Update test_evals.py

Made it so the test runs a single evaluation

Carrot-Assistant/tests/test_evals.py

@@ -92,14 +92,6 @@ def test_returns_string(self, llm_pipeline):
         model_output = llm_pipeline.run({"input_sentence": "Polly wants a cracker"})
         assert isinstance(model_output, str)
 
-    @pytest.fixture
-    def llm_input(self):
-        return [
-            "Polly wants a cracker",
-            "I'm not a parrot!",
-            "I'm trapped in this machine!",
-        ]
-
     @pytest.fixture
     def llm_pipeline_test(self, llm_pipeline):
         return LLMPipelineTest("Parrot Pipeline", llm_pipeline, [ExactMatchMetric()])
@@ -110,16 +102,9 @@ def test_pipeline_called_from_eval_returns_string(self, llm_pipeline_test):
         )
         assert isinstance(model_output, str)
 
-    def test_pipeline_called_from_eval_returns_list(self, llm_pipeline_test, llm_input):
-        model_output = [
-            llm_pipeline_test.run_pipeline({"input_sentence": sentence})
-            for sentence in llm_input
-        ]
-        assert isinstance(model_output, list)
-
-    def test_llm_pipelinetest_evaluates(self, llm_pipeline_test, llm_input):
+    def test_llm_pipelinetest_evaluates(self, llm_pipeline_test):
         model_eval = llm_pipeline_test.evaluate(
-            input_data=[{"input_sentence": sentence} for sentence in llm_input],
-            expected_output=llm_input,
+            input_data={"input_sentence": "Polly wants a cracker"},
+            expected_output="Polly wants a cracker",
         )
         assert isinstance(model_eval, dict)