- Coalesce Qoder's empty finish-in-delta frame with the later choices:[] usage frame so OpenAI and Claude clients receive prompt_tokens, completion_tokens and cache-hit tokens (the dashboard already saw them) - Upload inlined images through /api/v2/image/upload like qodercli, and stub oversized non-image files instead of stuffing 30MB+ data URIs into agent_chat_generation - Emit response.completed -> response.usage for chat-native upstreams so /v1/responses clients (Codex CLI, sub2api) no longer log 0/0/0 - Keep Claude message_delta.usage working when usage arrives without choices[0] - Escalate to the smallest advertised Qoder context tier (200K/400K/1M) when the estimated prompt no longer fits max_input_tokens - Pass apiKey for PAT connections and list hidden enable:false catalog keys from /v1/models
194 lines
7.8 KiB
JavaScript
194 lines
7.8 KiB
JavaScript
/**
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* Qoder context-window tiers + routable model listing.
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*
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* The Qoder IDE lets a user pick 200K / 400K / 1M for a model; qodercli-style
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* requests (what 9router sends) only carry the default max_input_tokens. These
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* tests pin the escalation policy and the payload fields the IDE writes.
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*/
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import { describe, it, expect } from "vitest";
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import {
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parseTierTokenCount,
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getQoderContextTiers,
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estimateQoderPromptTokens,
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resolveQoderContextTier,
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applyQoderContextTier,
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} from "../../open-sse/shared/qoder/contextTier.js";
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import { routableQoderModels } from "../../open-sse/services/qoderModels.js";
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// Shape mirrors the live /algo/api/v2/model/list entry for qmodel_38max.
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const MODEL_CONFIG = {
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key: "qmodel_38max",
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display_name: "Qwen3.8-Max",
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is_reasoning: true,
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max_input_tokens: 180_000,
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max_output_tokens: 32_768,
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context_config: [
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{ name: "200K", tokenCount: 200_000, isDefault: true },
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{ name: "400K", tokenCount: 400_000, isDefault: false },
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{ name: "1M", tokenCount: 1_000_000, isDefault: false },
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],
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};
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function promptOfTokens(n) {
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// ~4 ASCII chars per token
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return { system: "", messages: [{ role: "user", content: "abcd".repeat(n) }], tools: [] };
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}
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describe("parseTierTokenCount", () => {
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it("accepts numbers and K/M suffixed strings", () => {
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expect(parseTierTokenCount(204800)).toBe(204800);
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expect(parseTierTokenCount("200K")).toBe(200_000);
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expect(parseTierTokenCount("1M")).toBe(1_000_000);
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expect(parseTierTokenCount("1.5m")).toBe(1_500_000);
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expect(parseTierTokenCount("131072")).toBe(131072);
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});
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it("returns 0 for garbage", () => {
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expect(parseTierTokenCount(null)).toBe(0);
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expect(parseTierTokenCount("big")).toBe(0);
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expect(parseTierTokenCount(-5)).toBe(0);
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});
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});
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describe("getQoderContextTiers", () => {
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it("sorts tiers ascending and keeps the default flag", () => {
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const tiers = getQoderContextTiers({
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context_config: [
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{ name: "1M", tokenCount: 1_000_000 },
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{ name: "200K", tokenCount: 200_000, isDefault: true },
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],
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});
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expect(tiers.map((t) => t.tokenCount)).toEqual([200_000, 1_000_000]);
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expect(tiers[0].isDefault).toBe(true);
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expect(tiers[1].isDefault).toBe(false);
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});
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it("understands camelCase / snake_case variants and derives names", () => {
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const tiers = getQoderContextTiers({
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contextConfig: [{ token_count: "400K", is_default: true }, { max_input_tokens: 1_000_000 }],
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});
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expect(tiers).toEqual([
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{ name: "400K", tokenCount: 400_000, isDefault: true },
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{ name: "1M", tokenCount: 1_000_000, isDefault: false },
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]);
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});
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it("returns [] when the model has no tiers", () => {
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expect(getQoderContextTiers({ max_input_tokens: 131072 })).toEqual([]);
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expect(getQoderContextTiers(null)).toEqual([]);
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});
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});
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describe("estimateQoderPromptTokens", () => {
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it("counts CJK characters as ~1 token each instead of chars/4", () => {
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const ascii = estimateQoderPromptTokens({ messages: [{ role: "user", content: "a".repeat(4000) }] });
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const cjk = estimateQoderPromptTokens({ messages: [{ role: "user", content: "中".repeat(4000) }] });
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expect(ascii).toBeLessThan(1_200);
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expect(cjk).toBeGreaterThan(4_000);
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});
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});
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describe("resolveQoderContextTier (auto)", () => {
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it("leaves the payload untouched while the prompt fits the current max_input_tokens", () => {
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expect(resolveQoderContextTier(MODEL_CONFIG, promptOfTokens(50_000))).toBeNull();
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});
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it("escalates to the smallest tier that fits once the prompt outgrows the default", () => {
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const choice = resolveQoderContextTier(MODEL_CONFIG, promptOfTokens(250_000));
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expect(choice).not.toBeNull();
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expect(choice.tier.name).toBe("400K");
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expect(choice.reason).toBe("auto:fits");
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expect(choice.estimatedTokens).toBeGreaterThan(240_000);
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});
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it("falls back to the largest tier when nothing fits (upstream decides)", () => {
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const choice = resolveQoderContextTier(MODEL_CONFIG, promptOfTokens(1_200_000));
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expect(choice.tier.name).toBe("1M");
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expect(choice.reason).toBe("auto:largest");
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});
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it("applies headroom so a prompt just under the limit still escalates", () => {
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// 170K estimated * 1.15 = 195.5K > 180K current → smallest tier above the current limit (200K)
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expect(resolveQoderContextTier(MODEL_CONFIG, promptOfTokens(170_000))?.tier.name).toBe("200K");
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// 190K * 1.15 = 218.5K → 200K no longer fits → 400K
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expect(resolveQoderContextTier(MODEL_CONFIG, promptOfTokens(190_000))?.tier.name).toBe("400K");
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});
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it("returns null for models without context_config", () => {
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expect(resolveQoderContextTier({ max_input_tokens: 131072 }, promptOfTokens(500_000))).toBeNull();
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});
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it("never escalates when the current limit is already the largest tier", () => {
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const cfg = { ...MODEL_CONFIG, max_input_tokens: 1_000_000 };
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expect(resolveQoderContextTier(cfg, promptOfTokens(1_500_000))).toBeNull();
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});
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});
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describe("resolveQoderContextTier (forced via QODER_CONTEXT_TIER)", () => {
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it("max picks the largest tier regardless of prompt size", () => {
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const choice = resolveQoderContextTier(MODEL_CONFIG, promptOfTokens(10), { preference: "max" });
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expect(choice.tier.name).toBe("1M");
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expect(choice.reason).toBe("forced:max");
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});
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it("default picks the isDefault tier", () => {
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const choice = resolveQoderContextTier(MODEL_CONFIG, promptOfTokens(10), { preference: "default" });
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expect(choice.tier.name).toBe("200K");
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});
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it("a tier name or token count selects that tier", () => {
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expect(resolveQoderContextTier(MODEL_CONFIG, promptOfTokens(10), { preference: "400k" }).tier.tokenCount).toBe(400_000);
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expect(resolveQoderContextTier(MODEL_CONFIG, promptOfTokens(10), { preference: "1000000" }).tier.name).toBe("1M");
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});
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it("an unknown tier name falls back to auto", () => {
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expect(resolveQoderContextTier(MODEL_CONFIG, promptOfTokens(10), { preference: "9M" })).toBeNull();
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expect(resolveQoderContextTier(MODEL_CONFIG, promptOfTokens(250_000), { preference: "9M" }).tier.name).toBe("400K");
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});
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});
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describe("applyQoderContextTier", () => {
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it("mirrors the tier into the three places the IDE writes", () => {
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const payload = {
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parameters: { max_tokens: 32_768 },
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chat_context: { extra: { context: [], modelConfig: { key: "qmodel_38max" } } },
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model_config: { ...MODEL_CONFIG },
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};
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applyQoderContextTier(payload, { name: "1M", tokenCount: 1_000_000 });
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expect(payload.parameters).toEqual({ max_tokens: 32_768, context_length: 1_000_000 });
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expect(payload.chat_context.extra.ideModelConfigOverride).toEqual({ max_input_tokens: 1_000_000 });
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expect(payload.chat_context.extra.modelConfig).toEqual({ key: "qmodel_38max" });
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expect(payload.model_config.max_input_tokens).toBe(1_000_000);
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expect(payload.model_config.context_config).toHaveLength(3);
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});
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it("is a no-op without a tier", () => {
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const payload = { parameters: { max_tokens: 1 } };
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expect(applyQoderContextTier(payload, null)).toBe(payload);
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expect(payload).toEqual({ parameters: { max_tokens: 1 } });
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});
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});
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describe("routableQoderModels", () => {
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it("lists visible models first, then hidden (enable:false) catalog keys", () => {
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const catalog = {
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models: [{ id: "qmodel_38max", name: "Qwen3.8-Max" }],
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rawConfigs: new Map([
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["qmodel_38max", { key: "qmodel_38max", enable: true }],
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["qfmodel", { key: "qfmodel", enable: false, display_name: "Qwen Fast" }],
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["dmodel", { key: "dmodel", enable: false }],
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]),
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};
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expect(routableQoderModels(catalog)).toEqual([
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{ id: "qmodel_38max", name: "Qwen3.8-Max", hidden: false },
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{ id: "qfmodel", name: "Qwen Fast", hidden: true },
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{ id: "dmodel", name: "dmodel", hidden: true },
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]);
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});
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it("returns [] for a failed catalog fetch", () => {
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expect(routableQoderModels(null)).toEqual([]);
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});
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});
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