) }],
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});
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const tool = createLlmTaskTool(fakeApi() as any);
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const res = await tool.execute("id", { prompt: "return foo" });
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expect((res as any).details.json).toEqual({ foo: "bar" });
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});
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it("validates schema", async () => {
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(runEmbeddedPiAgent as any).mockResolvedValueOnce({
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meta: {},
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payloads: [{ text: JSON.stringify({ foo: "bar" }) }],
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});
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const tool = createLlmTaskTool(fakeApi() as any);
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const schema = {
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type: "object",
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properties: { foo: { type: "string" } },
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required: ["foo"],
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additionalProperties: false,
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};
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const res = await tool.execute("id", { prompt: "return foo", schema });
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expect((res as any).details.json).toEqual({ foo: "bar" });
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});
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it("throws on invalid json", async () => {
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(runEmbeddedPiAgent as any).mockResolvedValueOnce({ meta: {}, payloads: [{ text: "not-json" }] });
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const tool = createLlmTaskTool(fakeApi() as any);
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await expect(tool.execute("id", { prompt: "x" })).rejects.toThrow(/invalid json/i);
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});
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it("throws on schema mismatch", async () => {
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(runEmbeddedPiAgent as any).mockResolvedValueOnce({
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meta: {},
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payloads: [{ text: JSON.stringify({ foo: 1 }) }],
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});
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const tool = createLlmTaskTool(fakeApi() as any);
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const schema = { type: "object", properties: { foo: { type: "string" } }, required: ["foo"] };
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await expect(tool.execute("id", { prompt: "x", schema })).rejects.toThrow(/match schema/i);
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});
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it("passes provider/model overrides to embedded runner", async () => {
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(runEmbeddedPiAgent as any).mockResolvedValueOnce({
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meta: {},
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payloads: [{ text: JSON.stringify({ ok: true }) }],
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});
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const tool = createLlmTaskTool(fakeApi() as any);
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await tool.execute("id", { prompt: "x", provider: "anthropic", model: "claude-4-sonnet" });
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const call = (runEmbeddedPiAgent as any).mock.calls[0]?.[0];
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expect(call.provider).toBe("anthropic");
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expect(call.model).toBe("claude-4-sonnet");
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});
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it("enforces allowedModels", async () => {
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(runEmbeddedPiAgent as any).mockResolvedValueOnce({
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meta: {},
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payloads: [{ text: JSON.stringify({ ok: true }) }],
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});
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const tool = createLlmTaskTool(fakeApi({ pluginConfig: { allowedModels: ["openai-codex/gpt-5.2"] } }) as any);
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await expect(tool.execute("id", { prompt: "x", provider: "anthropic", model: "claude-4-sonnet" })).rejects.toThrow(
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/not allowed/i,
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);
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});
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});
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200
extensions/llm-task/src/llm-task-tool.ts
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200
extensions/llm-task/src/llm-task-tool.ts
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import os from "node:os";
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import path from "node:path";
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import fs from "node:fs/promises";
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import Ajv from "ajv";
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import { Type } from "@sinclair/typebox";
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// NOTE: This extension is intended to be bundled with Clawdbot.
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// When running from source (tests/dev), Clawdbot internals live under src/.
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// When running from a built install, internals live under dist/ (no src/ tree).
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// So we resolve internal imports dynamically with src-first, dist-fallback.
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import type { ClawdbotPluginApi } from "../../../src/plugins/types.js";
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type RunEmbeddedPiAgentFn = (params: any) => Promise<any>;
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async function loadRunEmbeddedPiAgent(): Promise<RunEmbeddedPiAgentFn> {
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// Source checkout (tests/dev)
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try {
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const mod = await import("../../../src/agents/pi-embedded-runner.js");
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if (typeof (mod as any).runEmbeddedPiAgent === "function") return (mod as any).runEmbeddedPiAgent;
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} catch {
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// ignore
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}
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// Bundled install (built)
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const mod = await import("../../../agents/pi-embedded-runner.js");
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if (typeof (mod as any).runEmbeddedPiAgent !== "function") {
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throw new Error("Internal error: runEmbeddedPiAgent not available");
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}
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return (mod as any).runEmbeddedPiAgent;
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}
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function stripCodeFences(s: string): string {
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const trimmed = s.trim();
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const m = trimmed.match(/^```(?:json)?s*([sS]*?)s*```$/i);
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if (m) return (m[1] ?? "").trim();
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return trimmed;
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}
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function collectText(payloads: Array<{ text?: string; isError?: boolean }> | undefined): string {
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const texts = (payloads ?? [])
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.filter((p) => !p.isError && typeof p.text === "string")
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.map((p) => p.text ?? "");
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return texts.join("n").trim();
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}
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function toModelKey(provider?: string, model?: string): string | undefined {
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const p = provider?.trim();
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const m = model?.trim();
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if (!p || !m) return undefined;
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return `${p}/${m}`;
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}
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type PluginCfg = {
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defaultProvider?: string;
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defaultModel?: string;
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defaultAuthProfileId?: string;
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allowedModels?: string[];
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maxTokens?: number;
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timeoutMs?: number;
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};
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export function createLlmTaskTool(api: ClawdbotPluginApi) {
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return {
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name: "llm-task",
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description:
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"Run a generic JSON-only LLM task and return schema-validated JSON. Designed for orchestration from Lobster workflows via clawd.invoke.",
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parameters: Type.Object({
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prompt: Type.String({ description: "Task instruction for the LLM." }),
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input: Type.Optional(Type.Unknown({ description: "Optional input payload for the task." })),
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schema: Type.Optional(Type.Unknown({ description: "Optional JSON Schema to validate the returned JSON." })),
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provider: Type.Optional(Type.String({ description: "Provider override (e.g. openai-codex, anthropic)." })),
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model: Type.Optional(Type.String({ description: "Model id override." })),
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authProfileId: Type.Optional(Type.String({ description: "Auth profile override." })),
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temperature: Type.Optional(Type.Number({ description: "Best-effort temperature override." })),
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maxTokens: Type.Optional(Type.Number({ description: "Best-effort maxTokens override." })),
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timeoutMs: Type.Optional(Type.Number({ description: "Timeout for the LLM run." })),
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}),
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async execute(_id: string, params: Record<string, unknown>) {
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const prompt = String(params.prompt ?? "");
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if (!prompt.trim()) throw new Error("prompt required");
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const pluginCfg = (api.pluginConfig ?? {}) as PluginCfg;
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const primary = api.config?.agents?.defaults?.model?.primary;
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const primaryProvider = typeof primary === "string" ? primary.split("/")[0] : undefined;
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const primaryModel = typeof primary === "string" ? primary.split("/").slice(1).join("/") : undefined;
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const provider =
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(typeof params.provider === "string" && params.provider.trim()) ||
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(typeof pluginCfg.defaultProvider === "string" && pluginCfg.defaultProvider.trim()) ||
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primaryProvider ||
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undefined;
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const model =
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(typeof params.model === "string" && params.model.trim()) ||
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(typeof pluginCfg.defaultModel === "string" && pluginCfg.defaultModel.trim()) ||
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primaryModel ||
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undefined;
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const authProfileId =
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(typeof (params as any).authProfileId === "string" && (params as any).authProfileId.trim()) ||
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(typeof pluginCfg.defaultAuthProfileId === "string" && pluginCfg.defaultAuthProfileId.trim()) ||
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undefined;
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const modelKey = toModelKey(provider, model);
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if (!provider || !model || !modelKey) {
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throw new Error(
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`provider/model could not be resolved (provider=${String(provider ?? "")}, model=${String(model ?? "")})`,
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);
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}
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const allowed = Array.isArray(pluginCfg.allowedModels) ? pluginCfg.allowedModels : undefined;
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if (allowed && allowed.length > 0 && !allowed.includes(modelKey)) {
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throw new Error(
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`Model not allowed by llm-task plugin config: ${modelKey}. Allowed models: ${allowed.join(", ")}`,
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);
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}
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const timeoutMs =
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(typeof params.timeoutMs === "number" && params.timeoutMs > 0 ? params.timeoutMs : undefined) ||
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(typeof pluginCfg.timeoutMs === "number" && pluginCfg.timeoutMs > 0 ? pluginCfg.timeoutMs : undefined) ||
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30_000;
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const streamParams = {
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temperature: typeof params.temperature === "number" ? params.temperature : undefined,
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maxTokens:
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typeof params.maxTokens === "number"
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? params.maxTokens
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: typeof pluginCfg.maxTokens === "number"
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? pluginCfg.maxTokens
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: undefined,
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};
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const input = (params as any).input as unknown;
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const system = [
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"You are a JSON-only function.",
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"Return ONLY a valid JSON value.",
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"Do not wrap in markdown fences.",
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"Do not include commentary.",
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"Do not call tools.",
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].join(" ");
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const fullPrompt = `${system}nnTASK:n${prompt}nnINPUT_JSON:n${JSON.stringify(input ?? null, null, 2)}n`;
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const tmpDir = await fs.mkdtemp(path.join(os.tmpdir(), "clawdbot-llm-task-"));
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const sessionId = `llm-task-${Date.now()}`;
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const sessionFile = path.join(tmpDir, "session.json");
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const runEmbeddedPiAgent = await loadRunEmbeddedPiAgent();
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const result = await runEmbeddedPiAgent({
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sessionId,
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sessionFile,
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workspaceDir: api.config?.agents?.defaults?.workspace ?? process.cwd(),
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config: api.config,
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prompt: fullPrompt,
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timeoutMs,
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runId: `llm-task-${Date.now()}`,
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provider,
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model,
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authProfileId,
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authProfileIdSource: authProfileId ? "user" : "auto",
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streamParams,
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});
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const text = collectText((result as any).payloads);
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if (!text) throw new Error("LLM returned empty output");
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const raw = stripCodeFences(text);
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let parsed: unknown;
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try {
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parsed = JSON.parse(raw);
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} catch {
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throw new Error("LLM returned invalid JSON");
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}
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const schema = (params as any).schema as unknown;
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if (schema && typeof schema === "object") {
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const ajv = new Ajv({ allErrors: true, strict: false });
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const validate = ajv.compile(schema as any);
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const ok = validate(parsed);
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if (!ok) {
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const msg =
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validate.errors?.map((e) => `${e.instancePath || "<root>"} ${e.message || "invalid"}`).join("; ") ??
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"invalid";
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throw new Error(`LLM JSON did not match schema: ${msg}`);
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}
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}
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return {
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content: [{ type: "text", text: JSON.stringify(parsed, null, 2) }],
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details: { json: parsed, provider, model },
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};
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},
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};
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}
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