475 lines
17 KiB
TypeScript
475 lines
17 KiB
TypeScript
/**
|
|
* QwenWebExecutor — Alibaba Tongyi Qwen Chat via chat.qwen.ai (v2 API)
|
|
*
|
|
* Routes requests through Qwen's consumer chat API. The legacy v1 endpoint
|
|
* (`/api/chat/completions`) was retired upstream in 2026 and now answers 504
|
|
* HTML from Alibaba's gateway for every request, regardless of credentials
|
|
* (#3288 / discussion #2768). The current contract is a two-step v2 flow:
|
|
*
|
|
* 1. POST /api/v2/chats/new → create a chat, returns chat_id
|
|
* 2. POST /api/v2/chat/completions?chat_id= → phase-based SSE stream
|
|
*
|
|
* The v2 endpoints sit behind Alibaba's "baxia" WAF, which requires the full
|
|
* browser cookie jar from a real logged-in session (cna, ssxmod_itna,
|
|
* ssxmod_itna2, token, ...). We therefore replay the captured/pasted Cookie
|
|
* header verbatim plus the bearer token, mirroring how grok-web replays its
|
|
* anti-bot cookies.
|
|
*
|
|
* SSE chunks carry `choices[0].delta` with a `phase` field: `think` /
|
|
* `thinking_summary` map to reasoning, `answer` (or a null phase) carries the
|
|
* assistant content.
|
|
*
|
|
* Reference implementations: gpt4free `g4f/Provider/Qwen.py`,
|
|
* Chat2API `proxy/adapters/qwen-ai.ts`.
|
|
*
|
|
* Auth: full Cookie header from chat.qwen.ai + bearer token (localStorage
|
|
* `token`, also mirrored to a `token` cookie).
|
|
* Format: OpenAI-compatible (translated from Qwen's phase protocol).
|
|
*/
|
|
import { BaseExecutor, type ExecuteInput } from "./base.ts";
|
|
import { makeExecutorErrorResult as makeErrorResult } from "../utils/error.ts";
|
|
import { prepareToolMessages, buildToolAwareResult } from "../translator/webTools.ts";
|
|
import { buildQwenCookieHeader, extractQwenToken } from "@/lib/providers/webCookieAuth";
|
|
|
|
const BASE_URL = "https://chat.qwen.ai";
|
|
const CHATS_NEW_URL = `${BASE_URL}/api/v2/chats/new`;
|
|
const CHAT_COMPLETIONS_URL = `${BASE_URL}/api/v2/chat/completions`;
|
|
const USER_AGENT =
|
|
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/149.0.0.0 Safari/537.36";
|
|
|
|
// Anti-bot headers the v2 endpoint expects. `bx-umidtoken` is normally minted
|
|
// per-session from sg-wum.alibaba.com; a captured value travels with the cookie
|
|
// jar, but we also send a static fallback so the header is always present.
|
|
const BX_VERSION = "2.5.36";
|
|
const BX_UMIDTOKEN_FALLBACK = "T2gA0000000000000000000000000000000000000000";
|
|
|
|
// Qwen SPA version — required by the v2 chat completion endpoint. Without this
|
|
// header the upstream returns HTTP 200 with `{"success":false,"data":{"code":"Bad_Request"}}`
|
|
// for every completion request, even with a valid session. The version string is
|
|
// the SPA build identifier shipped in the React client's `version` request header.
|
|
// Pinned from a live capture (2026-07); bump if Qwen ships a breaking change.
|
|
const QWEN_SPA_VERSION = "0.2.66";
|
|
|
|
const MODEL_ALIASES: Record<string, string> = {
|
|
// Legacy OmniRoute ids → current upstream catalog (GET /api/models).
|
|
"qwen-plus": "qwen3.7-plus",
|
|
"qwen-max": "qwen3.7-max",
|
|
"qwen-turbo": "qwen3.6-plus",
|
|
"qwen3-plus": "qwen3.7-plus",
|
|
"qwen3-max": "qwen3.7-max",
|
|
"qwen3-flash": "qwen3.6-plus",
|
|
// Note: `qwen3-coder-plus` is a real upstream model id (Qwen3-Coder) and
|
|
// must NOT be aliased — the previous `"qwen3-coder-plus": "qwen3.7-max"`
|
|
// entry silently rewrote valid coder requests to the wrong model.
|
|
"qwen3-coder-flash": "qwen3.6-plus",
|
|
qwen: "qwen3.7-max",
|
|
qwen3: "qwen3.7-max",
|
|
};
|
|
|
|
const DEFAULT_MODEL = "qwen3.7-max";
|
|
|
|
function mapModel(modelId: string): string {
|
|
return MODEL_ALIASES[modelId] || modelId;
|
|
}
|
|
|
|
function uuid(): string {
|
|
return crypto.randomUUID();
|
|
}
|
|
|
|
/** Detect Alibaba's WAF / retired-v1 gateway page so we never surface raw HTML. */
|
|
function isWafResponse(status: number, contentType: string, bodyText: string): boolean {
|
|
if (contentType.includes("text/html")) return true;
|
|
if (status === 504) return true;
|
|
return /aliyun_waf|baxia|<html/i.test(bodyText);
|
|
}
|
|
|
|
const WAF_ERROR_MESSAGE =
|
|
"Qwen session expired or blocked by Alibaba's WAF. Re-login at https://chat.qwen.ai and " +
|
|
"paste a fresh full Cookie header (must include cna, ssxmod_itna and token) — a bearer token " +
|
|
"alone is no longer accepted by the v2 endpoint.";
|
|
|
|
export class QwenWebExecutor extends BaseExecutor {
|
|
constructor() {
|
|
super("qwen-web", { id: "qwen-web", baseUrl: BASE_URL });
|
|
}
|
|
|
|
private buildHeaders(
|
|
token: string,
|
|
cookieHeader: string,
|
|
chatId?: string
|
|
): Record<string, string> {
|
|
const headers: Record<string, string> = {
|
|
"Content-Type": "application/json",
|
|
Accept: "*/*",
|
|
"User-Agent": USER_AGENT,
|
|
Origin: BASE_URL,
|
|
Referer: chatId ? `${BASE_URL}/c/${chatId}` : `${BASE_URL}/`,
|
|
source: "web",
|
|
version: QWEN_SPA_VERSION,
|
|
"x-request-id": uuid(),
|
|
"bx-v": BX_VERSION,
|
|
"bx-umidtoken": BX_UMIDTOKEN_FALLBACK,
|
|
};
|
|
if (token) headers["Authorization"] = `Bearer ${token}`;
|
|
if (cookieHeader) headers["Cookie"] = cookieHeader;
|
|
return headers;
|
|
}
|
|
|
|
async execute(input: ExecuteInput) {
|
|
const { body, credentials, signal, stream: wantStream } = input;
|
|
const bodyObj = (body || {}) as Record<string, unknown>;
|
|
|
|
const rawCred = String(credentials?.apiKey ?? "").trim();
|
|
const cookieHeader = buildQwenCookieHeader(rawCred);
|
|
let token = extractQwenToken(rawCred);
|
|
if (!token && credentials?.accessToken) token = String(credentials.accessToken).trim();
|
|
|
|
const messages = (bodyObj.messages as Array<{ role: string; content: string }>) || [];
|
|
const requestedModel = (bodyObj.model as string) || DEFAULT_MODEL;
|
|
const modelId = mapModel(requestedModel);
|
|
|
|
const { hasTools, requestedTools, effectiveMessages } = prepareToolMessages(bodyObj, messages);
|
|
|
|
// Qwen Web is single-turn: fold the conversation into one user prompt.
|
|
const prompt = this.foldMessages(effectiveMessages);
|
|
|
|
// ── Step 1: create a chat ────────────────────────────────────────────────
|
|
let chatId: string;
|
|
try {
|
|
const newChatRes = await fetch(CHATS_NEW_URL, {
|
|
method: "POST",
|
|
headers: this.buildHeaders(token, cookieHeader),
|
|
body: JSON.stringify({
|
|
title: "New Chat",
|
|
models: [modelId],
|
|
chat_mode: "normal",
|
|
chat_type: "t2t",
|
|
timestamp: Date.now(),
|
|
}),
|
|
signal,
|
|
});
|
|
|
|
const ct = newChatRes.headers.get("content-type") || "";
|
|
if (!newChatRes.ok || ct.includes("text/html")) {
|
|
const text = await newChatRes.text().catch(() => "");
|
|
if (isWafResponse(newChatRes.status, ct, text)) {
|
|
return makeErrorResult(401, WAF_ERROR_MESSAGE, body, CHATS_NEW_URL);
|
|
}
|
|
return makeErrorResult(
|
|
newChatRes.status || 502,
|
|
`Qwen create-chat failed: ${text.slice(0, 300)}`,
|
|
body,
|
|
CHATS_NEW_URL
|
|
);
|
|
}
|
|
|
|
const data = (await newChatRes.json()) as { data?: { id?: string } };
|
|
chatId = data?.data?.id ?? "";
|
|
if (!chatId) {
|
|
return makeErrorResult(502, "Qwen create-chat returned no chat id", body, CHATS_NEW_URL);
|
|
}
|
|
} catch (err) {
|
|
return makeErrorResult(
|
|
502,
|
|
`Qwen create-chat error: ${err instanceof Error ? err.message : "unknown"}`,
|
|
body,
|
|
CHATS_NEW_URL
|
|
);
|
|
}
|
|
|
|
// ── Step 2: send the message ─────────────────────────────────────────────
|
|
const completionUrl = `${CHAT_COMPLETIONS_URL}?chat_id=${chatId}`;
|
|
const msgPayload = this.buildMessagePayload(chatId, modelId, prompt, requestedModel);
|
|
|
|
let upstream: Response;
|
|
try {
|
|
upstream = await fetch(completionUrl, {
|
|
method: "POST",
|
|
headers: this.buildHeaders(token, cookieHeader, chatId),
|
|
body: JSON.stringify(msgPayload),
|
|
signal,
|
|
});
|
|
} catch (err) {
|
|
return makeErrorResult(
|
|
502,
|
|
`Qwen completion fetch failed: ${err instanceof Error ? err.message : "unknown"}`,
|
|
body,
|
|
completionUrl
|
|
);
|
|
}
|
|
|
|
const ct = upstream.headers.get("content-type") || "";
|
|
if (!upstream.ok || ct.includes("text/html")) {
|
|
const errText = await upstream.text().catch(() => "");
|
|
if (isWafResponse(upstream.status, ct, errText)) {
|
|
return makeErrorResult(401, WAF_ERROR_MESSAGE, body, completionUrl);
|
|
}
|
|
return makeErrorResult(
|
|
upstream.status || 502,
|
|
`Qwen error: ${errText.slice(0, 300)}`,
|
|
body,
|
|
completionUrl
|
|
);
|
|
}
|
|
|
|
if (!wantStream) {
|
|
const { content } = await this.collectStream(upstream);
|
|
const finalText = content;
|
|
|
|
if (hasTools) {
|
|
const {
|
|
content: toolContent,
|
|
toolCalls,
|
|
finishReason,
|
|
} = buildToolAwareResult(finalText, requestedTools, "qwen");
|
|
const message: Record<string, unknown> = { role: "assistant", content: toolContent };
|
|
if (toolCalls) {
|
|
message.tool_calls = toolCalls;
|
|
message.content = null;
|
|
}
|
|
return this.jsonResponse(modelId, message, finishReason, completionUrl, msgPayload);
|
|
}
|
|
|
|
return this.jsonResponse(
|
|
modelId,
|
|
{ role: "assistant", content: finalText },
|
|
"stop",
|
|
completionUrl,
|
|
msgPayload
|
|
);
|
|
}
|
|
|
|
// Streaming: transform Qwen phase SSE → OpenAI chat.completion.chunk SSE.
|
|
const stream = this.buildClientStream(upstream, modelId, hasTools, requestedTools, signal);
|
|
return {
|
|
response: new Response(stream, {
|
|
headers: {
|
|
"Content-Type": "text/event-stream",
|
|
"Cache-Control": "no-cache",
|
|
Connection: "keep-alive",
|
|
},
|
|
}),
|
|
url: completionUrl,
|
|
headers: this.buildHeaders(token, cookieHeader, chatId),
|
|
transformedBody: msgPayload,
|
|
};
|
|
}
|
|
|
|
private foldMessages(messages: Array<{ role: string; content: unknown }>): string {
|
|
let systemContent = "";
|
|
let userContent = "";
|
|
for (const m of messages) {
|
|
const text = String(m.content ?? "");
|
|
if (m.role === "system") {
|
|
systemContent += (systemContent ? "\n\n" : "") + text;
|
|
} else if (m.role === "user") {
|
|
userContent = text;
|
|
}
|
|
}
|
|
return systemContent ? `${systemContent}\n\nUser: ${userContent}` : userContent;
|
|
}
|
|
|
|
private buildMessagePayload(
|
|
chatId: string,
|
|
modelId: string,
|
|
prompt: string,
|
|
requestedModel: string
|
|
): Record<string, unknown> {
|
|
const fid = uuid();
|
|
const enableThinking = /think|reason|r1/i.test(requestedModel);
|
|
const featureConfig: Record<string, unknown> = {
|
|
thinking_enabled: enableThinking,
|
|
output_schema: "phase",
|
|
auto_thinking: enableThinking,
|
|
research_mode: "normal",
|
|
auto_search: false,
|
|
};
|
|
return {
|
|
stream: true,
|
|
incremental_output: true,
|
|
chat_id: chatId,
|
|
chat_mode: "normal",
|
|
model: modelId,
|
|
parent_id: null,
|
|
messages: [
|
|
{
|
|
fid,
|
|
parentId: null,
|
|
childrenIds: [],
|
|
role: "user",
|
|
content: prompt,
|
|
user_action: "chat",
|
|
files: [],
|
|
timestamp: Math.floor(Date.now() / 1000),
|
|
models: [modelId],
|
|
chat_type: "t2t",
|
|
feature_config: featureConfig,
|
|
sub_chat_type: "t2t",
|
|
parent_id: null,
|
|
},
|
|
],
|
|
};
|
|
}
|
|
|
|
/** Read the whole upstream SSE stream, returning the joined answer + reasoning. */
|
|
private async collectStream(upstream: Response): Promise<{ content: string; reasoning: string }> {
|
|
const reader = upstream.body?.getReader();
|
|
const decoder = new TextDecoder();
|
|
let content = "";
|
|
let reasoning = "";
|
|
if (!reader) return { content, reasoning };
|
|
|
|
let buffer = "";
|
|
try {
|
|
while (true) {
|
|
const { done, value } = await reader.read();
|
|
if (done) break;
|
|
buffer += decoder.decode(value, { stream: true });
|
|
const lines = buffer.split("\n");
|
|
buffer = lines.pop() || "";
|
|
for (const line of lines) {
|
|
const delta = parseSseDelta(line);
|
|
if (!delta) continue;
|
|
if (delta.kind === "answer") content += delta.text;
|
|
else if (delta.kind === "think") reasoning += delta.text;
|
|
}
|
|
}
|
|
} catch {
|
|
/* upstream closed mid-stream — return what we have */
|
|
}
|
|
return { content, reasoning };
|
|
}
|
|
|
|
/** Transform the Qwen phase SSE into OpenAI chat.completion.chunk SSE. */
|
|
private buildClientStream(
|
|
upstream: Response,
|
|
modelId: string,
|
|
hasTools: boolean,
|
|
requestedTools: unknown,
|
|
signal: AbortSignal | null | undefined
|
|
): ReadableStream {
|
|
const encoder = new TextEncoder();
|
|
const decoder = new TextDecoder();
|
|
const id = `chatcmpl-qwen-${Date.now()}`;
|
|
const created = Math.floor(Date.now() / 1000);
|
|
const emitChunk = (delta: Record<string, unknown>, finishReason: string | null) =>
|
|
`data: ${JSON.stringify({
|
|
id,
|
|
object: "chat.completion.chunk",
|
|
created,
|
|
model: modelId,
|
|
choices: [{ index: 0, delta, finish_reason: finishReason }],
|
|
})}\n\n`;
|
|
|
|
return new ReadableStream({
|
|
async start(controller) {
|
|
const reader = upstream.body?.getReader();
|
|
if (!reader) {
|
|
controller.enqueue(encoder.encode("data: [DONE]\n\n"));
|
|
controller.close();
|
|
return;
|
|
}
|
|
let buffer = "";
|
|
let fullContent = "";
|
|
controller.enqueue(encoder.encode(emitChunk({ role: "assistant", content: "" }, null)));
|
|
try {
|
|
while (true) {
|
|
const { done, value } = await reader.read();
|
|
if (done) break;
|
|
buffer += decoder.decode(value, { stream: true });
|
|
const lines = buffer.split("\n");
|
|
buffer = lines.pop() || "";
|
|
for (const line of lines) {
|
|
const delta = parseSseDelta(line);
|
|
if (!delta || !delta.text) continue;
|
|
if (delta.kind === "answer") {
|
|
fullContent += delta.text;
|
|
if (!hasTools) {
|
|
controller.enqueue(encoder.encode(emitChunk({ content: delta.text }, null)));
|
|
}
|
|
} else if (delta.kind === "think" && !hasTools) {
|
|
controller.enqueue(
|
|
encoder.encode(emitChunk({ reasoning_content: delta.text }, null))
|
|
);
|
|
}
|
|
}
|
|
}
|
|
} catch (err) {
|
|
if (!signal?.aborted) {
|
|
controller.error(err);
|
|
return;
|
|
}
|
|
}
|
|
|
|
if (hasTools) {
|
|
const { content, toolCalls, finishReason } = buildToolAwareResult(
|
|
fullContent,
|
|
requestedTools,
|
|
"qwen"
|
|
);
|
|
const delta = toolCalls
|
|
? { role: "assistant", content: null, tool_calls: toolCalls }
|
|
: { role: "assistant", content };
|
|
controller.enqueue(encoder.encode(emitChunk(delta, null)));
|
|
controller.enqueue(encoder.encode(emitChunk({}, finishReason)));
|
|
} else {
|
|
controller.enqueue(encoder.encode(emitChunk({}, "stop")));
|
|
}
|
|
controller.enqueue(encoder.encode("data: [DONE]\n\n"));
|
|
controller.close();
|
|
},
|
|
});
|
|
}
|
|
|
|
private jsonResponse(
|
|
modelId: string,
|
|
message: Record<string, unknown>,
|
|
finishReason: string,
|
|
url: string,
|
|
transformedBody: unknown
|
|
) {
|
|
return {
|
|
response: new Response(
|
|
JSON.stringify({
|
|
id: `chatcmpl-qwen-${Date.now()}`,
|
|
object: "chat.completion",
|
|
created: Math.floor(Date.now() / 1000),
|
|
model: modelId,
|
|
choices: [{ index: 0, message, finish_reason: finishReason }],
|
|
}),
|
|
{ headers: { "Content-Type": "application/json" } }
|
|
),
|
|
url,
|
|
headers: {} as Record<string, string>,
|
|
transformedBody,
|
|
};
|
|
}
|
|
}
|
|
|
|
/** Parse one SSE line into a typed delta, or null if it carries no content. */
|
|
function parseSseDelta(line: string): { kind: "answer" | "think"; text: string } | null {
|
|
if (!line.startsWith("data:")) return null;
|
|
const payload = line.slice(5).trim();
|
|
if (!payload || payload === "[DONE]") return null;
|
|
let parsed: {
|
|
choices?: Array<{ delta?: { phase?: string | null; content?: unknown } }>;
|
|
};
|
|
try {
|
|
parsed = JSON.parse(payload);
|
|
} catch {
|
|
return null;
|
|
}
|
|
const delta = parsed?.choices?.[0]?.delta;
|
|
if (!delta) return null;
|
|
const phase = delta.phase;
|
|
const content = typeof delta.content === "string" ? delta.content : "";
|
|
if (phase === "think" || phase === "thinking_summary") {
|
|
return { kind: "think", text: content };
|
|
}
|
|
// `answer` phase or a null/absent phase both carry assistant content.
|
|
if (phase === "answer" || phase === null || phase === undefined) {
|
|
return { kind: "answer", text: content };
|
|
}
|
|
return null;
|
|
}
|