mirror of
https://github.com/NanmiCoder/cc-haha
synced 2026-07-16 13:03:31 +08:00
e8f42840a2
Bypass all three gating layers (compile-time feature flag, subscription check, GrowthBook remote config) and replace Anthropic's private native modules (@ant/computer-use-swift, @ant/computer-use-input) with a Python bridge using pyautogui + mss + pyobjc. Works on any macOS with any Anthropic-protocol compatible model.
109 lines
3.4 KiB
TypeScript
109 lines
3.4 KiB
TypeScript
/**
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* Port of the API's image transcoder target-size algorithm. Pre-sizing
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* screenshots to this function's output means the API's early-return fires
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* (tokens ≤ max) and the image is NOT resized server-side — so the model
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* sees exactly the dimensions in `ScreenshotResult.width/height` and
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* `scaleCoord` stays coherent.
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*
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* Rust reference: api/api/image_transcoder/rust_transcoder/src/utils/resize.rs
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* Sibling TS port: apps/claude-browser-use/src/utils/imageResize.ts (identical
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* algorithm, lives in the Chrome extension tree — not a shared package).
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*
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* See COORDINATES.md for why this matters for click accuracy.
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*/
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export interface ResizeParams {
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pxPerToken: number;
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maxTargetPx: number;
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maxTargetTokens: number;
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}
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/**
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* Production defaults — match `resize.rs:160-164` and Chrome's
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* `CDPService.ts:638-642`. Vision encoder uses 28px tiles; 1568 is both
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* the long-edge cap (56 tiles) AND the token budget.
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*/
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export const API_RESIZE_PARAMS: ResizeParams = {
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pxPerToken: 28,
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maxTargetPx: 1568,
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maxTargetTokens: 1568,
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};
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/** ceil(px / pxPerToken). Matches resize.rs:74-76 (which uses integer ceil-div). */
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export function nTokensForPx(px: number, pxPerToken: number): number {
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return Math.floor((px - 1) / pxPerToken) + 1;
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}
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function nTokensForImg(
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width: number,
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height: number,
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pxPerToken: number,
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): number {
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return nTokensForPx(width, pxPerToken) * nTokensForPx(height, pxPerToken);
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}
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/**
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* Binary-search along the width dimension for the largest image that:
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* - preserves the input aspect ratio
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* - has long edge ≤ maxTargetPx
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* - has ceil(w/pxPerToken) × ceil(h/pxPerToken) ≤ maxTargetTokens
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*
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* Returns [width, height]. No-op if input already satisfies all three.
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*
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* The long-edge constraint alone (what we used to use) is insufficient on
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* squarer-than-16:9 displays: 1568×1014 (MBP 16" AR) is 56×37 = 2072 tokens,
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* over budget, and gets server-resized to 1372×887 — model then clicks in
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* 1372-space but scaleCoord assumed 1568-space → ~14% coord error.
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*
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* Matches resize.rs:91-155 exactly (verified against its test vectors).
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*/
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export function targetImageSize(
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width: number,
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height: number,
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params: ResizeParams,
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): [number, number] {
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const { pxPerToken, maxTargetPx, maxTargetTokens } = params;
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if (
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width <= maxTargetPx &&
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height <= maxTargetPx &&
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nTokensForImg(width, height, pxPerToken) <= maxTargetTokens
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) {
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return [width, height];
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}
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// Normalize to landscape for the search; transpose result back.
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if (height > width) {
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const [w, h] = targetImageSize(height, width, params);
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return [h, w];
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}
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const aspectRatio = width / height;
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// Loop invariant: lowerBoundWidth is always valid, upperBoundWidth is
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// always invalid. ~12 iterations for a 4000px image.
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let upperBoundWidth = width;
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let lowerBoundWidth = 1;
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for (;;) {
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if (lowerBoundWidth + 1 === upperBoundWidth) {
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return [
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lowerBoundWidth,
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Math.max(Math.round(lowerBoundWidth / aspectRatio), 1),
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];
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}
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const middleWidth = Math.floor((lowerBoundWidth + upperBoundWidth) / 2);
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const middleHeight = Math.max(Math.round(middleWidth / aspectRatio), 1);
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if (
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middleWidth <= maxTargetPx &&
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nTokensForImg(middleWidth, middleHeight, pxPerToken) <= maxTargetTokens
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) {
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lowerBoundWidth = middleWidth;
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} else {
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upperBoundWidth = middleWidth;
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}
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}
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}
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