import streamlit as st 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.")