2025-03-18 11:32:29 +08:00

755 lines
22 KiB
TypeScript

import express, {Request, Response, RequestHandler} from 'express';
import cors from 'cors';
import {getResponse} from './agent';
import {
TrackerContext,
ChatCompletionRequest,
ChatCompletionResponse,
ChatCompletionChunk,
AnswerAction,
Model, StepAction, VisitAction
} from './types';
import {TokenTracker} from "./utils/token-tracker";
import {ActionTracker} from "./utils/action-tracker";
import {ObjectGeneratorSafe} from "./utils/safe-generator";
import {jsonSchema} from "ai"; // or another converter library
const app = express();
// Get secret from command line args for optional authentication
const secret = process.argv.find(arg => arg.startsWith('--secret='))?.split('=')[1];
app.use(cors());
app.use(express.json({
limit: '10mb'
}));
// Add health check endpoint for Docker container verification
app.get('/health', (req, res) => {
res.json({status: 'ok'});
});
async function* streamTextNaturally(text: string, streamingState: StreamingState) {
// Split text into chunks that preserve CJK characters, URLs, and regular words
const chunks = splitTextIntoChunks(text);
let burstMode = false;
let consecutiveShortItems = 0;
for (const chunk of chunks) {
if (!streamingState.currentlyStreaming) {
yield chunks.slice(chunks.indexOf(chunk)).join('');
return;
}
const delay = calculateDelay(chunk, burstMode);
// Handle consecutive short items
if (getEffectiveLength(chunk) <= 3 && chunk.trim().length > 0) {
consecutiveShortItems++;
if (consecutiveShortItems >= 3) {
burstMode = true;
}
} else {
consecutiveShortItems = 0;
burstMode = false;
}
await new Promise(resolve => setTimeout(resolve, delay));
yield chunk;
}
}
function splitTextIntoChunks(text: string): string[] {
const chunks: string[] = [];
let currentChunk = '';
let inURL = false;
const pushCurrentChunk = () => {
if (currentChunk) {
chunks.push(currentChunk);
currentChunk = '';
}
};
for (let i = 0; i < text.length; i++) {
const char = text[i];
const nextChar = text[i + 1] || '';
// URL detection
if (char === 'h' && text.slice(i, i + 8).match(/https?:\/\//)) {
pushCurrentChunk();
inURL = true;
}
if (inURL) {
currentChunk += char;
// End of URL detection (whitespace or certain punctuation)
if (/[\s\])}"']/.test(nextChar) || i === text.length - 1) {
pushCurrentChunk();
inURL = false;
}
continue;
}
// CJK character detection (including kana and hangul)
if (/[\u4e00-\u9fff\u3040-\u30ff\uac00-\ud7af]/.test(char)) {
pushCurrentChunk();
chunks.push(char);
continue;
}
// Whitespace handling
if (/\s/.test(char)) {
pushCurrentChunk();
chunks.push(char);
continue;
}
// Regular word building
currentChunk += char;
// Break on punctuation
if (/[.!?,;:]/.test(nextChar)) {
pushCurrentChunk();
}
}
pushCurrentChunk();
return chunks.filter(chunk => chunk !== '');
}
function calculateDelay(chunk: string, burstMode: boolean): number {
const trimmedChunk = chunk.trim();
// Handle whitespace
if (trimmedChunk.length === 0) {
return Math.random() * 20 + 10;
}
// Special handling for URLs
if (chunk.match(/^https?:\/\//)) {
return Math.random() * 50 + 10; // Slower typing for URLs
}
// Special handling for CJK characters
if (/^[\u4e00-\u9fff\u3040-\u30ff\uac00-\ud7af]$/.test(chunk)) {
return Math.random() * 25 + 10; // Longer delay for individual CJK characters
}
// Base delay calculation
let baseDelay;
if (burstMode) {
baseDelay = Math.random() * 30 + 10;
} else {
const effectiveLength = getEffectiveLength(chunk);
const perCharacterDelay = Math.max(10, 40 - effectiveLength * 2);
baseDelay = Math.random() * perCharacterDelay + 10;
}
// Add variance based on chunk characteristics
if (/[A-Z]/.test(chunk[0])) {
baseDelay += Math.random() * 20 + 10;
}
if (/[^a-zA-Z\s]/.test(chunk)) {
baseDelay += Math.random() * 30 + 10;
}
// Add pauses for punctuation
if (/[.!?]$/.test(chunk)) {
baseDelay += Math.random() * 200 + 10;
} else if (/[,;:]$/.test(chunk)) {
baseDelay += Math.random() * 100 + 10;
}
return baseDelay;
}
function getEffectiveLength(chunk: string): number {
// Count CJK characters as 2 units
const cjkCount = (chunk.match(/[\u4e00-\u9fff\u3040-\u30ff\uac00-\ud7af]/g) || []).length;
const regularCount = chunk.length - cjkCount;
return regularCount + (cjkCount * 2);
}
// Helper function to emit remaining content immediately
async function emitRemainingContent(
res: Response,
requestId: string,
created: number,
model: string,
content: string,
) {
if (!content) return;
const chunk: ChatCompletionChunk = {
id: requestId,
object: 'chat.completion.chunk',
created,
model: model,
system_fingerprint: 'fp_' + requestId,
choices: [{
index: 0,
delta: {content, type: "think"},
logprobs: null,
finish_reason: null
}],
};
res.write(`data: ${JSON.stringify(chunk)}\n\n`);
}
interface StreamingState {
currentlyStreaming: boolean;
currentGenerator: AsyncGenerator<string> | null;
remainingContent: string;
isEmitting: boolean;
queue: { content: string; resolve: () => void }[];
processingQueue: boolean;
}
function getTokenBudgetAndMaxAttempts(
reasoningEffort: 'low' | 'medium' | 'high' | null = 'medium',
maxCompletionTokens: number | null = null
): { tokenBudget: number, maxBadAttempts: number } {
if (maxCompletionTokens !== null) {
return {
tokenBudget: maxCompletionTokens,
maxBadAttempts: 2 // Default to medium setting for max attempts
};
}
switch (reasoningEffort) {
case 'low':
return {tokenBudget: 100000, maxBadAttempts: 1};
case 'high':
return {tokenBudget: 1000000, maxBadAttempts: 2};
case 'medium':
default:
return {tokenBudget: 500000, maxBadAttempts: 2};
}
}
async function completeCurrentStreaming(
streamingState: StreamingState,
res: Response,
requestId: string,
created: number,
model: string
) {
if (streamingState.currentlyStreaming && streamingState.remainingContent) {
// Force completion of current streaming
await emitRemainingContent(
res,
requestId,
created,
model,
streamingState.remainingContent
);
// Reset streaming state
streamingState.currentlyStreaming = false;
streamingState.remainingContent = '';
streamingState.currentGenerator = null;
}
}
// OpenAI-compatible chat completions endpoint
// Models API endpoints
app.get('/v1/models', (async (_req: Request, res: Response) => {
const models: Model[] = [{
id: 'jina-deepsearch-v1',
object: 'model',
created: 1686935002,
owned_by: 'jina-ai'
}];
res.json({
object: 'list',
data: models
});
}) as RequestHandler);
app.get('/v1/models/:model', (async (req: Request, res: Response) => {
const modelId = req.params.model;
if (modelId === 'jina-deepsearch-v1') {
res.json({
id: 'jina-deepsearch-v1',
object: 'model',
created: 1686935002,
owned_by: 'jina-ai'
});
} else {
res.status(404).json({
error: {
message: `Model '${modelId}' not found`,
type: 'invalid_request_error',
param: null,
code: 'model_not_found'
}
});
}
}) as RequestHandler);
if (secret) {
// Check authentication only if secret is set
app.use((req, res, next) => {
const authHeader = req.headers.authorization;
if (!authHeader || !authHeader.startsWith('Bearer ') || authHeader.split(' ')[1] !== secret) {
console.log('[chat/completions] Unauthorized request');
res.status(401).json({error: 'Unauthorized'});
return;
}
return next();
});
}
async function processQueue(streamingState: StreamingState, res: Response, requestId: string, created: number, model: string) {
if (streamingState.processingQueue) return;
streamingState.processingQueue = true;
while (streamingState.queue.length > 0) {
const current = streamingState.queue[0];
// Clear any previous state
streamingState.remainingContent = ''; // Add this line
// Reset streaming state for new content
streamingState.currentlyStreaming = true;
streamingState.remainingContent = current.content;
streamingState.isEmitting = true;
try {
// Add a check to prevent duplicate streaming
if (streamingState.currentGenerator) {
streamingState.currentGenerator = null; // Add this line
}
for await (const word of streamTextNaturally(current.content, streamingState)) {
const chunk: ChatCompletionChunk = {
id: requestId,
object: 'chat.completion.chunk',
created,
model,
system_fingerprint: 'fp_' + requestId,
choices: [{
index: 0,
delta: {content: word, type: 'think'},
logprobs: null,
finish_reason: null
}]
};
res.write(`data: ${JSON.stringify(chunk)}\n\n`);
}
} catch (error) {
console.error('Error in streaming:', error);
} finally {
// Clear state before moving to next item
streamingState.isEmitting = false;
streamingState.currentlyStreaming = false;
streamingState.remainingContent = '';
streamingState.queue.shift();
current.resolve();
}
}
streamingState.processingQueue = false;
}
app.post('/v1/chat/completions', (async (req: Request, res: Response) => {
// Check authentication only if secret is set
if (secret) {
const authHeader = req.headers.authorization;
if (!authHeader || !authHeader.startsWith('Bearer ') || authHeader.split(' ')[1] !== secret) {
console.log('[chat/completions] Unauthorized request');
res.status(401).json({error: 'Unauthorized'});
return;
}
}
// Log request details (excluding sensitive data)
console.log('[chat/completions] Request:', {
model: req.body.model,
stream: req.body.stream,
messageCount: req.body.messages?.length,
hasAuth: !!req.headers.authorization,
requestId: Date.now().toString()
});
const body = req.body as ChatCompletionRequest;
if (!body.messages?.length) {
return res.status(400).json({error: 'Messages array is required and must not be empty'});
}
const lastMessage = body.messages[body.messages.length - 1];
if (lastMessage.role !== 'user') {
return res.status(400).json({error: 'Last message must be from user'});
}
console.log('messages', JSON.stringify(body.messages));
// clean <think> from all assistant messages
body.messages = body.messages?.filter(message => {
if (message.role === 'assistant') {
// 2 cases message.content can be a string or an array
if (typeof message.content === 'string') {
message.content = (message.content as string).replace(/<think>[\s\S]*?<\/think>/g, '').trim();
// Filter out the message if the content is empty after <think> removal
return message.content !== '';
} else if (Array.isArray(message.content)) {
// find all type: text and clean <think> from .text
message.content.forEach((content: any) => {
if (content.type === 'text') {
content.text = (content.text as string).replace(/<think>[\s\S]*?<\/think>/g, '').trim();
}
});
//Filter out any content objects in the array that now have null/undefined/empty text.
message.content = message.content.filter((content: any) =>
!(content.type === 'text' && content.text === '')
);
//Filter out the message if the array is now empty
return message.content.length > 0;
}
return true; // Keep the message if it's not an assistant message, or if assistant message has non string or array content.
} else if (message.role === 'user' && Array.isArray(message.content)) {
message.content = message.content.map((content: any) => {
if (content.type === 'image_url') {
return {
type: 'image',
image: content.image_url?.url || '',
}
}
return content;
});
return true;
} else if (message.role === 'system') {
if (Array.isArray(message.content)) {
message.content = message.content.map((content: any) => `${content.text || content}`).join(' ');
}
return true;
}
return true; // Keep other messages
});
let {tokenBudget, maxBadAttempts} = getTokenBudgetAndMaxAttempts(
body.reasoning_effort,
body.max_completion_tokens
);
if (body.budget_tokens) {
tokenBudget = body.budget_tokens;
}
if (body.max_attempts) {
maxBadAttempts = body.max_attempts;
}
let responseSchema = undefined;
if (body.response_format?.json_schema) {
// Convert JSON schema to Zod schema using a proper converter
try {
responseSchema = jsonSchema(body.response_format.json_schema);
console.log(responseSchema)
} catch (error: any) {
return res.status(400).json({error: `Invalid JSON schema: ${error.message}`});
}
}
const requestId = Date.now().toString();
const created = Math.floor(Date.now() / 1000);
const context: TrackerContext = {
tokenTracker: new TokenTracker(),
actionTracker: new ActionTracker()
};
// Add this inside the chat completions endpoint, before setting up the action listener
const streamingState: StreamingState = {
currentlyStreaming: false,
currentGenerator: null,
remainingContent: '',
isEmitting: false,
queue: [],
processingQueue: false
};
if (body.stream) {
res.setHeader('Content-Type', 'text/event-stream');
res.setHeader('Cache-Control', 'no-cache');
res.setHeader('Connection', 'keep-alive');
// Send initial chunk with opening think tag
const initialChunk: ChatCompletionChunk = {
id: requestId,
object: 'chat.completion.chunk',
created,
model: body.model,
system_fingerprint: 'fp_' + requestId,
choices: [{
index: 0,
delta: {role: 'assistant', content: '<think>', type: 'think'},
logprobs: null,
finish_reason: null
}]
};
res.write(`data: ${JSON.stringify(initialChunk)}\n\n`);
// Set up progress listener with cleanup
const actionListener = async (step: StepAction) => {
// Add content to queue for both thinking steps and final answer
if (step.action === 'visit') {
// emit every url in the visit action in url field
(step as VisitAction).URLTargets.forEach((url) => {
const chunk: ChatCompletionChunk = {
id: requestId,
object: 'chat.completion.chunk',
created,
model: body.model,
system_fingerprint: 'fp_' + requestId,
choices: [{
index: 0,
delta: {type: 'think', url},
logprobs: null,
finish_reason: null,
}]
};
res.write(`data: ${JSON.stringify(chunk)}\n\n`);
});
}
if (step.think) {
// if not ends with a space, add one
const content = step.think + ' ';
await new Promise<void>(resolve => {
streamingState.queue.push({
content,
resolve
});
// Single call to process queue is sufficient
processQueue(streamingState, res, requestId, created, body.model);
});
}
};
context.actionTracker.on('action', actionListener);
// Make sure to update the cleanup code
res.on('finish', () => {
streamingState.currentlyStreaming = false;
streamingState.currentGenerator = null;
streamingState.remainingContent = '';
context.actionTracker.removeListener('action', actionListener);
});
}
try {
const {
result: finalStep,
visitedURLs,
readURLs,
allURLs
} = await getResponse(undefined,
tokenBudget,
maxBadAttempts,
context,
body.messages,
body.max_returned_urls,
body.no_direct_answer,
body.boost_hostnames,
body.bad_hostnames,
)
let finalAnswer = (finalStep as AnswerAction).mdAnswer;
const annotations = (finalStep as AnswerAction).references?.map(ref => ({
type: 'url_citation' as const,
url_citation: {
title: ref.title,
exactQuote: ref.exactQuote,
url: ref.url,
dateTime: ref.dateTime,
}
}))
if (responseSchema) {
try {
const generator = new ObjectGeneratorSafe(context?.tokenTracker);
const result = await generator.generateObject({
model: 'agent',
schema: responseSchema,
prompt: finalAnswer,
system: "Extract the structured data from the text according to the JSON schema.",
});
// Use the generated object as the response content
finalAnswer = JSON.stringify(result.object, null, 2);
console.log('Generated object:', finalAnswer)
} catch (error) {
console.error('Error processing response with schema:', error);
}
}
const usage = context.tokenTracker.getTotalUsageSnakeCase();
if (body.stream) {
// Complete any ongoing streaming before sending final answer
await completeCurrentStreaming(streamingState, res, requestId, created, body.model);
// Send closing think tag
const closeThinkChunk: ChatCompletionChunk = {
id: requestId,
object: 'chat.completion.chunk',
created,
model: body.model,
system_fingerprint: 'fp_' + requestId,
choices: [{
index: 0,
delta: {content: `</think>\n\n`, type: 'think'},
logprobs: null,
finish_reason: 'thinking_end'
}]
};
res.write(`data: ${JSON.stringify(closeThinkChunk)}\n\n`);
// After the content is fully streamed, send the final chunk with finish_reason and usage
const finalChunk: ChatCompletionChunk = {
id: requestId,
object: 'chat.completion.chunk',
created,
model: body.model,
system_fingerprint: 'fp_' + requestId,
choices: [{
index: 0,
delta: {
content: finalAnswer,
type: responseSchema ? 'json' : 'text',
annotations,
},
logprobs: null,
finish_reason: 'stop'
}],
usage,
visitedURLs,
readURLs,
numURLs: allURLs.length
};
res.write(`data: ${JSON.stringify(finalChunk)}\n\n`);
res.end();
} else {
const response: ChatCompletionResponse = {
id: requestId,
object: 'chat.completion',
created,
model: body.model,
system_fingerprint: 'fp_' + requestId,
choices: [{
index: 0,
message: {
role: 'assistant',
content: finalStep.action === 'answer' ? (finalAnswer || '') : finalStep.think,
type: responseSchema ? 'json' : 'text',
annotations,
},
logprobs: null,
finish_reason: 'stop'
}],
usage,
visitedURLs,
readURLs,
numURLs: allURLs.length
};
// Log final response (excluding full content for brevity)
console.log('[chat/completions] Response:', {
id: response.id,
status: 200,
contentLength: response.choices[0].message.content.length,
usage: response.usage,
visitedURLs: response.visitedURLs,
readURLs: response.readURLs,
numURLs: allURLs.length
});
res.json(response);
}
} catch (error: any) {
// Log error details
console.error('[chat/completions] Error:', {
message: error?.message || 'An error occurred',
stack: error?.stack,
type: error?.constructor?.name,
requestId
});
// Track error as rejected tokens with Vercel token counting
const errorMessage = error?.message || 'An error occurred';
// Clean up event listeners
context.actionTracker.removeAllListeners('action');
// Get token usage in OpenAI API format
const usage = context.tokenTracker.getTotalUsageSnakeCase();
if (body.stream && res.headersSent) {
// For streaming responses that have already started, send error as a chunk
// First send closing think tag if we're in the middle of thinking
const closeThinkChunk: ChatCompletionChunk = {
id: requestId,
object: 'chat.completion.chunk',
created,
model: body.model,
system_fingerprint: 'fp_' + requestId,
choices: [{
index: 0,
delta: {content: '</think>', type: 'think'},
logprobs: null,
finish_reason: 'error'
}],
usage,
};
res.write(`data: ${JSON.stringify(closeThinkChunk)}\n\n`);
const errorChunk: ChatCompletionChunk = {
id: requestId,
object: 'chat.completion.chunk',
created,
model: body.model,
system_fingerprint: 'fp_' + requestId,
choices: [{
index: 0,
delta: {content: errorMessage, type: 'error'},
logprobs: null,
finish_reason: 'error'
}],
usage
};
res.write(`data: ${JSON.stringify(errorChunk)}\n\n`);
res.end();
} else {
// For non-streaming or not-yet-started responses, send error as JSON
const response: ChatCompletionResponse = {
id: requestId,
object: 'chat.completion',
created,
model: body.model,
system_fingerprint: 'fp_' + requestId,
choices: [{
index: 0,
message: {
role: 'assistant',
content: `Error: ${errorMessage}`,
type: 'error'
},
logprobs: null,
finish_reason: 'error'
}],
usage,
};
res.json(response);
}
}
}) as RequestHandler);
export default app;