2e254ac19a
Add ability to fetch and inject web page content into chat as context. Includes SSRF protection (blocks private IPs, localhost), content extraction (strips scripts/styles/nav), and a clean popover UI. Reimplements the concept from PR #1703 without the issues (duplicated ChatBox, dual API routes, SSRF vulnerability, window.prompt UX). Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
686 lines
22 KiB
TypeScript
686 lines
22 KiB
TypeScript
import { useStore } from '@nanostores/react';
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import type { Message } from 'ai';
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import { useChat } from '@ai-sdk/react';
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import { useAnimate } from 'framer-motion';
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import { memo, useCallback, useEffect, useRef, useState } from 'react';
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import { toast } from 'react-toastify';
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import { useMessageParser, usePromptEnhancer, useShortcuts } from '~/lib/hooks';
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import { description, useChatHistory } from '~/lib/persistence';
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import { chatStore } from '~/lib/stores/chat';
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import { workbenchStore } from '~/lib/stores/workbench';
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import { DEFAULT_MODEL, DEFAULT_PROVIDER, PROMPT_COOKIE_KEY, PROVIDER_LIST } from '~/utils/constants';
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import { cubicEasingFn } from '~/utils/easings';
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import { createScopedLogger, renderLogger } from '~/utils/logger';
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import { BaseChat } from './BaseChat';
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import Cookies from 'js-cookie';
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import { debounce } from '~/utils/debounce';
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import { useSettings } from '~/lib/hooks/useSettings';
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import type { ProviderInfo } from '~/types/model';
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import { useSearchParams } from '@remix-run/react';
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import { createSampler } from '~/utils/sampler';
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import { getTemplates, selectStarterTemplate } from '~/utils/selectStarterTemplate';
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import { logStore } from '~/lib/stores/logs';
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import { streamingState } from '~/lib/stores/streaming';
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import { filesToArtifacts } from '~/utils/fileUtils';
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import { supabaseConnection } from '~/lib/stores/supabase';
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import { defaultDesignScheme, type DesignScheme } from '~/types/design-scheme';
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import type { ElementInfo } from '~/components/workbench/Inspector';
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import type { TextUIPart, FileUIPart, Attachment } from '@ai-sdk/ui-utils';
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import { useMCPStore } from '~/lib/stores/mcp';
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import type { LlmErrorAlertType } from '~/types/actions';
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const logger = createScopedLogger('Chat');
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export function Chat() {
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renderLogger.trace('Chat');
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const { ready, initialMessages, storeMessageHistory, importChat, exportChat } = useChatHistory();
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const title = useStore(description);
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useEffect(() => {
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workbenchStore.setReloadedMessages(initialMessages.map((m) => m.id));
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}, [initialMessages]);
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return (
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<>
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{ready && (
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<ChatImpl
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description={title}
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initialMessages={initialMessages}
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exportChat={exportChat}
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storeMessageHistory={storeMessageHistory}
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importChat={importChat}
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/>
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)}
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</>
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);
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}
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const processSampledMessages = createSampler(
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(options: {
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messages: Message[];
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initialMessages: Message[];
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isLoading: boolean;
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parseMessages: (messages: Message[], isLoading: boolean) => void;
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storeMessageHistory: (messages: Message[]) => Promise<void>;
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}) => {
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const { messages, initialMessages, isLoading, parseMessages, storeMessageHistory } = options;
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parseMessages(messages, isLoading);
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if (messages.length > initialMessages.length) {
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storeMessageHistory(messages).catch((error) => toast.error(error.message));
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}
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},
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50,
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);
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interface ChatProps {
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initialMessages: Message[];
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storeMessageHistory: (messages: Message[]) => Promise<void>;
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importChat: (description: string, messages: Message[]) => Promise<void>;
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exportChat: () => void;
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description?: string;
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}
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export const ChatImpl = memo(
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({ description, initialMessages, storeMessageHistory, importChat, exportChat }: ChatProps) => {
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useShortcuts();
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const textareaRef = useRef<HTMLTextAreaElement>(null);
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const [chatStarted, setChatStarted] = useState(initialMessages.length > 0);
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const [uploadedFiles, setUploadedFiles] = useState<File[]>([]);
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const [imageDataList, setImageDataList] = useState<string[]>([]);
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const [searchParams, setSearchParams] = useSearchParams();
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const [fakeLoading, setFakeLoading] = useState(false);
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const files = useStore(workbenchStore.files);
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const [designScheme, setDesignScheme] = useState<DesignScheme>(defaultDesignScheme);
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const actionAlert = useStore(workbenchStore.alert);
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const deployAlert = useStore(workbenchStore.deployAlert);
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const supabaseConn = useStore(supabaseConnection);
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const selectedProject = supabaseConn.stats?.projects?.find(
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(project) => project.id === supabaseConn.selectedProjectId,
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);
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const supabaseAlert = useStore(workbenchStore.supabaseAlert);
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const { activeProviders, promptId, autoSelectTemplate, contextOptimizationEnabled } = useSettings();
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const [llmErrorAlert, setLlmErrorAlert] = useState<LlmErrorAlertType | undefined>(undefined);
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const [model, setModel] = useState(() => {
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const savedModel = Cookies.get('selectedModel');
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return savedModel || DEFAULT_MODEL;
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});
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const [provider, setProvider] = useState(() => {
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const savedProvider = Cookies.get('selectedProvider');
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return (PROVIDER_LIST.find((p) => p.name === savedProvider) || DEFAULT_PROVIDER) as ProviderInfo;
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});
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const { showChat } = useStore(chatStore);
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const [animationScope, animate] = useAnimate();
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const [apiKeys, setApiKeys] = useState<Record<string, string>>({});
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const [chatMode, setChatMode] = useState<'discuss' | 'build'>('build');
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const [selectedElement, setSelectedElement] = useState<ElementInfo | null>(null);
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const mcpSettings = useMCPStore((state) => state.settings);
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const {
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messages,
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isLoading,
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input,
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handleInputChange,
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setInput,
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stop,
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append,
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setMessages,
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reload,
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error,
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data: chatData,
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setData,
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addToolResult,
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} = useChat({
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api: '/api/chat',
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body: {
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apiKeys,
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files,
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promptId,
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contextOptimization: contextOptimizationEnabled,
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chatMode,
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designScheme,
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supabase: {
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isConnected: supabaseConn.isConnected,
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hasSelectedProject: !!selectedProject,
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credentials: {
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supabaseUrl: supabaseConn?.credentials?.supabaseUrl,
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anonKey: supabaseConn?.credentials?.anonKey,
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},
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},
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maxLLMSteps: mcpSettings.maxLLMSteps,
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},
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sendExtraMessageFields: true,
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onError: (e) => {
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setFakeLoading(false);
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handleError(e, 'chat');
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},
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onFinish: (message, response) => {
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const usage = response.usage;
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setData(undefined);
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if (usage) {
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console.log('Token usage:', usage);
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logStore.logProvider('Chat response completed', {
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component: 'Chat',
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action: 'response',
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model,
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provider: provider.name,
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usage,
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messageLength: message.content.length,
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});
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}
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logger.debug('Finished streaming');
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},
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initialMessages,
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initialInput: Cookies.get(PROMPT_COOKIE_KEY) || '',
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});
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useEffect(() => {
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const prompt = searchParams.get('prompt');
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// console.log(prompt, searchParams, model, provider);
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if (prompt) {
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setSearchParams({});
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runAnimation();
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append({
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role: 'user',
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content: `[Model: ${model}]\n\n[Provider: ${provider.name}]\n\n${prompt}`,
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});
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}
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}, [model, provider, searchParams]);
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const { enhancingPrompt, promptEnhanced, enhancePrompt, resetEnhancer } = usePromptEnhancer();
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const { parsedMessages, parseMessages } = useMessageParser();
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const TEXTAREA_MAX_HEIGHT = chatStarted ? 400 : 200;
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useEffect(() => {
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chatStore.setKey('started', initialMessages.length > 0);
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}, []);
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useEffect(() => {
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processSampledMessages({
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messages,
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initialMessages,
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isLoading,
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parseMessages,
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storeMessageHistory,
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});
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}, [messages, isLoading, parseMessages]);
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const scrollTextArea = () => {
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const textarea = textareaRef.current;
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if (textarea) {
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textarea.scrollTop = textarea.scrollHeight;
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}
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};
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const abort = () => {
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stop();
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chatStore.setKey('aborted', true);
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workbenchStore.abortAllActions();
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logStore.logProvider('Chat response aborted', {
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component: 'Chat',
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action: 'abort',
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model,
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provider: provider.name,
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});
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};
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const handleError = useCallback(
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(error: any, context: 'chat' | 'template' | 'llmcall' = 'chat') => {
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logger.error(`${context} request failed`, error);
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stop();
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setFakeLoading(false);
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let errorInfo = {
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message: 'An unexpected error occurred',
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isRetryable: true,
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statusCode: 500,
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provider: provider.name,
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type: 'unknown' as const,
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retryDelay: 0,
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};
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if (error.message) {
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try {
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const parsed = JSON.parse(error.message);
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if (parsed.error || parsed.message) {
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errorInfo = { ...errorInfo, ...parsed };
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} else {
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errorInfo.message = error.message;
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}
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} catch {
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errorInfo.message = error.message;
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}
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}
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let errorType: LlmErrorAlertType['errorType'] = 'unknown';
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let title = 'Request Failed';
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if (errorInfo.statusCode === 401 || errorInfo.message.toLowerCase().includes('api key')) {
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errorType = 'authentication';
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title = 'Authentication Error';
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} else if (errorInfo.statusCode === 429 || errorInfo.message.toLowerCase().includes('rate limit')) {
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errorType = 'rate_limit';
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title = 'Rate Limit Exceeded';
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} else if (errorInfo.message.toLowerCase().includes('quota')) {
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errorType = 'quota';
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title = 'Quota Exceeded';
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} else if (errorInfo.statusCode >= 500) {
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errorType = 'network';
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title = 'Server Error';
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}
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logStore.logError(`${context} request failed`, error, {
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component: 'Chat',
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action: 'request',
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error: errorInfo.message,
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context,
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retryable: errorInfo.isRetryable,
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errorType,
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provider: provider.name,
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});
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// Create API error alert
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setLlmErrorAlert({
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type: 'error',
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title,
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description: errorInfo.message,
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provider: provider.name,
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errorType,
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});
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setData([]);
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},
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[provider.name, stop],
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);
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const clearApiErrorAlert = useCallback(() => {
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setLlmErrorAlert(undefined);
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}, []);
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useEffect(() => {
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const textarea = textareaRef.current;
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if (textarea) {
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textarea.style.height = 'auto';
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const scrollHeight = textarea.scrollHeight;
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textarea.style.height = `${Math.min(scrollHeight, TEXTAREA_MAX_HEIGHT)}px`;
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textarea.style.overflowY = scrollHeight > TEXTAREA_MAX_HEIGHT ? 'auto' : 'hidden';
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}
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}, [input, textareaRef]);
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const runAnimation = async () => {
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if (chatStarted) {
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return;
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}
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await Promise.all([
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animate('#examples', { opacity: 0, display: 'none' }, { duration: 0.1 }),
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animate('#intro', { opacity: 0, flex: 1 }, { duration: 0.2, ease: cubicEasingFn }),
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]);
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chatStore.setKey('started', true);
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setChatStarted(true);
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};
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// Helper function to create message parts array from text and images
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const createMessageParts = (text: string, images: string[] = []): Array<TextUIPart | FileUIPart> => {
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// Create an array of properly typed message parts
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const parts: Array<TextUIPart | FileUIPart> = [
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{
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type: 'text',
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text,
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},
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];
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// Add image parts if any
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images.forEach((imageData) => {
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// Extract correct MIME type from the data URL
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const mimeType = imageData.split(';')[0].split(':')[1] || 'image/jpeg';
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// Create file part according to AI SDK format
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parts.push({
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type: 'file',
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mimeType,
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data: imageData.replace(/^data:image\/[^;]+;base64,/, ''),
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});
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});
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return parts;
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};
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// Helper function to convert File[] to Attachment[] for AI SDK
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const filesToAttachments = async (files: File[]): Promise<Attachment[] | undefined> => {
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if (files.length === 0) {
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return undefined;
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}
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const attachments = await Promise.all(
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files.map(
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(file) =>
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new Promise<Attachment>((resolve) => {
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const reader = new FileReader();
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reader.onloadend = () => {
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resolve({
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name: file.name,
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contentType: file.type,
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url: reader.result as string,
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});
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};
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reader.readAsDataURL(file);
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}),
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),
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);
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return attachments;
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};
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const sendMessage = async (_event: React.UIEvent, messageInput?: string) => {
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const messageContent = messageInput || input;
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if (!messageContent?.trim()) {
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return;
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}
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if (isLoading) {
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abort();
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return;
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}
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let finalMessageContent = messageContent;
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if (selectedElement) {
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console.log('Selected Element:', selectedElement);
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const elementInfo = `<div class=\"__boltSelectedElement__\" data-element='${JSON.stringify(selectedElement)}'>${JSON.stringify(`${selectedElement.displayText}`)}</div>`;
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finalMessageContent = messageContent + elementInfo;
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}
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runAnimation();
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if (!chatStarted) {
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setFakeLoading(true);
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if (autoSelectTemplate) {
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const { template, title } = await selectStarterTemplate({
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message: finalMessageContent,
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model,
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provider,
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});
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if (template !== 'blank') {
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const temResp = await getTemplates(template, title).catch((e) => {
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if (e.message.includes('rate limit')) {
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toast.warning('Rate limit exceeded. Skipping starter template\n Continuing with blank template');
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} else {
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toast.warning('Failed to import starter template\n Continuing with blank template');
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}
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return null;
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});
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if (temResp) {
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const { assistantMessage, userMessage } = temResp;
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const userMessageText = `[Model: ${model}]\n\n[Provider: ${provider.name}]\n\n${finalMessageContent}`;
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setMessages([
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{
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id: `1-${new Date().getTime()}`,
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role: 'user',
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content: userMessageText,
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parts: createMessageParts(userMessageText, imageDataList),
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},
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{
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id: `2-${new Date().getTime()}`,
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role: 'assistant',
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content: assistantMessage,
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},
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{
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id: `3-${new Date().getTime()}`,
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role: 'user',
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content: `[Model: ${model}]\n\n[Provider: ${provider.name}]\n\n${userMessage}`,
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annotations: ['hidden'],
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},
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]);
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const reloadOptions =
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uploadedFiles.length > 0
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? { experimental_attachments: await filesToAttachments(uploadedFiles) }
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: undefined;
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reload(reloadOptions);
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setInput('');
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Cookies.remove(PROMPT_COOKIE_KEY);
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setUploadedFiles([]);
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setImageDataList([]);
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resetEnhancer();
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textareaRef.current?.blur();
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setFakeLoading(false);
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return;
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}
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}
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}
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// If autoSelectTemplate is disabled or template selection failed, proceed with normal message
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const userMessageText = `[Model: ${model}]\n\n[Provider: ${provider.name}]\n\n${finalMessageContent}`;
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const attachments = uploadedFiles.length > 0 ? await filesToAttachments(uploadedFiles) : undefined;
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setMessages([
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{
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id: `${new Date().getTime()}`,
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role: 'user',
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content: userMessageText,
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parts: createMessageParts(userMessageText, imageDataList),
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experimental_attachments: attachments,
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},
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]);
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reload(attachments ? { experimental_attachments: attachments } : undefined);
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setFakeLoading(false);
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setInput('');
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Cookies.remove(PROMPT_COOKIE_KEY);
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setUploadedFiles([]);
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setImageDataList([]);
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resetEnhancer();
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textareaRef.current?.blur();
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return;
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}
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if (error != null) {
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setMessages(messages.slice(0, -1));
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}
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const modifiedFiles = workbenchStore.getModifiedFiles();
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chatStore.setKey('aborted', false);
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if (modifiedFiles !== undefined) {
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const userUpdateArtifact = filesToArtifacts(modifiedFiles, `${Date.now()}`);
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const messageText = `[Model: ${model}]\n\n[Provider: ${provider.name}]\n\n${userUpdateArtifact}${finalMessageContent}`;
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const attachmentOptions =
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uploadedFiles.length > 0 ? { experimental_attachments: await filesToAttachments(uploadedFiles) } : undefined;
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append(
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{
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role: 'user',
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content: messageText,
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parts: createMessageParts(messageText, imageDataList),
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},
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attachmentOptions,
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);
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workbenchStore.resetAllFileModifications();
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} else {
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const messageText = `[Model: ${model}]\n\n[Provider: ${provider.name}]\n\n${finalMessageContent}`;
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const attachmentOptions =
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uploadedFiles.length > 0 ? { experimental_attachments: await filesToAttachments(uploadedFiles) } : undefined;
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append(
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{
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role: 'user',
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content: messageText,
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parts: createMessageParts(messageText, imageDataList),
|
|
},
|
|
attachmentOptions,
|
|
);
|
|
}
|
|
|
|
setInput('');
|
|
Cookies.remove(PROMPT_COOKIE_KEY);
|
|
|
|
setUploadedFiles([]);
|
|
setImageDataList([]);
|
|
|
|
resetEnhancer();
|
|
|
|
textareaRef.current?.blur();
|
|
};
|
|
|
|
/**
|
|
* Handles the change event for the textarea and updates the input state.
|
|
* @param event - The change event from the textarea.
|
|
*/
|
|
const onTextareaChange = (event: React.ChangeEvent<HTMLTextAreaElement>) => {
|
|
handleInputChange(event);
|
|
};
|
|
|
|
/**
|
|
* Debounced function to cache the prompt in cookies.
|
|
* Caches the trimmed value of the textarea input after a delay to optimize performance.
|
|
*/
|
|
const debouncedCachePrompt = useCallback(
|
|
debounce((event: React.ChangeEvent<HTMLTextAreaElement>) => {
|
|
const trimmedValue = event.target.value.trim();
|
|
Cookies.set(PROMPT_COOKIE_KEY, trimmedValue, { expires: 30 });
|
|
}, 1000),
|
|
[],
|
|
);
|
|
|
|
useEffect(() => {
|
|
const storedApiKeys = Cookies.get('apiKeys');
|
|
|
|
if (storedApiKeys) {
|
|
setApiKeys(JSON.parse(storedApiKeys));
|
|
}
|
|
}, []);
|
|
|
|
const handleModelChange = (newModel: string) => {
|
|
setModel(newModel);
|
|
Cookies.set('selectedModel', newModel, { expires: 30 });
|
|
};
|
|
|
|
const handleProviderChange = (newProvider: ProviderInfo) => {
|
|
setProvider(newProvider);
|
|
Cookies.set('selectedProvider', newProvider.name, { expires: 30 });
|
|
};
|
|
|
|
const handleWebSearchResult = useCallback(
|
|
(result: string) => {
|
|
const currentInput = input || '';
|
|
const newInput = currentInput.length > 0 ? `${result}\n\n${currentInput}` : result;
|
|
|
|
// Update the input via the same mechanism as handleInputChange
|
|
const syntheticEvent = {
|
|
target: { value: newInput },
|
|
} as React.ChangeEvent<HTMLTextAreaElement>;
|
|
handleInputChange(syntheticEvent);
|
|
},
|
|
[input, handleInputChange],
|
|
);
|
|
|
|
return (
|
|
<BaseChat
|
|
ref={animationScope}
|
|
textareaRef={textareaRef}
|
|
input={input}
|
|
showChat={showChat}
|
|
chatStarted={chatStarted}
|
|
isStreaming={isLoading || fakeLoading}
|
|
onStreamingChange={(streaming) => {
|
|
streamingState.set(streaming);
|
|
}}
|
|
enhancingPrompt={enhancingPrompt}
|
|
promptEnhanced={promptEnhanced}
|
|
sendMessage={sendMessage}
|
|
model={model}
|
|
setModel={handleModelChange}
|
|
provider={provider}
|
|
setProvider={handleProviderChange}
|
|
providerList={activeProviders}
|
|
handleInputChange={(e) => {
|
|
onTextareaChange(e);
|
|
debouncedCachePrompt(e);
|
|
}}
|
|
handleStop={abort}
|
|
description={description}
|
|
importChat={importChat}
|
|
exportChat={exportChat}
|
|
messages={messages.map((message, i) => {
|
|
if (message.role === 'user') {
|
|
return message;
|
|
}
|
|
|
|
return {
|
|
...message,
|
|
content: parsedMessages[i] || '',
|
|
};
|
|
})}
|
|
enhancePrompt={() => {
|
|
enhancePrompt(
|
|
input,
|
|
(input) => {
|
|
setInput(input);
|
|
scrollTextArea();
|
|
},
|
|
model,
|
|
provider,
|
|
apiKeys,
|
|
);
|
|
}}
|
|
uploadedFiles={uploadedFiles}
|
|
setUploadedFiles={setUploadedFiles}
|
|
imageDataList={imageDataList}
|
|
setImageDataList={setImageDataList}
|
|
actionAlert={actionAlert}
|
|
clearAlert={() => workbenchStore.clearAlert()}
|
|
supabaseAlert={supabaseAlert}
|
|
clearSupabaseAlert={() => workbenchStore.clearSupabaseAlert()}
|
|
deployAlert={deployAlert}
|
|
clearDeployAlert={() => workbenchStore.clearDeployAlert()}
|
|
llmErrorAlert={llmErrorAlert}
|
|
clearLlmErrorAlert={clearApiErrorAlert}
|
|
data={chatData}
|
|
chatMode={chatMode}
|
|
setChatMode={setChatMode}
|
|
append={append}
|
|
designScheme={designScheme}
|
|
setDesignScheme={setDesignScheme}
|
|
selectedElement={selectedElement}
|
|
setSelectedElement={setSelectedElement}
|
|
addToolResult={addToolResult}
|
|
onWebSearchResult={handleWebSearchResult}
|
|
/>
|
|
);
|
|
},
|
|
);
|