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.
168 lines
5.9 KiB
JavaScript
168 lines
5.9 KiB
JavaScript
import { describe, it, expect } from "vitest";
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import { CursorExecutor } from "../../open-sse/executors/cursor.js";
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import { encodeField, wrapConnectRPCFrame } from "../../open-sse/utils/cursorProtobuf.js";
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const LEN = 2;
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// agent.v1.AgentServerMessage.exec_request (field 2) carrying one ExecServerMessage variant.
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function execRequestFrame(execField) {
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const execServerMessage = Buffer.from(encodeField(execField, LEN, new Uint8Array()));
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return Buffer.from(wrapConnectRPCFrame(encodeField(2, LEN, execServerMessage)));
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}
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// agent.v1.AgentServerMessage.interaction_update (field 1) → text delta.
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function textFrame(text) {
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const textPart = Buffer.from(encodeField(1, LEN, text));
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const update = Buffer.from(encodeField(1, LEN, textPart));
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return Buffer.from(wrapConnectRPCFrame(encodeField(1, LEN, update)));
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}
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// InteractionUpdate.thinking_delta (field 4) + turn_ended (field 14).
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function thinkingFrame(text) {
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const thinkingPart = Buffer.from(encodeField(1, LEN, text));
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const update = Buffer.from(encodeField(4, LEN, thinkingPart));
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return Buffer.from(wrapConnectRPCFrame(encodeField(1, LEN, update)));
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}
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function turnEndedFrame() {
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const update = Buffer.from(encodeField(14, LEN, new Uint8Array()));
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return Buffer.from(wrapConnectRPCFrame(encodeField(1, LEN, update)));
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}
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function stubAgentSession(executor, frames) {
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const written = [];
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const queue = [...frames];
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executor.openAgentHttp2Stream = () => ({
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responseHeaders: Promise.resolve({ ":status": 200 }),
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write: (frame) => written.push(Buffer.from(frame)),
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end() {},
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close() {},
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async read() {
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if (!queue.length) return { value: undefined, done: true };
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return { value: queue.shift(), done: false };
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},
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});
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return written;
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}
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const credentials = {
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accessToken: "test-token",
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providerSpecificData: { machineId: "a".repeat(64) },
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};
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function parseSSE(text) {
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return text
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.split("\n\n")
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.filter((chunk) => chunk.startsWith("data: "))
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.map((chunk) => chunk.slice("data: ".length))
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.filter((data) => data !== "[DONE]")
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.map((data) => JSON.parse(data));
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}
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async function runAgent({ frames, stream, model = "gpt-5.2", tools }) {
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const executor = new CursorExecutor();
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const written = stubAgentSession(executor, frames);
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const result = await executor.executeAgent({
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model,
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body: { messages: [{ role: "user", content: "hi" }], ...(tools ? { tools } : {}) },
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stream,
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credentials,
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});
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return { result, written };
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}
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describe("CursorExecutor AgentService exec_request handling", () => {
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it("acknowledges a request-context exec request without ending the turn", async () => {
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const { result, written } = await runAgent({
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frames: [execRequestFrame(10), textFrame("hello")],
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stream: true,
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});
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expect(written.length).toBe(2); // run frame + request-context reply
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const events = parseSSE(await result.response.text());
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const content = events.map((e) => e.choices?.[0]?.delta?.content || "").join("");
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expect(content).toBe("hello");
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});
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it("does not echo client tools on the request_context ack", async () => {
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const { written, result } = await runAgent({
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tools: [{ function: { name: "read_file", parameters: { type: "object" } } }],
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frames: [execRequestFrame(10), textFrame("hello")],
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stream: true,
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});
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expect(written.length).toBe(2);
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expect(written[1].toString("utf8")).not.toContain("read_file");
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const content = parseSSE(await result.response.text())
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.map((e) => e.choices?.[0]?.delta?.content || "")
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.join("");
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expect(content).toBe("hello");
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});
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it("does not render an unsupported exec request as assistant content", async () => {
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const { result, written } = await runAgent({
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frames: [textFrame("partial answer"), execRequestFrame(2), textFrame(" more")],
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stream: true,
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});
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const body = await result.response.text();
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expect(body).not.toContain("unsupported IDE tool");
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const events = parseSSE(body);
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const content = events.map((e) => e.choices?.[0]?.delta?.content || "").join("");
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expect(content).toBe("partial answer more");
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expect(events.some((e) => e.error)).toBe(false);
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expect(written.length).toBe(2); // run frame + IDE rejection
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});
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it("still emits later text after rejecting an IDE exec in the same read", async () => {
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const { result } = await runAgent({
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frames: [Buffer.concat([execRequestFrame(2), textFrame("late")])],
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stream: true,
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});
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const body = await result.response.text();
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expect(body).not.toContain("unsupported IDE tool");
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expect(body).toContain("late");
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});
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it("returns a non-200 error body for an unsupported exec request when not streaming", async () => {
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const { result } = await runAgent({
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frames: [execRequestFrame(11)],
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stream: false,
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});
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expect(result.response.status).not.toBe(200);
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const payload = await result.response.json();
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expect(payload.error.message).toContain("unsupported IDE tool");
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});
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it("streams Composer visible content from thinking_delta after </think>", async () => {
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const { result } = await runAgent({
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model: "composer-2.5",
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frames: [
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thinkingFrame("private reasoning that must not leak</think>OK"),
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turnEndedFrame(),
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],
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stream: true,
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});
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const events = parseSSE(await result.response.text());
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const content = events.map((e) => e.choices?.[0]?.delta?.content || "").join("");
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expect(content).toBe("OK");
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expect(JSON.stringify(events)).not.toContain("private reasoning");
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});
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it("flushes Grok thinking as visible content when the turn has no text_delta", async () => {
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const { result } = await runAgent({
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model: "grok-4.5",
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frames: [thinkingFrame("hello from grok"), turnEndedFrame()],
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stream: true,
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});
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const events = parseSSE(await result.response.text());
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const content = events.map((e) => e.choices?.[0]?.delta?.content || "").join("");
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expect(content).toBe("hello from grok");
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});
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});
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