mirror of
https://gitea.toothfairyai.com/ToothFairyAI/tf_code.git
synced 2026-03-30 13:54:01 +00:00
a8b73fd754
- Rename packages/opencode → packages/tfcode (directory only) - Rename bin/opencode → bin/tfcode (CLI binary) - Rename .opencode → .tfcode (config directory) - Update package.json name and bin field - Update config directory path references (.tfcode) - Keep internal code references as 'opencode' for easy upstream sync - Keep @opencode-ai/* workspace package names This minimal branding approach allows clean merges from upstream opencode repository while providing tfcode branding for users.
102 lines
3.5 KiB
TypeScript
102 lines
3.5 KiB
TypeScript
import { describe, expect, test } from "bun:test"
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import path from "path"
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import { Instance } from "../../src/project/instance"
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import { WebFetchTool } from "../../src/tool/webfetch"
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import { SessionID, MessageID } from "../../src/session/schema"
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const projectRoot = path.join(import.meta.dir, "../..")
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const ctx = {
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sessionID: SessionID.make("ses_test"),
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messageID: MessageID.make("message"),
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callID: "",
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agent: "build",
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abort: AbortSignal.any([]),
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messages: [],
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metadata: () => {},
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ask: async () => {},
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}
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async function withFetch(
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mockFetch: (input: string | URL | Request, init?: RequestInit) => Promise<Response>,
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fn: () => Promise<void>,
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) {
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const originalFetch = globalThis.fetch
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globalThis.fetch = mockFetch as unknown as typeof fetch
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try {
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await fn()
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} finally {
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globalThis.fetch = originalFetch
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}
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}
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describe("tool.webfetch", () => {
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test("returns image responses as file attachments", async () => {
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const bytes = new Uint8Array([137, 80, 78, 71, 13, 10, 26, 10])
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await withFetch(
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async () => new Response(bytes, { status: 200, headers: { "content-type": "IMAGE/PNG; charset=binary" } }),
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async () => {
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await Instance.provide({
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directory: projectRoot,
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fn: async () => {
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const webfetch = await WebFetchTool.init()
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const result = await webfetch.execute({ url: "https://example.com/image.png", format: "markdown" }, ctx)
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expect(result.output).toBe("Image fetched successfully")
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expect(result.attachments).toBeDefined()
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expect(result.attachments?.length).toBe(1)
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expect(result.attachments?.[0].type).toBe("file")
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expect(result.attachments?.[0].mime).toBe("image/png")
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expect(result.attachments?.[0].url.startsWith("data:image/png;base64,")).toBe(true)
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expect(result.attachments?.[0]).not.toHaveProperty("id")
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expect(result.attachments?.[0]).not.toHaveProperty("sessionID")
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expect(result.attachments?.[0]).not.toHaveProperty("messageID")
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},
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})
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},
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)
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})
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test("keeps svg as text output", async () => {
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const svg = '<svg xmlns="http://www.w3.org/2000/svg"><text>hello</text></svg>'
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await withFetch(
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async () =>
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new Response(svg, {
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status: 200,
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headers: { "content-type": "image/svg+xml; charset=UTF-8" },
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}),
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async () => {
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await Instance.provide({
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directory: projectRoot,
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fn: async () => {
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const webfetch = await WebFetchTool.init()
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const result = await webfetch.execute({ url: "https://example.com/image.svg", format: "html" }, ctx)
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expect(result.output).toContain("<svg")
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expect(result.attachments).toBeUndefined()
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},
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})
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},
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)
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})
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test("keeps text responses as text output", async () => {
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await withFetch(
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async () =>
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new Response("hello from webfetch", {
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status: 200,
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headers: { "content-type": "text/plain; charset=utf-8" },
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}),
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async () => {
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await Instance.provide({
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directory: projectRoot,
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fn: async () => {
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const webfetch = await WebFetchTool.init()
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const result = await webfetch.execute({ url: "https://example.com/file.txt", format: "text" }, ctx)
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expect(result.output).toBe("hello from webfetch")
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expect(result.attachments).toBeUndefined()
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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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