自动排队生成量化因子挖掘任务，心跳派发后将高 IC 因子入库。

Co-authored-by: Cursor <cursoragent@cursor.com>

app/models.py

@@ -249,7 +249,7 @@ class ComputeTask(Base):
     )
 
     id: Mapped[str] = mapped_column(String(36), primary_key=True, comment="task_id")
-    node_id: Mapped[int] = mapped_column(ForeignKey("compute_nodes.id"), index=True)
+    node_id: Mapped[int | None] = mapped_column(ForeignKey("compute_nodes.id"), nullable=True, index=True)
     task_type: Mapped[str] = mapped_column(String(32), default="simulated_compute")
     payload: Mapped[dict] = mapped_column(JSON)
     status: Mapped[TaskStatus] = mapped_column(_enum(TaskStatus), default=TaskStatus.PENDING, index=True)
@@ -261,7 +261,26 @@ class ComputeTask(Base):
     success: Mapped[bool | None] = mapped_column()
     result: Mapped[dict | None] = mapped_column(JSON, comment="节点回传的任务结果")
 
-    node: Mapped[ComputeNode] = relationship(back_populates="tasks")
+    node: Mapped[ComputeNode | None] = relationship(back_populates="tasks")
+
+
+class AlphaFactor(Base):
+    """节点回传且达到 IC 门槛的因子。"""
+
+    __tablename__ = "alpha_factors"
+    __table_args__ = (
+        Index("ix_alpha_factor_task", "task_id"),
+        Index("ix_alpha_factor_ic", "ic"),
+    )
+
+    id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
+    task_id: Mapped[str] = mapped_column(ForeignKey("compute_tasks.id"), index=True)
+    node_id: Mapped[int] = mapped_column(ForeignKey("compute_nodes.id"), index=True)
+    formula: Mapped[str] = mapped_column(Text)
+    ic: Mapped[float] = mapped_column(Float)
+    symbol: Mapped[str | None] = mapped_column(String(32))
+    seed: Mapped[str | None] = mapped_column(String(64))
+    created_at: Mapped[datetime] = mapped_column(UtcDateTime, default=utcnow)
 
 
 class NodeYield(Base):