- Auto-detect screen resolution and compute dynamic swipe coordinates - Detect foreground app each step via dumpsys activity - Smart element filtering: deduplicate by position, score by relevance, compact to essentials - Session logging with crash-safe .partial.json writes and final summary - Real multimodal vision: send base64 screenshots to LLMs (off/fallback/always modes) - Multi-turn conversation memory: maintain full chat history across steps with trimming - Multi-step planning: think/plan/planProgress fields on every LLM decision - Streaming responses for all 4 providers (OpenAI, Groq, OpenRouter, Bedrock) - Comprehensive README with examples, architecture docs, and troubleshooting Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
417 lines
12 KiB
TypeScript
417 lines
12 KiB
TypeScript
/**
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* Android Action Kernel - Main Agent Loop (TypeScript/Bun Edition)
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*
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* An AI agent that controls Android devices through the accessibility API.
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* Uses LLMs to make decisions based on screen context.
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*
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* Features:
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* - Perception -> Reasoning -> Action loop
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* - Screen state diffing (stuck loop detection)
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* - Error recovery with retries
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* - Vision fallback & always-on multimodal screenshots
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* - Dynamic early exit on goal completion
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* - Smart element filtering (compact JSON, top-N scoring)
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* - Multi-turn conversation memory
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* - Multi-step planning (think/plan/planProgress)
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* - Streaming LLM responses
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* - Session logging with crash-safe partial writes
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* - Auto-detect screen resolution & foreground app
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* - 15 actions: tap, type, enter, swipe, home, back, wait, done,
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* longpress, screenshot, launch, clear, clipboard_get, clipboard_set, shell
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*
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* Usage:
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* bun run src/kernel.ts
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*/
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import { existsSync, readFileSync } from "fs";
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import { Config } from "./config.js";
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import {
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executeAction,
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runAdbCommand,
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getScreenResolution,
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getForegroundApp,
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initDeviceContext,
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type ActionDecision,
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type ActionResult,
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} from "./actions.js";
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import {
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getLlmProvider,
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trimMessages,
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SYSTEM_PROMPT,
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type LLMProvider,
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type ChatMessage,
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type ContentPart,
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} from "./llm-providers.js";
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import {
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getInteractiveElements,
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computeScreenHash,
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filterElements,
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type UIElement,
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} from "./sanitizer.js";
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import {
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DEVICE_SCREENSHOT_PATH,
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LOCAL_SCREENSHOT_PATH,
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} from "./constants.js";
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import { SessionLogger } from "./logger.js";
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// ===========================================
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// Screen Perception
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// ===========================================
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interface ScreenState {
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elements: UIElement[];
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compactJson: string;
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}
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/**
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* Dumps the current UI XML and returns parsed elements + compact filtered JSON for the LLM.
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*/
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function getScreenState(): ScreenState {
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try {
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runAdbCommand(["shell", "uiautomator", "dump", Config.SCREEN_DUMP_PATH]);
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runAdbCommand(["pull", Config.SCREEN_DUMP_PATH, Config.LOCAL_DUMP_PATH]);
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} catch {
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console.log("Warning: ADB screen capture failed.");
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return { elements: [], compactJson: "Error: Could not capture screen." };
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}
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if (!existsSync(Config.LOCAL_DUMP_PATH)) {
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return { elements: [], compactJson: "Error: Could not capture screen." };
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}
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const xmlContent = readFileSync(Config.LOCAL_DUMP_PATH, "utf-8");
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const elements = getInteractiveElements(xmlContent);
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const compact = filterElements(elements, Config.MAX_ELEMENTS);
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return { elements, compactJson: JSON.stringify(compact) };
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}
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/**
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* Captures a screenshot and returns the base64-encoded PNG, or null on failure.
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*/
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function captureScreenshotBase64(): string | null {
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try {
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runAdbCommand(["shell", "screencap", "-p", DEVICE_SCREENSHOT_PATH]);
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runAdbCommand(["pull", DEVICE_SCREENSHOT_PATH, LOCAL_SCREENSHOT_PATH]);
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if (existsSync(LOCAL_SCREENSHOT_PATH)) {
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const buffer = readFileSync(LOCAL_SCREENSHOT_PATH);
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return Buffer.from(buffer).toString("base64");
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}
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} catch {
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console.log("Warning: Screenshot capture failed.");
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}
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return null;
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}
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// ===========================================
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// Screen State Diffing
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// ===========================================
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interface ScreenDiff {
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changed: boolean;
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addedTexts: string[];
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removedTexts: string[];
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summary: string;
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}
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function diffScreenState(
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prevElements: UIElement[],
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currElements: UIElement[]
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): ScreenDiff {
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const prevTexts = new Set(prevElements.map((e) => e.text).filter(Boolean));
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const currTexts = new Set(currElements.map((e) => e.text).filter(Boolean));
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const addedTexts = [...currTexts].filter((t) => !prevTexts.has(t));
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const removedTexts = [...prevTexts].filter((t) => !currTexts.has(t));
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const prevHash = computeScreenHash(prevElements);
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const currHash = computeScreenHash(currElements);
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const changed = prevHash !== currHash;
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let summary = "";
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if (!changed) {
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summary = "Screen has NOT changed since last action.";
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} else {
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const parts: string[] = [];
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if (addedTexts.length > 0) {
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parts.push(`New on screen: ${addedTexts.slice(0, 5).join(", ")}`);
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}
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if (removedTexts.length > 0) {
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parts.push(`Gone from screen: ${removedTexts.slice(0, 5).join(", ")}`);
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}
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summary = parts.join(". ") || "Screen layout changed.";
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}
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return { changed, addedTexts, removedTexts, summary };
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}
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// ===========================================
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// Streaming LLM Consumer
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// ===========================================
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async function getDecisionStreaming(
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llm: LLMProvider,
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messages: ChatMessage[]
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): Promise<ActionDecision> {
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if (!Config.STREAMING_ENABLED || !llm.capabilities.supportsStreaming || !llm.getDecisionStream) {
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return llm.getDecision(messages);
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}
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let accumulated = "";
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process.stdout.write("Thinking");
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for await (const chunk of llm.getDecisionStream(messages)) {
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accumulated += chunk;
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process.stdout.write(".");
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}
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process.stdout.write("\n");
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return parseJsonResponse(accumulated);
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}
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/** Simple JSON parser with markdown fallback (duplicated from llm-providers for streaming path) */
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function parseJsonResponse(text: string): ActionDecision {
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try {
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return JSON.parse(text);
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} catch {
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const match = text.match(/\{[\s\S]*?\}/);
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if (match) {
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try {
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return JSON.parse(match[0]);
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} catch {
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// fall through
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}
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}
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console.log(`Warning: Could not parse streamed response: ${text.slice(0, 200)}`);
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return { action: "wait", reason: "Failed to parse response, waiting" };
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}
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}
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// ===========================================
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// Main Agent Loop
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// ===========================================
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async function runAgent(goal: string, maxSteps?: number): Promise<void> {
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const steps = maxSteps ?? Config.MAX_STEPS;
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// Phase 1A: Auto-detect screen resolution
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const resolution = getScreenResolution();
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if (resolution) {
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initDeviceContext(resolution);
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console.log(`Screen resolution: ${resolution[0]}x${resolution[1]}`);
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} else {
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console.log("Screen resolution: using default 1080x2400 swipe coords");
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}
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console.log("Android Action Kernel Started");
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console.log(`Goal: ${goal}`);
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console.log(`Provider: ${Config.LLM_PROVIDER} (${Config.getModel()})`);
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console.log(`Max steps: ${steps} | Step delay: ${Config.STEP_DELAY}s`);
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console.log(`Vision: ${Config.VISION_MODE} | Streaming: ${Config.STREAMING_ENABLED}`);
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console.log(`Max elements: ${Config.MAX_ELEMENTS} | History: ${Config.MAX_HISTORY_STEPS} steps`);
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const llm = getLlmProvider();
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// Phase 2B: Session logging
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const logger = new SessionLogger(
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Config.LOG_DIR,
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goal,
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Config.LLM_PROVIDER,
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Config.getModel()
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);
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// Phase 4A: Multi-turn conversation memory
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const messages: ChatMessage[] = [
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{ role: "system", content: SYSTEM_PROMPT },
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];
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let prevElements: UIElement[] = [];
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let stuckCount = 0;
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for (let step = 0; step < steps; step++) {
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console.log(`\n--- Step ${step + 1}/${steps} ---`);
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// 1. Perception: Capture screen state
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console.log("Scanning screen...");
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const { elements, compactJson: screenContext } = getScreenState();
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// 1B. Foreground app detection
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const foregroundApp = getForegroundApp();
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if (foregroundApp) {
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console.log(`Foreground: ${foregroundApp}`);
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}
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// 2. Screen diff: detect stuck loops
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let diffContext = "";
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let screenChanged = true;
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if (step > 0) {
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const diff = diffScreenState(prevElements, elements);
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screenChanged = diff.changed;
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diffContext = `\n\nSCREEN_CHANGE: ${diff.summary}`;
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if (!diff.changed) {
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stuckCount++;
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console.log(
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`Warning: Screen unchanged for ${stuckCount} step(s).`
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);
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if (stuckCount >= Config.STUCK_THRESHOLD) {
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console.log(
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`Stuck for ${stuckCount} steps. Injecting recovery hint.`
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);
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diffContext +=
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`\nWARNING: You have been stuck for ${stuckCount} steps. ` +
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`The screen is NOT changing. Try a DIFFERENT action: ` +
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`swipe to scroll, press back, go home, or launch a different app.` +
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`\nYour plan is not working. Create a NEW plan with a different approach.`;
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}
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} else {
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stuckCount = 0;
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}
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}
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prevElements = elements;
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// 3. Vision: capture screenshot based on VISION_MODE
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let screenshotBase64: string | null = null;
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let visionContext = "";
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const shouldCaptureVision =
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Config.VISION_MODE === "always" ||
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(Config.VISION_MODE === "fallback" && elements.length === 0);
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if (shouldCaptureVision) {
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screenshotBase64 = captureScreenshotBase64();
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if (elements.length === 0) {
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visionContext =
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"\n\nVISION_FALLBACK: The accessibility tree returned NO elements. " +
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"A screenshot has been captured. The screen likely contains custom-drawn " +
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"content (game, WebView, or Flutter). Try using coordinate-based taps on " +
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"common UI positions, or use 'back'/'home' to navigate away.";
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}
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if (screenshotBase64 && llm.capabilities.supportsImages) {
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console.log("Sending screenshot to LLM");
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}
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}
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// 4. Build user message with all context
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const foregroundLine = foregroundApp
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? `FOREGROUND_APP: ${foregroundApp}\n\n`
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: "";
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const textContent =
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`GOAL: ${goal}\n\n${foregroundLine}SCREEN_CONTEXT:\n${screenContext}${diffContext}${visionContext}`;
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// Build content parts (text + optional image)
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const userContent: ContentPart[] = [{ type: "text", text: textContent }];
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if (screenshotBase64 && llm.capabilities.supportsImages) {
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userContent.push({
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type: "image",
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base64: screenshotBase64,
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mimeType: "image/png",
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});
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}
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messages.push({ role: "user", content: userContent });
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// Trim messages to keep within history limit
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const trimmed = trimMessages(messages, Config.MAX_HISTORY_STEPS);
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// 5. Reasoning: Get LLM decision
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const llmStart = performance.now();
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let decision: ActionDecision;
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try {
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decision = await getDecisionStreaming(llm, trimmed);
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} catch (err) {
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console.log(`LLM Error: ${(err as Error).message}`);
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console.log("Falling back to wait action.");
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decision = { action: "wait", reason: "LLM request failed, waiting" };
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}
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const llmLatency = performance.now() - llmStart;
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// Log thinking and planning
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if (decision.think) {
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console.log(`Think: ${decision.think}`);
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}
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if (decision.plan) {
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console.log(`Plan: ${decision.plan.join(" -> ")}`);
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}
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if (decision.planProgress) {
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console.log(`Progress: ${decision.planProgress}`);
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}
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console.log(`Decision: ${decision.action} — ${decision.reason ?? "no reason"} (${Math.round(llmLatency)}ms)`);
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// Append assistant response to conversation
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messages.push({
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role: "assistant",
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content: JSON.stringify(decision),
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});
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// 6. Action: Execute the decision
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const actionStart = performance.now();
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let result: ActionResult;
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try {
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result = executeAction(decision);
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} catch (err) {
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console.log(`Action Error: ${(err as Error).message}`);
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result = { success: false, message: (err as Error).message };
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}
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const actionLatency = performance.now() - actionStart;
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// Log step
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logger.logStep(
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step + 1,
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foregroundApp,
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elements.length,
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screenChanged,
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decision,
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result,
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Math.round(llmLatency),
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Math.round(actionLatency)
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);
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console.log(`Messages in context: ${trimmed.length}`);
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// 7. Check for goal completion
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if (decision.action === "done") {
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console.log("\nTask completed successfully.");
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logger.finalize(true);
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return;
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}
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// Wait for UI to update
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await Bun.sleep(Config.STEP_DELAY * 1000);
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}
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console.log("\nMax steps reached. Task may be incomplete.");
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logger.finalize(false);
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}
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// ===========================================
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// Entry Point
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// ===========================================
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async function main(): Promise<void> {
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try {
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Config.validate();
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} catch (e) {
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console.log(`Configuration Error: ${(e as Error).message}`);
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return;
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}
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// Read user input from stdin
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process.stdout.write("Enter your goal: ");
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const goal = await new Promise<string>((resolve) => {
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const reader = Bun.stdin.stream().getReader();
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reader.read().then(({ value }) => {
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resolve(new TextDecoder().decode(value).trim());
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reader.releaseLock();
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});
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});
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if (!goal) {
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console.log("No goal provided. Exiting.");
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return;
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}
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await runAgent(goal);
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}
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main();
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