Files
9router/open-sse/utils/bypassHandler.js
2026-01-14 15:42:38 +07:00

271 lines
7.3 KiB
JavaScript

import { detectFormat } from "../services/provider.js";
import { translateResponse, initState } from "../translator/index.js";
import { FORMATS } from "../translator/formats.js";
import { SKIP_PATTERNS } from "../config/constants.js";
import { formatSSE } from "./stream.js";
/**
* Check for bypass patterns - return fake response without calling provider
* Only works for Claude CLI requests
*/
export function handleBypassRequest(body, model, userAgent = "") {
if (!userAgent.includes("claude-cli")) return null;
if (!body.messages?.length) return null;
const messages = body.messages;
const getText = (content) => {
if (typeof content === "string") return content;
if (Array.isArray(content)) {
return content.filter(c => c.type === "text").map(c => c.text).join(" ");
}
return "";
};
let shouldBypass = false;
// Pattern 1: Title extraction (assistant message = "{")
const lastMsg = messages[messages.length - 1];
if (lastMsg?.role === "assistant" && lastMsg.content?.[0]?.text === "{") {
shouldBypass = true;
}
// Pattern 2: Warmup
if (!shouldBypass) {
const firstText = getText(messages[0]?.content);
if (firstText === "Warmup") {
shouldBypass = true;
}
}
// Pattern 3: Count
if (!shouldBypass && messages.length === 1 && messages[0]?.role === "user") {
const firstText = getText(messages[0]?.content);
if (firstText === "count") {
shouldBypass = true;
}
}
// Pattern 4: Skip patterns
if (!shouldBypass && SKIP_PATTERNS?.length) {
const userMessages = messages.filter(m => m.role === "user");
const userText = userMessages.map(m => getText(m.content)).join(" ");
if (SKIP_PATTERNS.some(p => userText.includes(p))) {
shouldBypass = true;
}
}
if (!shouldBypass) return null;
const sourceFormat = detectFormat(body);
const stream = body.stream !== false;
return stream
? createStreamingResponse(sourceFormat, model)
: createNonStreamingResponse(sourceFormat, model);
}
/**
* Create OpenAI standard format response
*/
function createOpenAIResponse(model) {
const id = `chatcmpl-${Date.now()}`;
const created = Math.floor(Date.now() / 1000);
const text = "CLI Command Execution: Clear Terminal";
return {
id,
object: "chat.completion",
created,
model,
choices: [{
index: 0,
message: {
role: "assistant",
content: text
},
finish_reason: "stop"
}],
usage: {
prompt_tokens: 1,
completion_tokens: 1,
total_tokens: 2
}
};
}
/**
* Create non-streaming response with translation
* Use translator to convert OpenAI → sourceFormat
*/
function createNonStreamingResponse(sourceFormat, model) {
const openaiResponse = createOpenAIResponse(model);
// If sourceFormat is OpenAI, return directly
if (sourceFormat === FORMATS.OPENAI) {
return {
success: true,
response: new Response(JSON.stringify(openaiResponse), {
headers: {
"Content-Type": "application/json",
"Access-Control-Allow-Origin": "*"
}
})
};
}
// Use translator to convert: simulate streaming then collect all chunks
const state = initState(sourceFormat);
state.model = model;
const openaiChunks = createOpenAIStreamingChunks(openaiResponse);
const allTranslated = [];
for (const chunk of openaiChunks) {
const translated = translateResponse(FORMATS.OPENAI, sourceFormat, chunk, state);
if (translated?.length > 0) {
allTranslated.push(...translated);
}
}
// Flush remaining
const flushed = translateResponse(FORMATS.OPENAI, sourceFormat, null, state);
if (flushed?.length > 0) {
allTranslated.push(...flushed);
}
// For non-streaming, merge all chunks into final response
const finalResponse = mergeChunksToResponse(allTranslated, sourceFormat);
return {
success: true,
response: new Response(JSON.stringify(finalResponse), {
headers: {
"Content-Type": "application/json",
"Access-Control-Allow-Origin": "*"
}
})
};
}
/**
* Create streaming response with translation
* Use translator to convert OpenAI chunks → sourceFormat
*/
function createStreamingResponse(sourceFormat, model) {
const openaiResponse = createOpenAIResponse(model);
const state = initState(sourceFormat);
state.model = model;
// Create OpenAI streaming chunks
const openaiChunks = createOpenAIStreamingChunks(openaiResponse);
// Translate each chunk to sourceFormat using translator
const translatedChunks = [];
for (const chunk of openaiChunks) {
const translated = translateResponse(FORMATS.OPENAI, sourceFormat, chunk, state);
if (translated?.length > 0) {
for (const item of translated) {
translatedChunks.push(formatSSE(item, sourceFormat));
}
}
}
// Flush remaining events
const flushed = translateResponse(FORMATS.OPENAI, sourceFormat, null, state);
if (flushed?.length > 0) {
for (const item of flushed) {
translatedChunks.push(formatSSE(item, sourceFormat));
}
}
// Add [DONE]
translatedChunks.push("data: [DONE]\n\n");
return {
success: true,
response: new Response(translatedChunks.join(""), {
headers: {
"Content-Type": "text/event-stream",
"Cache-Control": "no-cache",
"Connection": "keep-alive",
"Access-Control-Allow-Origin": "*"
}
})
};
}
/**
* Merge translated chunks into final response object (for non-streaming)
* Takes the last complete chunk as the final response
*/
function mergeChunksToResponse(chunks, sourceFormat) {
if (!chunks || chunks.length === 0) {
return createOpenAIResponse("unknown");
}
// For most formats, the last chunk before done contains the complete response
// Find the most complete chunk (usually the last one with content)
let finalChunk = chunks[chunks.length - 1];
// For Claude format, find the message_stop or final message
if (sourceFormat === FORMATS.CLAUDE) {
const messageStop = chunks.find(c => c.type === "message_stop");
if (messageStop) {
// Reconstruct complete message from chunks
const contentDelta = chunks.find(c => c.type === "content_block_delta");
const messageDelta = chunks.find(c => c.type === "message_delta");
const messageStart = chunks.find(c => c.type === "message_start");
if (messageStart?.message) {
finalChunk = messageStart.message;
// Merge usage if available
if (messageDelta?.usage) {
finalChunk.usage = messageDelta.usage;
}
}
}
}
return finalChunk;
}
/**
* Create OpenAI streaming chunks from complete response
*/
function createOpenAIStreamingChunks(completeResponse) {
const { id, created, model, choices } = completeResponse;
const content = choices[0].message.content;
return [
// Chunk with content
{
id,
object: "chat.completion.chunk",
created,
model,
choices: [{
index: 0,
delta: {
role: "assistant",
content
},
finish_reason: null
}]
},
// Final chunk with finish_reason
{
id,
object: "chat.completion.chunk",
created,
model,
choices: [{
index: 0,
delta: {},
finish_reason: "stop"
}],
usage: completeResponse.usage
}
];
}