merge annotate /ANNOTATE/core into /core.

fix chart updates

core/data_models.py

@@ -758,4 +758,62 @@ def create_model_output(model_type: str, model_name: str, symbol: str,
         predictions=predictions,
         hidden_states=hidden_states or {},
         metadata=metadata or {}
-    )
+    )
+
+
+class InferenceFrameReference:
+    """
+    Reference to inference data stored in DuckDB with human-readable prediction outputs.
+    No copying - just store timestamp ranges and query when needed.
+    
+    Moved from ANNOTATE/core to main core for unified architecture.
+    """
+    inference_id: str  # Unique ID for this inference
+    symbol: str
+    timeframe: str
+    prediction_timestamp: datetime  # When prediction was made
+    target_timestamp: Optional[datetime] = None  # When result will be available (for candles)
+    
+    # Reference to data in DuckDB (timestamp range)
+    data_range_start: datetime  # Start of 600-candle window
+    data_range_end: datetime  # End of 600-candle window
+    
+    # Normalization parameters (small, can be stored)
+    norm_params: Dict[str, Dict[str, float]] = field(default_factory=dict)
+    
+    # ENHANCED: Human-readable prediction outputs
+    predicted_action: Optional[str] = None  # 'BUY', 'SELL', 'HOLD'
+    predicted_candle: Optional[Dict[str, List[float]]] = None  # {timeframe: [O,H,L,C,V]}
+    predicted_price: Optional[float] = None  # Main predicted price
+    confidence: float = 0.0
+    
+    # Model metadata for decision making
+    model_type: str = 'transformer'  # 'transformer', 'cnn', 'dqn'
+    prediction_steps: int = 1  # Number of steps predicted ahead
+    
+    # Training status
+    trained: bool = False
+    training_timestamp: Optional[datetime] = None
+    training_loss: Optional[float] = None
+    training_accuracy: Optional[float] = None
+    
+    # Actual results (filled when candle completes)
+    actual_candle: Optional[List[float]] = None  # [O,H,L,C,V]
+    actual_price: Optional[float] = None
+    prediction_error: Optional[float] = None  # |predicted - actual|
+    direction_correct: Optional[bool] = None  # Did we predict direction correctly?
+
+@dataclass
+class TrainingSession:
+    """Real training session tracking - moved from ANNOTATE/core"""
+    training_id: str
+    symbol: str
+    timeframe: str
+    model_type: str
+    start_time: datetime
+    end_time: Optional[datetime] = None
+    status: str = 'running'  # 'running', 'completed', 'failed'
+    loss: Optional[float] = None
+    accuracy: Optional[float] = None
+    samples_trained: int = 0
+    error_message: Optional[str] = None