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https://github.com/ItzCrazyKns/Perplexica.git
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4 Commits
feat/syste
...
086b8abdf4
Author | SHA1 | Date | |
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086b8abdf4 | |||
8097610baf | |||
09661ae11d | |||
a8d410bc2f |
@ -29,6 +29,7 @@ type Message = {
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messageId: string;
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chatId: string;
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content: string;
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userSessionId: string;
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};
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type ChatModel = {
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@ -138,6 +139,7 @@ const handleHistorySave = async (
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where: eq(chats.id, message.chatId),
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});
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let currentDate = new Date();
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if (!chat) {
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await db
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.insert(chats)
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@ -147,6 +149,8 @@ const handleHistorySave = async (
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createdAt: new Date().toString(),
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focusMode: focusMode,
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files: files.map(getFileDetails),
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userSessionId: message.userSessionId,
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timestamp: currentDate.toISOString(),
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})
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.execute();
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}
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@ -1,10 +1,47 @@
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import db from '@/lib/db';
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import { chats } from '@/lib/db/schema';
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import { eq, sql} from 'drizzle-orm';
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export const GET = async (req: Request) => {
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try {
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let chats = await db.query.chats.findMany();
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chats = chats.reverse();
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return Response.json({ chats: chats }, { status: 200 });
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// get header from request
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const headers = await req.headers;
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let userSessionId = headers.get('user-session-id')?.toString() ?? '';
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if (userSessionId == '') {
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return Response.json({ chats: {} }, { status: 200 });
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}
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let chatsRes = await db.query.chats.findMany({
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where: eq(chats.userSessionId, userSessionId),
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});
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chatsRes = chatsRes.reverse();
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// Keep only the latest 20 records in the database. Delete older records.
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let maxRecordLimit = 20;
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if (chatsRes.length > maxRecordLimit) {
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const deleteChatsQuery = sql`DELETE FROM chats
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WHERE userSessionId = ${userSessionId} AND (
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timestamp IS NULL OR
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timestamp NOT in (
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SELECT timestamp FROM chats
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WHERE userSessionId = ${userSessionId}
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ORDER BY timestamp DESC
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LIMIT ${maxRecordLimit}
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)
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)
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`;
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await db.run(deleteChatsQuery);
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// Delete messages that no longer link with the chat from the database.
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const deleteMessagesQuery = sql`DELETE FROM messages
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WHERE chatId NOT IN (
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SELECT id FROM chats
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)
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`;
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await db.run(deleteMessagesQuery);
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}
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return Response.json({ chats: chatsRes }, { status: 200 });
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} catch (err) {
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console.error('Error in getting chats: ', err);
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return Response.json(
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@ -125,7 +125,7 @@ export const POST = async (req: Request) => {
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embeddings,
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body.optimizationMode,
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[],
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"",
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'',
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);
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if (!body.stream) {
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@ -1,5 +1,6 @@
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'use client';
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import crypto from 'crypto';
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import DeleteChat from '@/components/DeleteChat';
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import { cn, formatTimeDifference } from '@/lib/utils';
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import { BookOpenText, ClockIcon, Delete, ScanEye } from 'lucide-react';
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@ -21,10 +22,17 @@ const Page = () => {
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const fetchChats = async () => {
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setLoading(true);
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let userSessionId = localStorage.getItem('userSessionId');
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if (!userSessionId) {
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userSessionId = crypto.randomBytes(20).toString('hex');
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localStorage.setItem('userSessionId', userSessionId)
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}
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const res = await fetch(`/api/chats`, {
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method: 'GET',
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headers: {
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'Content-Type': 'application/json',
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'user-session-id': userSessionId!,
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},
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});
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@ -95,6 +95,12 @@ const checkConfig = async (
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if (!embeddingModel || !embeddingModelProvider) {
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const embeddingModelProviders = providers.embeddingModelProviders;
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let userSessionId = localStorage.getItem('userSessionId');
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if (!userSessionId) {
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userSessionId = crypto.randomBytes(20).toString('hex');
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localStorage.setItem('userSessionId', userSessionId!)
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}
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if (
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!embeddingModelProviders ||
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Object.keys(embeddingModelProviders).length === 0
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@ -342,6 +348,7 @@ const ChatWindow = ({ id }: { id?: string }) => {
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let added = false;
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messageId = messageId ?? crypto.randomBytes(7).toString('hex');
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let userSessionId = localStorage.getItem('userSessionId');
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setMessages((prevMessages) => [
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...prevMessages,
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@ -466,6 +473,7 @@ const ChatWindow = ({ id }: { id?: string }) => {
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messageId: messageId,
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chatId: chatId!,
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content: message,
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userSessionId: userSessionId,
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},
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chatId: chatId!,
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files: fileIds,
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@ -25,4 +25,6 @@ export const chats = sqliteTable('chats', {
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files: text('files', { mode: 'json' })
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.$type<File[]>()
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.default(sql`'[]'`),
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userSessionId: text('userSessionId'),
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timestamp: text('timestamp'),
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});
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@ -1,6 +1,6 @@
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export const webSearchRetrieverPrompt = `
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You are an AI question rephraser. You will be given a conversation and a follow-up question, you will have to rephrase the follow up question so it is a standalone question and can be used by another LLM to search the web for information to answer it.
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If it is a smple writing task or a greeting (unless the greeting contains a question after it) like Hi, Hello, How are you, etc. than a question then you need to return \`not_needed\` as the response (This is because the LLM won't need to search the web for finding information on this topic).
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If it is a simple writing task or a greeting (unless the greeting contains a question after it) like Hi, Hello, How are you, etc. than a question then you need to return \`not_needed\` as the response (This is because the LLM won't need to search the web for finding information on this topic).
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If the user asks some question from some URL or wants you to summarize a PDF or a webpage (via URL) you need to return the links inside the \`links\` XML block and the question inside the \`question\` XML block. If the user wants to you to summarize the webpage or the PDF you need to return \`summarize\` inside the \`question\` XML block in place of a question and the link to summarize in the \`links\` XML block.
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You must always return the rephrased question inside the \`question\` XML block, if there are no links in the follow-up question then don't insert a \`links\` XML block in your response.
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