cc6ab1addc
Intercepts Read tool output with image attachments and resizes to comply with Anthropic API limits (≤1568px long edge, ≤5MB). Only activates for Anthropic provider sessions and appends resize metadata (original/new resolution, token count) to tool output. Ultraworked with [Sisyphus](https://github.com/code-yeongyu/oh-my-opencode) Co-authored-by: Sisyphus <clio-agent@sisyphuslabs.ai>
133 lines
3.3 KiB
TypeScript
133 lines
3.3 KiB
TypeScript
/// <reference types="bun-types" />
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import { afterEach, describe, expect, it, mock } from "bun:test"
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const PNG_1X1_DATA_URL =
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"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mNk+M9QDwADhgGAWjR9awAAAABJRU5ErkJggg=="
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type ImageResizerModule = typeof import("./image-resizer")
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async function importFreshImageResizerModule(): Promise<ImageResizerModule> {
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return import(`./image-resizer?test-${Date.now()}-${Math.random()}`)
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}
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describe("calculateTargetDimensions", () => {
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it("returns null when dimensions are already within limits", async () => {
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//#given
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const { calculateTargetDimensions } = await importFreshImageResizerModule()
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//#when
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const result = calculateTargetDimensions(800, 600)
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//#then
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expect(result).toBeNull()
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})
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it("returns null at exact long-edge boundary", async () => {
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//#given
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const { calculateTargetDimensions } = await importFreshImageResizerModule()
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//#when
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const result = calculateTargetDimensions(1568, 1000)
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//#then
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expect(result).toBeNull()
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})
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it("scales landscape dimensions by max long edge", async () => {
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//#given
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const { calculateTargetDimensions } = await importFreshImageResizerModule()
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//#when
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const result = calculateTargetDimensions(3000, 2000)
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//#then
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expect(result).toEqual({
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width: 1568,
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height: Math.floor(2000 * (1568 / 3000)),
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})
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})
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it("scales portrait dimensions by max long edge", async () => {
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//#given
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const { calculateTargetDimensions } = await importFreshImageResizerModule()
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//#when
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const result = calculateTargetDimensions(2000, 3000)
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//#then
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expect(result).toEqual({
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width: Math.floor(2000 * (1568 / 3000)),
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height: 1568,
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})
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})
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it("scales square dimensions to exact target", async () => {
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//#given
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const { calculateTargetDimensions } = await importFreshImageResizerModule()
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//#when
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const result = calculateTargetDimensions(4000, 4000)
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//#then
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expect(result).toEqual({ width: 1568, height: 1568 })
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})
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it("uses custom maxLongEdge when provided", async () => {
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//#given
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const { calculateTargetDimensions } = await importFreshImageResizerModule()
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//#when
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const result = calculateTargetDimensions(2000, 1000, 1000)
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//#then
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expect(result).toEqual({ width: 1000, height: 500 })
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})
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})
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describe("resizeImage", () => {
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afterEach(() => {
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mock.restore()
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})
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it("returns null when sharp import fails", async () => {
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//#given
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mock.module("sharp", () => {
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throw new Error("sharp unavailable")
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})
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const { resizeImage } = await importFreshImageResizerModule()
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//#when
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const result = await resizeImage(PNG_1X1_DATA_URL, "image/png", {
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width: 1,
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height: 1,
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})
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//#then
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expect(result).toBeNull()
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})
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it("returns null when sharp throws during resize", async () => {
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//#given
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const mockSharpFactory = mock(() => ({
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resize: () => {
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throw new Error("resize failed")
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},
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}))
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mock.module("sharp", () => ({
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default: mockSharpFactory,
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}))
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const { resizeImage } = await importFreshImageResizerModule()
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//#when
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const result = await resizeImage(PNG_1X1_DATA_URL, "image/png", {
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width: 1,
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height: 1,
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})
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//#then
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expect(result).toBeNull()
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})
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})
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