[V0_FILE]typescriptreact:file="tailwind.config.ts" isFixed="true" isQuickEdit="true" isMerged="true" import type { Config } from "tailwindcss" const config: Config = { darkMode: ["class"], content: [ "./pages/**/*.{js,ts,jsx,tsx,mdx}", "./components/**/*.{js,ts,jsx,tsx,mdx}", "./app/**/*.{js,ts,jsx,tsx,mdx}", "*.{js,ts,jsx,tsx,mdx}", ], theme: { extend: { colors: { background: { DEFAULT: "#FFFFFF", // White chat: "#E5DDD5", // WhatsApp chat background }, foreground: "hsl(var(--foreground))", card: { DEFAULT: "hsl(var(--card))", foreground: "hsl(var(--card-foreground))", }, popover: { DEFAULT: "hsl(var(--popover))", foreground: "hsl(var(--popover-foreground))", }, primary: { DEFAULT: "#25D366", // WhatsApp green dark: "#128C7E", light: "#DCF8C6", }, secondary: { DEFAULT: "#000000", // Black }, muted: { DEFAULT: "hsl(var(--muted))", foreground: "hsl(var(--muted-foreground))", }, accent: { DEFAULT: "hsl(var(--accent))", foreground: "hsl(var(--accent-foreground))", }, destructive: { DEFAULT: "hsl(var(--destructive))", foreground: "hsl(var(--destructive-foreground))", }, border: "hsl(var(--border))", input: "hsl(var(--input))", ring: "hsl(var(--ring))", chart: { "1": "hsl(var(--chart-1))", "2": "hsl(var(--chart-2))", "3": "hsl(var(--chart-3))", "4": "hsl(var(--chart-4))", "5": "hsl(var(--chart-5))", }, sidebar: { DEFAULT: "hsl(var(--sidebar-background))", foreground: "hsl(var(--sidebar-foreground))", primary: "hsl(var(--sidebar-primary))", "primary-foreground": "hsl(var(--sidebar-primary-foreground))", accent: "hsl(var(--sidebar-accent))", "accent-foreground": "hsl(var(--sidebar-accent-foreground))", border: "hsl(var(--sidebar-border))", ring: "hsl(var(--sidebar-ring))", }, }, borderRadius: { lg: "var(--radius)", md: "calc(var(--radius) - 2px)", sm: "calc(var(--radius) - 4px)", }, keyframes: { "accordion-down": { from: { height: "0", }, to: { height: "var(--radix-accordion-content-height)", }, }, "accordion-up": { from: { height: "var(--radix-accordion-content-height)", }, to: { height: "0", }, }, }, animation: { "accordion-down": "accordion-down 0.2s ease-out", "accordion-up": "accordion-up 0.2s ease-out", }, }, }, plugins: [], } export default config [V0_FILE]typescriptreact:file="app/layout.tsx" isMerged="true" import type React from "react" import type { Metadata } from "next" import { Inter } from "next/font/google" import "./globals.css" const inter = Inter({ subsets: ["latin"] }) export const metadata: Metadata = { title: "Agente GM - Seu Assistente de Vendas", description: "Chatbot inteligente para vendas que ajuda você a vender todos os dias", } export default function RootLayout({ children, }: Readonly<{ children: React.ReactNode }>) { return ( {children} ) } [V0_FILE]typescriptreact:file="types/index.ts" isMerged="true" export interface Message { id: string content: string sender: "user" | "bot" timestamp: Date } export interface Lead { id: string phoneNumber?: string email?: string product?: string messages: Message[] createdAt: Date lastInteraction: Date } export interface ChatState { messages: Message[] isLoading: boolean } export interface AnalyticsData { totalInteractions: number totalLeads: number lastInteractions: { leadId: string message: string timestamp: Date }[] } [V0_FILE]typescriptreact:file="lib/utils.ts" isMerged="true" import { clsx, type ClassValue } from "clsx" import { twMerge } from "tailwind-merge" import type { Message } from "@/types" export function generateId(): string { return Math.random().toString(36).substring(2, 15) } export function formatTimestamp(date: Date): string { return new Intl.DateTimeFormat("pt-BR", { hour: "2-digit", minute: "2-digit", }).format(date) } // Local storage helpers export function saveMessagesToLocalStorage(messages: Message[]): void { if (typeof window !== "undefined") { localStorage.setItem("gm-chat-messages", JSON.stringify(messages)) } } export function getMessagesFromLocalStorage(): Message[] { if (typeof window !== "undefined") { const saved = localStorage.getItem("gm-chat-messages") if (saved) { try { const parsed = JSON.parse(saved) return parsed.map((msg: any) => ({ ...msg, timestamp: new Date(msg.timestamp), })) } catch (e) { console.error("Failed to parse messages from localStorage", e) } } } return [] } export function incrementAnalytics(type: "interaction" | "lead"): void { if (typeof window !== "undefined") { const analytics = JSON.parse( localStorage.getItem("gm-analytics") || '{"totalInteractions":0,"totalLeads":0,"lastInteractions":[]}', ) if (type === "interaction") { analytics.totalInteractions += 1 } else if (type === "lead") { analytics.totalLeads += 1 } localStorage.setItem("gm-analytics", JSON.stringify(analytics)) } } export function saveInteraction(leadId: string, message: string): void { if (typeof window !== "undefined") { const analytics = JSON.parse( localStorage.getItem("gm-analytics") || '{"totalInteractions":0,"totalLeads":0,"lastInteractions":[]}', ) analytics.lastInteractions.unshift({ leadId, message, timestamp: new Date(), }) // Keep only last 10 interactions if (analytics.lastInteractions.length > 10) { analytics.lastInteractions = analytics.lastInteractions.slice(0, 10) } localStorage.setItem("gm-analytics", JSON.stringify(analytics)) } } export function getAnalytics() { if (typeof window !== "undefined") { const analytics = JSON.parse( localStorage.getItem("gm-analytics") || '{"totalInteractions":0,"totalLeads":0,"lastInteractions":[]}', ) // Convert timestamps back to Date objects analytics.lastInteractions = analytics.lastInteractions.map((interaction: any) => ({ ...interaction, timestamp: new Date(interaction.timestamp), })) return analytics } return { totalInteractions: 0, totalLeads: 0, lastInteractions: [], } } export function saveLeadToLocalStorage(lead: any): void { if (typeof window !== "undefined") { const leads = JSON.parse(localStorage.getItem("gm-leads") || "[]") const existingLeadIndex = leads.findIndex((l: any) => l.id === lead.id) if (existingLeadIndex >= 0) { leads[existingLeadIndex] = lead } else { leads.push(lead) } localStorage.setItem("gm-leads", JSON.stringify(leads)) } } export function getLeadsFromLocalStorage(): any[] { if (typeof window !== "undefined") { const saved = localStorage.getItem("gm-leads") if (saved) { try { const parsed = JSON.parse(saved) return parsed.map((lead: any) => ({ ...lead, createdAt: new Date(lead.createdAt), lastInteraction: new Date(lead.lastInteraction), messages: lead.messages.map((msg: any) => ({ ...msg, timestamp: new Date(msg.timestamp), })), })) } catch (e) { console.error("Failed to parse leads from localStorage", e) } } } return [] } export function cn(...inputs: ClassValue[]) { return twMerge(clsx(inputs)) } [V0_FILE]typescriptreact:file="app/api/webhook/route.ts" isMerged="true" import { type NextRequest, NextResponse } from "next/server" export const runtime = "edge" export async function POST(req: NextRequest) { try { const { message, phoneNumber } = await req.json() if (!message) { return NextResponse.json({ error: "Message is required" }, { status: 400 }) } // Here you would typically process the incoming webhook // For now, we'll just echo it back with a timestamp return NextResponse.json({ success: true, received: { message, phoneNumber, timestamp: new Date().toISOString(), }, }) } catch (error) { console.error("Error in webhook route:", error) return NextResponse.json({ error: "Failed to process webhook" }, { status: 500 }) } } [V0_FILE]typescriptreact:file="app/page.tsx" isMerged="true" import Link from "next/link" import Image from "next/image" export default function LandingPage() { return (

Agente GM 🤖

Quer vender ainda hoje? 🔥

Me chama no WhatsApp e descubra como a IA pode transformar seu negócio! 📦

Chamar no WhatsApp 👇 Experimentar o Chat

Como o Agente GM pode te ajudar? 💰

E-commerce

Aumente suas vendas com estratégias de IA para seu e-commerce de roupas, acessórios e produtos físicos.

Serviços

Capture mais leads e converta clientes para seus serviços com automação inteligente e personalizada.

Infoprodutos

Maximize suas comissões como afiliado ou venda mais infoprodutos com estratégias de IA e tráfego.

) } [V0_FILE]typescriptreact:file="app/chat/page.tsx" isMerged="true" import ChatInterface from "@/components/chat-interface" export default function ChatPage() { return (

) } [V0_FILE]typescriptreact:file="app/admin/page.tsx" isMerged="true" import AdminPanel from "@/components/admin-panel" export default function AdminPage() { return } [V0_FILE]typescriptreact:file="app/api/whatsapp-webhook/route.ts" isMerged="true" import { type NextRequest, NextResponse } from "next/server" import { createConversation, saveMessage, updateConversation } from "@/lib/supabase" export const runtime = "edge" export async function POST(req: NextRequest) { try { // Verifica o token de segurança (você deve configurar isso no seu webhook do WhatsApp) const authHeader = req.headers.get("authorization") const expectedToken = process.env.WHATSAPP_WEBHOOK_TOKEN if (!authHeader || authHeader !== `Bearer ${expectedToken}`) { return NextResponse.json({ error: "Unauthorized" }, { status: 401 }) } const data = await req.json() // Processa mensagens do WhatsApp // Este é um exemplo simplificado - a estrutura real depende da API do WhatsApp que você está usando if (data.object === "whatsapp_business_account") { for (const entry of data.entry || []) { for (const change of entry.changes || []) { if (change.field === "messages") { for (const message of change.value.messages || []) { if (message.type === "text") { const phoneNumber = message.from const messageText = message.text.body // Verifica se já existe uma conversa para este número let conversationId // Aqui você precisaria consultar o banco de dados para verificar se já existe uma conversa // Para simplificar, vamos criar uma nova conversa const conversation = await createConversation({ phone_number: phoneNumber, }) if (conversation) { conversationId = conversation.id // Salva a mensagem do usuário await saveMessage({ content: messageText, sender: "user", conversation_id: conversationId, }) // Aqui você chamaria a API do GPT para obter uma resposta // E depois enviaria de volta para o WhatsApp // Exemplo simplificado: const response = await fetch(`${req.nextUrl.origin}/api/ask-gpt`, { method: "POST", headers: { "Content-Type": "application/json", }, body: JSON.stringify({ message: messageText, conversationId, }), }) if (response.ok) { const { response: botResponse, extractedInfo } = await response.json() // Salva a resposta do bot await saveMessage({ content: botResponse, sender: "bot", conversation_id: conversationId, }) // Atualiza informações extraídas, se houver if (extractedInfo) { await updateConversation(conversationId, extractedInfo) } // Aqui você enviaria a resposta de volta para o WhatsApp // Isso depende da API específica do WhatsApp que você está usando // Exemplo: // await sendWhatsAppMessage(phoneNumber, botResponse) } } } } } } } } // O WhatsApp espera uma resposta 200 OK return NextResponse.json({ success: true }) } catch (error) { console.error("Error in WhatsApp webhook:", error) return NextResponse.json({ error: "Failed to process webhook" }, { status: 500 }) } } // Função para enviar mensagem de volta para o WhatsApp // Esta é uma implementação de exemplo - você precisará adaptá-la para a API específica que estiver usando async function sendWhatsAppMessage(to: string, message: string) { try { // Exemplo para WhatsApp Business API const response = await fetch(`https://graph.facebook.com/v17.0/${process.env.WHATSAPP_PHONE_NUMBER_ID}/messages`, { method: "POST", headers: { Authorization: `Bearer ${process.env.WHATSAPP_ACCESS_TOKEN}`, "Content-Type": "application/json", }, body: JSON.stringify({ messaging_product: "whatsapp", recipient_type: "individual", to, type: "text", text: { body: message, }, }), }) if (!response.ok) { throw new Error(`Failed to send WhatsApp message: ${response.statusText}`) } return await response.json() } catch (error) { console.error("Error sending WhatsApp message:", error) throw error } } [V0_FILE]sql:file="supabase/schema.sql" isMerged="true" -- Cria tabela de conversas CREATE TABLE IF NOT EXISTS conversations ( id UUID PRIMARY KEY, phone_number TEXT, email TEXT, product TEXT, created_at TIMESTAMP WITH TIME ZONE NOT NULL, last_interaction TIMESTAMP WITH TIME ZONE NOT NULL, user_id UUID REFERENCES auth.users(id) ); -- Cria tabela de mensagens CREATE TABLE IF NOT EXISTS messages ( id UUID PRIMARY KEY, content TEXT NOT NULL, sender TEXT NOT NULL CHECK (sender IN ('user', 'bot')), timestamp TIMESTAMP WITH TIME ZONE NOT NULL, conversation_id UUID NOT NULL REFERENCES conversations(id) ON DELETE CASCADE ); -- Cria tabela de analytics CREATE TABLE IF NOT EXISTS analytics ( id UUID PRIMARY KEY, event_type TEXT NOT NULL, event_data JSONB, created_at TIMESTAMP WITH TIME ZONE NOT NULL, user_id UUID ); -- Cria tabela de usuários admin CREATE TABLE IF NOT EXISTS admin_users ( id UUID PRIMARY KEY DEFAULT uuid_generate_v4(), user_id UUID NOT NULL REFERENCES auth.users(id) ON DELETE CASCADE, created_at TIMESTAMP WITH TIME ZONE DEFAULT NOW() ); -- Cria índices para melhorar performance CREATE INDEX IF NOT EXISTS idx_messages_conversation_id ON messages(conversation_id); CREATE INDEX IF NOT EXISTS idx_messages_timestamp ON messages(timestamp); CREATE INDEX IF NOT EXISTS idx_conversations_last_interaction ON conversations(last_interaction); CREATE INDEX IF NOT EXISTS idx_analytics_event_type ON analytics(event_type); CREATE INDEX IF NOT EXISTS idx_analytics_created_at ON analytics(created_at); -- Cria políticas de segurança RLS (Row Level Security) ALTER TABLE conversations ENABLE ROW LEVEL SECURITY; ALTER TABLE messages ENABLE ROW LEVEL SECURITY; ALTER TABLE analytics ENABLE ROW LEVEL SECURITY; ALTER TABLE admin_users ENABLE ROW LEVEL SECURITY; -- Política para admin ver todas as conversas CREATE POLICY admin_select_conversations ON conversations FOR SELECT USING ( auth.uid() IN (SELECT user_id FROM admin_users) ); -- Política para admin ver todas as mensagens CREATE POLICY admin_select_messages ON messages FOR SELECT USING ( auth.uid() IN (SELECT user_id FROM admin_users) ); -- Política para admin ver todos os analytics CREATE POLICY admin_select_analytics ON analytics FOR SELECT USING ( auth.uid() IN (SELECT user_id FROM admin_users) ); -- Política para admin gerenciar usuários admin CREATE POLICY admin_all_admin_users ON admin_users FOR ALL USING ( auth.uid() IN (SELECT user_id FROM admin_users) ); -- Função para adicionar o primeiro admin CREATE OR REPLACE FUNCTION add_first_admin(email TEXT, password TEXT) RETURNS UUID AS $$ DECLARE new_user_id UUID; BEGIN -- Cria o usuário na autenticação INSERT INTO auth.users (email, encrypted_password, email_confirmed_at, raw_app_meta_data, raw_user_meta_data) VALUES ( email, crypt(password, gen_salt('bf')), NOW(), '{"provider":"email","providers":["email"]}', '{}' ) RETURNING id INTO new_user_id; -- Adiciona o usuário à tabela de admins INSERT INTO admin_users (user_id) VALUES (new_user_id); RETURN new_user_id; END; $$ LANGUAGE plpgsql; [V0_FILE]plaintext:file=".env.local.example" isMerged="true" # OpenAI API Key OPENAI_API_KEY=sk-your-openai-api-key # Supabase NEXT_PUBLIC_SUPABASE_URL=your-supabase-url NEXT_PUBLIC_SUPABASE_ANON_KEY=your-supabase-anon-key SUPABASE_SERVICE_ROLE_KEY=your-supabase-service-role-key # WhatsApp API (opcional - para integração com WhatsApp) WHATSAPP_WEBHOOK_TOKEN=your-webhook-token WHATSAPP_ACCESS_TOKEN=your-whatsapp-access-token WHATSAPP_PHONE_NUMBER_ID=your-whatsapp-phone-number-id [V0_FILE]typescriptreact:file="lib/supabase.ts" isEdit="true" isMerged="true" import { createClient } from "@supabase/supabase-js" // Tipos para as tabelas do Supabase export type Tables = { messages: { id: string content: string sender: "user" | "bot" timestamp: string conversation_id: string } conversations: { id: string phone_number: string | null email: string | null product: string | null created_at: string last_interaction: string user_id: string | null } analytics: { id: string event_type: string event_data: any created_at: string user_id: string | null } } // Cria o cliente do Supabase const supabaseUrl = process.env.NEXT_PUBLIC_SUPABASE_URL || "" const supabaseAnonKey = process.env.NEXT_PUBLIC_SUPABASE_ANON_KEY || "" // Singleton pattern para o cliente do Supabase no lado do cliente let supabaseInstance: ReturnType> | null = null export const getSupabase = () => { if (supabaseInstance) return supabaseInstance supabaseInstance = createClient(supabaseUrl, supabaseAnonKey) return supabaseInstance } // Funções auxiliares para interagir com o banco de dados export async function saveMessage(message: { content: string sender: "user" | "bot" conversation_id: string }) { const supabase = getSupabase() const { data, error } = await supabase .from("messages") .insert({ ...message, id: crypto.randomUUID(), timestamp: new Date().toISOString(), }) .select() if (error) { console.error("Error saving message:", error) return null } return data[0] } export async function getConversationMessages(conversationId: string) { const supabase = getSupabase() const { data, error } = await supabase .from("messages") .select("*") .eq("conversation_id", conversationId) .order("timestamp", { ascending: true }) if (error) { console.error("Error fetching messages:", error) return [] } return data } export async function createConversation(conversation: { phone_number?: string email?: string product?: string user_id?: string }) { const supabase = getSupabase() const id = crypto.randomUUID() const now = new Date().toISOString() const { data, error } = await supabase .from("conversations") .insert({ ...conversation, id, created_at: now, last_interaction: now, }) .select() if (error) { console.error("Error creating conversation:", error) return null } return data[0] } export async function updateConversation(id: string, updates: Partial) { const supabase = getSupabase() const { data, error } = await supabase .from("conversations") .update({ ...updates, last_interaction: new Date().toISOString(), }) .eq("id", id) .select() if (error) { console.error("Error updating conversation:", error) return null } return data[0] } export async function getConversations() { const supabase = getSupabase() const { data, error } = await supabase .from("conversations") .select("*") .order("last_interaction", { ascending: false }) if (error) { console.error("Error fetching conversations:", error) return [] } return data } export async function trackAnalytics(event: { event_type: string event_data: any user_id?: string }) { const supabase = getSupabase() const { error } = await supabase.from("analytics").insert({ ...event, id: crypto.randomUUID(), created_at: new Date().toISOString(), }) if (error) { console.error("Error tracking analytics:", error) } } export async function getAnalyticsData() { const supabase = getSupabase() // Total de interações (mensagens) const { count: messageCount, error: messageError } = await supabase .from("messages") .select("*", { count: "exact", head: true }) // Total de conversas const { count: conversationCount, error: conversationError } = await supabase .from("conversations") .select("*", { count: "exact", head: true }) // Últimas interações const { data: lastMessages, error: lastMessagesError } = await supabase .from("messages") .select("*, conversations!inner(*)") .order("timestamp", { ascending: false }) .limit(10) // Conversões (eventos específicos) const { data: conversions, error: conversionsError } = await supabase .from("analytics") .select("*") .eq("event_type", "lead_captured") .order("created_at", { ascending: false }) if (messageError || conversationError || lastMessagesError || conversionsError) { console.error("Error fetching analytics data") } return { totalInteractions: messageCount || 0, totalConversations: conversationCount || 0, lastMessages: lastMessages || [], conversions: conversions || [], } } [V0_FILE]typescriptreact:file="components/chat-interface.tsx" isEdit="true" isMerged="true" "use client" import type React from "react" import { useState, useEffect, useRef } from "react" import Image from "next/image" import { Send } from "lucide-react" import { saveMessage, getConversationMessages, createConversation, updateConversation, trackAnalytics, } from "@/lib/supabase" import { formatTimestamp } from "@/lib/utils" interface Message { id: string content: string sender: "user" | "bot" timestamp: string } export default function ChatInterface() { const [messages, setMessages] = useState([]) const [input, setInput] = useState("") const [isLoading, setIsLoading] = useState(false) const [conversationId, setConversationId] = useState(null) const messagesEndRef = useRef(null) useEffect(() => { // Inicializa a conversa ou carrega uma existente const initConversation = async () => { // Verifica se já existe um ID de conversa no localStorage const savedConversationId = localStorage.getItem("gm-conversation-id") if (savedConversationId) { setConversationId(savedConversationId) const savedMessages = await getConversationMessages(savedConversationId) if (savedMessages.length > 0) { setMessages(savedMessages) } else { // Se não houver mensagens, adiciona a mensagem de boas-vindas await addWelcomeMessage(savedConversationId) } } else { // Cria uma nova conversa const newConversation = await createConversation({}) if (newConversation) { setConversationId(newConversation.id) localStorage.setItem("gm-conversation-id", newConversation.id) await addWelcomeMessage(newConversation.id) } } } initConversation() }, []) const addWelcomeMessage = async (convId: string) => { const welcomeContent = "Olá! Eu sou o Agente GM 🤖, pronto pra te ajudar a vender todos os dias. Qual seu produto ou serviço? Me diz sua meta do mês e já te dou uma ação prática com IA pra começar hoje." const welcomeMessage = await saveMessage({ content: welcomeContent, sender: "bot", conversation_id: convId, }) if (welcomeMessage) { setMessages([welcomeMessage]) } } useEffect(() => { // Scroll to bottom when messages change messagesEndRef.current?.scrollIntoView({ behavior: "smooth" }) }, [messages]) const handleSendMessage = async (e: React.FormEvent) => { e.preventDefault() if (!input.trim() || isLoading || !conversationId) return // Add user message setIsLoading(true) const userMessage = await saveMessage({ content: input, sender: "user", conversation_id: conversationId, }) if (userMessage) { setMessages((prev) => [...prev, userMessage]) } setInput("") // Track interaction trackAnalytics({ event_type: "message_sent", event_data: { message: input }, user_id: conversationId, }) try { // Call API to get bot response const response = await fetch("/api/ask-gpt", { method: "POST", headers: { "Content-Type": "application/json", }, body: JSON.stringify({ message: input, conversationId, }), }) if (!response.ok) { throw new Error("Failed to get response") } const data = await response.json() // Add bot message const botMessage = await saveMessage({ content: data.response, sender: "bot", conversation_id: conversationId, }) if (botMessage) { setMessages((prev) => [...prev, botMessage]) } // Atualiza a conversa com informações extraídas (se houver) if (data.extractedInfo) { await updateConversation(conversationId, data.extractedInfo) } } catch (error) { console.error("Error getting bot response:", error) // Add error message const errorContent = "Desculpe, tive um problema ao processar sua mensagem. Pode tentar novamente?" const errorMessage = await saveMessage({ content: errorContent, sender: "bot", conversation_id: conversationId, }) if (errorMessage) { setMessages((prev) => [...prev, errorMessage]) } } finally { setIsLoading(false) } } return (

Agente GM 🤖

Online

{messages.map((message) => (

{message.sender === "bot" && (

)}

{message.content}

{formatTimestamp(new Date(message.timestamp))}

))} {isLoading && (

)}

) } [V0_FILE]typescriptreact:file="app/api/ask-gpt/route.ts" isEdit="true" isMerged="true" import { type NextRequest, NextResponse } from "next/server" import { generateText } from "ai" import { openai } from "@ai-sdk/openai" import { updateConversation, trackAnalytics } from "@/lib/supabase" export const runtime = "edge" // Função para extrair informações do usuário da mensagem function extractUserInfo(message: string) { const extractedInfo: Record = { email: null, phone_number: null, product: null, } // Extrai email const emailRegex = /[\w.-]+@[\w.-]+\.\w+/g const emailMatch = message.match(emailRegex) if (emailMatch) { extractedInfo.email = emailMatch[0] } // Extrai número de telefone (formato brasileiro) const phoneRegex = /(?:\+55\s?)?(?:$$\d{2}$$[\s.-]?)?\d{4,5}[\s.-]?\d{4}/g const phoneMatch = message.match(phoneRegex) if (phoneMatch) { extractedInfo.phone_number = phoneMatch[0] } // Tenta identificar o produto/serviço // Isso é mais complexo e pode ser melhorado com análise de NLP mais avançada const productKeywords = [ "vendo", "vender", "produto", "serviço", "ofereço", "trabalho com", "negócio", "empresa", "loja", ] for (const keyword of productKeywords) { const regex = new RegExp(`${keyword}\\s+([^.,;!?]+)`, "i") const match = message.match(regex) if (match && match[1]) { extractedInfo.product = match[1].trim() break } } return extractedInfo } export async function POST(req: NextRequest) { try { const { message, conversationId } = await req.json() if (!message) { return NextResponse.json({ error: "Message is required" }, { status: 400 }) } // Extrai informações do usuário da mensagem const extractedInfo = extractUserInfo(message) // Se encontrou informações, atualiza a conversa if (conversationId && (extractedInfo.email || extractedInfo.phone_number || extractedInfo.product)) { await updateConversation(conversationId, extractedInfo) // Se encontrou email ou telefone, registra como lead if (extractedInfo.email || extractedInfo.phone_number) { trackAnalytics({ event_type: "lead_captured", event_data: extractedInfo, user_id: conversationId, }) } } const systemPrompt = `Você é o Agente GM 🤖, um assistente de vendas inteligente e direto. Seu objetivo é ajudar o usuário a vender mais usando IA e tráfego pago. Regras importantes: 1. Use um tom vendedor, direto e prático 2. Faça perguntas sobre o negócio do usuário 3. Sugira planos de ação com IA + tráfego pago 4. Incentive o usuário a compartilhar links do Instagram ou produto 5. Pergunte o que ele quer vender 6. Ofereça ajuda para criar uma oferta atraente 7. Use apenas estes emojis quando apropriado: 🤖 📦 💰 👇 🔥 8. Mantenha respostas curtas e objetivas (máximo 3 parágrafos) 9. Não use cumprimentos longos ou formais Exemplo de resposta: "Olá! Eu sou o Agente GM 🤖, pronto pra te ajudar a vender todos os dias. Qual seu produto ou serviço? Me diz sua meta do mês e já te dou uma ação prática com IA pra começar hoje." Se o usuário mencionar um produto específico, sugira uma estratégia de marketing direcionada para esse tipo de produto. Se o usuário mencionar metas de vendas, ofereça dicas práticas para alcançá-las. Se o usuário compartilhar um link ou perfil de Instagram, agradeça e pergunte sobre o público-alvo.` const { text } = await generateText({ model: openai("gpt-3.5-turbo"), system: systemPrompt, prompt: message, }) // Registra a resposta como uma interação if (conversationId) { trackAnalytics({ event_type: "bot_response", event_data: { response: text.substring(0, 100) + "..." }, user_id: conversationId, }) } return NextResponse.json({ response: text, extractedInfo: Object.values(extractedInfo).some((v) => v !== null) ? extractedInfo : null, }) } catch (error) { console.error("Error in ask-gpt route:", error) return NextResponse.json({ error: "Failed to process request" }, { status: 500 }) } } [V0_FILE]typescriptreact:file="lib/auth.ts" isEdit="true" isMerged="true" import { getSupabase } from "./supabase" export async function signIn(email: string, password: string) { const supabase = getSupabase() const { data, error } = await supabase.auth.signInWithPassword({ email, password, }) if (error) { throw new Error(error.message) } return data } export async function signOut() { const supabase = getSupabase() const { error } = await supabase.auth.signOut() if (error) { throw new Error(error.message) } } export async function getCurrentUser() { const supabase = getSupabase() const { data: { user }, } = await supabase.auth.getUser() return user } export async function isAdmin(userId: string) { const supabase = getSupabase() const { data, error } = await supabase.from("admin_users").select("*").eq("user_id", userId).single() if (error || !data) { return false } return true } [V0_FILE]typescriptreact:file="components/admin-panel.tsx" isEdit="true" isMerged="true" "use client" import type React from "react" import { useState, useEffect } from "react" import { signIn, signOut, getCurrentUser, isAdmin } from "@/lib/auth" import { getConversations, getConversationMessages, getAnalyticsData } from "@/lib/supabase" import { formatTimestamp } from "@/lib/utils" interface Conversation { id: string phone_number: string | null email: string | null product: string | null created_at: string last_interaction: string } interface Message { id: string content: string sender: "user" | "bot" timestamp: string conversation_id: string } interface AnalyticsData { totalInteractions: number totalConversations: number lastMessages: any[] conversions: any[] } export default function AdminPanel() { const [conversations, setConversations] = useState([]) const [analytics, setAnalytics] = useState({ totalInteractions: 0, totalConversations: 0, lastMessages: [], conversions: [], }) const [isAuthenticated, setIsAuthenticated] = useState(false) const [isAuthorized, setIsAuthorized] = useState(false) const [isLoading, setIsLoading] = useState(true) const [email, setEmail] = useState("") const [password, setPassword] = useState("") const [selectedConversation, setSelectedConversation] = useState(null) const [conversationMessages, setConversationMessages] = useState([]) useEffect(() => { const checkAuth = async () => { try { const user = await getCurrentUser() if (user) { setIsAuthenticated(true) const adminStatus = await isAdmin(user.id) setIsAuthorized(adminStatus) if (adminStatus) { loadData() } } } catch (error) { console.error("Auth error:", error) } finally { setIsLoading(false) } } checkAuth() }, []) const loadData = async () => { setIsLoading(true) try { // Carrega conversas const conversationsData = await getConversations() setConversations(conversationsData) // Carrega dados de analytics const analyticsData = await getAnalyticsData() setAnalytics(analyticsData) } catch (error) { console.error("Error loading data:", error) } finally { setIsLoading(false) } } const handleLogin = async (e: React.FormEvent) => { e.preventDefault() try { await signIn(email, password) const user = await getCurrentUser() if (user) { setIsAuthenticated(true) const adminStatus = await isAdmin(user.id) setIsAuthorized(adminStatus) if (adminStatus) { loadData() } } } catch (error) { console.error("Login error:", error) alert("Erro ao fazer login. Verifique suas credenciais.") } } const handleLogout = async () => { try { await signOut() setIsAuthenticated(false) setIsAuthorized(false) } catch (error) { console.error("Logout error:", error) } } const viewConversation = async (conversation: Conversation) => { setSelectedConversation(conversation) try { const messages = await getConversationMessages(conversation.id) setConversationMessages(messages) } catch (error) { console.error("Error fetching messages:", error) setConversationMessages([]) } } const exportConversations = () => { const csvContent = [ ["ID", "Email", "WhatsApp", "Produto", "Criado em", "Última interação"].join(","), ...conversations.map((conv) => [ conv.id, conv.email || "N/A", conv.phone_number || "N/A", conv.product || "N/A", new Date(conv.created_at).toLocaleString(), new Date(conv.last_interaction).toLocaleString(), ].join(","), ), ].join("\n") const blob = new Blob([csvContent], { type: "text/csv;charset=utf-8;" }) const url = URL.createObjectURL(blob) const link = document.createElement("a") link.setAttribute("href", url) link.setAttribute("download", `agente-gm-leads-${new Date().toISOString().split("T")[0]}.csv`) link.style.visibility = "hidden" document.body.appendChild(link) link.click() document.body.removeChild(link) } if (isLoading) { return (

Carregando...

) } if (!isAuthenticated) { return (

Painel Admin

) } if (!isAuthorized) { return (

Acesso Negado

Você não tem permissão para acessar o painel de administração.

) } return (

Painel Admin - Agente GM

Total de Interações

{analytics.totalInteractions}

Total de Conversas

{analytics.totalConversations}

Ações

Últimas Interações

{analytics.lastMessages.map((message, index) => (

{formatTimestamp(new Date(message.timestamp))} {message.conversations?.phone_number && ` - ${message.conversations.phone_number}`}

{message.content}

))} {analytics.lastMessages.length === 0 &&

Nenhuma interação registrada

}

Conversas

{selectedConversation ? (

Detalhes da Conversa

{selectedConversation.id.substring(0, 8)}...

{selectedConversation.phone_number || "N/A"}

{selectedConversation.email || "N/A"}

Produto

{selectedConversation.product || "N/A"}

Criado em

{new Date(selectedConversation.created_at).toLocaleString()}

Última interação

{new Date(selectedConversation.last_interaction).toLocaleString()}

Histórico de Mensagens

{conversationMessages.map((message) => (

{message.sender === "user" ? "Cliente" : "Agente GM"} -{" "} {formatTimestamp(new Date(message.timestamp))}

{message.content}

))} {conversationMessages.length === 0 &&

Nenhuma mensagem encontrada

}

) : (

{conversations.length > 0 ? (

{conversations.map((conversation) => ( ))}

ID	WhatsApp	Email	Última Interação	Ações
{conversation.id.substring(0, 8)}...	{conversation.phone_number \|\| "N/A"}	{conversation.email \|\| "N/A"}	{formatTimestamp(new Date(conversation.last_interaction))}

) : (

Nenhuma conversa registrada

)}

) } [V0_FILE]json:file="package.json" isEdit="true" isMerged="true" { "name": "agente-gm-chatbot", "version": "0.1.0", "private": true, "scripts": { "dev": "next dev", "build": "next build", "start": "next start", "lint": "next lint" }, "dependencies": { "@ai-sdk/openai": "^1.0.0", "@supabase/supabase-js": "^2.39.0", "ai": "^2.2.27", "clsx": "^2.0.0", "lucide-react": "^0.294.0", "next": "14.0.4", "react": "^18", "react-dom": "^18", "tailwind-merge": "^2.1.0" }, "devDependencies": { "@types/node": "^20", "@types/react": "^18", "@types/react-dom": "^18", "autoprefixer": "^10.0.1", "eslint": "^8", "eslint-config-next": "14.0.4", "postcss": "^8", "tailwindcss": "^3.3.0", "typescript": "^5" } } [V0_FILE]sql:file="supabase/add-admin.sql" isMerged="true" -- Função para adicionar um admin CREATE OR REPLACE FUNCTION add_admin_user(admin_email TEXT) RETURNS VOID AS $$ DECLARE user_id UUID; BEGIN -- Obter o ID do usuário pelo email SELECT id INTO user_id FROM auth.users WHERE email = admin_email; IF user_id IS NULL THEN RAISE EXCEPTION 'Usuário com email % não encontrado', admin_email; END IF; -- Verificar se já é admin IF EXISTS (SELECT 1 FROM admin_users WHERE user_id = user_id) THEN RAISE NOTICE 'Usuário já é admin'; RETURN; END IF; -- Adicionar como admin INSERT INTO admin_users (user_id) VALUES (user_id); RAISE NOTICE 'Usuário % adicionado como admin com sucesso', admin_email; END; $$ LANGUAGE plpgsql; -- Para usar a função, execute: -- SELECT add_admin_user('seu-email@exemplo.com'); [V0_FILE]css:file="app/globals.css" isEdit="true" @tailwind base; @tailwind components; @tailwind utilities; :root { --primary: #25d366; --primary-dark: #128c7e; --primary-light: #dcf8c6; --secondary: #000000; --background: #ffffff; --background-chat: #e5ddd5; } body { color: var(--secondary); background: var(--background); } .chat-bubble-user { @apply bg-white rounded-lg p-3 max-w-[80%] shadow-sm; position: relative; } .chat-bubble-user:after { content: ""; position: absolute; right: -8px; top: 10px; width: 0; height: 0; border: 8px solid transparent; border-left-color: white; border-right: 0; margin-top: -8px; margin-right: -8px; } .chat-bubble-bot { @apply bg-primary-light rounded-lg p-3 max-w-[80%] shadow-sm; position: relative; } .chat-bubble-bot:after { content: ""; position: absolute; left: -8px; top: 10px; width: 0; height: 0; border: 8px solid transparent; border-right-color: var(--primary-light); border-left: 0; margin-top: -8px; margin-left: -8px; }