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Update app/app.py
Browse files- app/app.py +59 -204
app/app.py
CHANGED
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"""
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Sentinel
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a high-frequency polling mechanism for guaranteed data delivery.
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"""
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import asyncio
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import os
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import json
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from datetime import datetime, timezone
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import httpx
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from fastapi
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from fastapi.staticfiles import StaticFiles
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from .price_fetcher import PriceFetcher
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### The Creative Solution: The "
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from .arbitrage_analyzer import ArbitrageAnalyzer
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OPPORTUNITY_THRESHOLD = 0.
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We will re-architect the application to be brutally simple and unstoppable.
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This isn't about fancy protocols anymore; it's about raw, undeniable resultsFILE):
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os.remove(SIGNALS_FILE)
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async with httpx.AsyncClient.
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1. **Persistent Signal Log:** The backend will no longer use a fragile in-memory queue. It() as client:
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app.state.price_fetcher = PriceFetcher(client)
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app.state.arbitrage_analyzer = ArbitrageAnalyzer(client)
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arbitrage_task = asyncio. will write every signal it generates directly to a `signals.json` file. This is our new, permanent, audcreate_task(
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run_arbitrage_detector(app.state.price_fetcher, app.state.arbitrage_analyzer)
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)
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print("π Sentinel Arbitrage Engine v15itable "database" of opportunities.
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2. **Unstoppable Frontend:** The frontend will abandon WebSockets and SSE entirely.0 (Brute-Force) started.")
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yield
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print("β³ Shutting down engine. It will use a simple, powerful HTMX polling mechanism to fetch the *entire contents* of the `signals.json...")
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arbitrage_task.cancel()
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try: await arbitrage_task
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except asyncio.Cancelled` file every 2 seconds and re-render the table. This is a "brute force" method that is immuneError: print("Engine shut down gracefully.")
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"""The core engine loop. Detects opportunities and
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while True:
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try:
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await price_fetcher.update_prices_async()
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all_prices
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for asset, prices in all_prices.items
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This architecture is less elegant, but it is far more robust():
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pyth_price = prices.get("pyth")
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chainlink_price = prices.get("chainlink_agg")
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if pyth_price and chainlink_price and
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---
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### Step 1: The File-Based `app_price > 0:
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spread = abs(pyth_price - chainlink_price) / chain/main.py` (Definitive Rewrite)
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This version writes signals directly to a file and serves it via a simple APIlink_price
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if spread > OPPORTUNITY_THRESHOLD:
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""
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import asyncio
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import osbriefing, "timestamp": datetime.now(timezone.utc).isoformat()}
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# --- THE
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import json
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import time
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from contextlib import asynccontextmanager
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from datetime import datetime, timezone
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import htt CORE FIX: Write signal directly to the JSON file ---
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current_signals = []
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try:
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px
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from fastapi import FastAPI, Request
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from fastapi.responses import FileResponse, HTMLResponse
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from fastapi.staticfiles import Static with open(SIGNALS_FILE, 'r') as f:
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current_signals = json.loadFiles
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from .price_fetcher import PriceFetcher
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from .arbitrage_analyzer import ArbitrageAnalyzer
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OPPORTUNITY_THRESHOLD = 0.0015
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SIGNALS_FILE = "signals.json"
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@asynccontext(f)
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except (FileNotFoundError, json.JSONDecodeError):
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pass # File doesn't existmanager
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async def lifespan(app: FastAPI):
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# Clear the log on startup for a fresh session
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if os yet or is empty
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current_signals.insert(0, signal) # Prepend new signal
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with open(SIGNALS_FILE, 'w') as f:
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json.dump(current_signals, f)
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print(f"β
Signal LOGGED for {asset}: {signal['spread_pct']:.3f}%")
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except Exception as e:
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print(f"β ERROR in engine loop: {e}")
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await asyncio.sleep(15)
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# ---
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entire table body."""
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try:
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with open(SIGNALS_FILE, 'r') as f: arbitrage_task = asyncio.create_task(
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run_arbitrage_detector(app.state
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signals = json.load(f)
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except (FileNotFoundError, json.JSONDecodeError):
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signals.price_fetcher, app.state.arbitrage_analyzer)
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)
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print(" = []
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if not signals:
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return HTMLResponse('<tr id="placeholder-row"><td colspan="7π Sentinel Arbitrage Engine v15.0 (File-Based) started.")
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yield
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" style="text-align:center;">Monitoring for arbitrage opportunities...</td></tr>')
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except asyncio.CancelledError: print("Engine shut down gracefully.")
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async def run_arbitrage_detector(price = []
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total_profit = 0
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for s in signals:
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is_pyth__fetcher, analyzer):
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"""The core engine loop. Detects opportunities and writes them to a file."""
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cheaper = s['pyth_price'] < s['chainlink_price']
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profit = abs( while True:
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try:
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await price_fetcher.update_prices_async()
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s['chainlink_price'] - s['pyth_price'])
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total_profit += profit * (all_prices = price_fetcher.get_all_prices()
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for asset, prices in all_prices.items():
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pyth_price = prices.get("pyth")
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chainlink_1 - 0.002) # Assume 0.2% total fees
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table_rows_html.append(f"""
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<tr>
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<td>{datetime.fromisoformat(s['timestamp']).strftime('%Hprice = prices.get("chainlink_agg")
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if pyth_price and chainlink_:%M:%S')}</td>
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<td><strong>{s['asset']}/USD</strong></td>
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<td><spanprice and pyth_price > 0:
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spread = abs(pyth_price - chainlink_ class="{'buy' if is_pyth_cheaper else 'sell'}">${s["pyth_priceprice) / chainlink_price
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if spread > OPPORTUNITY_THRESHOLD:
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opportunity = {
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"]:,.2f}</span></td>
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<td><span class="{'sell' if is_pyth_che"asset": asset, "pyth_price": pyth_price,
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"chainlink_price": chainlink_price, "spread_pct": spread * 100
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}
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briefing = await analyzer.get_alpha_briefing(asset, opportunity)
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if briefing:
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signal = {**opportunity, **briefing, "timestamp": datetime.now(timezone.utc).isoformat()}
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aper else 'buy'}">${s["chainlink_price"]:,.2f}</span></td>
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<td><strong # --- THE FIX: Write signal directly to the JSON file ---
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current_signals = []
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if class="buy">{s['spread_pct']:.3f}%</strong></td>
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<td><span class="risk-{s.get('risk', 'low').lower()}">{s.get('risk', 'N/A')} os.path.exists(SIGNALS_FILE):
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with open(SIGNALS_FILE, 'r')</span></td>
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<td>{s.get('strategy', 'N/A')}</td>
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</tr>
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""") as f:
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try:
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current_signals = json.load(f)
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profit_html = f'<span id="pnl-ticker" hx-swap-oob="except json.JSONDecodeError:
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pass # File might be empty or corrupt
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current_signals.true">Simulated P/L: <span style="color: #34D399;">${totalinsert(0, signal) # Prepend new signal
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with open(SIGNALS_FILE, '_profit:,.2f}</span></span>'
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return HTMLResponse(profit_html + "".join(table_w') as f:
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json.dump(current_signals, f)
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print(f"β
Signal LOGGED for {asset}: {signal['spread_pct']:.3f}%")
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exceptrows_html))
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# This single mount point serves index.html for the root path "/"
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app.mount("/", Exception as e:
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print(f"β ERROR in engine loop: {e}")
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"""
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Sentinel Arbitrage Engine - v15.0 OMEGA (Socket.IO Perfected)
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The definitive, money-spinning engine. This version uses a perfectly
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configured Socket.IO server to push real-time, multi-asset arbitrage
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signals directly to a dynamic frontend. This is the final architecture.
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"""
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import asyncio
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import os
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import json
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import time
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from datetime import datetime, timezone
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import httpx
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import socketio
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from fastapi import FastAPI
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from fastapi.staticfiles import StaticFiles
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from .price_fetcher import PriceFetcher
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from .arbitrage_analyzer import ArbitrageAnalyzer
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OPPORTUNITY_THRESHOLD = 0.0015
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# --- Socket.IO Server Setup ---
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# We create the server instance that will manage all real-time communication.
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sio = socketio.AsyncServer(async_mode='asgi', cors_allowed_origins='*')
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# --- FastAPI App Setup ---
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# The FastAPI app is now simpler. It only serves the static files.
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app = FastAPI()
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app.mount("/", StaticFiles(directory="static", html=True), name="static")
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# --- Background Engine ---
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async def run_arbitrage_detector(price_fetcher, analyzer):
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"""The core engine loop. Detects opportunities and emits them via Socket.IO."""
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while True:
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try:
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await price_fetcher.update_prices_async()
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all_prices = price_fetcher.get_all_prices()
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for asset, prices in all_prices.items():
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pyth_price = prices.get("pyth")
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chainlink_price = prices.get("chainlink_agg")
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if pyth_price and chainlink_price and pyth_price > 0:
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spread = abs(pyth_price - chainlink_price) / chainlink_price
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if spread > OPPORTUNITY_THRESHOLD:
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current_time = time.time()
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# Simple throttle to avoid spamming Gemini for the same opportunity
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if not hasattr(analyzer, 'last_call') or current_time - analyzer.last_call.get(asset, 0) > 60:
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analyzer.last_call = getattr(analyzer, 'last_call', {})
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analyzer.last_call[asset] = current_time
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opportunity = {
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"asset": asset, "pyth_price": pyth_price,
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"chainlink_price": chainlink_price, "spread_pct": spread * 100
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}
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print(f"β‘οΈ Dislocation for {asset}: {opportunity['spread_pct']:.3f}%")
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briefing = await analyzer.get_alpha_briefing(asset, opportunity)
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if briefing:
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signal = {**opportunity, **briefing, "timestamp": datetime.now(timezone.utc).isoformat()}
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await sio.emit('new_signal', signal)
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print(f"β
Signal Emitted for {asset}: {signal['strategy']}")
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except Exception as e:
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print(f"β ERROR in engine loop: {e}")
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await asyncio.sleep(15)
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# --- Socket.IO Lifespan Events ---
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# This is the CORRECT way to manage background tasks with python-socketio.
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@sio.on('connect')
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async def connect(sid, environ):
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print(f"β
Client connected: {sid}")
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# Start the engine only when the first user connects.
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if sio.background_task is None:
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print("π First client connected. Starting Sentinel Engine...")
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price_fetcher = PriceFetcher(httpx.AsyncClient())
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arbitrage_analyzer = ArbitrageAnalyzer(httpx.AsyncClient())
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sio.background_task = sio.start_background_task(
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run_arbitrage_detector, price_fetcher, arbitrage_analyzer
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)
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@sio.on('disconnect')
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def disconnect(sid):
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print(f"π₯ Client disconnected: {sid}")
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# --- Final ASGI App ---
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# We wrap the FastAPI app (for static files) and the Socket.IO app together.
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# The Socket.IO server is the primary application.
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combined_app = socketio.ASGIApp(sio, other_asgi_app=app)
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