Update app.py

app.py

@@ -2,15 +2,12 @@ import os
 import time
 import logging
 import traceback
-from datetime import datetime
 
 import gradio as gr
 import pandas as pd
 import numpy as np
-import joblib
 import requests
-
-from binance.client import Client
+import joblib
 
 from sklearn.preprocessing import MinMaxScaler
 from sklearn.model_selection import TimeSeriesSplit
@@ -31,27 +28,19 @@ SYMBOLS = [
     "BNBUSDT",
     "XRPUSDT",
     "DOGEUSDT",
-    "AVAXUSDT",
-    "LINKUSDT",
 ]
 
 WINDOW = 20
 
 MODEL_DIR = "models"
 DATA_DIR = "data"
-LOG_DIR = "logs"
 
 os.makedirs(MODEL_DIR, exist_ok=True)
 os.makedirs(DATA_DIR, exist_ok=True)
-os.makedirs(LOG_DIR, exist_ok=True)
-
-BOT_TOKEN = "YOUR_BOT_TOKEN"
-CHAT_ID = "YOUR_CHAT_ID"
 
 CACHE_SECONDS = 60
 
 LAST_DOWNLOAD = {}
-LAST_SIGNALS = {}
 LAST_RETRAIN = 0
 
 
@@ -64,13 +53,6 @@ logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger("crypto_ai")
 
 
-# ============================================================
-# BINANCE CLIENT
-# ============================================================
-
-client = Client()
-
-
 # ============================================================
 # PATHS
 # ============================================================
@@ -99,36 +81,6 @@ def data_path(symbol):
     )
 
 
-# ============================================================
-# TELEGRAM
-# ============================================================
-
-def send_telegram(message):
-
-    try:
-
-        if "YOUR_BOT_TOKEN" in BOT_TOKEN:
-            return
-
-        url = (
-            f"https://api.telegram.org/"
-            f"bot{BOT_TOKEN}/sendMessage"
-        )
-
-        requests.post(
-            url,
-            data={
-                "chat_id": CHAT_ID,
-                "text": message
-            },
-            timeout=10
-        )
-
-    except Exception as e:
-
-        logger.warning(e)
-
-
 # ============================================================
 # DOWNLOAD BINANCE DATA
 # ============================================================
@@ -157,21 +109,33 @@ def safe_download(symbol):
                     parse_dates=True
                 )
 
-                return df, True
+                return df
 
         # ============================================
-        # DOWNLOAD
+        # BINANCE PUBLIC API
         # ============================================
 
-        klines = client.get_klines(
-            symbol=symbol,
-            interval=Client.KLINE_INTERVAL_1HOUR,
-            limit=1000
+        url = (
+            "https://api.binance.com/api/v3/klines"
+        )
+
+        params = {
+            "symbol": symbol,
+            "interval": "1h",
+            "limit": 1000
+        }
+
+        response = requests.get(
+            url,
+            params=params,
+            timeout=20
         )
 
+        data = response.json()
+
         rows = []
 
-        for k in klines:
+        for k in data:
 
             rows.append({
                 "time": pd.to_datetime(
@@ -193,13 +157,11 @@ def safe_download(symbol):
 
         LAST_DOWNLOAD[symbol] = now
 
-        return df, True
+        return df
 
     except Exception as e:
 
-        logger.warning(
-            f"{symbol} download failed: {e}"
-        )
+        logger.warning(e)
 
     # ============================================
     # FALLBACK CACHE
@@ -219,13 +181,13 @@ def safe_download(symbol):
                 parse_dates=True
             )
 
-            return df, False
+            return df
 
     except Exception as e:
 
         logger.warning(e)
 
-    return None, False
+    return None
 
 
 # ============================================================
@@ -234,7 +196,7 @@ def safe_download(symbol):
 
 def fetch_and_prepare(symbol):
 
-    df, is_real = safe_download(symbol)
+    df = safe_download(symbol)
 
     if df is None:
 
@@ -537,7 +499,7 @@ def train_all():
 
             run_train(symbol)
 
-            time.sleep(0.5)
+            time.sleep(1)
 
         except Exception as e:
 
@@ -693,30 +655,6 @@ def run_predict(symbol):
         signal
     )
 
-    previous = LAST_SIGNALS.get(symbol)
-
-    if previous != signal:
-
-        LAST_SIGNALS[symbol] = signal
-
-        send_telegram(
-            f"""
-🚨 NEW SIGNAL
-
-PAIR: {symbol}
-
-SIGNAL: {signal}
-
-CONFIDENCE: {confidence:.2f}%
-
-ENTRY: {levels['entry']}
-TP1: {levels['tp1']}
-TP2: {levels['tp2']}
-TP3: {levels['tp3']}
-SL: {levels['sl']}
-"""
-        )
-
     return {
         "Pair": symbol,
         "Signal": signal,
@@ -761,7 +699,7 @@ def realtime_scan():
 
         try:
 
-            time.sleep(0.3)
+            time.sleep(0.5)
 
             result = run_predict(symbol)