Fix Dockerfile build issue

autorag/evaluation/metric/util.py

@@ -0,0 +1,88 @@
+import functools
+from typing import List
+
+import numpy as np
+
+from autorag.schema.metricinput import MetricInput
+from autorag.utils.util import convert_inputs_to_list
+
+
+def calculate_cosine_similarity(a, b):
+	dot_product = np.dot(a, b)
+	norm_a = np.linalg.norm(a)
+	norm_b = np.linalg.norm(b)
+	similarity = dot_product / (norm_a * norm_b)
+	return similarity
+
+
+def calculate_l2_distance(a, b):
+	return np.linalg.norm(a - b)
+
+
+def calculate_inner_product(a, b):
+	return np.dot(a, b)
+
+
+def autorag_metric(fields_to_check: List[str]):
+	def decorator_autorag_metric(func):
+		@functools.wraps(func)
+		@convert_inputs_to_list
+		def wrapper(metric_inputs: List[MetricInput], **kwargs) -> List[float]:
+			"""
+			Use 'for loop' to run each metric input.
+			Put the single metric input into the metric function.
+
+			:param metric_inputs: A list MetricInput schema for AutoRAG metric.
+			:param kwargs: The additional arguments for metric function.
+			:return: A list of computed metric scores.
+			"""
+			results = []
+			for metric_input in metric_inputs:
+				if metric_input.is_fields_notnone(fields_to_check=fields_to_check):
+					results.append(func(metric_input, **kwargs))
+				else:
+					results.append(None)
+			return results
+
+		return wrapper
+
+	return decorator_autorag_metric
+
+
+def autorag_metric_loop(fields_to_check: List[str]):
+	def decorator_autorag_generation_metric(func):
+		@functools.wraps(func)
+		@convert_inputs_to_list
+		def wrapper(metric_inputs: List[MetricInput], **kwargs) -> List[float]:
+			"""
+			Put the list of metric inputs into the metric function.
+
+			:param metric_inputs: A list MetricInput schema for AutoRAG metric.
+			:param kwargs: The additional arguments for metric function.
+			:return: A list of computed metric scores.
+			"""
+			bool_list = [
+				metric_input.is_fields_notnone(fields_to_check=fields_to_check)
+				for metric_input in metric_inputs
+			]
+			valid_inputs = [
+				metric_input
+				for metric_input, is_valid in zip(metric_inputs, bool_list)
+				if is_valid
+			]
+
+			results = [None] * len(metric_inputs)
+			if valid_inputs:
+				processed_valid = func(valid_inputs, **kwargs)
+
+				valid_index = 0
+				for i, is_valid in enumerate(bool_list):
+					if is_valid:
+						results[i] = processed_valid[valid_index]
+						valid_index += 1
+
+			return results
+
+		return wrapper
+
+	return decorator_autorag_generation_metric