feat(bias): implement data models and storage for tool weighting and bias profiles

src/models.py

@@ -368,18 +368,70 @@ class Preset:
   )
 
 @dataclass
-class ToolPreset:
+class Tool:
  name: str
- categories: Dict[str, Dict[str, Any]]
+ approval: str = 'auto'
+ weight: int = 3
+ parameter_bias: Dict[str, str] = field(default_factory=dict)
 
  def to_dict(self) -> Dict[str, Any]:
   return {
-   "categories": self.categories,
+   "name": self.name,
+   "approval": self.approval,
+   "weight": self.weight,
+   "parameter_bias": self.parameter_bias,
+  }
+
+ @classmethod
+ def from_dict(cls, data: Dict[str, Any]) -> "Tool":
+  return cls(
+   name=data["name"],
+   approval=data.get("approval", "auto"),
+   weight=data.get("weight", 3),
+   parameter_bias=data.get("parameter_bias", {}),
+  )
+
+@dataclass
+class ToolPreset:
+ name: str
+ categories: Dict[str, List[Union[Tool, Any]]]
+
+ def to_dict(self) -> Dict[str, Any]:
+  serialized_categories = {}
+  for cat, tools in self.categories.items():
+   serialized_categories[cat] = [t.to_dict() if isinstance(t, Tool) else t for t in tools]
+  return {
+   "categories": serialized_categories,
   }
 
  @classmethod
  def from_dict(cls, name: str, data: Dict[str, Any]) -> "ToolPreset":
+  raw_categories = data.get("categories", {})
+  parsed_categories = {}
+  for cat, tools in raw_categories.items():
+   parsed_categories[cat] = [Tool.from_dict(t) if isinstance(t, dict) else t for t in tools]
   return cls(
    name=name,
-   categories=data.get("categories", {}),
+   categories=parsed_categories,
+  )
+
+@dataclass
+class BiasProfile:
+ name: str
+ tool_weights: Dict[str, int] = field(default_factory=dict)
+ category_multipliers: Dict[str, float] = field(default_factory=dict)
+
+ def to_dict(self) -> Dict[str, Any]:
+  return {
+   "name": self.name,
+   "tool_weights": self.tool_weights,
+   "category_multipliers": self.category_multipliers,
+  }
+
+ @classmethod
+ def from_dict(cls, data: Dict[str, Any]) -> "BiasProfile":
+  return cls(
+   name=data["name"],
+   tool_weights=data.get("tool_weights", {}),
+   category_multipliers=data.get("category_multipliers", {}),
   )