From 76790f37b1a7d41ba1442d2d9e9f9ec11da20e38 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Thu, 26 Sep 2024 22:36:36 +0000
Subject: [PATCH] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 evals/metrics/ragas/ragas.py | 12 +++++++-----
 tests/test_ragas.py          |  6 ++----
 2 files changed, 9 insertions(+), 9 deletions(-)

diff --git a/evals/metrics/ragas/ragas.py b/evals/metrics/ragas/ragas.py
index 89cc8b0b..c80ff94e 100644
--- a/evals/metrics/ragas/ragas.py
+++ b/evals/metrics/ragas/ragas.py
@@ -33,7 +33,7 @@ def __init__(
         self.model = model
         self.embeddings = embeddings
         self.metrics = metrics
-        
+
         # self.validated_list = [
         #     "answer_correctness",
         #     "answer_relevancy",
@@ -53,11 +53,12 @@ def measure(self, test_case: Dict):
         try:
             from ragas import evaluate
             from ragas.metrics import ALL_METRICS
-            self.metric_names = [metric.__class__.__name__ for metric in ALL_METRICS] 
-            self.metric_names = [re.sub(r'(?<!^)(?=[A-Z])', '_', name).lower() for name in self.metric_names]
+
+            self.metric_names = [metric.__class__.__name__ for metric in ALL_METRICS]
+            self.metric_names = [re.sub(r"(?<!^)(?=[A-Z])", "_", name).lower() for name in self.metric_names]
             self.metric_names = list(set(self.metric_names))
             # Note - summarization score metric is not working with best open-source LLMs
-            # Note - which is why we are removing it from our offering at the moment. 
+            # Note - which is why we are removing it from our offering at the moment.
             self.metric_names.remove("summarization_score")
             self.metric_instances = {}
             for metric in self.metric_names:
@@ -141,7 +142,7 @@ def measure(self, test_case: Dict):
             "response": "answer",
             "reference": "ground_truth",
             "retrieved_contexts": "contexts",
-            "reference_contexts": "reference_contexts"
+            "reference_contexts": "reference_contexts",
         }
         for metric in self.metrics:
             if hasattr(metric, "_required_columns"):
@@ -149,6 +150,7 @@ def measure(self, test_case: Dict):
                     _required_columns.add(column_map[column])
             elif hasattr(metric, "evaluation_mode"):
                 from ragas.metrics.base import get_required_columns
+
                 for column in get_required_columns(metric.evaluation_mode):
                     _required_columns.add(column)
             else:
diff --git a/tests/test_ragas.py b/tests/test_ragas.py
index c72aa31e..c0412c61 100644
--- a/tests/test_ragas.py
+++ b/tests/test_ragas.py
@@ -30,15 +30,13 @@ def test_ragas(self):
 
         embeddings = HuggingFaceBgeEmbeddings(model_name="BAAI/bge-base-en-v1.5")
 
-        metric = RagasMetric(threshold=0.5, 
-                                model=f"http://{host_ip}:{port}", 
-                                embeddings=embeddings)
+        metric = RagasMetric(threshold=0.5, model=f"http://{host_ip}:{port}", embeddings=embeddings)
         test_case = {
             "question": ["What if these shoes don't fit?"],
             "answer": [actual_output],
             "ground_truth": [expected_output],
             "contexts": [retrieval_context],
-            "reference_contexts": [reference_context]
+            "reference_contexts": [reference_context],
         }
 
         metric.measure(test_case)