Files
oh-my-pi/packages/coding-agent/test/model-resolver.test.ts
T
can1357 e78e936fb6 feat(coding-agent): kept retired variant-id selectors resolving after catalog collapsing
- Resolved retired effort-tier variant ids in `model-resolver.ts` through the hand-table aliases (`resolveVariantAlias`, `resolveBareVariantAlias`) plus the `X-thinking` → `X` grammar (`stripThinkingVariantToken`), with exact matches always winning while a raw id is live and explicit `:effort` suffixes transferring unchanged.
- Re-keyed models.yml `modelOverrides` and rate-limit selector suppressions from raw member ids onto the collapsed model in `model-registry.ts` (`normalizeSuppressedSelector`, lazy `hasLiveModel` checks so live raw ids keep their own overrides).
- Collapsed custom/config provider model lists at registry rebuild via `collapseBuiltModelVariants`, folding config-defined `X`/`X-thinking` twins into one entry.
- Extended `model-registry.test.ts` and `model-resolver.test.ts` with effort-tier variant collapsing and alias-resolution coverage.
2026-06-12 07:37:26 +02:00

1254 lines
45 KiB
TypeScript

import { describe, expect, test } from "bun:test";
import { type Api, Effort, type Model } from "@oh-my-pi/pi-ai";
import { buildModel } from "@oh-my-pi/pi-catalog/build";
import type { CanonicalModelVariant } from "@oh-my-pi/pi-coding-agent/config/model-registry";
import {
expandRoleAlias,
filterAvailableModelsByEnabledPatterns,
parseModelPattern,
parseModelString,
resolveAgentModelPatterns,
resolveCliModel,
resolveModelFromString,
resolveModelOverride,
resolveModelRoleValue,
resolveModelScope,
} from "@oh-my-pi/pi-coding-agent/config/model-resolver";
import { Settings } from "@oh-my-pi/pi-coding-agent/config/settings";
// Mock models for testing
const mockModels: Model<"anthropic-messages">[] = [
buildModel({
id: "claude-sonnet-4-5",
name: "Claude Sonnet 4.5",
api: "anthropic-messages",
provider: "anthropic",
baseUrl: "https://api.anthropic.com",
reasoning: true,
thinking: {
mode: "budget",
efforts: [Effort.Minimal, Effort.Low, Effort.Medium, Effort.High],
},
input: ["text", "image"],
cost: { input: 3, output: 15, cacheRead: 0.3, cacheWrite: 3.75 },
contextWindow: 200000,
maxTokens: 8192,
}),
buildModel({
id: "gpt-4o",
name: "GPT-4o",
api: "anthropic-messages", // Using same type for simplicity
provider: "openai",
baseUrl: "https://api.openai.com",
reasoning: false,
input: ["text", "image"],
cost: { input: 5, output: 15, cacheRead: 0.5, cacheWrite: 5 },
contextWindow: 128000,
maxTokens: 4096,
}),
];
// Mock OpenRouter models with colons in IDs
const mockOpenRouterModels: Model<Api>[] = [
buildModel({
id: "qwen/qwen3-coder:exacto",
name: "Qwen3 Coder Exacto",
api: "anthropic-messages",
provider: "openrouter",
baseUrl: "https://openrouter.ai/api/v1",
reasoning: true,
thinking: {
mode: "budget",
efforts: [Effort.Minimal, Effort.Low, Effort.Medium, Effort.High],
},
input: ["text"],
cost: { input: 1, output: 2, cacheRead: 0.1, cacheWrite: 1 },
contextWindow: 128000,
maxTokens: 8192,
}),
buildModel({
id: "openai/gpt-4o:extended",
name: "GPT-4o Extended",
api: "anthropic-messages",
provider: "openrouter",
baseUrl: "https://openrouter.ai/api/v1",
reasoning: false,
input: ["text", "image"],
cost: { input: 5, output: 15, cacheRead: 0.5, cacheWrite: 5 },
contextWindow: 128000,
maxTokens: 4096,
}),
buildModel({
id: "z-ai/glm-4.7",
name: "GLM 4.7",
api: "openai-completions",
provider: "openrouter",
baseUrl: "https://openrouter.ai/api/v1",
reasoning: true,
thinking: {
mode: "budget",
efforts: [Effort.Minimal, Effort.Low, Effort.Medium, Effort.High],
},
input: ["text"],
cost: { input: 1, output: 2, cacheRead: 0.1, cacheWrite: 1 },
contextWindow: 128000,
maxTokens: 8192,
}),
];
const mockProviderOverlapModels: Model<"anthropic-messages">[] = [
buildModel({
id: "kimi-k2.5",
name: "Kimi K2.5",
api: "anthropic-messages",
provider: "kimi-code",
baseUrl: "https://api.kimi.ai",
reasoning: false,
input: ["text"],
cost: { input: 2, output: 6, cacheRead: 0.2, cacheWrite: 2 },
contextWindow: 128000,
maxTokens: 8192,
}),
buildModel({
id: "moonshotai/kimi-k2.5",
name: "Kimi K2.5 (OpenRouter)",
api: "anthropic-messages",
provider: "openrouter",
baseUrl: "https://openrouter.ai/api/v1",
reasoning: false,
input: ["text"],
cost: { input: 2.2, output: 6.2, cacheRead: 0.22, cacheWrite: 2.2 },
contextWindow: 128000,
maxTokens: 8192,
}),
];
const mockCodexOverlapModels: Model<"anthropic-messages">[] = [
buildModel({
id: "gpt-5.3-codex",
name: "GPT-5.3 Codex",
api: "anthropic-messages",
provider: "openai-codex",
baseUrl: "https://api.openai.com",
reasoning: true,
thinking: {
mode: "effort",
efforts: [Effort.Low, Effort.Medium, Effort.High, Effort.XHigh],
},
input: ["text"],
cost: { input: 1.5, output: 6, cacheRead: 0.15, cacheWrite: 1.5 },
contextWindow: 200000,
maxTokens: 8192,
}),
buildModel({
id: "gpt-5.3-codex-spark",
name: "GPT-5.3 Codex Spark",
api: "anthropic-messages",
provider: "openai-codex",
baseUrl: "https://api.openai.com",
reasoning: true,
thinking: {
mode: "effort",
efforts: [Effort.Low, Effort.Medium, Effort.High, Effort.XHigh],
},
input: ["text"],
cost: { input: 1, output: 4, cacheRead: 0.1, cacheWrite: 1 },
contextWindow: 200000,
maxTokens: 8192,
}),
];
function createOpusModel(provider: string, id: string, name: string): Model<"anthropic-messages"> {
return buildModel({
id,
name,
api: "anthropic-messages",
provider,
baseUrl: provider === "anthropic" ? "https://api.anthropic.com" : "https://api.githubcopilot.com",
reasoning: true,
thinking: {
mode: "budget",
efforts: [Effort.Minimal, Effort.Low, Effort.Medium, Effort.High, Effort.XHigh],
},
input: ["text", "image"],
cost: { input: 15, output: 75, cacheRead: 1.5, cacheWrite: 18.75 },
contextWindow: 200000,
maxTokens: 32000,
});
}
const canonicalVariantModels: Model<"anthropic-messages">[] = [
buildModel({
id: "claude-sonnet-4-5",
name: "Claude Sonnet 4.5",
api: "anthropic-messages",
provider: "anthropic",
baseUrl: "https://api.anthropic.com",
reasoning: true,
thinking: {
mode: "budget",
efforts: [Effort.Minimal, Effort.Low, Effort.Medium, Effort.High],
},
input: ["text", "image"],
cost: { input: 3, output: 15, cacheRead: 0.3, cacheWrite: 3.75 },
contextWindow: 200000,
maxTokens: 8192,
}),
buildModel({
id: "anthropic/claude-sonnet-4.5",
name: "Claude Sonnet 4.5 (Copilot)",
api: "anthropic-messages",
provider: "github-copilot",
baseUrl: "https://api.githubcopilot.com",
reasoning: true,
thinking: {
mode: "budget",
efforts: [Effort.Minimal, Effort.Low, Effort.Medium, Effort.High],
},
input: ["text", "image"],
cost: { input: 3, output: 15, cacheRead: 0.3, cacheWrite: 3.75 },
contextWindow: 200000,
maxTokens: 8192,
}),
];
const canonicalRegistry = {
resolveCanonicalModel: (canonicalId: string, options?: { candidates?: Model<"anthropic-messages">[] }) => {
if (canonicalId !== "claude-sonnet-4-5") return undefined;
const candidates = options?.candidates ?? canonicalVariantModels;
return (
candidates.find(model => model.provider === "github-copilot") ??
candidates.find(model => model.provider === "anthropic")
);
},
getCanonicalVariants: (canonicalId: string, options?: { candidates?: Model<"anthropic-messages">[] }) => {
if (canonicalId !== "claude-sonnet-4-5") return [];
const candidates = options?.candidates ?? canonicalVariantModels;
return candidates.map(model => ({
canonicalId,
selector: `${model.provider}/${model.id}`,
model,
source: model.id === canonicalId ? "bundled" : "heuristic",
}));
},
getCanonicalId: () => "claude-sonnet-4-5",
getAvailable: () => canonicalVariantModels,
} as unknown as Parameters<typeof resolveCliModel>[0]["modelRegistry"];
const allModels = [...mockModels, ...mockOpenRouterModels, ...mockProviderOverlapModels, ...mockCodexOverlapModels];
describe("parseModelPattern", () => {
describe("simple patterns without colons", () => {
test("exact match returns model with undefined thinking level", () => {
const result = parseModelPattern("claude-sonnet-4-5", allModels);
expect(result.model?.id).toBe("claude-sonnet-4-5");
expect(result.thinkingLevel).toBeUndefined();
expect(result.explicitThinkingLevel).toBe(false);
expect(result.warning).toBeUndefined();
});
test("partial match returns best model with undefined thinking level", () => {
const result = parseModelPattern("sonnet", allModels);
expect(result.model?.id).toBe("claude-sonnet-4-5");
expect(result.thinkingLevel).toBeUndefined();
expect(result.explicitThinkingLevel).toBe(false);
expect(result.warning).toBeUndefined();
});
test("no match returns undefined model and thinking level", () => {
const result = parseModelPattern("nonexistent", allModels);
expect(result.model).toBeUndefined();
expect(result.thinkingLevel).toBeUndefined();
expect(result.explicitThinkingLevel).toBe(false);
expect(result.warning).toBeUndefined();
});
});
describe("patterns with valid thinking levels", () => {
test("sonnet:high returns sonnet with high thinking level", () => {
const result = parseModelPattern("sonnet:high", allModels);
expect(result.model?.id).toBe("claude-sonnet-4-5");
expect(result.thinkingLevel).toBe(Effort.High);
expect(result.warning).toBeUndefined();
});
test("gpt-4o:medium returns gpt-4o with medium thinking level", () => {
const result = parseModelPattern("gpt-4o:medium", allModels);
expect(result.model?.id).toBe("gpt-4o");
expect(result.thinkingLevel).toBe(Effort.Medium);
expect(result.warning).toBeUndefined();
});
test("all valid thinking levels work", () => {
const levels = ["off", Effort.Minimal, Effort.Low, Effort.Medium, Effort.High, Effort.XHigh] as const;
for (const level of levels) {
const result = parseModelPattern(`sonnet:${level}`, allModels);
expect(result.model?.id).toBe("claude-sonnet-4-5");
expect(result.thinkingLevel).toBe(level);
expect(result.warning).toBeUndefined();
}
});
});
describe("patterns with invalid thinking levels", () => {
test("sonnet:random returns sonnet with undefined thinking level and warning", () => {
const result = parseModelPattern("sonnet:random", allModels);
expect(result.model?.id).toBe("claude-sonnet-4-5");
expect(result.thinkingLevel).toBeUndefined();
expect(result.explicitThinkingLevel).toBe(false);
expect(result.warning).toContain("Invalid thinking level");
expect(result.warning).toContain("random");
});
test("gpt-4o:invalid returns gpt-4o with undefined thinking level and warning", () => {
const result = parseModelPattern("gpt-4o:invalid", allModels);
expect(result.model?.id).toBe("gpt-4o");
expect(result.thinkingLevel).toBeUndefined();
expect(result.explicitThinkingLevel).toBe(false);
expect(result.warning).toContain("Invalid thinking level");
});
});
describe("OpenRouter models with colons in IDs", () => {
test("qwen3-coder:exacto matches the model with undefined thinking level", () => {
const result = parseModelPattern("qwen/qwen3-coder:exacto", allModels);
expect(result.model?.id).toBe("qwen/qwen3-coder:exacto");
expect(result.thinkingLevel).toBeUndefined();
expect(result.explicitThinkingLevel).toBe(false);
expect(result.warning).toBeUndefined();
});
test("openrouter/qwen/qwen3-coder:exacto matches with provider prefix", () => {
const result = parseModelPattern("openrouter/qwen/qwen3-coder:exacto", allModels);
expect(result.model?.id).toBe("qwen/qwen3-coder:exacto");
expect(result.model?.provider).toBe("openrouter");
expect(result.thinkingLevel).toBeUndefined();
expect(result.explicitThinkingLevel).toBe(false);
expect(result.warning).toBeUndefined();
});
test("qwen3-coder:exacto:high matches model with high thinking level", () => {
const result = parseModelPattern("qwen/qwen3-coder:exacto:high", allModels);
expect(result.model?.id).toBe("qwen/qwen3-coder:exacto");
expect(result.thinkingLevel).toBe(Effort.High);
expect(result.explicitThinkingLevel).toBe(true);
expect(result.warning).toBeUndefined();
});
test("openrouter/qwen/qwen3-coder:exacto:high matches with provider and thinking level", () => {
const result = parseModelPattern("openrouter/qwen/qwen3-coder:exacto:high", allModels);
expect(result.model?.id).toBe("qwen/qwen3-coder:exacto");
expect(result.model?.provider).toBe("openrouter");
expect(result.thinkingLevel).toBe(Effort.High);
expect(result.explicitThinkingLevel).toBe(true);
expect(result.warning).toBeUndefined();
});
test("gpt-4o:extended matches the extended model with undefined thinking level", () => {
const result = parseModelPattern("openai/gpt-4o:extended", allModels);
expect(result.model?.id).toBe("openai/gpt-4o:extended");
expect(result.thinkingLevel).toBeUndefined();
expect(result.explicitThinkingLevel).toBe(false);
expect(result.warning).toBeUndefined();
});
test("supports OpenRouter route suffixes that are not present in the catalog", () => {
const result = parseModelPattern("openrouter/z-ai/glm-4.7-20251222:nitro", allModels);
expect(result.model?.provider).toBe("openrouter");
expect(result.model?.id).toBe("z-ai/glm-4.7-20251222:nitro");
expect(result.thinkingLevel).toBeUndefined();
expect(result.explicitThinkingLevel).toBe(false);
expect(result.warning).toBeUndefined();
});
test("supports OpenRouter route suffixes with an appended thinking level", () => {
const result = parseModelPattern("openrouter/z-ai/glm-4.7-20251222:nitro:high", allModels);
expect(result.model?.provider).toBe("openrouter");
expect(result.model?.id).toBe("z-ai/glm-4.7-20251222:nitro");
expect(result.thinkingLevel).toBe(Effort.High);
expect(result.explicitThinkingLevel).toBe(true);
expect(result.warning).toBeUndefined();
});
});
describe("invalid thinking levels with OpenRouter models", () => {
test("qwen3-coder:exacto:random returns model with undefined thinking level and warning", () => {
const result = parseModelPattern("qwen/qwen3-coder:exacto:random", allModels);
expect(result.model?.id).toBe("qwen/qwen3-coder:exacto");
expect(result.thinkingLevel).toBeUndefined();
expect(result.explicitThinkingLevel).toBe(false);
expect(result.warning).toContain("Invalid thinking level");
expect(result.warning).toContain("random");
});
test("qwen3-coder:exacto:high:random returns model with undefined thinking level and warning", () => {
const result = parseModelPattern("qwen/qwen3-coder:exacto:high:random", allModels);
expect(result.model?.id).toBe("qwen/qwen3-coder:exacto");
expect(result.thinkingLevel).toBeUndefined();
expect(result.explicitThinkingLevel).toBe(false);
expect(result.warning).toContain("Invalid thinking level");
expect(result.warning).toContain("random");
});
});
describe("edge cases", () => {
test("empty pattern matches via partial matching", () => {
// Empty string is included in all model IDs, so partial matching finds a match
const result = parseModelPattern("", allModels);
expect(result.model).not.toBeNull();
expect(result.thinkingLevel).toBeUndefined();
expect(result.explicitThinkingLevel).toBe(false);
});
test("pattern ending with colon treats empty suffix as invalid", () => {
const result = parseModelPattern("sonnet:", allModels);
// Empty string after colon is not a valid thinking level
// So it tries to match "sonnet:" which won't match, then tries "sonnet"
expect(result.model?.id).toBe("claude-sonnet-4-5");
expect(result.warning).toContain("Invalid thinking level");
});
});
describe("preference logic", () => {
test("prefers most recently used model when multiple providers match", () => {
const result = parseModelPattern("k2.5", allModels, {
usageOrder: ["kimi-code/kimi-k2.5"],
});
expect(result.model?.provider).toBe("kimi-code");
});
test("prefers first-party providers over OpenRouter when no usage data exists", () => {
const result = parseModelPattern("k2.5", allModels, { usageOrder: [] });
expect(result.model?.provider).toBe("kimi-code");
});
test("respects most recently used provider even if openrouter", () => {
const result = parseModelPattern("k2.5", allModels, {
usageOrder: ["openrouter/moonshotai/kimi-k2.5"],
});
expect(result.model?.provider).toBe("openrouter");
expect(result.model?.id).toBe("moonshotai/kimi-k2.5");
});
});
describe("canonical ids", () => {
test("resolves an exact canonical id through the registry before bare-id matching", () => {
const result = parseModelPattern("claude-sonnet-4-5", canonicalVariantModels, undefined, {
modelRegistry: canonicalRegistry,
});
expect(result.model?.provider).toBe("github-copilot");
expect(result.model?.id).toBe("anthropic/claude-sonnet-4.5");
});
});
});
describe("resolveModelRoleValue", () => {
test("resolves pi/<role>:<thinking> by expanding role alias before parsing thinking", () => {
const settings = {
getModelRole: (role: string) => (role === "smol" ? "openrouter/qwen/qwen3-coder:exacto" : undefined),
} as NonNullable<Parameters<typeof resolveModelRoleValue>[2]>["settings"];
const result = resolveModelRoleValue("pi/smol:high", allModels, { settings });
expect(result.model?.provider).toBe("openrouter");
expect(result.model?.id).toBe("qwen/qwen3-coder:exacto");
expect(result.thinkingLevel).toBe(Effort.High);
expect(result.explicitThinkingLevel).toBe(true);
});
test("resolves pi/default through configured default role alias", () => {
const settings = {
getModelRole: (role: string) => (role === "default" ? "openrouter/qwen/qwen3-coder:exacto" : undefined),
} as NonNullable<Parameters<typeof resolveModelRoleValue>[2]>["settings"];
const result = resolveModelRoleValue("pi/default", allModels, { settings });
expect(result.model?.provider).toBe("openrouter");
expect(result.model?.id).toBe("qwen/qwen3-coder:exacto");
expect(result.thinkingLevel).toBeUndefined();
expect(result.explicitThinkingLevel).toBe(false);
expect(result.warning).toBeUndefined();
});
test("splits direct comma fallback chains before parsing thinking selectors", () => {
const result = resolveModelRoleValue("anthropic/claude-sonnet-4-5:off,openai/gpt-4o:off", allModels);
expect(result.model?.provider).toBe("anthropic");
expect(result.model?.id).toBe("claude-sonnet-4-5");
expect(result.thinkingLevel).toBe("off");
expect(result.explicitThinkingLevel).toBe(true);
expect(result.warning).toBeUndefined();
});
test("tries later direct comma fallback entries when earlier entries miss", () => {
const result = resolveModelRoleValue("anthropic/missing:off,openai/gpt-4o:off", allModels);
expect(result.model?.provider).toBe("openai");
expect(result.model?.id).toBe("gpt-4o");
expect(result.thinkingLevel).toBe("off");
expect(result.explicitThinkingLevel).toBe(true);
expect(result.warning).toBeUndefined();
});
test("does not resolve exact codex role values to codex-spark via substring matching", () => {
const providerQualified = resolveModelRoleValue("openai-codex/gpt-5.3-codex:xhigh", allModels);
expect(providerQualified.model?.provider).toBe("openai-codex");
expect(providerQualified.model?.id).toBe("gpt-5.3-codex");
expect(providerQualified.thinkingLevel).toBe(Effort.XHigh);
expect(providerQualified.explicitThinkingLevel).toBe(true);
const idOnly = resolveModelRoleValue("gpt-5.3-codex:xhigh", allModels);
expect(idOnly.model?.provider).toBe("openai-codex");
expect(idOnly.model?.id).toBe("gpt-5.3-codex");
expect(idOnly.thinkingLevel).toBe(Effort.XHigh);
expect(idOnly.explicitThinkingLevel).toBe(true);
});
test("clamps explicit thinking selectors from model metadata", () => {
const result = resolveModelRoleValue("anthropic/claude-sonnet-4-5:xhigh", allModels);
expect(result.model?.provider).toBe("anthropic");
expect(result.model?.id).toBe("claude-sonnet-4-5");
expect(result.thinkingLevel).toBe(Effort.High);
expect(result.explicitThinkingLevel).toBe(true);
});
});
describe("resolveAgentModelPatterns", () => {
test("falls back to the active session model when pi/task is unset", () => {
const settings = Settings.isolated({
modelRoles: { default: "anthropic/claude-sonnet-4-5" },
});
const result = resolveAgentModelPatterns({
agentModel: "pi/task",
settings,
activeModelPattern: "openai/gpt-4o",
});
expect(result).toEqual(["openai/gpt-4o"]);
});
test("uses the configured task role before falling back to the session model", () => {
const settings = Settings.isolated({
modelRoles: {
default: "openai/gpt-4o",
task: "anthropic/claude-sonnet-4-5:high",
},
});
const result = resolveAgentModelPatterns({
agentModel: "pi/task",
settings,
activeModelPattern: "openai/gpt-4o",
});
expect(result).toEqual(["anthropic/claude-sonnet-4-5:high"]);
});
test("uses default for unconfigured smol, slow, and designer agent roles before priority defaults", () => {
const settings = Settings.isolated({
modelRoles: { default: "local/llama" },
});
expect(resolveAgentModelPatterns({ agentModel: "pi/smol", settings })).toEqual(["local/llama"]);
expect(resolveAgentModelPatterns({ agentModel: "pi/slow", settings })).toEqual(["local/llama"]);
expect(resolveAgentModelPatterns({ agentModel: "pi/designer", settings })).toEqual(["local/llama"]);
});
test("keeps built-in priority defaults when default aliases the same unset role", () => {
const smolSettings = Settings.isolated({
modelRoles: { default: "pi/smol" },
});
const slowSettings = Settings.isolated({
modelRoles: { default: "pi/slow" },
});
const designerSettings = Settings.isolated({
modelRoles: { default: "pi/designer" },
});
expect(resolveAgentModelPatterns({ agentModel: "pi/smol", settings: smolSettings })).toEqual([
"cerebras/zai-glm-4.7",
"cerebras/zai-glm-4.6",
"cerebras/zai-glm",
"haiku-4-5",
"haiku-4.5",
"haiku",
"flash",
"mini",
]);
expect(resolveAgentModelPatterns({ agentModel: "pi/slow", settings: slowSettings })[0]).toBe("gpt-5.4");
expect(resolveAgentModelPatterns({ agentModel: "pi/designer", settings: designerSettings })[0]).toBe(
"google-gemini-cli/gemini-3.1-pro",
);
});
test("expands cross-role default aliases when inheriting for an unset role", () => {
const settings = Settings.isolated({
modelRoles: { default: "pi/slow", slow: "anthropic/claude-sonnet-4-5" },
});
expect(resolveAgentModelPatterns({ agentModel: "pi/smol", settings })).toEqual(["anthropic/claude-sonnet-4-5"]);
});
test("recurses into priority defaults when default points at another unset role", () => {
const settings = Settings.isolated({
modelRoles: { default: "pi/slow" },
});
expect(resolveAgentModelPatterns({ agentModel: "pi/smol", settings })[0]).toBe("gpt-5.4");
});
test("expands pi/designer to priority defaults when default is unset", () => {
const settings = Settings.isolated();
const result = resolveAgentModelPatterns({
agentModel: "pi/designer",
settings,
});
expect(result).toEqual([
"google-gemini-cli/gemini-3.1-pro",
"google-gemini-cli/gemini-3-pro",
"gemini-3.1-pro",
"gemini-3-1-pro",
"gemini-3-pro",
"gemini-3",
]);
});
test("prefers configured designer role override over priority defaults", () => {
const settings = Settings.isolated({
modelRoles: {
default: "anthropic/claude-sonnet-4-5",
designer: "openai/gpt-4o",
},
});
const result = resolveAgentModelPatterns({
agentModel: "pi/designer",
settings,
});
expect(result).toEqual(["openai/gpt-4o"]);
});
test("slow priority falls forward to Opus 4.8 before older Opus aliases", () => {
const settings = Settings.isolated();
const patterns = resolveAgentModelPatterns({ agentModel: "pi/slow", settings });
const dottedRegistry = {
getAvailable: () => [
createOpusModel("github-copilot", "claude-opus-4.7", "Claude Opus 4.7"),
createOpusModel("github-copilot", "claude-opus-4.8", "Claude Opus 4.8"),
],
} as Parameters<typeof resolveModelOverride>[1];
const dotted = resolveModelOverride(patterns, dottedRegistry, settings);
expect(dotted.model?.provider).toBe("github-copilot");
expect(dotted.model?.id).toBe("claude-opus-4.8");
const dashedRegistry = {
getAvailable: () => [
createOpusModel("anthropic", "claude-opus-4-7", "Claude Opus 4.7"),
createOpusModel("anthropic", "claude-opus-4-8", "Claude Opus 4.8"),
],
} as Parameters<typeof resolveModelOverride>[1];
const dashed = resolveModelOverride(patterns, dashedRegistry, settings);
expect(dashed.model?.provider).toBe("anthropic");
expect(dashed.model?.id).toBe("claude-opus-4-8");
});
});
describe("resolveModelFromString", () => {
test("falls back to pattern parsing for provider/model:thinking when strict provider+id miss", () => {
const resolved = resolveModelFromString("openrouter/qwen/qwen3-coder:exacto:high", allModels);
expect(resolved?.provider).toBe("openrouter");
expect(resolved?.id).toBe("qwen/qwen3-coder:exacto");
});
test("treats colon-containing model IDs without thinking suffix as exact IDs", () => {
const resolved = resolveModelFromString("openrouter/qwen/qwen3-coder:exacto", allModels);
expect(resolved?.provider).toBe("openrouter");
expect(resolved?.id).toBe("qwen/qwen3-coder:exacto");
});
});
describe("resolveModelOverride", () => {
test("preserves explicit off and explicit-thinking metadata", () => {
const registry = {
getAvailable: () => allModels,
} as Parameters<typeof resolveModelOverride>[1];
const result = resolveModelOverride(["sonnet:off"], registry);
expect(result.model?.id).toBe("claude-sonnet-4-5");
expect(result.thinkingLevel).toBe("off");
expect(result.explicitThinkingLevel).toBe(true);
});
test("resolves colon-containing model IDs with appended thinking suffix", () => {
const registry = {
getAvailable: () => allModels,
} as Parameters<typeof resolveModelOverride>[1];
const result = resolveModelOverride(["openrouter/qwen/qwen3-coder:exacto:high"], registry);
expect(result.model?.provider).toBe("openrouter");
expect(result.model?.id).toBe("qwen/qwen3-coder:exacto");
expect(result.thinkingLevel).toBe(Effort.High);
expect(result.explicitThinkingLevel).toBe(true);
});
});
describe("resolveCliModel", () => {
test("resolves exact canonical ids to the preferred concrete provider", () => {
const result = resolveCliModel({
cliModel: "claude-sonnet-4-5",
modelRegistry: {
...canonicalRegistry,
getAll: () => canonicalVariantModels,
} as unknown as Parameters<typeof resolveCliModel>[0]["modelRegistry"],
});
expect(result.error).toBeUndefined();
expect(result.selector).toBe("claude-sonnet-4-5");
expect(result.model?.provider).toBe("github-copilot");
expect(result.model?.id).toBe("anthropic/claude-sonnet-4.5");
});
test("resolves --model provider/id without --provider", () => {
const registry = {
getAll: () => allModels,
} as unknown as Parameters<typeof resolveCliModel>[0]["modelRegistry"];
const result = resolveCliModel({
cliModel: "openai/gpt-4o",
modelRegistry: registry,
});
expect(result.error).toBeUndefined();
expect(result.model?.provider).toBe("openai");
expect(result.model?.id).toBe("gpt-4o");
});
test("resolves fuzzy patterns within an explicit provider", () => {
const registry = {
getAll: () => allModels,
} as unknown as Parameters<typeof resolveCliModel>[0]["modelRegistry"];
const result = resolveCliModel({
cliProvider: "openai",
cliModel: "4o",
modelRegistry: registry,
});
expect(result.error).toBeUndefined();
expect(result.model?.provider).toBe("openai");
expect(result.model?.id).toBe("gpt-4o");
});
test("supports --model <pattern>:<thinking> (without explicit --thinking)", () => {
const registry = {
getAll: () => allModels,
} as unknown as Parameters<typeof resolveCliModel>[0]["modelRegistry"];
const result = resolveCliModel({
cliModel: "sonnet:high",
modelRegistry: registry,
});
expect(result.error).toBeUndefined();
expect(result.model?.id).toBe("claude-sonnet-4-5");
expect(result.thinkingLevel).toBe(Effort.High);
});
test("prefers exact model id match over provider inference (OpenRouter-style ids)", () => {
const registry = {
getAll: () => allModels,
} as unknown as Parameters<typeof resolveCliModel>[0]["modelRegistry"];
const result = resolveCliModel({
cliModel: "openai/gpt-4o:extended",
modelRegistry: registry,
});
expect(result.error).toBeUndefined();
expect(result.model?.provider).toBe("openrouter");
expect(result.model?.id).toBe("openai/gpt-4o:extended");
});
test("does not strip invalid :suffix as thinking level in --model (fail fast)", () => {
const registry = {
getAll: () => allModels,
} as unknown as Parameters<typeof resolveCliModel>[0]["modelRegistry"];
const result = resolveCliModel({
cliProvider: "openai",
cliModel: "gpt-4o:extended",
modelRegistry: registry,
});
expect(result.model).toBeUndefined();
expect(result.error).toContain("not found");
});
test("supports provider-prefixed OpenRouter route suffixes even when the base model is cataloged without them", () => {
const registry = {
getAll: () => allModels,
} as unknown as Parameters<typeof resolveCliModel>[0]["modelRegistry"];
const result = resolveCliModel({
cliModel: "openrouter/z-ai/glm-4.7-20251222:nitro",
modelRegistry: registry,
});
expect(result.error).toBeUndefined();
expect(result.model?.provider).toBe("openrouter");
expect(result.model?.id).toBe("z-ai/glm-4.7-20251222:nitro");
});
test("supports explicit OpenRouter provider with route suffixes that are not in the catalog", () => {
const registry = {
getAll: () => allModels,
} as unknown as Parameters<typeof resolveCliModel>[0]["modelRegistry"];
const result = resolveCliModel({
cliProvider: "openrouter",
cliModel: "z-ai/glm-4.7-20251222:nitro",
modelRegistry: registry,
});
expect(result.error).toBeUndefined();
expect(result.model?.provider).toBe("openrouter");
expect(result.model?.id).toBe("z-ai/glm-4.7-20251222:nitro");
});
test("returns a clear error when there are no models", () => {
const registry = {
getAll: () => [],
} as unknown as Parameters<typeof resolveCliModel>[0]["modelRegistry"];
const result = resolveCliModel({
cliProvider: "openai",
cliModel: "gpt-4o",
modelRegistry: registry,
});
expect(result.model).toBeUndefined();
expect(result.error).toContain("No models available");
});
test("resolves provider-prefixed fuzzy patterns (openrouter/qwen -> openrouter model)", () => {
const registry = {
getAll: () => allModels,
} as unknown as Parameters<typeof resolveCliModel>[0]["modelRegistry"];
const result = resolveCliModel({
cliModel: "openrouter/qwen",
modelRegistry: registry,
});
expect(result.error).toBeUndefined();
expect(result.model?.provider).toBe("openrouter");
expect(result.model?.id).toBe("qwen/qwen3-coder:exacto");
});
test("prefers decomposed provider+id over flat id match when ambiguous", () => {
// Simulates the zai/glm-5 bug: vercel-ai-gateway has id="zai/glm-5",
// zai has id="glm-5". Input "zai/glm-5" should resolve to provider=zai.
const ambiguousModels: Model<"anthropic-messages">[] = [
buildModel({
id: "zai/glm-5",
name: "GLM-5 (Vercel)",
api: "anthropic-messages",
provider: "vercel-ai-gateway",
baseUrl: "https://vercel.ai",
reasoning: false,
input: ["text"],
cost: { input: 1, output: 2, cacheRead: 0.1, cacheWrite: 1 },
contextWindow: 128000,
maxTokens: 4096,
}),
buildModel({
id: "glm-5",
name: "GLM-5",
api: "anthropic-messages",
provider: "zai",
baseUrl: "https://api.z.ai",
reasoning: false,
input: ["text"],
cost: { input: 1, output: 2, cacheRead: 0.1, cacheWrite: 1 },
contextWindow: 128000,
maxTokens: 4096,
}),
];
const registry = {
getAll: () => ambiguousModels,
} as unknown as Parameters<typeof resolveCliModel>[0]["modelRegistry"];
const result = resolveCliModel({
cliModel: "zai/glm-5",
modelRegistry: registry,
});
expect(result.error).toBeUndefined();
expect(result.model?.provider).toBe("zai");
expect(result.model?.id).toBe("glm-5");
});
});
describe("resolveModelScope", () => {
test("expands exact canonical ids into all concrete variants", async () => {
const scoped = await resolveModelScope(["claude-sonnet-4-5"], {
getAvailable: () => canonicalVariantModels,
getCanonicalVariants: (canonicalId: string, options?: { candidates?: Model<"anthropic-messages">[] }) =>
canonicalRegistry.getCanonicalVariants!(canonicalId, options),
} as unknown as Parameters<typeof resolveModelScope>[1]);
expect(scoped).toHaveLength(2);
expect(scoped.map(entry => `${entry.model.provider}/${entry.model.id}`).sort()).toEqual([
"anthropic/claude-sonnet-4-5",
"github-copilot/anthropic/claude-sonnet-4.5",
]);
});
});
describe("parseModelString", () => {
test("parses standard provider/id format", () => {
const result = parseModelString("anthropic/claude-sonnet-4-5");
expect(result).toEqual({ provider: "anthropic", id: "claude-sonnet-4-5" });
});
test("returns undefined for strings without a slash", () => {
expect(parseModelString("claude-sonnet-4-5")).toBeUndefined();
expect(parseModelString("")).toBeUndefined();
expect(parseModelString("sonnet:high")).toBeUndefined();
});
test("returns undefined for strings starting with slash", () => {
expect(parseModelString("/claude-sonnet-4-5")).toBeUndefined();
});
describe("thinking level suffix extraction", () => {
test("extracts valid thinking level from provider/id:level", () => {
const result = parseModelString("anthropic/claude-sonnet-4-5:high");
expect(result).toEqual({ provider: "anthropic", id: "claude-sonnet-4-5", thinkingLevel: Effort.High });
});
test("extracts all valid thinking levels", () => {
const levels = ["off", Effort.Minimal, Effort.Low, Effort.Medium, Effort.High, Effort.XHigh] as const;
for (const level of levels) {
const result = parseModelString(`anthropic/claude-sonnet-4-5:${level}`);
expect(result?.id).toBe("claude-sonnet-4-5");
expect(result?.thinkingLevel).toBe(level);
}
});
test("does NOT strip invalid suffix — treats it as part of model ID", () => {
const result = parseModelString("openrouter/qwen/qwen3-coder:exacto");
expect(result).toEqual({ provider: "openrouter", id: "qwen/qwen3-coder:exacto" });
});
test("handles model ID with colon followed by valid thinking level", () => {
// e.g. "openrouter/qwen/qwen3-coder:exacto:high" — last colon is thinking level
const result = parseModelString("openrouter/qwen/qwen3-coder:exacto:high");
expect(result).toEqual({
provider: "openrouter",
id: "qwen/qwen3-coder:exacto",
thinkingLevel: Effort.High,
});
});
test("does not extract thinking level from model ID with invalid suffix", () => {
const result = parseModelString("openrouter/openai/gpt-4o:extended");
// :extended is not a valid thinking level, so it stays as part of the ID
expect(result).toEqual({ provider: "openrouter", id: "openai/gpt-4o:extended" });
});
test("handles empty suffix after colon", () => {
const result = parseModelString("anthropic/claude-sonnet-4-5:");
// Empty string is not a valid thinking level, so colon stays as part of ID
expect(result).toEqual({ provider: "anthropic", id: "claude-sonnet-4-5:" });
});
});
});
describe("expandRoleAlias", () => {
test("expands pi/vision to configured vision role", () => {
const settings = Settings.isolated();
settings.setModelRole("vision", "openai/gpt-4o");
expect(expandRoleAlias("pi/vision", settings)).toBe("openai/gpt-4o");
});
test("keeps pi/vision alias when vision role is unset", () => {
const settings = Settings.isolated();
settings.setModelRole("default", "anthropic/claude-sonnet-4-5");
expect(expandRoleAlias("pi/vision", settings)).toBe("pi/vision");
});
});
describe("provider routing selector (@upstream)", () => {
const openRouterOnly = (model: Model<Api> | undefined): string[] | undefined =>
(model?.compat as { openRouterRouting?: { only?: string[] } } | undefined)?.openRouterRouting?.only;
test("pins an OpenRouter model to one upstream via @slug", () => {
const result = parseModelPattern("openrouter/z-ai/glm-4.7@cerebras", allModels);
expect(result.model?.id).toBe("z-ai/glm-4.7");
expect(result.model?.provider).toBe("openrouter");
expect(result.upstream).toBe("cerebras");
expect(openRouterOnly(result.model)).toEqual(["cerebras"]);
});
test("resolves @slug without an explicit provider prefix", () => {
const result = parseModelPattern("z-ai/glm-4.7@cerebras", allModels);
expect(result.model?.id).toBe("z-ai/glm-4.7");
expect(openRouterOnly(result.model)).toEqual(["cerebras"]);
});
test("combines @slug with a trailing thinking level", () => {
const result = parseModelPattern("openrouter/z-ai/glm-4.7@cerebras:high", allModels);
expect(result.model?.id).toBe("z-ai/glm-4.7");
expect(result.thinkingLevel).toBe(Effort.High);
expect(openRouterOnly(result.model)).toEqual(["cerebras"]);
});
test("routes Vercel AI Gateway models via vercelGatewayRouting", () => {
const gatewayModel: Model<"openai-completions"> = buildModel({
id: "zai/glm-4.7",
name: "GLM 4.7 (Gateway)",
api: "openai-completions",
provider: "vercel-ai-gateway",
baseUrl: "https://ai-gateway.vercel.sh/v1",
reasoning: true,
input: ["text"],
cost: { input: 1, output: 2, cacheRead: 0.1, cacheWrite: 1 },
contextWindow: 128000,
maxTokens: 8192,
});
const result = parseModelPattern("vercel-ai-gateway/zai/glm-4.7@cerebras", [gatewayModel]);
expect(result.model?.id).toBe("zai/glm-4.7");
expect(
(result.model?.compat as { vercelGatewayRouting?: { only?: string[] } } | undefined)?.vercelGatewayRouting
?.only,
).toEqual(["cerebras"]);
expect(openRouterOnly(result.model)).toBeUndefined();
});
test("does not split a model id that legitimately ends in @ (Vertex)", () => {
const vertexModel: Model<"anthropic-messages"> = buildModel({
id: "claude-opus-4-8@default",
name: "Claude Opus 4.8",
api: "anthropic-messages",
provider: "google-vertex",
baseUrl: "https://us-aiplatform.googleapis.com",
reasoning: true,
input: ["text"],
cost: { input: 15, output: 75, cacheRead: 1.5, cacheWrite: 18.75 },
contextWindow: 200000,
maxTokens: 32000,
});
const result = parseModelPattern("claude-opus-4-8@default", [vertexModel]);
expect(result.model?.id).toBe("claude-opus-4-8@default");
expect(result.upstream).toBeUndefined();
expect(openRouterOnly(result.model)).toBeUndefined();
});
test("ignores @slug on a non-aggregator model (no silent routing)", () => {
const result = parseModelPattern("gpt-4o@cerebras", allModels);
expect(result.model).toBeUndefined();
});
test("resolveCliModel round-trips @upstream in the selector and carries compat", () => {
const registry = { getAll: () => allModels } as unknown as Parameters<typeof resolveCliModel>[0]["modelRegistry"];
const result = resolveCliModel({ cliModel: "openrouter/z-ai/glm-4.7@cerebras", modelRegistry: registry });
expect(result.model?.id).toBe("z-ai/glm-4.7");
expect(result.selector).toBe("openrouter/z-ai/glm-4.7@cerebras");
expect(openRouterOnly(result.model)).toEqual(["cerebras"]);
});
});
describe("filterAvailableModelsByEnabledPatterns", () => {
const models = mockModels as Model[];
const registry = {
getCanonicalVariants: (_id: string, _opts?: unknown): CanonicalModelVariant[] => [],
};
test("returns all models when patterns is empty", () => {
expect(filterAvailableModelsByEnabledPatterns(models, [], registry)).toEqual(models);
});
test("filters by exact provider/modelId", () => {
const result = filterAvailableModelsByEnabledPatterns(models, ["anthropic/claude-sonnet-4-5"], registry);
expect(result).toHaveLength(1);
expect(result[0].id).toBe("claude-sonnet-4-5");
});
test("filters by bare model id matching across providers", () => {
const result = filterAvailableModelsByEnabledPatterns(models, ["claude-sonnet-4-5"], registry);
expect(result).toHaveLength(1);
expect(result[0].provider).toBe("anthropic");
});
test("expands canonical id via registry", () => {
const canonicalRegistry = {
getCanonicalVariants: (id: string, _opts?: unknown): CanonicalModelVariant[] =>
id === "claude-sonnet-4-5"
? [
{
canonicalId: "claude-sonnet-4-5",
selector: "anthropic/claude-sonnet-4-5",
model: models[0],
source: "bundled",
},
]
: [],
};
const result = filterAvailableModelsByEnabledPatterns(models, ["claude-sonnet-4-5"], canonicalRegistry);
expect(result).toHaveLength(1);
expect(result[0].id).toBe("claude-sonnet-4-5");
});
test("strips :thinkingLevel suffix before matching", () => {
const result = filterAvailableModelsByEnabledPatterns(models, ["anthropic/claude-sonnet-4-5:high"], registry);
expect(result).toHaveLength(1);
expect(result[0].id).toBe("claude-sonnet-4-5");
});
test("preserves colon-bearing OpenRouter ids (suffix is not a thinking level)", () => {
const openRouterModels = mockOpenRouterModels as Model[];
const result = filterAvailableModelsByEnabledPatterns(
openRouterModels,
["openrouter/qwen/qwen3-coder:exacto"],
registry,
);
expect(result).toHaveLength(1);
expect(result[0].id).toBe("qwen/qwen3-coder:exacto");
});
test("matches bare OpenRouter-style model id with slash but no provider prefix", () => {
const openRouterModels = mockOpenRouterModels as Model[];
const result = filterAvailableModelsByEnabledPatterns(openRouterModels, ["qwen/qwen3-coder:exacto"], registry);
expect(result).toHaveLength(1);
expect(result[0].id).toBe("qwen/qwen3-coder:exacto");
expect(result[0].provider).toBe("openrouter");
});
test("evaluates glob patterns against provider/modelId", () => {
const result = filterAvailableModelsByEnabledPatterns(models, ["anthropic/*"], registry);
expect(result).toHaveLength(1);
expect(result[0].provider).toBe("anthropic");
});
test("evaluates glob patterns against bare model id", () => {
const result = filterAvailableModelsByEnabledPatterns(models, ["claude-*"], registry);
expect(result).toHaveLength(1);
expect(result[0].id).toBe("claude-sonnet-4-5");
});
test("applies glob and exact patterns together", () => {
const result = filterAvailableModelsByEnabledPatterns(models, ["anthropic/*", "openai/gpt-4o"], registry);
expect(result).toHaveLength(2);
});
test("returns empty list when no pattern matches (misconfiguration)", () => {
const result = filterAvailableModelsByEnabledPatterns(models, ["nonexistent-model"], registry);
expect(result).toHaveLength(0);
});
test("includes multiple patterns from different providers", () => {
const result = filterAvailableModelsByEnabledPatterns(
models,
["anthropic/claude-sonnet-4-5", "openai/gpt-4o"],
registry,
);
expect(result).toHaveLength(2);
});
});
describe("effort-tier variant aliases", () => {
const variantModels: Model<Api>[] = [
buildModel({
id: "gemini-3.5-flash",
requestModelId: "gemini-3.5-flash-extra-low",
name: "Gemini 3.5 Flash",
api: "google-gemini-cli",
provider: "google-antigravity",
baseUrl: "https://daily-cloudcode-pa.googleapis.com",
reasoning: true,
thinking: {
mode: "google-level",
efforts: [Effort.Minimal, Effort.Low, Effort.Medium, Effort.High],
effortRouting: {
off: "gemini-3.5-flash-extra-low",
[Effort.Minimal]: "gemini-3-flash-agent",
[Effort.Low]: "gemini-3.5-flash-extra-low",
[Effort.Medium]: "gemini-3.5-flash-extra-low",
[Effort.High]: "gemini-3.5-flash-low",
},
suppressWhenOff: true,
},
input: ["text", "image"],
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
contextWindow: 1_048_576,
maxTokens: 65_535,
}),
// Live legacy model whose id is also a recycled alias of the family —
// exact matches must keep winning while it exists.
buildModel({
id: "gemini-3-flash",
name: "Gemini 3 Flash",
api: "google-gemini-cli",
provider: "google-antigravity",
baseUrl: "https://daily-cloudcode-pa.googleapis.com",
reasoning: true,
thinking: { mode: "google-level", efforts: [Effort.Minimal, Effort.Low, Effort.Medium, Effort.High] },
input: ["text", "image"],
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
contextWindow: 1_048_576,
maxTokens: 65_535,
}),
// Auto-derived pair target on a provider without a hand table.
buildModel({
id: "kimi-k2",
name: "Kimi K2",
api: "openai-completions",
provider: "venice",
baseUrl: "https://api.venice.ai/api/v1",
reasoning: true,
thinking: { mode: "budget", efforts: [Effort.Minimal, Effort.Low, Effort.Medium, Effort.High] },
input: ["text"],
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
contextWindow: 128_000,
maxTokens: 8_192,
}),
];
test("provider-qualified retired tier ids resolve to the collapsed model", () => {
const result = parseModelPattern("google-antigravity/gemini-3.5-flash-low", variantModels);
expect(result.model?.id).toBe("gemini-3.5-flash");
expect(result.thinkingLevel).toBeUndefined();
});
test("retired tier ids keep explicit :level suffixes", () => {
const result = parseModelPattern("google-antigravity/gemini-3.5-flash-low:high", variantModels);
expect(result.model?.id).toBe("gemini-3.5-flash");
expect(result.thinkingLevel).toBe(Effort.High);
});
test("bare retired tier ids resolve through the alias table", () => {
const result = parseModelPattern("gemini-3.5-flash-extra-low", variantModels);
expect(result.model?.id).toBe("gemini-3.5-flash");
expect(result.model?.provider).toBe("google-antigravity");
});
test("live models always beat recycled aliases", () => {
const result = parseModelPattern("google-antigravity/gemini-3-flash", variantModels);
expect(result.model?.id).toBe("gemini-3-flash");
});
test("consumed X-thinking twins resolve via the grammar fallback", () => {
expect(parseModelPattern("venice/kimi-k2-thinking", variantModels).model?.id).toBe("kimi-k2");
expect(parseModelPattern("kimi-k2-thinking", variantModels).model?.id).toBe("kimi-k2");
});
});