Update app.py

app.py

@@ -3,7 +3,6 @@ import numpy as np
 import pandas as pd
 from datetime import datetime
 import random
-import json
 from collections import defaultdict
 import math
 import traceback
@@ -155,7 +154,7 @@ class SequenceAnalyzer:
         
         diffs = [abs(seq1[i] - seq2[i]) / (max(seq1[i], seq2[i]) + 0.1) 
                 for i in range(len(seq1))]
-        avg_diff = np.mean(diffs)
+        avg_diff = np.mean(diffs) if diffs else 1
         return max(0, 1 - avg_diff)
     
     def predict(self, history):
@@ -394,9 +393,6 @@ class EnsemblePredictor:
             confidences = [p.get('confidence', 0.3) for p in predictions.values()]
             avg_confidence = np.mean(confidences) if confidences else 0.3
             
-            # প্যাটার্ন মেমরি বুস্ট (সিম্পলিফাইড)
-            pattern_boost = 0
-            
             # পিঙ্ক সম্ভাবনা
             pink_prob = self.calculate_pink_probability(history, predictions, time_window)
             is_pink_expected = pink_prob > 0.4
@@ -440,7 +436,7 @@ class EnsemblePredictor:
                 'statisticalModel': '📊 স্ট্যাট'
             }
             display_name = model_names.get(name, name)
-            lines.append(f"{display_name}: {pred['prediction']:.2f}x (কনফি: {int(pred['confidence']*100)}%) - {pred.get('analysis', '')[:30]}")
+            lines.append(f"{display_name}: {pred.get('prediction', 1.5):.2f}x (কনফি: {int(pred.get('confidence', 0)*100)}%) - {pred.get('analysis', '')[:30]}")
         return "\n".join(lines)
     
     def get_default_prediction(self):
@@ -481,13 +477,15 @@ class EnsemblePredictor:
             factors.append(time_window['probability'])
         
         # মডেল কনসেনসাস
-        pink_predictions = sum(1 for p in predictions.values() 
-                              if p.get('prediction', 1.5) >= CONFIG["PINK_THRESHOLD"])
-        factors.append(pink_predictions / len(predictions) if predictions else 0)
+        if predictions:
+            pink_predictions = sum(1 for p in predictions.values() 
+                                  if p.get('prediction', 1.5) >= CONFIG["PINK_THRESHOLD"])
+            factors.append(pink_predictions / len(predictions))
         
         # হিস্টোরিক্যাল ফ্যাক্টর
-        recent_pinks = sum(1 for v in history[:20] if v >= CONFIG["PINK_THRESHOLD"])
-        factors.append(min(0.9, recent_pinks / 20 if history else 0))
+        if history:
+            recent_pinks = sum(1 for v in history[:20] if v >= CONFIG["PINK_THRESHOLD"])
+            factors.append(min(0.9, recent_pinks / 20))
         
         return np.mean(factors) if factors else 0.2
     
@@ -579,7 +577,7 @@ class AviatorPredictorApp:
         return self.last_prediction
     
     def get_history_table(self):
-        """হিস্ট্রি টেবিল রিটার্ন করে"""
+        """হিস্ট্রি টেবিল রিটার্ন করে (শুধু ডাটা, কোন বুলিয়ান না)"""
         return [[i+1, f"{val:.2f}x"] for i, val in enumerate(self.history[:50])]
     
     def get_time_status(self):
@@ -658,39 +656,123 @@ class AviatorPredictorApp:
         """
 
 
-# ==================== গ্র্যাডিও ইন্টারফেস ====================
-
-# কাস্টম সিএসএস
+# ==================== কাস্টম সিএসএস ====================
 CUSTOM_CSS = """
+/* ডার্ক মোড বেস */
+.gradio-container {
+    background: #0a0a0f !important;
+    color: #ffffff !important;
+}
 footer {visibility: hidden}
-.active-window { background: linear-gradient(135deg, #ff1493, #ff69b4) !important; color: white !important; }
-.approaching-window { background: linear-gradient(135deg, #ffa726, #ff9800) !important; color: white !important; }
-.waiting-window { background: linear-gradient(135deg, #1a1a2e, #16213e) !important; color: white !important; }
-.pink-text { color: #ff1493 !important; font-weight: bold !important; }
-.confidence-bar { height: 8px; background: #333; border-radius: 4px; overflow: hidden; margin: 5px 0; }
-.confidence-fill { height: 100%; background: linear-gradient(90deg, #00d4ff, #ff1493); transition: width 0.3s; }
-.time-box { text-align: center; padding: 15px; border-radius: 10px; margin-bottom: 20px; transition: all 0.3s; font-weight: 500; }
-.prediction-interval { font-size: 32px; font-weight: 700; text-align: center; margin: 10px 0; }
-.prediction-interval.pink-mode { color: #ff1493; text-shadow: 0 0 10px #ff1493; }
-.interval-lower { color: #00d4ff; }
-.interval-upper { color: #ffa726; }
-.interval-separator { color: white; margin: 0 10px; }
-.model-details { background: rgba(255,255,255,0.1); border-radius: 8px; padding: 10px; margin: 10px 0; font-size: 12px; font-family: monospace; white-space: pre-line; }
-.gradio-container { background: #0a0a0f !important; }
-h1 { text-align: center; margin-bottom: 10px; }
+
+/* ট��ইম বক্স স্টাইল */
+.time-box {
+    text-align: center;
+    padding: 15px;
+    border-radius: 10px;
+    margin-bottom: 20px;
+    transition: all 0.3s;
+    font-weight: 500;
+}
+.active-window {
+    background: linear-gradient(135deg, #ff1493, #ff69b4) !important;
+    color: white !important;
+    box-shadow: 0 0 20px #ff1493;
+}
+.approaching-window {
+    background: linear-gradient(135deg, #ffa726, #ff9800) !important;
+    color: white !important;
+    box-shadow: 0 0 20px #ffa726;
+}
+.waiting-window {
+    background: linear-gradient(135deg, #1a1a2e, #16213e) !important;
+    color: white !important;
+    border: 1px solid #00d4ff;
+}
+
+/* পিঙ্ক টেক্সট */
+.pink-text {
+    color: #ff1493 !important;
+    font-weight: bold !important;
+}
+
+/* কনফিডেন্স বার */
+.confidence-bar {
+    height: 8px;
+    background: #333;
+    border-radius: 4px;
+    overflow: hidden;
+    margin: 5px 0;
+}
+.confidence-fill {
+    height: 100%;
+    background: linear-gradient(90deg, #00d4ff, #ff1493);
+    transition: width 0.3s;
+}
+
+/* প্রেডিকশন ইন্টারভ্যাল */
+.prediction-interval {
+    font-size: 32px;
+    font-weight: 700;
+    text-align: center;
+    margin: 10px 0;
+    padding: 15px;
+    background: rgba(255,255,255,0.05);
+    border-radius: 10px;
+}
+.prediction-interval.pink-mode {
+    color: #ff1493;
+    text-shadow: 0 0 10px #ff1493;
+}
+.interval-lower {
+    color: #00d4ff;
+}
+.interval-upper {
+    color: #ffa726;
+}
+.interval-separator {
+    color: white;
+    margin: 0 10px;
+}
+
+/* টেক্সটবক্স স্টাইল */
+.gr-box {
+    border: 1px solid #333 !important;
+    background: rgba(255,255,255,0.05) !important;
+}
+.gr-box label {
+    color: #00d4ff !important;
+}
+
+/* বাটন স্টাইল */
+.gr-button-primary {
+    background: linear-gradient(135deg, #00d4ff, #0088ff) !important;
+    border: none !important;
+}
+.gr-button-secondary {
+    background: rgba(255,255,255,0.1) !important;
+    border: 1px solid #00d4ff !important;
+}
+
+/* ডাটাফ্রেম */
+.gr-dataframe {
+    background: rgba(255,255,255,0.05) !important;
+}
 """
 
+# ==================== গ্র্যাডিও ইন্টারফেস ====================
+
 # অ্যাপ ইনিশিয়ালাইজ
 app = AviatorPredictorApp()
 app.reset()  # শুরুতেই কিছু ডাটা জেনারেট করে
 
 # গ্র্যাডিও ইন্টারফেস
-with gr.Blocks() as demo:
+with gr.Blocks(css=CUSTOM_CSS) as demo:
     # হেডার
     gr.HTML("""
     <div style="text-align: center; margin-bottom: 20px;">
         <h1 style="color: #00d4ff; font-size: 48px; margin: 0; text-shadow: 0 0 10px #00d4ff;">✈️ AVOLD ML</h1>
-        <p style="color: #888; font-size: 14px;">এনসেম্বল এমএল এভিয়েটর প্রেডিক্টর v2.0</p>
+        <p style="color: #888; font-size: 14px;">এনসেম্বল এমএল এভিয়েটর প্রেডিক্টর v3.0</p>
     </div>
     """)
     
@@ -750,7 +832,7 @@ with gr.Blocks() as demo:
     
     # ---------- আপডেট ফাংশন ----------
     def update_all():
-        """সব ডিসপ্লে আপডেট করে"""
+        """সব ডিসপ্লে আপডেট করে - শুধু ডাটা রিটার্ন করে, কোন বুলিয়ান না"""
         try:
             pred = app.get_prediction()
             history_table = app.get_history_table()
@@ -784,26 +866,31 @@ with gr.Blocks() as demo:
             model_text = pred.get('model_details', 'কোন ডাটা নেই')
             
             return [
-                history_table,
-                time_status,
-                confidence,
-                prediction_html_str,
-                f"{pred.get('prediction', 1.5):.2f}x",
-                pred.get('analysis', 'অ্যানালাইসিস নেই'),
-                decision,
-                pred.get('risk', 'মাঝারি ⚖️'),
-                pink_prob_text,
-                model_text
+                history_table,      # dataframe
+                time_status,        # html
+                confidence,         # html
+                prediction_html_str, # html
+                f"{pred.get('prediction', 1.5):.2f}x",  # textbox
+                pred.get('analysis', 'অ্যানালাইসিস নেই'),  # textbox
+                decision,           # textbox
+                pred.get('risk', 'মাঝারি ⚖️'),  # textbox
+                pink_prob_text,     # textbox
+                model_text          # textbox
             ]
         except Exception as e:
             print(f"Update error: {e}")
             traceback.print_exc()
             # এরর হলে ডিফল্ট ভ্যালু রিটার্ন
+            default_table = [[1, "1.00x"]]
+            default_time = '<div class="time-box waiting-window"><div style="font-size:24px;">--:--:--</div><div>আপডেট এরর</div></div>'
+            default_conf = '<div>এমএল কনফিডেন্স: 0%</div>'
+            default_pred = '<div class="prediction-interval"><span class="interval-lower">1.30x</span><span class="interval-separator">—</span><span class="interval-upper">1.70x</span></div>'
+            
             return [
-                [[1, "1.00x"]],
-                app.get_time_status(),
-                app.get_confidence_html(),
-                '<div class="prediction-interval"><span class="interval-lower">1.30x</span><span class="interval-separator">—</span><span class="interval-upper">1.70x</span></div>',
+                default_table,
+                default_time,
+                default_conf,
+                default_pred,
                 "1.50x",
                 "আপডেট এরর",
                 "ছোট 🎯",
@@ -814,7 +901,10 @@ with gr.Blocks() as demo:
     
     # অ্যাড বাটন ক্লিক
     add_btn.click(
-        fn=lambda x: (app.add_round(x),) + tuple(update_all()),
+        fn=lambda x: (
+            app.add_round(x),  # এইটা True রিটার্ন করে, কিন্তু আমরা ইউজ করছি না
+            *update_all()       # শুধু আপডেট ডাটা রিটার্ন করছি
+        )[-10:],  # শুধু শেষ ১০টি ভ্যালু নিচ্ছি (ডাটাফ্রেম থেকে শুরু)
         inputs=[new_multiplier],
         outputs=[rounds_table, time_html, confidence_html, prediction_html, 
                  expected_out, analysis_out, decision_out, risk_out, 
@@ -823,7 +913,10 @@ with gr.Blocks() as demo:
     
     # রিসেট বাটন ক্লিক
     reset_btn.click(
-        fn=lambda: (app.reset(),) + tuple(update_all()),
+        fn=lambda: (
+            app.reset(),
+            *update_all()
+        )[-10:],
         outputs=[rounds_table, time_html, confidence_html, prediction_html,
                  expected_out, analysis_out, decision_out, risk_out,
                  pink_prob_out, model_details]
@@ -831,7 +924,7 @@ with gr.Blocks() as demo:
     
     # ইনিশিয়াল লোড
     demo.load(
-        fn=lambda: update_all(),
+        fn=update_all,
         outputs=[rounds_table, time_html, confidence_html, prediction_html,
                  expected_out, analysis_out, decision_out, risk_out,
                  pink_prob_out, model_details]
@@ -842,6 +935,5 @@ if __name__ == "__main__":
     demo.launch(
         server_name="0.0.0.0",
         server_port=7860,
-        theme='dark',
-        css=CUSTOM_CSS
+        share=False
     )