Cursor-hosted models (cu/composer-2.5, cu/cursor-grok-*, cu/default) returned HTTP 200 with an empty turn, or hung, whenever a client sent tools. - Fold system prompts into the current user message. custom_system_prompt (RunRequest field 8) makes AgentService return an empty turn. - Send ModelDetails (field 3); thinking variants (Composer, Grok, *-thinking) return an empty turn when only requested_model (field 9) is set. - Route tool-call history and declared tool schemas through AgentService: encode OpenAI tools into mcp_tools (field 4), decode McpArgs and emit real tool_calls with finish_reason tool_calls. - Map Composer thinking / Grok thinking_delta (field 4) into visible content instead of dropping the answer with the unsigned reasoning. - Ack request_context without echoing MCP tools (double-advertise stalls the HTTP/2 stream) and ack kv_server_message so the run proceeds. - Reject IDE builtin execs instead of failing the turn, so the model can continue with MCP tools or a text answer. - Add google.protobuf.Value / MCP encoders and a FIXED64 branch to encodeField in cursorProtobuf.js. RTK now compresses the source-format body before translation for cursor only: its translator rewrites role:tool into user XML, so the post-translate pass missed those tool results. Every other provider keeps the post-translate pass unchanged.
132 lines
4.4 KiB
JavaScript
132 lines
4.4 KiB
JavaScript
import { describe, it, expect, vi, beforeEach } from "vitest";
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const { executeMock } = vi.hoisted(() => ({
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executeMock: vi.fn(),
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}));
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vi.mock("../../open-sse/executors/index.js", () => ({
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getExecutor: () => ({
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noAuth: true,
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execute: executeMock,
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}),
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}));
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vi.mock("../../open-sse/utils/requestLogger.js", () => ({
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createRequestLogger: async () => ({
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logClientRawRequest: vi.fn(),
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logRawRequest: vi.fn(),
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logTargetRequest: vi.fn(),
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logProviderResponse: vi.fn(),
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logConvertedResponse: vi.fn(),
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logError: vi.fn(),
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}),
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}));
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vi.mock("../../open-sse/utils/stream.js", () => ({
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COLORS: { red: "", reset: "" },
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createPassthroughStreamWithLogger: vi.fn(() => new TransformStream()),
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}));
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vi.mock("@/lib/usageDb.js", () => ({
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trackPendingRequest: vi.fn(),
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appendRequestLog: vi.fn(async () => {}),
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saveRequestDetail: vi.fn(async () => {}),
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}));
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const { handleChatCore } = await import("../../open-sse/handlers/chatCore.js");
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function makeLongDiff() {
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const lines = ["diff --git a/foo.js b/foo.js", "index abc..def 100644", "--- a/foo.js", "+++ b/foo.js", "@@ -1,3 +1,200 @@"];
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for (let i = 0; i < 200; i++) lines.push(`+added line ${i} UNIQUE_PADDING_${i} ${"x".repeat(20)}`);
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return lines.join("\n");
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}
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describe("token savers on Cursor (pre-translate RTK)", () => {
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beforeEach(() => {
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vi.clearAllMocks();
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global.fetch = vi.fn(async (url, init) => {
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if (String(url).includes("/v1/compress")) {
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const payload = JSON.parse(init.body);
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return new Response(JSON.stringify({
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messages: payload.messages,
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tokens_before: 8000,
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tokens_after: 2500,
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tokens_saved: 5500,
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}), { status: 200, headers: { "content-type": "application/json" } });
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}
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throw new Error(`unexpected fetch: ${url}`);
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});
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executeMock.mockResolvedValue({
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response: new Response(JSON.stringify({
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id: "chatcmpl-test",
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object: "chat.completion",
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choices: [{ message: { role: "assistant", content: "ok" }, finish_reason: "stop", index: 0 }],
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}), { status: 200, headers: { "content-type": "application/json" } }),
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url: "https://api2.cursor.sh/agent",
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headers: {},
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transformedBody: null,
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});
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});
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it("compresses role:tool git diffs before openai→cursor rewrite, then injects Headroom/Caveman/Ponytail", async () => {
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const diff = makeLongDiff();
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const log = { debug: vi.fn(), info: vi.fn(), warn: vi.fn(), line: vi.fn() };
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await handleChatCore({
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body: {
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model: "cu/default",
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stream: false,
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messages: [
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{ role: "system", content: "hi" },
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{ role: "user", content: "run git diff" },
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{
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role: "assistant",
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content: null,
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tool_calls: [{ id: "call_1", type: "function", function: { name: "Bash", arguments: JSON.stringify({ command: "git diff" }) } }],
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},
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{ role: "tool", tool_call_id: "call_1", content: diff },
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{ role: "user", content: "summarize" },
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],
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},
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modelInfo: { provider: "cursor", model: "default" },
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credentials: { apiKey: "test-key", providerSpecificData: {} },
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log,
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connectionId: "test-conn",
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rtkEnabled: true,
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headroomEnabled: true,
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headroomUrl: "http://localhost:8787",
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cavemanEnabled: true,
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cavemanLevel: "full",
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ponytailEnabled: true,
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ponytailLevel: "full",
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clientRawRequest: {
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endpoint: "/v1/chat/completions",
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body: { model: "cu/default" },
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headers: { accept: "application/json" },
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},
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});
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expect(executeMock).toHaveBeenCalled();
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const dispatched = executeMock.mock.calls[0][0].body;
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const blob = JSON.stringify(dispatched.messages);
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expect(dispatched.messages.some((m) => m.role === "tool")).toBe(false);
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expect(blob).toContain("<tool_result>");
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expect(blob).toContain("lines truncated");
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expect(blob).not.toContain("UNIQUE_PADDING_150");
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expect(blob).toContain("lazy senior developer");
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expect(blob).toMatch(/Respond like a caveman|drop filler|ACTIVE EVERY RESPONSE/i);
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expect(global.fetch).toHaveBeenCalledWith(
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"http://localhost:8787/v1/compress",
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expect.any(Object)
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);
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const xf = log.line.mock.calls.find((c) => c[1] === "⚙");
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expect(xf, "expected ⚙ saver log").toBeTruthy();
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expect(xf[2]).toContain("RTK:");
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expect(xf[2]).toContain("CAVEMAN:full");
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expect(xf[2]).toContain("PONYTAIL:full");
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});
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});
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