Upload t5_engine.py

t5_engine.py

@@ -64,7 +64,7 @@ def run_t5_pipeline():
     with open(RULES_FILE, "r") as f:
         rules_list = json.load(f)
         
-    rules_dict = {item['Ticker']: item['Rule'] for item in rules_list if item['Rule']}
+    rules_dict = {item['Ticker']: item for item in rules_list if item['Rule']}
     
     now = datetime.now(IST)
     # Fetch data for the last 5 days to ensure we have yesterday and today
@@ -131,13 +131,14 @@ def run_t5_pipeline():
         features['prev_ret'] = (prev_close - prev_open) / prev_open if prev_open else 0
         
         # Evaluate rule
-        rule = rules_dict.get(ticker)
-        if rule:
-            pred = evaluate_rule(rule, features)
+        rule_item = rules_dict.get(ticker)
+        if rule_item:
+            pred = evaluate_rule(rule_item['Rule'], features)
             predictions[ticker] = {
                 "prediction": "UP" if pred == 1 else ("DOWN" if pred == -1 else "FLAT"),
                 "features": features,
-                "rule_used": rule
+                "rule_used": rule_item['Rule'],
+                "accuracy": round(rule_item.get('Test_Acc', 0.6432) * 100, 2)
             }
         
         time.sleep(0.5) # Rate limiting