chore(vendor): import pi 1.3.0
Imported as a linear vendor commit so forge rebases do not replay the upstream root tree. git-subtree-dir: third_party/pi git-subtree-split: 71023aec1546d6d677a65669c5665c0927ce0dd0
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import { spawnSync } from "node:child_process";
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import { mkdtempSync, readFileSync, rmSync, writeFileSync } from "node:fs";
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import { tmpdir } from "node:os";
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import { join } from "node:path";
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import { fileURLToPath, pathToFileURL } from "node:url";
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import { afterEach, describe, expect, it } from "vitest";
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import type { ModelsDevReasoningOption } from "../scripts/models-dev-reasoning-options.ts";
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import { streamSimple } from "../src/api/anthropic-messages.ts";
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import { getSupportedThinkingLevels, hasApi } from "../src/models.ts";
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import type { Api, Model } from "../src/types.ts";
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import { normalizeContext } from "../src/utils/transcript.ts";
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const packageRoot = fileURLToPath(new URL("..", import.meta.url));
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const temporaryRoots: string[] = [];
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afterEach(() => {
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for (const root of temporaryRoots.splice(0)) rmSync(root, { force: true, recursive: true });
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});
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function generateFireworksModels(
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options: Record<string, ModelsDevReasoningOption[] | undefined>,
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): Record<string, Model<Api>> {
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const root = mkdtempSync(join(tmpdir(), "pi-fireworks-generation-"));
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temporaryRoots.push(root);
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const preloadPath = join(root, "mock-catalog.mjs");
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const outputPath = join(root, "catalog");
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const catalog = {
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"fireworks-ai": {
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models: Object.fromEntries(
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Object.entries(options).map(([id, reasoning_options]) => [
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`accounts/fireworks/models/${id}`,
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{ id, tool_call: true, reasoning: true, reasoning_options },
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]),
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),
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},
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};
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writeFileSync(
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preloadPath,
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`const catalog = ${JSON.stringify(catalog)};\n` +
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`globalThis.fetch = async (input) => {\n` +
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` const url = String(input);\n` +
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` if (url === "https://models.dev/api.json") return Response.json(catalog);\n` +
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` if (url === "https://models.dev/models.json?type=decision") return Response.json({ "typesafe/jev-latest": { name: "Jev", type: "decision", limit: { context: 64000, output: 0 } } });\n` +
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` if (url.startsWith("https://openrouter.ai/api/v1/models") || url === "https://ai-gateway.vercel.sh/v1/models") return Response.json({ data: [] });\n` +
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` if (url === "https://radius.pi.dev/v1/config") return Response.json({ baseUrl: "https://radius.pi.dev", models: [{ id: "test", name: "Test", reasoning: false, input: ["text"], cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 }, contextWindow: 4096, maxTokens: 4096 }] });\n` +
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` throw new Error(\`Unexpected fetch: \${url}\`);\n` +
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`};\n`,
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);
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const result = spawnSync(
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process.execPath,
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[
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"--import",
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pathToFileURL(preloadPath).href,
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"scripts/generate-models.ts",
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"--json-only",
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"--json-output",
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outputPath,
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],
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{ cwd: packageRoot, encoding: "utf8", timeout: 10_000 },
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);
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expect(result.status, `${result.stdout}\n${result.stderr}`).toBe(0);
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expect(result.stderr).toBe("");
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return JSON.parse(readFileSync(join(outputPath, "providers/fireworks.json"), "utf8")) as Record<string, Model<Api>>;
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}
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describe("Fireworks model generation", () => {
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// Regression for #9323: import catalog efforts and correct only the known omissions.
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it("combines upstream effort and toggle metadata with narrow corrections", () => {
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const models = generateFireworksModels({
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"deepseek-v4-flash-0731": [{ type: "toggle" }, { type: "effort", values: ["low", "high", "max"] }],
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"deepseek-v4-flash-vision-exp": [{ type: "toggle" }, { type: "effort", values: ["low", "high", "max"] }],
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"deepseek-v4-pro-0813": [{ type: "toggle" }, { type: "effort", values: ["high", "max"] }],
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"qwen3p8-max": [{ type: "toggle" }],
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"qwen3p8-2p4t-a95b": [{ type: "effort", values: ["low", "medium", "xhigh"] }],
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"kimi-k2p6": [{ type: "toggle" }],
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});
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for (const id of ["deepseek-v4-flash-0731", "deepseek-v4-flash-vision-exp", "deepseek-v4-pro-0813"]) {
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expect(models[`accounts/fireworks/models/${id}`].thinkingLevelMap).toEqual({
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off: "none",
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minimal: null,
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low: "low",
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medium: null,
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high: "high",
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xhigh: null,
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max: "max",
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});
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}
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for (const id of ["qwen3p8-max", "qwen3p8-2p4t-a95b"]) {
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expect(models[`accounts/fireworks/models/${id}`].thinkingLevelMap).toEqual({
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off: "none",
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minimal: null,
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low: "low",
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medium: "medium",
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high: null,
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xhigh: "xhigh",
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max: null,
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});
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}
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for (const model of Object.values(models)) {
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if (!hasApi(model, "anthropic-messages")) throw new Error("Expected Messages model");
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expect(model.compat?.allowEmptySignature).toBe(true);
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expect(model.compat?.forceAdaptiveThinking).toBe(model.id.endsWith("kimi-k2p6") ? undefined : true);
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}
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expect(models["accounts/fireworks/models/kimi-k2p6"].thinkingLevelMap).toBeUndefined();
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});
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// Regression for #9323: new effort-capable models must not require an allowlist update.
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it("automatically sends native effort for newly cataloged Messages models", async () => {
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const models = generateFireworksModels({
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"new-reasoner": [{ type: "toggle" }, { type: "effort", values: ["low", "max"] }],
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});
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const model = models["accounts/fireworks/models/new-reasoner"];
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if (!hasApi(model, "anthropic-messages")) throw new Error("Expected Messages model");
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expect(model.compat?.forceAdaptiveThinking).toBe(true);
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expect(getSupportedThinkingLevels(model)).toEqual(["off", "low", "max"]);
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let payload: Record<string, unknown> | undefined;
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await streamSimple(model, normalizeContext({ messages: [{ role: "user", content: "test", timestamp: 0 }] }), {
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apiKey: "test-fireworks-key",
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reasoning: "max",
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onPayload: (value) => {
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payload = value as Record<string, unknown>;
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throw new Error("payload captured");
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},
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}).result();
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expect(payload?.thinking).toEqual({ type: "adaptive", display: "summarized" });
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expect(payload?.output_config).toEqual({ effort: "max" });
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});
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it("does not infer adaptive thinking from toggle, budget, or missing metadata", () => {
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const models = generateFireworksModels({
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"toggle-only": [{ type: "toggle" }],
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"budget-only": [{ type: "budget_tokens", min: 1024 }],
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"fixed-reasoning": [],
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"missing-metadata": undefined,
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});
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for (const model of Object.values(models)) {
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if (!hasApi(model, "anthropic-messages")) throw new Error("Expected Messages model");
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expect(model.compat?.forceAdaptiveThinking).toBeUndefined();
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expect(model.thinkingLevelMap).toBeUndefined();
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}
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});
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// Regression for #9323: full hardcoded maps must not override updated catalog efforts.
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it("prefers updated upstream efforts over fixed maps and the Qwen fallback", () => {
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const models = generateFireworksModels({
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"deepseek-v4-flash-0731": [{ type: "effort", values: ["high", "max"] }],
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"qwen3p8-max": [{ type: "toggle" }, { type: "effort", values: ["medium", "xhigh"] }],
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});
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expect(models["accounts/fireworks/models/deepseek-v4-flash-0731"].thinkingLevelMap).toEqual({
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off: null,
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minimal: null,
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low: null,
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medium: null,
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high: "high",
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xhigh: null,
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max: "max",
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});
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expect(models["accounts/fireworks/models/qwen3p8-max"].thinkingLevelMap).toEqual({
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off: "none",
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minimal: null,
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low: null,
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medium: "medium",
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high: null,
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xhigh: "xhigh",
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max: null,
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});
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});
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});
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