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d9834a7a15 |
@@ -233,14 +233,13 @@ keep it or `git checkout` to throw it away. Nothing is committed for you.
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**For a skill that ships with gbrain** (anything under the gbrain repo's own
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`skills/`): SkillOpt refuses to overwrite it by default and writes the winner to
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`skills/<name>/skillopt/proposed.md` instead (while keeping `best.md` as the
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optimizer's current-best pointer), so an optimization pass can never silently
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mutate a skill other people depend on. Two ways to handle that:
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`skills/<name>/skillopt/best.md` instead, so an optimization pass can never
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silently mutate a skill other people depend on. Two ways to handle that:
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```bash
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# See the proposed improvement without touching SKILL.md (works for ANY skill):
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gbrain skillopt meeting-prep --split 1:1:1 --no-mutate
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# → writes skills/meeting-prep/skillopt/proposed.md, updates best.md, and prints the proposal path.
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# → writes skills/meeting-prep/skillopt/best.md (the proposed rewrite), prints its path. Copy what you want.
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# Actually rewrite a bundled skill (explicit opt-in + an independent held-out set):
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gbrain skillopt brain-ops --split 1:1:1 --allow-mutate-bundled \
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@@ -56,6 +56,36 @@ export const litellmProxy: Recipe = {
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cost_per_1m_output_usd: undefined,
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price_last_verified: '2026-06-14',
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},
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// LiteLLM normalizes Cohere / Voyage / Jina / etc. rerank backends to the
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// same wire shape gbrain's gateway.rerank() already speaks (the
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// ZeroEntropy/llama.cpp contract):
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// { model, query, documents, top_n } → { results: [{ index, relevance_score }] }
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// So any rerank model the user registers in their LiteLLM config is
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// reachable via `gbrain config set search.reranker.model litellm:<model>`
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// with no request/response adapter — same as embeddings ride the proxy.
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reranker: {
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models: [], // user-provided; whatever rerank models the proxy serves
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// No canonical default — the proxy defines its own model ids. The user
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// sets search.reranker.model explicitly (mirrors the embedding
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// touchpoint's user_provided_models contract).
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default_model: '',
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// The proxied backend bills (Cohere/Voyage/…); pricing-unknown is the
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// honest state — same stance as this recipe's embedding/chat
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// touchpoints and budget-tracker's deliberate litellm exclusion from
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// the free-provider sets.
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cost_per_1m_tokens_usd: undefined,
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price_last_verified: '2026-06-27',
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max_payload_bytes: 5_000_000,
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// LEAF path only (matches llama-server-reranker's convention). LiteLLM
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// serves both `/rerank` and `/v1/rerank`, and LITELLM_BASE_URL may be
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// set with or without the `/v1` suffix (the setup_hint allows both), so
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// the leaf form yields a valid route either way:
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// http://localhost:4000 + /rerank → /rerank ✓
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// http://localhost:4000/v1 + /rerank → /v1/rerank ✓
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// Pinning '/v1/rerank' here would double to /v1/v1/rerank → 404 on
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// /v1-suffixed bases.
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path: '/rerank',
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},
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},
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setup_hint: 'Run LiteLLM (https://docs.litellm.ai) in front of any provider; set LITELLM_BASE_URL (include the /v1 suffix if your proxy serves the OpenAI route there, e.g. http://localhost:4000/v1) + pass --embedding-model litellm:<model> and --embedding-dimensions <N>.',
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setup_hint: 'Run LiteLLM (https://docs.litellm.ai) in front of any provider; set LITELLM_BASE_URL (include the /v1 suffix if your proxy serves the OpenAI route there, e.g. http://localhost:4000/v1) + pass --embedding-model litellm:<model> and --embedding-dimensions <N>. For rerank: register a rerank model in LiteLLM and set search.reranker.model litellm:<model-name>.',
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};
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@@ -93,13 +93,7 @@ import { resolveLrSchedule } from './lr-schedule.ts';
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import { preflight, formatPreflightReport } from './preflight.ts';
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import { isRejected, loadRejectedBuffer, makeRejectedEntry, saveRejectedBuffer } from './rejected-buffer.ts';
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import { runReflect, runOneShotRewrite, describeJudges } from './reflect.ts';
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import {
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acceptCandidate,
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proposedPath as proposedFilePath,
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revertAllPending,
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skillPath,
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writeProposed,
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} from './version-store.ts';
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import { acceptCandidate, bestPath, revertAllPending, skillPath, writeProposed } from './version-store.ts';
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import { runValidationGate, scoreSkillOnTasks } from './validate-gate.ts';
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import { ROLLOUT_SUCCESS_THRESHOLD } from './types.ts';
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import type { SkillOptOpts, EditOp, RunReceipt, BenchmarkTask } from './types.ts';
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@@ -708,9 +702,9 @@ async function runOptimizationLoop(
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// to the catch's assignment values only (it can't prove the async callback ran).
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const finalOutcome = outcome as 'accepted' | 'no_improvement' | 'aborted' | 'errored';
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if (!mutateDecision.mutate && finalOutcome === 'accepted') {
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// writeProposed() emitted both the best pointer and the stable review
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// artifact in the accept branch. SKILL.md remains untouched.
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proposedPath = proposedFilePath(skillsDir, skillName);
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// best.md was written by writeProposed() in the accept branch (no-mutate
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// path); it doubles as proposed.md for human review. SKILL.md untouched.
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proposedPath = bestPath(skillsDir, skillName);
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} else if (mutateDecision.mutate) {
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mutatedSkillFile = finalOutcome === 'accepted';
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}
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@@ -23,7 +23,6 @@
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*
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* history.json
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* best.md
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* proposed.md
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* versions/
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* v0001_e1_s1.md
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* v0002_e1_s2.md
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@@ -53,10 +52,6 @@ export function bestPath(skillsDir: string, skillName: string): string {
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return path.join(skilloptDir(skillsDir, skillName), 'best.md');
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}
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export function proposedPath(skillsDir: string, skillName: string): string {
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return path.join(skilloptDir(skillsDir, skillName), 'proposed.md');
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}
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export function skillPath(skillsDir: string, skillName: string): string {
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return path.join(skillsDir, skillName, 'SKILL.md');
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}
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@@ -176,18 +171,17 @@ export function acceptCandidate(input: AcceptInput): AcceptResult {
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}
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/**
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* Write the candidate to both `best.md` and `proposed.md` WITHOUT touching
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* SKILL.md or the history ledger. `best.md` remains the optimizer's current
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* best pointer; `proposed.md` is the stable human-review artifact promised by
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* `--no-mutate`. Returns the proposal path. Each write is atomic (.tmp + rename).
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* Write the candidate to `best.md` (which doubles as `proposed.md`) WITHOUT
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* touching SKILL.md or the history ledger. Used by the `--no-mutate` /
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* bundled-without-allow paths: the optimizer found a better candidate but the
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* caller opted out of in-place mutation, so we surface it for human review.
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* Returns the path written. Atomic (.tmp + rename).
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*/
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export function writeProposed(skillsDir: string, skillName: string, candidateText: string): string {
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const best = bestPath(skillsDir, skillName);
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const proposed = proposedPath(skillsDir, skillName);
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fs.mkdirSync(path.dirname(best), { recursive: true });
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atomicWrite(best, candidateText);
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atomicWrite(proposed, candidateText);
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return proposed;
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const p = bestPath(skillsDir, skillName);
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fs.mkdirSync(path.dirname(p), { recursive: true });
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atomicWrite(p, candidateText);
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return p;
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}
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/**
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@@ -0,0 +1,88 @@
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/**
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* litellm-proxy reranker touchpoint smoke.
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*
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* Sibling of recipe-llama-server-reranker.test.ts. Pins the reranker
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* touchpoint on the LiteLLM proxy recipe so:
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* - the touchpoint exists with the LEAF '/rerank' path (LiteLLM serves both
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* /rerank and /v1/rerank, so the leaf form is valid whether or not the
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* user's LITELLM_BASE_URL carries the /v1 suffix the setup_hint allows)
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* - a /v1-suffixed base URL does NOT produce /v1/v1/rerank (the original
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* community PR pinned '/v1/rerank' which 404s on /v1-suffixed bases)
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* - models: [] (user-provided; proxy defines the model ids)
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* - pricing stays undefined (proxy can front a paid provider — same honest
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* pricing-unknown stance as the embedding/chat touchpoints)
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*
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* The gateway.rerank() URL tests drive the real URL builder via the stubbed
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* transport (same seam as test/ai/rerank.test.ts).
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*/
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import { describe, expect, test, afterEach } from 'bun:test';
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import { getRecipe } from '../../src/core/ai/recipes/index.ts';
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import {
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configureGateway,
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resetGateway,
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rerank,
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__setRerankTransportForTests,
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} from '../../src/core/ai/gateway.ts';
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afterEach(() => {
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__setRerankTransportForTests(null);
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resetGateway();
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});
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describe('recipe: litellm reranker touchpoint', () => {
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test('declares reranker touchpoint with leaf /rerank path', () => {
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const r = getRecipe('litellm')!;
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const tp = r.touchpoints.reranker;
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expect(tp).toBeDefined();
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expect(tp!.path).toBe('/rerank');
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expect(tp!.max_payload_bytes).toBe(5_000_000);
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});
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test('reranker touchpoint uses empty models[] for user-provided model ids', () => {
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const r = getRecipe('litellm')!;
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expect(r.touchpoints.reranker!.models).toEqual([]);
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});
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test('pricing stays undefined — proxy can front a paid provider', () => {
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const r = getRecipe('litellm')!;
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expect(r.touchpoints.reranker!.cost_per_1m_tokens_usd).toBeUndefined();
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});
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test('setup_hint keeps the /v1-suffix guidance AND mentions rerank', () => {
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const r = getRecipe('litellm')!;
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expect(r.setup_hint).toMatch(/\/v1 suffix/);
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expect(r.setup_hint).toMatch(/search\.reranker\.model litellm:/);
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});
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});
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describe('gateway.rerank() URL via litellm recipe', () => {
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async function capturedRerankUrl(baseUrl?: string): Promise<string> {
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configureGateway({
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reranker_model: 'litellm:my-reranker',
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env: {},
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...(baseUrl ? { base_urls: { litellm: baseUrl } } : {}),
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});
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let capturedUrl = '';
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__setRerankTransportForTests(async (url) => {
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capturedUrl = url;
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return new Response(
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JSON.stringify({ results: [{ index: 0, relevance_score: 0.9 }] }),
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{ status: 200, headers: { 'content-type': 'application/json' } },
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);
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});
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await rerank({ query: 'q', documents: ['d'] });
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return capturedUrl;
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}
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test('default base (no /v1 suffix) → /rerank', async () => {
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const url = await capturedRerankUrl();
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expect(url).toBe('http://localhost:4000/rerank');
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});
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test('/v1-suffixed base → /v1/rerank, NOT /v1/v1/rerank', async () => {
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const url = await capturedRerankUrl('http://localhost:4000/v1');
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expect(url).toBe('http://localhost:4000/v1/rerank');
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expect(url).not.toContain('/v1/v1/');
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});
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});
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@@ -39,7 +39,6 @@ import { runSkillOpt } from '../../src/core/skillopt/orchestrator.ts';
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import {
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bestPath,
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loadHistory,
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proposedPath,
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skillPath,
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} from '../../src/core/skillopt/version-store.ts';
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import { loadRejectedBuffer } from '../../src/core/skillopt/rejected-buffer.ts';
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@@ -742,7 +741,7 @@ describe('skillopt T3 — F11 held-out gate, ablation opts, no-DB-pollution', ()
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} finally { fixture.cleanup(); }
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});
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test('--no-mutate writes proposed.md and best.md, leaves SKILL.md untouched', async () => {
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test('--no-mutate writes proposed.md (best.md), leaves SKILL.md untouched', async () => {
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const fixture = setupFixture(SKILL_PEOPLE_ONLY, CITATIONS_BENCHMARK);
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try {
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installStub({
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@@ -754,9 +753,10 @@ describe('skillopt T3 — F11 held-out gate, ablation opts, no-DB-pollution', ()
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const result = await runOnce(fixture, { noMutate: true });
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expect(result.outcome).toBe('accepted');
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expect(result.mutatedSkillFile).toBe(false);
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expect(result.proposedPath).toBe(proposedPath(fixture.skillsDir, SKILL));
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expect(result.proposedPath).toBeDefined();
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// proposed.md (best.md) exists and carries the improvement.
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expect(fs.existsSync(result.proposedPath!)).toBe(true);
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expect(fs.readFileSync(result.proposedPath!, 'utf8')).toContain('## Citations');
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expect(fs.readFileSync(bestPath(fixture.skillsDir, SKILL), 'utf8')).toContain('## Citations');
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// SKILL.md on disk is UNCHANGED (still People-only).
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const skill = fs.readFileSync(skillPath(fixture.skillsDir, SKILL), 'utf8');
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expect(skill).not.toContain('## Citations');
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@@ -12,11 +12,9 @@ import {
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bestPath,
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historyPath,
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loadHistory,
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proposedPath,
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revertAllPending,
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skillPath,
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versionsDir,
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writeProposed,
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} from '../../src/core/skillopt/version-store.ts';
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let tmpDir: string;
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@@ -81,19 +79,6 @@ describe('acceptCandidate (D8 two-phase commit)', () => {
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});
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});
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describe('writeProposed', () => {
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test('writes distinct best and proposed artifacts without mutating SKILL.md (#2635)', () => {
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const candidate = '---\nname: test\n---\nproposed body\n';
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const written = writeProposed(tmpDir, SKILL, candidate);
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expect(written).toBe(proposedPath(tmpDir, SKILL));
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expect(fs.readFileSync(bestPath(tmpDir, SKILL), 'utf8')).toBe(candidate);
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expect(fs.readFileSync(proposedPath(tmpDir, SKILL), 'utf8')).toBe(candidate);
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expect(fs.readFileSync(skillPath(tmpDir, SKILL), 'utf8')).toContain('baseline body');
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});
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});
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describe('revertAllPending (D8 crash recovery)', () => {
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test('no-op when no pending rows', () => {
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const reverted = revertAllPending(tmpDir, SKILL);
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Reference in New Issue
Block a user