mvectors

semantic_search/llm_eval.py

@@ -73,19 +73,15 @@ def eval(question, answers):
     response = llm.invoke_llm_model(prompt,False)
     #response = textgen_llm(prompt)
     print("Response from LLM: ", response)
-    inter_trim =response.split("[")[1]
-    final_out = json.loads('{"results":['+inter_trim.split("]")[0]+']}')
+    # inter_trim =response.split("[")[1]
+    # final_out = json.loads('{"results":['+inter_trim.split("]")[0]+']}')
     llm_scores = []
     current_scores = []
     for idx,i in enumerate(answers[0]['answer']):
-        if('relevant' in final_out['results'][idx]):
-            relevance = final_out['results'][idx]['relevant']
-        else:
-            relevance = final_out['results'][idx]['Relevant']
-        if('score' in final_out['results'][idx]):
-            score_ = final_out['results'][idx]['score']
-        else:
-            score_ = final_out['results'][idx]['Score']
+        if('relevant' in response[idx]):
+            relevance = response[idx]['relevant']
+        if('score' in response[idx]):
+            score_ = response[idx]['relevant']
         i['relevant'] = relevance  
         llm_scores.append(score_)
         current_scores.append(i['score'])