wip symbols tidy up

.kiro/specs/multi-modal-trading-system/design.md

@@ -74,6 +74,16 @@ Based on the existing implementation in `core/data_provider.py`, we'll enhance i
    - 1,5,15 and 60s MA of the COB imbalance counting +- 5 COB buckets
 - ***OUTPUTS***: suggested trade action (BUY/SELL)
 
+# Standardized input for all models:
+{
+    'primary_symbol': 'ETH/USDT',
+    'reference_symbol': 'BTC/USDT', 
+    'eth_data': {'ETH_1s': df, 'ETH_1m': df, 'ETH_1h': df, 'ETH_1d': df},
+    'btc_data': {'BTC_1s': df},
+    'current_prices': {'ETH': price, 'BTC': price},
+    'data_completeness': {...}
+}
+
 ### 2. CNN Model
 
 The CNN Model is responsible for analyzing patterns in market data and predicting pivot points across multiple timeframes.

.kiro/specs/multi-modal-trading-system/tasks.md

@@ -197,7 +197,8 @@
   - Ensure validation occurs before any model inference
   - _Requirements: 9.1, 9.4_
 
-- [ ] 5.2. Implement persistent inference history storage
+- [x] 5.2. Implement persistent inference history storage
+
   - Create InferenceHistoryStore class for persistent storage
   - Store complete input data packages with each prediction
   - Include timestamp, symbol, input features, prediction outputs, confidence scores