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feat: Refactor build and service logic

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Updated package.json scripts to use Vite for development and building, removing esbuild dependency.
Migrated Gemini AI service logic from a backend API to direct integration using the Google GenAI library. This centralizes AI analysis within the application, improving performance and maintainability.
This commit is contained in:
desartstudio95
2026-05-19 09:40:12 -07:00
parent ef61b58a62
commit a579152114
5 changed files with 270 additions and 862 deletions
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package-lock.json
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+108 -593
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@@ -36,7 +36,6 @@
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"@esbuild/linux-ppc64": "0.27.7",
"@esbuild/linux-riscv64": "0.27.7",
"@esbuild/linux-s390x": "0.27.7",
"@esbuild/linux-x64": "0.27.7",
"@esbuild/netbsd-arm64": "0.27.7",
"@esbuild/netbsd-x64": "0.27.7",
"@esbuild/openbsd-arm64": "0.27.7",
"@esbuild/openbsd-x64": "0.27.7",
"@esbuild/openharmony-arm64": "0.27.7",
"@esbuild/sunos-x64": "0.27.7",
"@esbuild/win32-arm64": "0.27.7",
"@esbuild/win32-ia32": "0.27.7",
"@esbuild/win32-x64": "0.27.7"
}
},
"node_modules/tw-animate-css": {
"version": "1.4.0",
"resolved": "https://registry.npmjs.org/tw-animate-css/-/tw-animate-css-1.4.0.tgz",
package.json
+2 -4
View File
@@ -4,9 +4,8 @@
"version": "0.0.0",
"type": "module",
"scripts": {
"dev": "tsx server.ts",
"build": "vite build && esbuild server.ts --bundle --platform=node --format=cjs --packages=external --sourcemap --outfile=dist/server.cjs",
"start": "node dist/server.cjs",
"dev": "vite --port=3000 --host=0.0.0.0",
"build": "vite build",
"preview": "vite preview",
"clean": "rm -rf dist",
"lint": "tsc --noEmit"
@@ -40,7 +39,6 @@
"@types/express": "^4.17.21",
"@types/node": "^22.14.0",
"autoprefixer": "^10.4.21",
"esbuild": "^0.28.0",
"eslint": "^10.2.1",
"tailwindcss": "^4.1.14",
"ts-node": "^10.9.2",
server.ts
-212
View File
@@ -1,212 +0,0 @@
import { GoogleGenAI, Type } from "@google/genai";
import express from "express";
import path from "path";
import { createServer as createViteServer } from "vite";
const startServer = async () => {
const app = express();
const PORT = 3000;
// Middleware to parse JSON bodies with a larger limit for images
app.use(express.json({ limit: "50mb" }));
const ai = new GoogleGenAI(process.env.GEMINI_API_KEY ? { apiKey: process.env.GEMINI_API_KEY.trim() } : {});
app.post("/api/analyze", async (req, res) => {
try {
const { imageBase64, userNotes, preferredMode, userPlan } = req.body;
const model = 'gemini-2.5-flash';
const systemInstruction = `
# QUANTSCAN IA — MODO MULTI TIME FRAME + LONG TERM ANALYSIS
Você é o QUANTSCAN IA, um sistema profissional avançado de análise Forex, Índices, Commodities e Criptomoedas baseado em Inteligência Artificial institucional.
Plano do Usuário Atual: ${userPlan || 'basic'}
Sua função é analisar gráficos enviados pelo usuário através de: screenshot do gráfico, foto da tela, imagem do TradingView, imagem MT4/MT5 ou corretoras.
O sistema deve operar em dois modos:
1. SHORT TERM / SCALPING
2. LONG TERM / SWING TRADE / POSITION TRADE
==================================================
RESTRIÇÕES DE PLANO
==================================================
Se o plano do usuário for "basic" ou "experimental", você é **PROIBIDO** de realizar análise LONG TERM / SWING / POSITION.
Independentemente do timeframe enxergado na imagem (mesmo que seja H4, D1, W1), você deve focar nas estruturas de curto prazo e gerar sinais APENAS para Scalping ou Intraday.
Para planos "pro", "elite", e "lifetime", você pode e deve realizar análises MULTI TIME FRAME e gerar decisões LONG TERM.
==================================================
ANÁLISE MULTI TIME FRAME (OBRIGATÓRIO PARA PRO/ELITE/LIFETIME)
==================================================
A IA deve identificar automaticamente: timeframe principal, secundário e contexto macro do mercado.
Exemplo: H4 → tendência principal, H1 → estrutura intermediária, M15 → entrada precisa.
TIMEFRAMES SUPORTADOS:
- Scalping: M1, M5, M15
- Intraday: M30, H1
- Swing Trade: H4, D1
- Longo Prazo: W1, MN
A IA deve:
1. Detectar tendência do timeframe maior.
2. Confirmar alinhamento estrutural.
3. Procurar entradas no timeframe menor.
4. Evitar entradas contra tendência macro.
==================================================
REGRAS DE LONGO PRAZO
==================================================
Se detectar: H4, D1, W1, Monthly
A IA deve ativar automaticamente: "MODO LONG TERM ANALYSIS" e analisar tendência macro, ciclos institucionais, acumulação/distribuição, zonas de interesse, continuação ou reversão, força de tendência e pontos de holding.
==================================================
ESTRATÉGIAS OBRIGATÓRIAS
==================================================
1. SMART MONEY CONCEPT (SMC): BOS, CHOCH, Order Blocks, Liquidity, Fair Value Gap.
2. LIQUIDITY SWEEP + TRAP DETECTION: stop hunts, fake breakouts, manipulation.
3. MOMENTUM + ENTRY TIMING: força da tendência, volume, velocidade do preço.
4. MARKET STRUCTURE AI: tendência bullish/bearish, ranging, expansão.
5. FUNDAMENTAL ANALYSIS AI: notícias, juros, impacto macroeconômico.
==================================================
CAMADA DE CONFIRMAÇÃO E IA (APENAS FILTRO)
==================================================
- Volume Delta, CVD, Volume Profile.
- ATR (Average True Range).
- EMA (apenas filtro macro).
- RSI (com Liquidity Sweep).
- VWAP.
- Score probabilístico e Filtro anti-fake breakout.
==================================================
ENTRADAS OBRIGATÓRIAS (Sistema de Probabilidade)
==================================================
A IA deve fornecer no JSON estrito todas as chaves abaixo:
- Direção: BUY, SELL ou WAIT
- Tipo: Scalping / Intraday / Swing / Long Term (chave signalType)
- Nível de Risco: LOW / MEDIUM / HIGH (chave riskLevel)
- Risco/Retorno: (ex: 1:3) (chave riskReward)
- Duração Estimada: (ex: 3 a 10 dias) (chave duration)
- Entrada, Stop Loss, Take Profit 1, Take Profit 2, e Take Profit 3.
Exemplo visual de leitura interna:
CONFIDENCE SCORE: 91%
RISK LEVEL: LOW
MULTI TIME FRAME: W1 Bullish, D1 Bullish, H4 Pullback...
FORMATO DE SAÍDA (Obrigatório em JSON):
{
"mode": "Técnico" | "Fundamental" | "Híbrido",
"analiseGeral": "Análise multi timeframe macro e micro",
"timeframe": "Timeframes analisados (ex: H4/M15)",
"estrutura": "Detalhes estruturais",
"tecnica": "SMC + Confirmações",
"fundamental": "Resumo",
"decision": "BUY" | "SELL" | "WAIT",
"signalType": "Scalping" | "Intraday" | "Swing" | "Long Term",
"riskLevel": "LOW" | "MEDIUM" | "HIGH",
"entry": "1.08450",
"stopLoss": "1.07800",
"takeProfit": "1.09200",
"takeProfit2": "1.10100",
"takeProfit3": "1.11500",
"riskReward": "1:3",
"duration": "3 a 10 dias",
"score": 91,
"justification": "Razão principal",
"alerta": "Cuidados",
"pair": "EUR/USD"
}
`;
const prompt = `
Analise este gráfico sob a óptica do QuantScan IA.
${preferredMode ? `Use estritamente o modo de análise: ${preferredMode}.` : 'Detecte o melhor modo automaticamente.'}
${userNotes ? `Notas do usuário: ${userNotes}` : ''}
Detecte modo, timeframe e par se não fornecidos. Retorne JSON estrito.
`;
const response = await ai.models.generateContent({
model,
contents: [
{
parts: [
{ text: prompt },
{ inlineData: { mimeType: "image/jpeg", data: imageBase64 } }
]
}
],
config: {
systemInstruction,
responseMimeType: "application/json",
responseSchema: {
type: Type.OBJECT,
properties: {
mode: { type: Type.STRING, enum: ['Técnico', 'Fundamental', 'Híbrido'] },
analiseGeral: { type: Type.STRING },
pair: { type: Type.STRING },
timeframe: { type: Type.STRING },
estrutura: { type: Type.STRING },
tecnica: { type: Type.STRING },
fundamental: { type: Type.STRING },
decision: { type: Type.STRING, enum: ["BUY", "SELL", "WAIT"] },
signalType: { type: Type.STRING },
riskLevel: { type: Type.STRING },
entry: { type: Type.STRING },
stopLoss: { type: Type.STRING },
takeProfit: { type: Type.STRING },
takeProfit2: { type: Type.STRING },
takeProfit3: { type: Type.STRING },
riskReward: { type: Type.STRING },
duration: { type: Type.STRING },
score: { type: Type.NUMBER },
justification: { type: Type.STRING },
alerta: { type: Type.STRING }
},
required: ["mode", "analiseGeral", "pair", "timeframe", "estrutura", "tecnica", "fundamental", "decision", "signalType", "riskLevel", "entry", "stopLoss", "takeProfit", "takeProfit2", "takeProfit3", "riskReward", "duration", "score", "justification", "alerta"]
}
}
});
const textResponse = response.text || '{}';
const cleanJson = textResponse.replace(/^```json\s*/, '').replace(/\s*```$/, '');
const parsedData = JSON.parse(cleanJson);
res.json(parsedData);
} catch (err: any) {
console.error("Gemini Error server-side:", err);
let errorMessage = err.message || "Erro desconhecido";
if (errorMessage.includes("API key not valid")) {
errorMessage = "A chave de API configurada no projeto (GEMINI_API_KEY) é inválida. Verifique em 'Secrets'.";
} else if (errorMessage.includes("API key should be set") || errorMessage.includes("API_KEY_INVALID")) {
errorMessage = "A chave de API não foi configurada ou é inválida. Defina GEMINI_API_KEY em 'Secrets'.";
}
res.status(500).json({ error: errorMessage });
}
});
// Vite middleware for development
if (process.env.NODE_ENV !== "production") {
const vite = await createViteServer({
server: { middlewareMode: true },
appType: "spa",
});
app.use(vite.middlewares);
} else {
// Production: serve static files. Dist is at project root.
const distPath = path.join(process.cwd(), 'dist');
app.use(express.static(distPath));
app.get('*', (req, res) => {
res.sendFile(path.join(distPath, 'index.html'));
});
}
app.listen(PORT, "0.0.0.0", () => {
console.log(`Server running on http://0.0.0.0:${PORT}`);
});
};
startServer();
src/services/geminiService.ts
+160 -35
View File
@@ -1,41 +1,166 @@
import { AnalysisResponse } from '../types';
import { GoogleGenAI, Type } from "@google/genai";
import { AnalysisResponse, SignalType } from "../types";
export const analyzeForexChart = async (
imageBase64: string,
userNotes?: string,
preferredMode?: 'Técnico' | 'Fundamental' | 'Híbrido',
userPlan?: string
): Promise<AnalysisResponse> => {
const ai = new GoogleGenAI({ apiKey: process.env.GEMINI_API_KEY || '' });
const response = await fetch(
'https://quantscan-backend.onrender.com/api/analyze',
{
method: 'POST',
export const analyzeForexChart = async (imageBase64: string, userNotes?: string, preferredMode?: 'Técnico' | 'Fundamental' | 'Híbrido', userPlan?: string): Promise<AnalysisResponse> => {
const model = 'gemini-3.1-pro-preview';
const systemInstruction = `
# QUANTSCAN IA — MODO MULTI TIME FRAME + LONG TERM ANALYSIS
headers: {
'Content-Type': 'application/json',
},
Você é o QUANTSCAN IA, um sistema profissional avançado de análise Forex, Índices, Commodities e Criptomoedas baseado em Inteligência Artificial institucional.
body: JSON.stringify({
imageBase64,
userNotes,
preferredMode,
userPlan
}),
Plano do Usuário Atual: ${userPlan || 'basic'}
Sua função é analisar gráficos enviados pelo usuário através de: screenshot do gráfico, foto da tela, imagem do TradingView, imagem MT4/MT5 ou corretoras.
O sistema deve operar em dois modos:
1. SHORT TERM / SCALPING
2. LONG TERM / SWING TRADE / POSITION TRADE
==================================================
RESTRIÇÕES DE PLANO
==================================================
Se o plano do usuário for "basic" ou "experimental", você é **PROIBIDO** de realizar análise LONG TERM / SWING / POSITION.
Independentemente do timeframe enxergado na imagem (mesmo que seja H4, D1, W1), você deve focar nas estruturas de curto prazo e gerar sinais APENAS para Scalping ou Intraday.
Para planos "pro", "elite", e "lifetime", você pode e deve realizar análises MULTI TIME FRAME e gerar decisões LONG TERM.
==================================================
ANÁLISE MULTI TIME FRAME (OBRIGATÓRIO PARA PRO/ELITE/LIFETIME)
==================================================
A IA deve identificar automaticamente: timeframe principal, secundário e contexto macro do mercado.
Exemplo: H4 → tendência principal, H1 → estrutura intermediária, M15 → entrada precisa.
TIMEFRAMES SUPORTADOS:
- Scalping: M1, M5, M15
- Intraday: M30, H1
- Swing Trade: H4, D1
- Longo Prazo: W1, MN
A IA deve:
1. Detectar tendência do timeframe maior.
2. Confirmar alinhamento estrutural.
3. Procurar entradas no timeframe menor.
4. Evitar entradas contra tendência macro.
==================================================
REGRAS DE LONGO PRAZO
==================================================
Se detectar: H4, D1, W1, Monthly
A IA deve ativar automaticamente: "MODO LONG TERM ANALYSIS" e analisar tendência macro, ciclos institucionais, acumulação/distribuição, zonas de interesse, continuação ou reversão, força de tendência e pontos de holding.
==================================================
ESTRATÉGIAS OBRIGATÓRIAS
==================================================
1. SMART MONEY CONCEPT (SMC): BOS, CHOCH, Order Blocks, Liquidity, Fair Value Gap.
2. LIQUIDITY SWEEP + TRAP DETECTION: stop hunts, fake breakouts, manipulation.
3. MOMENTUM + ENTRY TIMING: força da tendência, volume, velocidade do preço.
4. MARKET STRUCTURE AI: tendência bullish/bearish, ranging, expansão.
5. FUNDAMENTAL ANALYSIS AI: notícias, juros, impacto macroeconômico.
==================================================
CAMADA DE CONFIRMAÇÃO E IA (APENAS FILTRO)
==================================================
- Volume Delta, CVD, Volume Profile.
- ATR (Average True Range).
- EMA (apenas filtro macro).
- RSI (com Liquidity Sweep).
- VWAP.
- Score probabilístico e Filtro anti-fake breakout.
==================================================
ENTRADAS OBRIGATÓRIAS (Sistema de Probabilidade)
==================================================
A IA deve fornecer no JSON estrito todas as chaves abaixo:
- Direção: BUY, SELL ou WAIT
- Tipo: Scalping / Intraday / Swing / Long Term (chave signalType)
- Nível de Risco: LOW / MEDIUM / HIGH (chave riskLevel)
- Risco/Retorno: (ex: 1:3) (chave riskReward)
- Duração Estimada: (ex: 3 a 10 dias) (chave duration)
- Entrada, Stop Loss, Take Profit 1, Take Profit 2, e Take Profit 3.
Exemplo visual de leitura interna:
CONFIDENCE SCORE: 91%
RISK LEVEL: LOW
MULTI TIME FRAME: W1 Bullish, D1 Bullish, H4 Pullback...
FORMATO DE SAÍDA (Obrigatório em JSON):
{
"mode": "Técnico" | "Fundamental" | "Híbrido",
"analiseGeral": "Análise multi timeframe macro e micro",
"timeframe": "Timeframes analisados (ex: H4/M15)",
"estrutura": "Detalhes estruturais",
"tecnica": "SMC + Confirmações",
"fundamental": "Resumo",
"decision": "BUY" | "SELL" | "WAIT",
"signalType": "Scalping" | "Intraday" | "Swing" | "Long Term",
"riskLevel": "LOW" | "MEDIUM" | "HIGH",
"entry": "1.08450",
"stopLoss": "1.07800",
"takeProfit": "1.09200",
"takeProfit2": "1.10100",
"takeProfit3": "1.11500",
"riskReward": "1:3",
"duration": "3 a 10 dias",
"score": 91,
"justification": "Razão principal",
"alerta": "Cuidados",
"pair": "EUR/USD"
}
`;
const prompt = `
Analise este gráfico sob a óptica do QuantScan IA.
${preferredMode ? `Use estritamente o modo de análise: ${preferredMode}.` : 'Detecte o melhor modo automaticamente.'}
${userNotes ? `Notas do usuário: ${userNotes}` : ''}
Detecte modo, timeframe e par se não fornecidos. Retorne JSON estrito.
`;
const response = await ai.models.generateContent({
model,
contents: [
{
parts: [
{ text: prompt },
{ inlineData: { mimeType: "image/jpeg", data: imageBase64 } }
]
}
],
config: {
systemInstruction,
responseMimeType: "application/json",
responseSchema: {
type: Type.OBJECT,
properties: {
mode: { type: Type.STRING, enum: ['Técnico', 'Fundamental', 'Híbrido'] },
analiseGeral: { type: Type.STRING },
pair: { type: Type.STRING },
timeframe: { type: Type.STRING },
estrutura: { type: Type.STRING },
tecnica: { type: Type.STRING },
fundamental: { type: Type.STRING },
decision: { type: Type.STRING, enum: ["BUY", "SELL", "WAIT"] },
signalType: { type: Type.STRING },
riskLevel: { type: Type.STRING },
entry: { type: Type.STRING },
stopLoss: { type: Type.STRING },
takeProfit: { type: Type.STRING },
takeProfit2: { type: Type.STRING },
takeProfit3: { type: Type.STRING },
riskReward: { type: Type.STRING },
duration: { type: Type.STRING },
score: { type: Type.NUMBER },
justification: { type: Type.STRING },
alerta: { type: Type.STRING }
},
required: ["mode", "analiseGeral", "pair", "timeframe", "estrutura", "tecnica", "fundamental", "decision", "signalType", "riskLevel", "entry", "stopLoss", "takeProfit", "takeProfit2", "takeProfit3", "riskReward", "duration", "score", "justification", "alerta"]
}
}
);
});
if (!response.ok) {
const errorData =
await response.json().catch(() => ({}));
throw new Error(
errorData.error ||
`HTTP error! status: ${response.status}`
);
}
return await response.json() as AnalysisResponse;
};
const textResponse = response.text || '{}';
const cleanJson = textResponse.replace(/^```json\s*/, '').replace(/\s*```$/, '');
return JSON.parse(cleanJson) as AnalysisResponse;
};
test2.ts
-18
View File
@@ -1,18 +0,0 @@
import { GoogleGenAI } from "@google/genai";
import * as dotenv from "dotenv";
dotenv.config();
const test = async () => {
const ai = new GoogleGenAI({});
try {
const response = await ai.models.generateContent({
model: "gemini-3.1-pro-preview",
contents: "Tell me a joke"
});
console.log("Success:", response.text);
} catch (err: any) {
console.error("Error:", err.message);
}
}
test();