Files
MeshBot/src/llm/llm.service.spec.ts
T
kamilkrzywda c5a2815c01
CI / build + unit (pull_request) Successful in 1m14s
Add OpenAI-compatible LLM client service (v0.19.0)
LlmService wraps the local OpenAI-compatible server (default
http://192.168.1.70:1111/v1, no auth) with native fetch only — no new
dependencies. listModels() -> data[].id; chat(messages, opts?) ->
choices[0].message.content (non-2xx throws with status + body snippet);
summarize(text) = chat() with a concise-summary system prompt.

Env: LLM_API_BASE / LLM_MODEL (qwen3.8-27b) / LLM_TIMEOUT_MS (60000,
AbortSignal.timeout). Plain feature module wired into app.module.ts;
docs synced (AGENTS.md, README env list).
2026-09-25 18:07:21 +00:00

105 lines
3.1 KiB
TypeScript

import { afterEach, beforeEach, describe, expect, it, vi } from 'vitest';
import type { ChatMessage } from './llm.service.js';
import { LlmService } from './llm.service.js';
const BASE = 'http://192.168.1.70:1111/v1';
function json(body: unknown): Response {
return { ok: true, status: 200, json: async () => body } as Response;
}
/** Fresh service with a clean env (explicit base/model/timeout). */
function makeService(): LlmService {
process.env.LLM_API_BASE = BASE;
process.env.LLM_MODEL = 'qwen3.8-27b';
process.env.LLM_TIMEOUT_MS = '60000';
return new LlmService();
}
describe('LlmService', () => {
let fetchMock: ReturnType<typeof vi.fn>;
beforeEach(() => {
fetchMock = vi.fn();
vi.stubGlobal('fetch', fetchMock);
});
afterEach(() => {
vi.unstubAllGlobals();
for (const k of ['LLM_API_BASE', 'LLM_MODEL', 'LLM_TIMEOUT_MS'])
delete process.env[k];
});
it('listModels returns the data[].id strings from GET /models', async () => {
const svc = makeService();
fetchMock.mockResolvedValueOnce(
json({
data: [
{ id: 'qwen3.8-27b' },
{ id: 'text-embedding-nomic-embed-text-v1.5' },
],
}),
);
await expect(svc.listModels()).resolves.toEqual([
'qwen3.8-27b',
'text-embedding-nomic-embed-text-v1.5',
]);
expect(fetchMock).toHaveBeenCalledTimes(1);
expect(fetchMock.mock.calls[0][0]).toBe(`${BASE}/models`);
});
it('chat posts model+messages and returns choices[0].message.content', async () => {
const svc = makeService();
fetchMock.mockResolvedValueOnce(
json({ choices: [{ message: { content: 'hello back' } }] }),
);
const messages: ChatMessage[] = [
{ role: 'system', content: 'be brief' },
{ role: 'user', content: 'hi' },
];
await expect(
svc.chat(messages, { maxTokens: 50, temperature: 0.2 }),
).resolves.toBe('hello back');
const [url, init] = fetchMock.mock.calls[0];
expect(url).toBe(`${BASE}/chat/completions`);
expect(init.method).toBe('POST');
expect(JSON.parse(init.body)).toEqual({
model: 'qwen3.8-27b',
messages,
maxTokens: 50,
temperature: 0.2,
});
});
it('chat throws on non-2xx with the HTTP status in the message', async () => {
const svc = makeService();
fetchMock.mockResolvedValueOnce({
ok: false,
status: 503,
text: async () => 'upstream down',
} as Response);
await expect(svc.chat([{ role: 'user', content: 'hi' }])).rejects.toThrow(
/HTTP 503.*upstream down/,
);
});
it('summarize calls chat with the system prompt plus the user text', async () => {
const svc = makeService();
fetchMock.mockResolvedValueOnce(
json({ choices: [{ message: { content: 'the summary' } }] }),
);
await expect(svc.summarize('a long text')).resolves.toBe('the summary');
const [, init] = fetchMock.mock.calls[0];
expect(JSON.parse(init.body).messages).toEqual([
{ role: 'system', content: 'Summarize the following text concisely.' },
{ role: 'user', content: 'a long text' },
]);
});
});