HomerandClaude Opus 5.5
28ff205ed0
LLeMbas CLI 2.0 is LLeMbas-server-specific (CLI rule 2). Removed: the anthropic, gemini, ollama and responses clients, context discovery and llama-swap unloading (discover.ts), the Connection schema with its dialect, auth, key_cmd, discover, unload_url and one_model_at_a_time, the model `fallback` (it only ever moved to another server), effort_map and cache, and the multi-connection refs. Kept: openai-chat, http, sse, think, effort, tokens and all of src/lembas. - connections.yaml holds the login (`type: webui`, as lembas login writes it). A custom entry from 1.x is read past with a warning that says how to log in, so an old file still starts; with several logins left, the latest is used and the others named. - A model's ref is the id the server serves it under; the older forms (`<login>/<id>`, `<login>/<model>`) still resolve and config.yaml is rewritten once. Without a login there is no model, and the error (and the first-run screen, now the sign-in alone) says `lembas login <address>`. - A login to another server signs this machine out of the previous one. - The window is the server's word (no discovery); a capacity group comes from the server's `capacity.group` alone; embeddings use the server's /v1/embeddings. - `lembas models` lists the server's models; install.sh's starter files, the README and the JSON schemas say the same. Tests: every fixture is a login now (the fake server lists models, answers other GETs with 404, and can hand one model to another script, as a server with several backends); the dialect suites and the cross-connection tests are gone with their code. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
65 lines
3.4 KiB
TypeScript
65 lines
3.4 KiB
TypeScript
import { afterEach, describe, expect, test } from "bun:test"
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import { mkdirSync, mkdtempSync, writeFileSync } from "node:fs"
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import { tmpdir } from "node:os"
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import { join } from "node:path"
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import { createApp } from "../src/app.ts"
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import type { AskReply } from "../src/bus/index.ts"
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import { paths } from "../src/config/paths.ts"
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import { attachmentsFor } from "../src/project/attach.ts"
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import { delta, fakeProvider, toolCall, type Fake } from "./fake-provider.ts"
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// A 1×1 PNG.
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const PNG = Buffer.from("iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mP8z8BQDwAEhQGAhKmMIQAAAABJRU5ErkJggg==", "base64")
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let fake: Fake | undefined
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afterEach(() => fake?.stop())
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function project() {
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const root = mkdtempSync(join(tmpdir(), "ph-img-"))
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writeFileSync(join(root, "shot.png"), PNG)
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return root
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}
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describe("images", () => {
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test("@image: attached as an image with vision; without, the model is told why not", () => {
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const root = project()
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const ctx = { root, cwd: root, readFiles: new Set<string>(), fileStamps: new Map() }
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const [withVision] = attachmentsFor("look at @shot.png", ctx, true)
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expect(withVision!.image).toEqual({ type: "image", mime: "image/png", data: PNG.toString("base64") })
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const [without] = attachmentsFor("look at @shot.png", ctx, false)
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expect(without!.image).toBeUndefined()
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expect(without!.text).toContain("not attached: this model has no vision")
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})
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function setup(vision: boolean, script: Parameters<typeof fakeProvider>[0]) {
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fake = fakeProvider(script)
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mkdirSync(paths.config, { recursive: true })
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writeFileSync(join(paths.config, "connections.yaml"), `connections:\n f:\n type: webui\n url: ${fake.url}\n models:\n f/m: { vision: ${vision} }\n`, { mode: 0o600 })
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writeFileSync(join(paths.config, "config.yaml"), "model: f/m\n")
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return createApp({ cwd: project(), mode: "edit", store: false, asker: { ask: async (): Promise<AskReply> => ({ kind: "once" }) } })
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}
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test("view_image: offered only with vision; the image follows the tool results as a user turn", async () => {
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const blind = setup(false, [{ chunks: [delta({ content: "ok" })] }])
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await blind.engine.prompt("hi")
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expect(fake!.requests[0].tools.map((t: any) => t.function.name)).not.toContain("view_image")
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fake!.stop()
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const app = setup(true, [{ chunks: [toolCall(0, "c1", "view_image", '{"path":"shot.png"}')] }, { chunks: [delta({ content: "A single pixel." })] }])
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await app.engine.prompt("what is in shot.png?")
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expect(fake!.requests[0].tools.map((t: any) => t.function.name)).toContain("view_image")
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const msgs = fake!.requests[1].messages
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expect(msgs.at(-2)).toMatchObject({ role: "tool", tool_call_id: "c1" })
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expect(msgs.at(-1).role).toBe("user")
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expect(msgs.at(-1).content[1]).toEqual({ type: "image_url", image_url: { url: `data:image/png;base64,${PNG.toString("base64")}` } })
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})
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test("a prompt with @image reaches an openai-chat vision model as image_url", async () => {
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const app = setup(true, [{ chunks: [delta({ content: "ok" })] }])
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const { attachmentsFor: att } = await import("../src/project/attach.ts")
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const atts = att("see @shot.png", app.engine.o.toolCtx, true)
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await app.engine.prompt("see @shot.png", atts.flatMap((a) => (a.image ? [a.text, a.image] : [a.text])))
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const content = fake!.requests[0].messages.at(-1).content
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expect(content.map((p: any) => p.type)).toEqual(["text", "text", "image_url"])
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})
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})
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