refactor(benchmarks): modularize benchmark system with config-driven execution

mini-nav/benchmarks/tasks/registry.py

@@ -0,0 +1,59 @@
+"""Task registry for benchmark evaluation."""
+
+from typing import Any, Type
+
+from benchmarks.base import BaseBenchmarkTask
+
+# Task registry: maps task type string to task class
+TASK_REGISTRY: dict[str, Type[BaseBenchmarkTask]] = {}
+
+
+class RegisterTask:
+    """Decorator class to register a benchmark task.
+
+    Usage:
+        @register_task("retrieval")
+        class RetrievalTask(BaseBenchmarkTask):
+            ...
+    """
+
+    def __init__(self, task_type: str):
+        """Initialize the decorator with task type.
+
+        Args:
+            task_type: Task type identifier.
+        """
+        self.task_type = task_type
+
+    def __call__(self, cls: type[BaseBenchmarkTask]) -> type[BaseBenchmarkTask]:
+        """Register the decorated class to the task registry.
+
+        Args:
+            cls: The class to be decorated.
+
+        Returns:
+            The unmodified class.
+        """
+        TASK_REGISTRY[self.task_type] = cls
+        return cls
+
+
+def get_task(task_type: str, **kwargs: Any) -> BaseBenchmarkTask:
+    """Get a benchmark task instance by type.
+
+    Args:
+        task_type: Task type identifier.
+        **kwargs: Additional arguments passed to task constructor.
+
+    Returns:
+        Task instance.
+
+    Raises:
+        ValueError: If task type is not registered.
+    """
+    if task_type not in TASK_REGISTRY:
+        available = list(TASK_REGISTRY.keys())
+        raise ValueError(
+            f"Unknown task type: {task_type}. Available tasks: {available}"
+        )
+    return TASK_REGISTRY[task_type](**kwargs)