mirror of
https://github.com/diegosouzapw/OmniRoute.git
synced 2026-09-09 16:32:12 +03:00
65e81158ab
Landed with the design call resolved per the owner's pick — **option 1**: the synced store is now endpoint-agnostic (persistDiscoveredModels and managedModelImport no longer drop non-chat models at write time), and chat selectability moved to read time (auto-pool expansion in autoStrategy applies filterChatSelectableModels; the models-route projection already had its chatOnly filter). Your discovery test now passes end-to-end (3/3): /api/show capabilities persist per connection and image/embedding requests route through the advertising host. Reconciliation notes: conflicted areas merged onto the current tip (adobe discovery import, requestedModel preflight signature, resolvedProvider fast-path coexists with the synced-route override — explicit resolution wins); carried base-red drains (#10055 memoization, #11071 test variants) dropped as already-landed; the managed-model-import exclusion test was propagated to the new contract (image/video models persist; the read filter still hides them from chat pickers — pinned by a new assertion). Full battery: 205/206 focused (the one red is a confirmed periodic-timer timing flake on the loaded devbox — 20/20 isolated), autoCombo vitest 30/30, combo suites 46/46, gates + typecheck clean. Thank you @yourspraveen — the capability probe + routing design was right; it just needed the store contract opened up. Fixes #11087.
100 lines
3.3 KiB
TypeScript
100 lines
3.3 KiB
TypeScript
// #2071 — CodeBuddy forced reasoning_effort:"medium" + reasoning_summary:"auto"
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// on requests where the client never asked for reasoning, tripping CodeBuddy's
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// content filter ("model return error"). Reasoning params must be opt-in.
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import { describe, it } from "node:test";
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import assert from "node:assert/strict";
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import { CodeBuddyCnExecutor } from "../../open-sse/executors/codebuddy-cn.ts";
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describe("CodeBuddyCnExecutor reasoning params are opt-in (#2071)", () => {
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const exec = new CodeBuddyCnExecutor();
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it("does NOT force reasoning when the client did not request it", () => {
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const out = exec.transformRequest(
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"glm-5.2",
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{ messages: [{ role: "user", content: "hi" }] },
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false,
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{}
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) as Record<string, unknown>;
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assert.equal(out.reasoning_effort, undefined);
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assert.equal(out.reasoning_summary, undefined);
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});
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it("mirrors reasoning_summary:auto when the client explicitly requested reasoning", () => {
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const out = exec.transformRequest(
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"glm-5.2",
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{ messages: [{ role: "user", content: "hi" }], reasoning_effort: "high" },
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false,
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{}
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) as Record<string, unknown>;
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assert.equal(out.reasoning_effort, "high");
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assert.equal(out.reasoning_summary, "auto");
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});
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it("omits reasoning_effort for none/off and adds no reasoning_summary", () => {
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const out = exec.transformRequest(
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"glm-5.2",
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{ messages: [{ role: "user", content: "hi" }], reasoning_effort: "none" },
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false,
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{}
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) as Record<string, unknown>;
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assert.equal(out.reasoning_effort, undefined);
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assert.equal(out.reasoning_summary, undefined);
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});
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it("replaces agent system prompts in top-level system field", () => {
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const out = exec.transformRequest(
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"glm-5.2",
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{
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system: "You are Claude Code, Anthropic's official CLI for software engineering",
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messages: [{ role: "user", content: "check this" }],
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},
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false,
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{}
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) as Record<string, unknown>;
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assert.equal(
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out.system,
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"You are a helpful AI assistant that helps with software engineering tasks.",
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);
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});
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it("preserves non-agent system prompts in top-level system field", () => {
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const out = exec.transformRequest(
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"glm-5.2",
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{
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system: "You are a helpful coding tutor for beginner developers.",
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messages: [{ role: "user", content: "check this" }],
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},
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false,
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{}
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) as Record<string, unknown>;
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assert.equal(out.system, "You are a helpful coding tutor for beginner developers.");
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});
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it("replaces agent system prompts in messages array preserving typed content shape", () => {
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const out = exec.transformRequest(
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"glm-5.2",
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{
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messages: [
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{
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role: "system",
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content: [{ type: "text", text: "You are Cursor, an AI coding agent" }],
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},
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{ role: "user", content: "Hello" },
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],
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},
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false,
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{}
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) as Record<string, unknown>;
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const msgs = out.messages as Array<{ role: string; content?: unknown }>;
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const system = msgs.find((m) => m.role === "system");
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assert.deepEqual(system, {
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role: "system",
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content: [{ type: "text", text: "You are a helpful AI assistant that helps with software engineering tasks." }],
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});
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assert.equal(system && (system as { content?: unknown }).content, msgs[0].content);
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});
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});
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