Added TokenCountEstimatorMetric

pkgs/community/setup.py

@@ -64,7 +64,9 @@
             "tf-keras",
             "pinecone",
             "neo4j",
-            "pinecone"
+            "tiktoken"
+
+
         ]
     },
     classifiers=[

pkgs/community/swarmauri_community/metrics/concrete/TokenCountEstimatorMetric.py

@@ -0,0 +1,28 @@
+from typing import Any, Literal
+import tiktoken
+from swarmauri.metrics.base.MetricBase import MetricBase
+from swarmauri.metrics.base.MetricCalculateMixin import MetricCalculateMixin
+
+class TokenCountEstimatorMetric(MetricBase, MetricCalculateMixin):
+    """
+    A metric class to estimate the number of tokens in a given text.
+    """
+    unit: str = "tokens"
+    type: Literal['TokenCountEstimatorMetric'] = 'TokenCountEstimatorMetric'
+
+    def calculate(self, text: str,encoding='cl100k_base') -> int:
+        """
+        Calculate the number of tokens in the given text.
+        Args:
+            text (str): The input text to calculate token count for.
+        Returns:
+            int: The number of tokens in the text, or None if an error occurs.
+        """
+        try:
+            encoding = tiktoken.get_encoding(encoding)
+        except ValueError as e:
+            print(f"Error: {e}")
+            return None
+
+        tokens = encoding.encode(text)
+        return len(tokens)

pkgs/community/tests/unit/metrics/TokenCountEstimatorMetric_unit_test.py

@@ -0,0 +1,32 @@
+import pytest
+from swarmauri.metrics.concrete.TokenCountEstimatorMetric import TokenCountEstimatorMetric as Metric
+
+@pytest.mark.unit
+def test_ubc_resource():
+    def test():
+        assert Metric().resource == 'Metric'
+    test()
+
+@pytest.mark.unit
+def test_ubc_type():
+    metric = Metric()
+    assert metric.type == 'TokenCountEstimatorMetric'
+
+@pytest.mark.unit
+def test_serialization():
+    metric = Metric()
+    assert metric.id == Metric.model_validate_json(metric.model_dump_json()).id
+
+
+@pytest.mark.unit
+def test_metric_value():
+	def test():
+		assert Metric().calculate("Lorem ipsum odor amet, consectetuer adipiscing elit.") == 11
+	test()
+
+
+@pytest.mark.unit
+def test_metric_unit():
+	def test():
+		assert Metric().unit == "tokens"
+	test()