90a70c8404
CI / python-lint (push) Has been skipped
CI / nodejs-lint (push) Has been skipped
CI / iace-gt-coverage (push) Has been skipped
CI / test-python-backend (push) Has been skipped
CI / test-python-document-crawler (push) Has been skipped
CI / test-python-dsms-gateway (push) Has been skipped
CI / detect-changes (push) Successful in 7s
CI / branch-name (push) Has been skipped
CI / guardrail-integrity (push) Has been skipped
CI / secret-scan (push) Has been skipped
CI / dep-audit (push) Has been skipped
CI / sbom-scan (push) Has been skipped
CI / build-sha-integrity (push) Successful in 5s
CI / validate-canonical-controls (push) Successful in 4s
CI / loc-budget (push) Successful in 17s
CI / go-lint (push) Has been skipped
CI / nodejs-build (push) Successful in 3m2s
CI / test-go (push) Has been skipped
Die Drafting-Engine (Dokument-Entwurf, v2-Pipeline, Validierung, Drafting-Chat, Vendor-Vertragspruefung) war auf prod doppelt tot: - RAG ueber bp-core-rag-service:8097 (existiert auf prod nicht) - LLM ueber OLLAMA_URL/api/chat mit qwen2.5vl (prod = ollama-embed, kein Chat-Modell) Fix (analog zum Compliance-Advisor): - rag-query.ts -> ai-compliance-sdk /sdk/v1/rag/search (bge-m3, prod-erreichbar). - Neue lib/sdk/drafting-engine/llm-cascade.ts: OVH/LiteLLM (gpt-oss-120b) zuerst, Ollama als Dev-Fallback; cascadeComplete (JSON) + cascadeStream. Das Backend nutzt OVH+JSON bereits erfolgreich auf prod (extract-datasheet). - 5 Aufrufstellen (draft-helpers, draft-helpers-v2, validate, chat, vendor-review) auf die Kaskade umgestellt; keine direkten Ollama-Calls mehr. - Tests: llm-cascade + rag-query aktualisiert. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
82 lines
3.2 KiB
TypeScript
82 lines
3.2 KiB
TypeScript
/**
|
|
* Tests fuer die Drafting-Engine LLM-Kaskade (OVH -> Ollama) + Stream-Parser.
|
|
*/
|
|
|
|
import { describe, it, expect, beforeEach, afterEach, vi } from 'vitest'
|
|
|
|
const mockFetch = vi.fn()
|
|
vi.stubGlobal('fetch', mockFetch)
|
|
|
|
describe('llm-cascade parser', () => {
|
|
it('parseOllamaLine extrahiert message.content', async () => {
|
|
const { parseOllamaLine } = await import('../llm-cascade')
|
|
expect(parseOllamaLine('{"message":{"content":"X"}}')).toBe('X')
|
|
expect(parseOllamaLine('')).toBeNull()
|
|
expect(parseOllamaLine('kaputt')).toBeNull()
|
|
})
|
|
|
|
it('parseSSELine extrahiert delta.content', async () => {
|
|
const { parseSSELine } = await import('../llm-cascade')
|
|
expect(parseSSELine('data: {"choices":[{"delta":{"content":"Y"}}]}')).toBe('Y')
|
|
expect(parseSSELine('data: [DONE]')).toBeNull()
|
|
expect(parseSSELine('event: ping')).toBeNull()
|
|
})
|
|
})
|
|
|
|
describe('cascadeComplete', () => {
|
|
beforeEach(() => {
|
|
vi.resetModules()
|
|
mockFetch.mockReset()
|
|
})
|
|
afterEach(() => {
|
|
vi.unstubAllEnvs()
|
|
})
|
|
|
|
it('nutzt OVH zuerst wenn konfiguriert (json + response_format)', async () => {
|
|
vi.stubEnv('OVH_LLM_URL', 'https://ovh.test')
|
|
vi.stubEnv('OVH_LLM_MODEL', 'gpt-oss-120b')
|
|
vi.stubEnv('OVH_LLM_KEY', 'k')
|
|
const { cascadeComplete } = await import('../llm-cascade')
|
|
mockFetch.mockResolvedValueOnce({
|
|
ok: true,
|
|
json: async () => ({ choices: [{ message: { content: '{"ok":1}' } }], usage: { completion_tokens: 42 } }),
|
|
})
|
|
const r = await cascadeComplete([{ role: 'user', content: 'hi' }], { json: true, maxTokens: 1000 })
|
|
expect(r).toEqual({ content: '{"ok":1}', tokensUsed: 42, provider: 'ovh' })
|
|
const [url, opts] = mockFetch.mock.calls[0]
|
|
expect(url).toContain('/v1/chat/completions')
|
|
const body = JSON.parse(opts.body)
|
|
expect(body.response_format).toEqual({ type: 'json_object' })
|
|
expect(body.stream).toBe(false)
|
|
})
|
|
|
|
it('faellt auf Ollama zurueck wenn OVH nicht konfiguriert ist', async () => {
|
|
const { cascadeComplete } = await import('../llm-cascade')
|
|
mockFetch.mockResolvedValueOnce({
|
|
ok: true,
|
|
json: async () => ({ message: { content: 'hallo' }, eval_count: 7 }),
|
|
})
|
|
const r = await cascadeComplete([{ role: 'user', content: 'hi' }])
|
|
expect(r).toEqual({ content: 'hallo', tokensUsed: 7, provider: 'ollama' })
|
|
expect(mockFetch.mock.calls[0][0]).toContain('/api/chat')
|
|
})
|
|
|
|
it('faellt auf Ollama zurueck wenn OVH einen Fehler liefert', async () => {
|
|
vi.stubEnv('OVH_LLM_URL', 'https://ovh.test')
|
|
vi.stubEnv('OVH_LLM_MODEL', 'gpt-oss-120b')
|
|
const { cascadeComplete } = await import('../llm-cascade')
|
|
mockFetch
|
|
.mockResolvedValueOnce({ ok: false, status: 502 })
|
|
.mockResolvedValueOnce({ ok: true, json: async () => ({ message: { content: 'fallback' }, eval_count: 3 }) })
|
|
const r = await cascadeComplete([{ role: 'user', content: 'hi' }])
|
|
expect(r?.provider).toBe('ollama')
|
|
expect(r?.content).toBe('fallback')
|
|
})
|
|
|
|
it('liefert null wenn weder OVH noch Ollama antworten', async () => {
|
|
const { cascadeComplete } = await import('../llm-cascade')
|
|
mockFetch.mockResolvedValue({ ok: false, status: 500 })
|
|
expect(await cascadeComplete([{ role: 'user', content: 'hi' }])).toBeNull()
|
|
})
|
|
})
|