mirror of
https://github.com/Nezumi-2711/9router.git
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fix(translator): ESM-safe registry + tool-id pairing + responses max_tokens; add real-creds tests
- translator/index.js: replace require() with static side-effect imports (ESM-safe), lazy-init registry maps to survive circular import order - openai-responses->openai: map max_output_tokens -> max_tokens (avoid leaking field upstream) - gemini/antigravity -> openai: derive deterministic tool_call id from name so functionCall/functionResponse pair correctly (fixes provider tool-pairing 400s) - add offline unit tests (finish-reason, usage, session-manager, ollama malformed args, const guard) - add real-creds integration tests (provider-cases + all-formats matrix: 6 inbound formats x 4 scenarios) Includes co-located provider registry refactor (pricing/capabilities/media providers) and sessionManager updates. Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
decolua
@@ -27,7 +27,7 @@ describe("Antigravity → OpenAI", () => {
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// antigravity-to-openai.js:167 — functionCall without id gets a random Date.now() id
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// KNOWN BUG: unstable id breaks matching with its functionResponse
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it.fails("functionCall without id keeps a stable matchable id", () => {
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it("functionCall without id keeps a stable matchable id", () => {
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const out = AG2O({
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contents: [
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{ role: "model", parts: [{ functionCall: { name: "search", args: { q: "x" } } }] },
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@@ -0,0 +1,293 @@
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// REAL matrix test: every active provider in DB x every inbound client format x 4 scenarios.
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// Goal: maximize translation-path coverage to surface real bugs (system, multimodal image,
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// tool-call/tool-result, reasoning) across all source formats.
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//
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// RUN_REAL=1 npx vitest run --config tests/vitest.config.js tests/translator/real/all-formats.real.test.js
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// RUN_REAL=1 REAL_PROVIDERS=gemini,kiro,codex npx vitest run ... (optional filter)
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//
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// Skips (console.warn + pass) when: no credential/model, auth/quota status (401/402/403/429),
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// or the model rejects a capability (e.g. image on a non-vision model).
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import { describe, it, expect } from "vitest";
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import { getProviderCredentials } from "../../../src/sse/services/auth.js";
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import { checkAndRefreshToken } from "../../../src/sse/services/tokenRefresh.js";
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import { handleChatCore } from "../../../open-sse/handlers/chatCore.js";
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import { getModelsByProviderId } from "../../../open-sse/config/providerModels.js";
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const RUN_REAL = process.env.RUN_REAL === "1";
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const TIMEOUT_MS = 90000;
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const CRED_ISSUE = [401, 402, 403, 429];
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// Account/plan/capability rejections -> skip (not a translate bug). Kept specific to avoid masking real bugs.
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const SKIP_MSG_RE = /image|multimodal|vision|modality|unsupported|not support|reasoning_effort|deprecated|temperature|subscription|valid.*plan|embedding|quota|insufficient|model not found|context length|organization policy|disallowed|allowedmodels|failed_precondition/i;
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const PROVIDER_FILTER = (process.env.REAL_PROVIDERS || "")
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.split(",").map((s) => s.trim()).filter(Boolean);
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// Tiny 1x1 transparent PNG (data URI body + raw base64) for multimodal scenarios.
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const PNG_B64 =
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"iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYPhfDwAChwGA60e6kgAAAABJRU5ErkJggg==";
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const PNG_DATA_URI = `data:image/png;base64,${PNG_B64}`;
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// Pick first chat LLM, excluding non-chat kinds (embedding/image/tts/stt/...).
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const NON_CHAT_KINDS = new Set(["embedding", "image", "imageToText", "tts", "stt", "video", "music", "webSearch"]);
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function firstLlmModel(providerId) {
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const models = getModelsByProviderId(providerId);
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const llm = models.find((m) => {
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const kind = m.kind || m.type || "llm";
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return kind === "llm" || (!NON_CHAT_KINDS.has(kind) && kind === "llm");
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}) || models.find((m) => !NON_CHAT_KINDS.has(m.kind || m.type || "llm"));
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return llm?.id || null;
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}
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async function drainSSE(response) {
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if (!response?.body) return "";
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const reader = response.body.getReader();
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const decoder = new TextDecoder();
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let out = "";
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while (true) {
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const { done, value } = await reader.read();
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if (done) break;
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out += decoder.decode(value, { stream: true });
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}
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return out;
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}
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async function prepare(providerId) {
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const model = firstLlmModel(providerId);
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if (!model) return null;
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const credentials = await getProviderCredentials(providerId, new Set(), model);
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if (!credentials || credentials.allRateLimited) return null;
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const refreshed = await checkAndRefreshToken(providerId, credentials);
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return { model, credentials, refreshed };
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}
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// Run one request. Returns { raw } | "skip" | throws (real translate/runtime bug).
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async function runChat(providerId, prep, body, sourceFormatOverride) {
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const result = await handleChatCore({
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body: { ...body, model: `${providerId}/${prep.model}` },
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modelInfo: { provider: providerId, model: prep.model },
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credentials: prep.refreshed,
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connectionId: prep.credentials.connectionId,
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sourceFormatOverride,
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});
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if (!result.success) {
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const status = Number(result.status);
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if (CRED_ISSUE.includes(status)) return "skip";
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// Upstream 5xx and 406 are provider-side issues, not translate bugs.
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if (status >= 500 || status === 406) return "skip";
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// Account/plan/capability rejection (e.g. non-vision model + image) is not a translate bug.
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if (status === 400 && SKIP_MSG_RE.test(String(result.error || ""))) return "skip";
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throw new Error(`${providerId} [${result.status}]: ${result.error}`);
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}
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return { raw: await drainSSE(result.response) };
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}
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// SSE validity marker per inbound format (response is re-encoded back to source format).
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const SSE_MARKER = {
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openai: /chat\.completion\.chunk|"delta"|\[DONE\]/,
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"openai-responses": /response\.|"type"\s*:\s*"response|\[DONE\]/,
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claude: /event:\s*\w|"type"\s*:\s*"(message_start|content_block|message_delta)"/,
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gemini: /"candidates"|"content"|data:/,
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"gemini-cli": /"candidates"|"content"|data:/,
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antigravity: /"candidates"|"content"|data:/,
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};
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// ---- Body builders: per format x scenario (full, spec-correct shapes) ----
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const COMMON = { temperature: 0.3, top_p: 0.9, max_tokens: 256 };
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// Reasoning models often reject custom temperature (must be default/1) -> omit sampling.
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const REASON_TOK = { max_tokens: 1024 };
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// OpenAI Chat Completions
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const openaiBody = {
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basic: () => ({
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...COMMON, stream: true, stream_options: { include_usage: true },
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messages: [
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{ role: "system", content: "You are concise." },
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{ role: "user", content: "Reply with the single word: hi" },
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],
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}),
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multimodal: () => ({
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...COMMON, stream: true,
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messages: [
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{ role: "system", content: "Describe images briefly." },
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{ role: "user", content: [
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{ type: "text", text: "What color dominates this image? One word." },
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{ type: "image_url", image_url: { url: PNG_DATA_URI } },
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] },
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],
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}),
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tools: () => ({
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...COMMON, stream: true, tool_choice: "auto",
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tools: [{ type: "function", function: { name: "get_weather", description: "Get weather", parameters: { type: "object", properties: { city: { type: "string" } }, required: ["city"] } } }],
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messages: [
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{ role: "user", content: "Weather in Paris?" },
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{ role: "assistant", content: "", tool_calls: [{ id: "call_1", type: "function", function: { name: "get_weather", arguments: '{"city":"Paris"}' } }] },
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{ role: "tool", tool_call_id: "call_1", content: '{"temp":"20C"}' },
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{ role: "user", content: "Summarize in one short sentence." },
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],
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}),
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reasoning: () => ({
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...REASON_TOK, stream: true, reasoning_effort: "low",
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messages: [{ role: "user", content: "What is 17 + 26? Reply with just the number." }],
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}),
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};
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// OpenAI Responses API
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const responsesBody = {
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basic: () => ({
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...COMMON, stream: true, max_output_tokens: 256,
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instructions: "You are concise.",
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input: [{ type: "message", role: "user", content: [{ type: "input_text", text: "Reply with the single word: hi" }] }],
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}),
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multimodal: () => ({
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...COMMON, stream: true, max_output_tokens: 256,
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instructions: "Describe images briefly.",
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input: [{ type: "message", role: "user", content: [
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{ type: "input_text", text: "What color dominates? One word." },
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{ type: "input_image", image_url: PNG_DATA_URI },
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] }],
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}),
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tools: () => ({
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...COMMON, stream: true,
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tools: [{ type: "function", name: "get_weather", description: "Get weather", parameters: { type: "object", properties: { city: { type: "string" } }, required: ["city"] } }],
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input: [
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{ type: "message", role: "user", content: [{ type: "input_text", text: "Weather in Paris?" }] },
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{ type: "function_call", call_id: "call_1", name: "get_weather", arguments: '{"city":"Paris"}' },
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{ type: "function_call_output", call_id: "call_1", output: '{"temp":"20C"}' },
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{ type: "message", role: "user", content: [{ type: "input_text", text: "Summarize in one short sentence." }] },
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],
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}),
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reasoning: () => ({
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...REASON_TOK, stream: true, max_output_tokens: 1024, reasoning: { effort: "low" },
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input: [{ type: "message", role: "user", content: [{ type: "input_text", text: "What is 17 + 26? Just the number." }] }],
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}),
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};
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// Anthropic Messages (Claude)
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const claudeBody = {
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basic: () => ({
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...COMMON, stream: true,
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system: [{ type: "text", text: "You are concise." }],
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messages: [{ role: "user", content: "Reply with the single word: hi" }],
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}),
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multimodal: () => ({
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...COMMON, stream: true,
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system: [{ type: "text", text: "Describe images briefly." }],
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messages: [{ role: "user", content: [
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{ type: "text", text: "What color dominates? One word." },
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{ type: "image", source: { type: "base64", media_type: "image/png", data: PNG_B64 } },
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] }],
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}),
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tools: () => ({
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...COMMON, stream: true,
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tools: [{ name: "get_weather", description: "Get weather", input_schema: { type: "object", properties: { city: { type: "string" } }, required: ["city"] } }],
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messages: [
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{ role: "user", content: "Weather in Paris?" },
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{ role: "assistant", content: [{ type: "tool_use", id: "toolu_1", name: "get_weather", input: { city: "Paris" } }] },
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{ role: "user", content: [{ type: "tool_result", tool_use_id: "toolu_1", content: '{"temp":"20C"}' }] },
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{ role: "user", content: "Summarize in one short sentence." },
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],
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}),
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reasoning: () => ({
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...REASON_TOK, stream: true, thinking: { type: "enabled", budget_tokens: 1024 },
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messages: [{ role: "user", content: "What is 17 + 26? Just the number." }],
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}),
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};
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// Gemini generateContent
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const geminiBody = {
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basic: () => ({
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systemInstruction: { parts: [{ text: "You are concise." }] },
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contents: [{ role: "user", parts: [{ text: "Reply with the single word: hi" }] }],
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generationConfig: { maxOutputTokens: 256, temperature: 0.3, topP: 0.9 },
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}),
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multimodal: () => ({
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systemInstruction: { parts: [{ text: "Describe images briefly." }] },
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contents: [{ role: "user", parts: [
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{ text: "What color dominates? One word." },
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{ inlineData: { mimeType: "image/png", data: PNG_B64 } },
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] }],
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generationConfig: { maxOutputTokens: 256 },
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}),
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tools: () => ({
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tools: [{ functionDeclarations: [{ name: "get_weather", description: "Get weather", parameters: { type: "object", properties: { city: { type: "string" } }, required: ["city"] } }] }],
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contents: [
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{ role: "user", parts: [{ text: "Weather in Paris?" }] },
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{ role: "model", parts: [{ functionCall: { name: "get_weather", args: { city: "Paris" } } }] },
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{ role: "user", parts: [{ functionResponse: { name: "get_weather", response: { temp: "20C" } } }] },
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{ role: "user", parts: [{ text: "Summarize in one short sentence." }] },
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],
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generationConfig: { maxOutputTokens: 256 },
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}),
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reasoning: () => ({
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contents: [{ role: "user", parts: [{ text: "What is 17 + 26? Just the number." }] }],
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generationConfig: { maxOutputTokens: 1024, thinkingConfig: { thinkingBudget: 512, includeThoughts: true } },
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}),
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};
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// Antigravity = Gemini body wrapped in { request, userAgent }.
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const wrapAntigravity = (fn) => () => ({ request: fn(), userAgent: "antigravity" });
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const antigravityBody = {
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basic: wrapAntigravity(geminiBody.basic),
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multimodal: wrapAntigravity(geminiBody.multimodal),
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tools: wrapAntigravity(geminiBody.tools),
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reasoning: wrapAntigravity(geminiBody.reasoning),
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};
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const BUILDERS = {
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openai: openaiBody,
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"openai-responses": responsesBody,
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claude: claudeBody,
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gemini: geminiBody,
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"gemini-cli": geminiBody,
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antigravity: antigravityBody,
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};
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const FORMATS = Object.keys(BUILDERS);
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const SCENARIOS = ["basic", "multimodal", "tools", "reasoning"];
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// Read active providers from DB at module-eval time (one test per provider/format/scenario).
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function targetProviders() {
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try {
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const Database = require("better-sqlite3");
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const os = require("os");
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const path = require("path");
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const dbPath = process.env.DATA_DIR
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? path.join(process.env.DATA_DIR, "db", "data.sqlite")
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: path.join(os.homedir(), ".9router", "db", "data.sqlite");
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const db = new Database(dbPath, { readonly: true });
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const rows = db.prepare("SELECT DISTINCT provider FROM providerConnections WHERE isActive = 1").all();
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db.close();
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let list = rows.map((r) => r.provider).sort();
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if (PROVIDER_FILTER.length) list = list.filter((p) => PROVIDER_FILTER.includes(p));
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return list;
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} catch {
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return [];
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}
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}
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describe.skipIf(!RUN_REAL)("REAL all-formats matrix", () => {
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const providers = RUN_REAL ? targetProviders() : [];
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it("has active providers in DB", () => {
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expect(providers.length).toBeGreaterThan(0);
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});
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for (const providerId of providers) {
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for (const fmt of FORMATS) {
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for (const scn of SCENARIOS) {
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it.concurrent(`${providerId} | ${fmt} | ${scn}`, async () => {
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const prep = await prepare(providerId);
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if (!prep) { console.warn(`[skip] ${providerId}: no cred/model`); return expect(true).toBe(true); }
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const body = BUILDERS[fmt][scn]();
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const out = await runChat(providerId, prep, body, fmt);
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if (out === "skip") { console.warn(`[skip] ${providerId} ${fmt}/${scn}: cred/quota/capability`); return expect(true).toBe(true); }
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expect(out.raw.length, `${providerId} ${fmt}/${scn}: empty SSE`).toBeGreaterThan(0);
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expect(SSE_MARKER[fmt].test(out.raw), `${providerId} ${fmt}/${scn}: invalid SSE shape`).toBe(true);
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}, TIMEOUT_MS);
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}
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}
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}
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});
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@@ -0,0 +1,168 @@
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// B2: REAL behavior assertions for the risky provider-specific cases.
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// Unlike smoke (only "doesn't crash"), each test asserts concrete OUTPUT.
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// Gated by RUN_REAL=1; any provider lacking creds/model or returning an auth/quota
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// status (401/402/403/429) is skipped (console.warn + pass).
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//
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// RUN_REAL=1 npx vitest run --config tests/vitest.config.js tests/translator/real/provider-cases.real.test.js
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import { describe, it, expect } from "vitest";
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import { getProviderCredentials } from "../../../src/sse/services/auth.js";
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import { checkAndRefreshToken } from "../../../src/sse/services/tokenRefresh.js";
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import { handleChatCore } from "../../../open-sse/handlers/chatCore.js";
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import { getModelsByProviderId } from "../../../open-sse/config/providerModels.js";
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const RUN_REAL = process.env.RUN_REAL === "1";
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const TIMEOUT_MS = 90000;
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const CRED_ISSUE = [401, 402, 403, 429];
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// Pick the first plain llm model for a provider.
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function firstLlmModel(providerId) {
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const models = getModelsByProviderId(providerId);
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const llm = models.find((m) => (m.type || "llm") === "llm");
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return llm?.id || null;
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}
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async function drainSSE(response) {
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if (!response?.body) return "";
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const reader = response.body.getReader();
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const decoder = new TextDecoder();
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let out = "";
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while (true) {
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const { done, value } = await reader.read();
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if (done) break;
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out += decoder.decode(value, { stream: true });
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}
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return out;
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}
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// Resolve creds+model for a provider, or null when unavailable (caller skips).
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async function prepare(providerId) {
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const model = firstLlmModel(providerId);
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if (!model) {
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console.warn(`[skip] ${providerId}: no llm model`);
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return null;
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}
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const credentials = await getProviderCredentials(providerId, new Set(), model);
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if (!credentials || credentials.allRateLimited) {
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console.warn(`[skip] ${providerId}: no usable credential`);
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return null;
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}
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const refreshed = await checkAndRefreshToken(providerId, credentials);
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return { model, credentials, refreshed };
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}
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// Run handleChatCore + drain; returns { raw } or null if cred/quota issue (caller skips).
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async function runChat(providerId, prep, body) {
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const result = await handleChatCore({
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body: { model: `${providerId}/${prep.model}`, ...body },
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modelInfo: { provider: providerId, model: prep.model },
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credentials: prep.refreshed,
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connectionId: prep.credentials.connectionId,
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});
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if (!result.success) {
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if (CRED_ISSUE.includes(Number(result.status))) {
|
||||
console.warn(`[skip] ${providerId}: ${result.status} (credential/quota)`);
|
||||
return null;
|
||||
}
|
||||
throw new Error(`${providerId} failed: ${result.status} ${result.error}`);
|
||||
}
|
||||
return { raw: await drainSSE(result.response) };
|
||||
}
|
||||
|
||||
describe.skipIf(!RUN_REAL)("REAL provider behavior cases", () => {
|
||||
// Case #1: Gemini normal prompt -> finish_reason "stop".
|
||||
it("gemini: finish_reason stop", async () => {
|
||||
const prep = await prepare("gemini");
|
||||
if (!prep) return expect(true).toBe(true);
|
||||
// Generous max_tokens so reasoning models (gemini-3 pro) don't hit "length" first.
|
||||
const out = await runChat("gemini", prep, {
|
||||
stream: true,
|
||||
max_tokens: 2048,
|
||||
messages: [{ role: "user", content: "Reply with the single word: hi" }],
|
||||
});
|
||||
if (!out) return expect(true).toBe(true);
|
||||
expect(/"finish_reason"\s*:\s*"stop"/.test(out.raw), "no stop finish_reason").toBe(true);
|
||||
}, TIMEOUT_MS);
|
||||
|
||||
// Case #4: Kiro tool turn -> tool_calls finish_reason + tool_calls delta.
|
||||
it("kiro: tool turn -> tool_calls", async () => {
|
||||
const prep = await prepare("kiro");
|
||||
if (!prep) return expect(true).toBe(true);
|
||||
const out = await runChat("kiro", prep, {
|
||||
stream: true,
|
||||
max_tokens: 128,
|
||||
tool_choice: "auto",
|
||||
tools: [{
|
||||
type: "function",
|
||||
function: {
|
||||
name: "get_weather",
|
||||
description: "Get the current weather for a city",
|
||||
parameters: {
|
||||
type: "object",
|
||||
properties: { city: { type: "string", description: "City name" } },
|
||||
required: ["city"],
|
||||
},
|
||||
},
|
||||
}],
|
||||
messages: [{ role: "user", content: "What's the weather in Paris? Use the get_weather tool." }],
|
||||
});
|
||||
if (!out) return expect(true).toBe(true);
|
||||
expect(/"finish_reason"\s*:\s*"tool_calls"/.test(out.raw), "no tool_calls finish_reason").toBe(true);
|
||||
expect(/"tool_calls"/.test(out.raw), "no tool_calls delta").toBe(true);
|
||||
}, TIMEOUT_MS);
|
||||
|
||||
// Case #3: Ollama tiny max_tokens + long prompt -> finish_reason "length".
|
||||
it("ollama: max_tokens -> length", async () => {
|
||||
const prep = await prepare("ollama");
|
||||
if (!prep) return expect(true).toBe(true);
|
||||
const out = await runChat("ollama", prep, {
|
||||
stream: true,
|
||||
max_tokens: 4,
|
||||
messages: [{ role: "user", content: "Write a long detailed essay about the history of computing." }],
|
||||
});
|
||||
if (!out) return expect(true).toBe(true);
|
||||
// length is model-dependent; if the model stopped on its own, skip rather than fail.
|
||||
if (!/"finish_reason"\s*:\s*"length"/.test(out.raw)) {
|
||||
console.warn("[skip] ollama: model did not hit length (output shorter than max_tokens)");
|
||||
return expect(true).toBe(true);
|
||||
}
|
||||
expect(/"finish_reason"\s*:\s*"length"/.test(out.raw)).toBe(true);
|
||||
}, TIMEOUT_MS);
|
||||
|
||||
// Case #4/#5: Codex multi-turn -> session stickiness (prompt-cache hit on 2nd turn).
|
||||
it("codex: session stickiness (cached_tokens on 2nd turn)", async () => {
|
||||
const prep = await prepare("codex");
|
||||
if (!prep) return expect(true).toBe(true);
|
||||
const longContext = "The capital of France is Paris. ".repeat(40);
|
||||
const messages = [
|
||||
{ role: "user", content: longContext },
|
||||
{ role: "assistant", content: "Understood. I have noted that context." },
|
||||
{ role: "user", content: "Reply with the single word: ok" },
|
||||
];
|
||||
const body = { stream: true, max_tokens: 32, messages };
|
||||
const first = await runChat("codex", prep, body);
|
||||
if (!first) return expect(true).toBe(true);
|
||||
const second = await runChat("codex", prep, body);
|
||||
if (!second) return expect(true).toBe(true);
|
||||
// 2nd identical-context turn should hit prompt cache when session is sticky.
|
||||
const m = second.raw.match(/"cached_tokens"\s*:\s*(\d+)/);
|
||||
if (!m) {
|
||||
console.warn("[skip] codex: no cached_tokens in usage (provider may not report)");
|
||||
return expect(true).toBe(true);
|
||||
}
|
||||
expect(Number(m[1]), "cached_tokens not > 0 on 2nd turn").toBeGreaterThan(0);
|
||||
}, TIMEOUT_MS);
|
||||
|
||||
// Case #1/#2: Antigravity normal prompt -> valid SSE response.
|
||||
it("antigravity: responds OK", async () => {
|
||||
const prep = await prepare("antigravity");
|
||||
if (!prep) return expect(true).toBe(true);
|
||||
const out = await runChat("antigravity", prep, {
|
||||
stream: true,
|
||||
max_tokens: 32,
|
||||
messages: [{ role: "user", content: "Reply with the single word: hi" }],
|
||||
});
|
||||
if (!out) return expect(true).toBe(true);
|
||||
expect(out.raw.length, "empty response").toBeGreaterThan(0);
|
||||
expect(/data:|finish_reason|"delta"|"content"|event:/.test(out.raw), "not SSE").toBe(true);
|
||||
}, TIMEOUT_MS);
|
||||
});
|
||||
Reference in New Issue
Block a user