Update llmeval.py

llmeval.py

@@ -214,7 +214,15 @@ class LLM_as_Evaluator():
             "unit_coherence": SYSTEM_PROMPT_FOR_TRIAD_COHERENCE
         }
         
-        evaluation_responses=[]
+        #evaluation_responses=[]
+        data={
+                "promptversion":promptversion,
+                "biological_context_alignment":"",
+                "contextual_relevance_alignment":"",
+                "unit_coherence":"",
+                "response_specificity":""
+        }
+        
         for metric in metrics:
             system_prompt = prompt_map[metric]
 
@@ -228,25 +236,8 @@ class LLM_as_Evaluator():
             ]
     
             evaluation_response = self.___engine_core(messages=messages)
-            evaluation_responses.append({metric: evaluation_response})
-
-  
-        
-        data={
-                "promptversion":promptversion,
-                "biological_context_alignment":"",
-                "contextual_relevance_alignment":"",
-                "unit_coherence":"",
-                "response_specificity":""
-        }
-            
-        for resp in evaluation_responses:
-                
-            data["biological_context_alignment"]=resp["biological_context_alignment"]
-            data["contextual_relevance_alignment"]=resp["contextual_relevance_alignment"]
-            data["unit_coherence"]=resp["unit_coherence"]
-            data["response_specificity"]=resp["response_specificity"]
-                
+            data[metric]=evaluation_response
+         
                 
         de.Update(data=data)