Update app.py

app.py

@@ -1,4 +1,3 @@
-%%writefile app.py
 import streamlit as st
 import ccxt
 import pandas as pd
@@ -19,7 +18,7 @@ def get_live_usdt_dominance():
     except Exception as e:
         return 0.0, 0.0
 
-# --- 1. Kaggle Heavy Compute Backend ---
+# --- 1. Cloud Compute Backend ---
 @st.cache_resource
 def train_spot_model(symbol):
     exchange = ccxt.bitget()
@@ -72,7 +71,7 @@ def train_spot_model(symbol):
 def analyze_live_market(symbol, model, features):
     exchange = ccxt.bitget()
     
-    ohlcv = exchange.fetch_ohlcv(symbol, '1h', limit=100) # Pulled more candles for a better chart view
+    ohlcv = exchange.fetch_ohlcv(symbol, '1h', limit=100) 
     df = pd.DataFrame(ohlcv, columns=['timestamp', 'open', 'high', 'low', 'close', 'volume'])
     df['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms')
     
@@ -102,12 +101,11 @@ def analyze_live_market(symbol, model, features):
     invalidation_level = limit_entry * 0.99
     take_profit = limit_entry * 1.02
     
-    # Return the dataframe as well so we can plot it
     return current_price, confidence, limit_entry, invalidation_level, take_profit, market_state, live_imbalance, df
 
 # --- 3. Streamlit UI ---
 st.set_page_config(page_title="AI Spot Sniper", layout="wide")
-st.title("🎯 Kaggle AI Spot Sniper Terminal")
+st.title("🎯 AI Spot Sniper Terminal")
 
 TOP_50_PAIRS = [
     'BTC/USDT', 'ETH/USDT', 'SOL/USDT', 'BNB/USDT', 'XRP/USDT', 'ADA/USDT',