Update llmeval.py

llmeval.py

@@ -194,32 +194,93 @@ class LLM_as_Evaluator():
 
     def Observation_LLM_Evaluator(self,promptversion):
         
-        metrics=["biological_context_alignment","contextual_relevance_alignment","coherence","response_specificity"]
+        metrics=["biological_context_alignment","contextual_relevance_alignment","response_specificity","unit_coherence"]
         
         data_to_evaluate=de.GetData(promptversion)
-        import time
         
-        for metric in metrics:
         
-            messages =[
-
-                {"role":"system","content":SYSTEM_FOR_BIO_CONTEXT_EVAL_FOR_OBSERVATION},
-                {"role":"user","content":f"""
-                    Prompt :{data_to_evaluate["prompt"]}
-                    Context :{data_to_evaluate["context"]}
-                    Agent's Response : {data_to_evaluate["response"]}
-                    """}
-            ]
-            evaluation_response=self.___engine_core(messages=messages)
+        evaluation_responses=[]
+
+        for metric in metrics:
         
+            match metric:
+                case "biological_context_alignment":
+                    
+                    messages =[
+
+                        {"role":"system","content":SYSTEM_FOR_BIO_CONTEXT_ALIGNMENT},
+                        {"role":"user","content":f"""
+                        Prompt :{data_to_evaluate["prompt"]}
+                        Context :{data_to_evaluate["context"]}
+                        Agent's Response : {data_to_evaluate["response"]}
+                        """}
+                    ]
+                    evaluation_response=self.___engine_core(messages=messages)
+                    evaluation_responses.append({"bio_context_alignment":evaluation_response})
+                
+                case "contextual_relevance_alignment":
+                    
+                    messages =[
+
+                        {"role":"system","content":SYSTEM_FOR_CONTEXTUAL_RELEVANCE_ALIGNMENT},
+                        {"role":"user","content":f"""
+                        Prompt :{data_to_evaluate["prompt"]}
+                        Context :{data_to_evaluate["context"]}
+                        Agent's Response : {data_to_evaluate["response"]}
+                        """}
+                    ]
+                    evaluation_response=self.___engine_core(messages=messages)
+                    evaluation_responses.append({"contextual_relevance_alignment":evaluation_response})
+            
+
+                case "response_specificity":
+                    
+                    messages =[
+
+                        {"role":"system","content":SYSTEM_PROMPT_FOR_RESPONSE_SPECIFICITY},
+                        {"role":"user","content":f"""
+                        Prompt :{data_to_evaluate["prompt"]}
+                        Context :{data_to_evaluate["context"]}
+                        Agent's Response : {data_to_evaluate["response"]}
+                        """}
+                    ]
+                    evaluation_response=self.___engine_core(messages=messages)
+                    evaluation_responses.append({"response_specificity":evaluation_response})
+
+
+                case "unit_coherence":
+            
+                    messages =[
+
+                        {"role":"system","content":SYSTEM_PROMPT_FOR_TRIAD_COHERENCE},
+                        {"role":"user","content":f"""
+                        Prompt :{data_to_evaluate["prompt"]}
+                        Context :{data_to_evaluate["context"]}
+                        Agent's Response : {data_to_evaluate["response"]}
+                        """}
+                    ]
+                    evaluation_response=self.___engine_core(messages=messages)
+                    evaluation_responses.append({"unit_coherence":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"]
+                
+                
             de.Update(data=data)