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import requests
import plotly.graph_objects as go
import plotly.express as px
import pandas as pd
from fpdf import FPDF
import json
import os
# --- CONFIGURACIÓN DE RUTAS Y RED ---
BACKEND_URL = "https://denisijcu-vertex-risk-engine.hf.space"
WATCHLIST_FILE = "app/watchlist.json"
def load_watchlist():
try:
if os.path.exists(WATCHLIST_FILE):
with open(WATCHLIST_FILE, "r") as f:
return json.load(f)
except Exception: pass
return ["INTC", "TSLA", "AAPL", "SAVE"]
def save_watchlist(watchlist):
os.makedirs(os.path.dirname(WATCHLIST_FILE), exist_ok=True)
with open(WATCHLIST_FILE, "w") as f:
json.dump(watchlist, f)
# --- MOTOR DE REPORTES PDF ---
class VertexReport(FPDF):
def header(self):
self.set_font('Arial', 'B', 15)
self.cell(0, 10, 'VERTEX CODERS LLC - AUDIT REPORT', 0, 1, 'C')
self.ln(10)
def generate_pdf(data):
pdf = VertexReport()
pdf.set_auto_page_break(auto=True, margin=15)
pdf.add_page()
pdf.set_font("Arial", 'B', 14)
pdf.set_fill_color(151, 231, 225)
pdf.cell(0, 12, f"AUDIT REPORT: {data.get('ticker', 'N/A')}", 1, 1, 'C', fill=True)
pdf.ln(5)
pdf.set_font("Arial", 'B', 12)
pdf.cell(0, 10, f"FINAL STATUS: {data.get('status', 'UNKNOWN')}", 0, 1)
semantic = data.get("semantic_analysis", {})
msg = str(semantic.get('summary', data.get('msg', 'No data'))).encode('latin-1', 'replace').decode('latin-1')
pdf.ln(5)
pdf.set_font("Arial", 'B', 11)
pdf.cell(0, 10, "1. EXECUTIVE VERDICT", 0, 1)
pdf.set_font("Arial", size=10)
pdf.multi_cell(0, 8, msg)
pdf.ln(5)
pdf.set_font("Arial", 'B', 11)
pdf.cell(0, 10, "2. FINANCIAL METRICS", 0, 1)
z_score = data.get("numeric_analysis", {}).get("altman_z") or data.get("z_score", 0)
pdf.cell(0, 8, f"- Altman Z-Score: {float(z_score):.2f}", 0, 1)
return pdf.output(dest='S')
# --- CONFIGURACIÓN DE LA UI ---
st.set_page_config(page_title="Vertex Risk Terminal | Némesis", page_icon="🛡️", layout="wide")
if "watchlist" not in st.session_state:
st.session_state.watchlist = load_watchlist()
# --- SIDEBAR ---
st.sidebar.title("🏢 Stock Watchlist")
new_ticker = st.sidebar.text_input("Add Ticker").upper()
if st.sidebar.button("➕ Add"):
if new_ticker and new_ticker not in st.session_state.watchlist:
st.session_state.watchlist.append(new_ticker)
save_watchlist(st.session_state.watchlist)
st.sidebar.success(f"✅ {new_ticker} saved!")
st.rerun()
selected_ticker = st.sidebar.selectbox("Analyze Company", st.session_state.watchlist)
st.sidebar.divider()
st.sidebar.subheader("📡 Bunker Status")
def check_health(url):
try: return "🟢 ONLINE" if requests.get(url, timeout=2).status_code == 200 else "🔴 OFFLINE"
except: return "🔴 OFFLINE"
st.sidebar.write(f"Backend Engine: {check_health(BACKEND_URL + '/docs')}")
# --- CUERPO PRINCIPAL ---
st.title("🛡️ Vertex Risk Terminal")
st.caption("Quantum Risk Analysis Platform | Enterprise Edition")
# REPARACIÓN DE TABS: Declaración única de las 4 pestañas
tab1, tab2, tab3, tab4, tab5 = st.tabs(["📈 Stock Audit", "🔗 Web3 Audit", "🔍 Auditoría Individual", "📊 Comparativa Vertex", "⚙️ Settings"])
with tab1:
if st.button("🚀 RUN FULL STOCK AUDIT", type="primary", use_container_width=True):
with st.spinner(f"Auditing {selected_ticker} through Némesis Engine..."):
try:
r = requests.get(f"{BACKEND_URL}/audit/{selected_ticker}", timeout=25)
r.raise_for_status()
st.session_state.last_audit = r.json()
st.rerun()
except Exception as e:
st.error(f"🔌 Connection Failure: {e}")
if "last_audit" in st.session_state:
res = st.session_state.last_audit
st.divider()
col_l, col_r = st.columns(2)
with col_l:
st.metric("FINAL STATUS", res.get("status", "UNKNOWN"))
z_val = res.get("numeric_analysis", {}).get("altman_z") or res.get("z_score", 0)
fig = go.Figure(go.Indicator(
mode="gauge+number",
value=float(z_val),
gauge={'axis': {'range': [0, 5]},
'steps': [{'range': [0, 1.1], 'color': "lightcoral"},
{'range': [1.1, 2.9], 'color': "lightyellow"},
{'range': [2.9, 5], 'color': "lightgreen"}]}))
fig.update_layout(height=300)
st.plotly_chart(fig, use_container_width=True)
with col_r:
st.subheader("🧠 Semantic Analysis")
sem = res.get("semantic_analysis", {})
st.info(sem.get("summary", res.get("msg", "No additional data.")))
st.download_button("📥 DOWNLOAD PDF REPORT", generate_pdf(res), f"Vertex_{selected_ticker}.pdf", "application/pdf", use_container_width=True)
with tab2:
st.subheader("🔗 Web3 Smart Contract Scanner")
contract = st.text_input("Dirección del Token (0x...)")
if st.button("🔍 SCAN WEB3 ASSET", use_container_width=True):
if contract:
with st.spinner("Escaneando seguridad...."):
try:
r = requests.get(f"{BACKEND_URL}/audit_contract/{contract}", timeout=120)
res_w3 = r.json()
st.divider()
status_w3 = res_w3.get("status", "UNKNOWN")
if status_w3 == "SAFE": st.success(f"✅ STATUS: {status_w3}")
elif status_w3 == "DANGER": st.error(f"🚨 STATUS: {status_w3}")
vulns = res_w3.get("vulnerabilities", [])
if vulns:
for v in vulns: st.error(f"**{v['description']}**")
with st.expander("Ver Código Fuente"):
st.code(res_w3.get("source_preview", ""), language='solidity')
except Exception as e: st.error(f"Error: {e}")
with tab3:
st.subheader("🔍 Auditoría Individual")
st.write(f"Vigilancia activa sobre: **{selected_ticker}**")
st.info("Este módulo utiliza análisis heurístico para reportes rápidos.")
with tab4:
st.subheader("📊 Comparativa de Salud Financiera")
comparison_list = st.multiselect("Compañías:", options=st.session_state.watchlist, default=st.session_state.watchlist[:3])
if st.button("📊 GENERAR COMPARATIVA", use_container_width=True):
comp_data = []
with st.spinner("Calculando ranking..."):
for t in comparison_list:
try:
r = requests.get(f"{BACKEND_URL}/audit/{t}", timeout=10)
if r.status_code == 200:
res = r.json()
z = res.get("numeric_analysis", {}).get("altman_z") or res.get("z_score", 0)
comp_data.append({"Ticker": t, "Z-Score": float(z)})
except: continue
if comp_data:
df = pd.DataFrame(comp_data)
fig_bar = px.bar(df, x='Ticker', y='Z-Score', color='Z-Score', color_continuous_scale=['red', 'yellow', 'green'], range_y=[0, 5])
fig_bar.add_hline(y=1.1, line_dash="dash", line_color="red")
fig_bar.add_hline(y=2.9, line_dash="dash", line_color="green")
st.plotly_chart(fig_bar, use_container_width=True)
with tab5:
st.header("⚙️ Configuración del Sistema")
st.info("Configura las credenciales de Telegram para que Némesis te envíe alertas automáticas.")
# Cargar configuraciones actuales si existen
if "settings" not in st.session_state:
st.session_state.settings = {"bot_token": "", "chat_id": ""}
with st.form("settings_form"):
bot_token = st.text_input("Telegram Bot Token", value=st.session_state.settings["bot_token"], type="password", help="El token que te dio BotFather")
chat_id = st.text_input("Telegram Chat ID", value=st.session_state.settings["chat_id"], help="Tu ID de usuario o el del grupo")
if st.form_submit_button("💾 Guardar Configuración"):
st.session_state.settings = {"bot_token": bot_token, "chat_id": chat_id}
# Aquí guardaríamos en un archivo que n8n vigile
with open("app/settings.json", "w") as f:
json.dump(st.session_state.settings, f)
st.success("✅ Configuración guardada. n8n ahora usará estas credenciales.") |