fix(minimax): preserve images on matched OpenAI transport

Prefer the sourceFormat-matched runtime transport over a model's
declared targetFormat when both apply. MiniMax-M3 previously resolved
to a Claude-shaped body while being posted to the already-selected
OpenAI endpoint, silently dropping image_url blocks from OpenAI
clients. Fixes #3418.
This commit is contained in:
turingcat
2026-08-28 16:33:29 +07:00
parent 2a9213c5bd
commit 28d005772a
2 changed files with 195 additions and 1 deletions

View File

@@ -91,7 +91,12 @@ export async function handleChatCore({ body, modelInfo, credentials, log, onCred
// differ — kimi/glm only do /chat/completions). Undeclared models keep the
// upstream default (use the transport), preserving behavior for glm/deepseek/...
const useTransport = (!modelSupportedFormats || modelSupportedFormats.includes(sourceFormat)) ? runtimeTransport : null;
const targetFormat = modelTargetFormat || useTransport?.format || getTargetFormat(provider, credentials);
// A source-format-matched endpoint keeps the request lossless. Prefer it
// over a model-level targetFormat, which is only the fallback for clients
// whose wire format has no supported transport (for example MiniMax-M3:
// OpenAI clients should stay on /chat/completions; other clients can fall
// back to its declared Claude target).
const targetFormat = useTransport?.format || modelTargetFormat || getTargetFormat(provider, credentials);
if (useTransport && credentials) credentials.runtimeTransport = useTransport;
const stripList = getModelStrip(alias, model);
const upstreamModel = getModelUpstreamId(alias, model);

View File

@@ -0,0 +1,189 @@
/**
* Multi-transport providers must keep the request body and selected endpoint on
* the same wire format. MiniMax-M3 declares a Claude target for compatibility,
* but an OpenAI client should use MiniMax's matching OpenAI transport without
* an OpenAI -> Claude translation.
* Regression: https://github.com/decolua/9router/issues/3418
*/
import { beforeEach, describe, expect, it, vi } from "vitest";
const {
executeMock,
translateRequestMock,
handleNonStreamingResponseMock,
} = vi.hoisted(() => ({
executeMock: vi.fn(),
translateRequestMock: vi.fn((sourceFormat, targetFormat, model, body) => ({
...body,
model,
_translatedFrom: sourceFormat,
_translatedTo: targetFormat,
})),
handleNonStreamingResponseMock: vi.fn(async () => ({ success: true })),
}));
vi.mock("../../open-sse/executors/index.js", () => ({
getExecutor: vi.fn(() => ({
execute: executeMock,
refreshCredentials: vi.fn().mockResolvedValue(null),
})),
}));
vi.mock("../../open-sse/translator/index.js", () => ({
translateRequest: translateRequestMock,
}));
vi.mock("../../open-sse/handlers/chatCore/nonStreamingHandler.js", () => ({
handleNonStreamingResponse: handleNonStreamingResponseMock,
}));
vi.mock("../../open-sse/utils/requestLogger.js", () => ({
createRequestLogger: vi.fn(async () => ({
logClientRawRequest: vi.fn(),
logRawRequest: vi.fn(),
logTargetRequest: vi.fn(),
logError: vi.fn(),
})),
}));
vi.mock("../../open-sse/utils/clientDetector.js", () => ({
detectClientTool: vi.fn(() => null),
isNativePassthrough: vi.fn(() => false),
}));
vi.mock("../../open-sse/utils/bypassHandler.js", () => ({
handleBypassRequest: vi.fn(() => null),
}));
vi.mock("../../open-sse/utils/streamHandler.js", () => ({
createStreamController: vi.fn(() => ({
signal: undefined,
handleComplete: vi.fn(),
handleError: vi.fn(),
})),
}));
vi.mock("../../open-sse/services/tokenRefresh.js", () => ({
refreshWithRetry: vi.fn(),
}));
vi.mock("../../open-sse/utils/proxyFetch.js", () => ({
default: vi.fn(),
proxyAwareFetch: vi.fn(),
}));
vi.mock("../../open-sse/translator/formats/claude.js", () => ({
normalizeClaudePassthrough: vi.fn(),
anchorClaudeCache: vi.fn(),
}));
vi.mock("../../open-sse/utils/toolDeduper.js", () => ({
dedupeTools: vi.fn((tools) => ({ tools, stripped: [] })),
}));
vi.mock("../../open-sse/rtk/caveman.js", () => ({ injectCaveman: vi.fn() }));
vi.mock("../../open-sse/rtk/ponytail.js", () => ({ injectPonytail: vi.fn() }));
vi.mock("../../open-sse/rtk/index.js", () => ({
compressMessages: vi.fn(() => null),
formatRtkLog: vi.fn(() => ""),
}));
vi.mock("../../open-sse/rtk/headroom.js", () => ({
compressWithHeadroom: vi.fn(async () => null),
formatHeadroomLog: vi.fn(() => ""),
formatHeadroomSizeLog: vi.fn(() => ""),
isHeadroomPhantomSavings: vi.fn(() => false),
}));
vi.mock("../../open-sse/rtk/pxpipe.js", () => ({
compressWithPxpipe: vi.fn(async () => ({ body: null, summary: null })),
}));
vi.mock("../../open-sse/translator/concerns/prefetch.js", () => ({
prefetchRemoteImages: vi.fn(async () => 0),
}));
vi.mock("../../open-sse/handlers/chatCore/requestDetail.js", () => ({
buildRequestDetail: vi.fn((detail) => detail),
extractRequestConfig: vi.fn((body, stream) => ({ body, stream })),
}));
vi.mock("../../open-sse/utils/error.js", () => ({
createErrorResult: vi.fn((status, message) => ({ success: false, status, error: message })),
formatProviderError: vi.fn((error) => error.message),
parseUpstreamError: vi.fn(),
}));
vi.mock("@/lib/usageDb.js", () => ({
trackPendingRequest: vi.fn(),
appendRequestLog: vi.fn(() => Promise.resolve()),
saveRequestDetail: vi.fn(() => Promise.resolve()),
}));
function makeOptions(body) {
return {
body,
modelInfo: { provider: "minimax-cn", model: "MiniMax-M3" },
credentials: { apiKey: "test-api-key", providerSpecificData: {} },
clientRawRequest: {
endpoint: "/v1/chat/completions",
body,
headers: { accept: "application/json" },
},
connectionId: "test-connection",
log: { debug: vi.fn(), info: vi.fn(), warn: vi.fn(), error: vi.fn() },
};
}
describe("MiniMax-M3 multi-transport routing", () => {
beforeEach(() => {
executeMock.mockReset();
translateRequestMock.mockClear();
handleNonStreamingResponseMock.mockClear();
executeMock.mockResolvedValue({
response: new Response("{}", {
status: 200,
headers: { "content-type": "application/json" },
}),
url: "https://api.minimaxi.com/v1/chat/completions",
headers: {},
transformedBody: {},
});
});
it("keeps OpenAI image blocks on the matching OpenAI transport", async () => {
const imageBlock = {
type: "image_url",
image_url: { url: "data:image/png;base64,AAAB" },
};
const body = {
model: "minimax-cn/MiniMax-M3",
stream: false,
messages: [{
role: "user",
content: [{ type: "text", text: "Describe this image" }, imageBlock],
}],
};
const { handleChatCore } = await import("../../open-sse/handlers/chatCore.js");
await handleChatCore(makeOptions(body));
expect(translateRequestMock).toHaveBeenCalledWith(
"openai",
"openai",
"MiniMax-M3",
expect.any(Object),
false,
expect.any(Object),
"minimax-cn",
expect.any(Object),
expect.anything(),
"test-connection",
null,
);
expect(executeMock).toHaveBeenCalledTimes(1);
const requestBody = executeMock.mock.calls[0][0].body;
expect(requestBody.messages[0].content).toContainEqual(imageBlock);
expect(requestBody._translatedTo).toBe("openai");
expect(requestBody).not.toHaveProperty("system");
expect(executeMock.mock.calls[0][0].credentials.runtimeTransport.format).toBe("openai");
});
});