fix evaluation, separation

evaluator.py

@@ -107,7 +107,7 @@ def gpt_evaluator(payload, fewshot, response_format):
             {"role": "system", "content": fewshot},
             {"role": "user", "content": str(payload)},
         ],
-        response_format=Evaluations)
+        response_format=response_format)
     json_str = response.choices[0].message.parsed
     return json_str
 
@@ -133,7 +133,7 @@ def evaluate_interview(competences: list[str], transcript: list):
     # global tags
     model_inputs = []
 
-    responses = extract_competences_and_responses(competences, transcript["behavioral"])
+    responses = extract_competences_and_responses(transcripts["comp_beha"], transcript["behavioral"])
 
     print(len(competences))
     print(len(responses))
@@ -199,7 +199,7 @@ def evaluate_interview(competences: list[str], transcript: list):
     ## output: 
     final_score = 0
     behavioral_scores = generate_behavioral_score(result.value)
-    technical_scores = generate_technical_score(competences, transcript["technical"])
+    technical_scores = generate_technical_score(transcript["comp_tech"], transcript["technical"])
 
     final_score = aggregate_scores(behavioral_scores, technical_scores)
 

extractor_helper.py

@@ -1,6 +1,8 @@
 
 def extract_technical(competences: list[str], transcripts: list[dict]):
     new_transcripts = {
+        "comp_tech": [],
+        "comp_beha": [],
         "behavioral": [],
         "technical": [],
     }
@@ -14,11 +16,13 @@ def extract_technical(competences: list[str], transcripts: list[dict]):
         # logger.info(transcript)
 
         if transcript[0]["question"].startswith("TECHNICAL:"):
-            new_transcripts["behavioral"].append(transcript[:-1])
+            # new_transcripts["behavioral"].append(transcript[0])
+            new_transcripts["comp_tech"].append(competences[i])
             new_transcripts["technical"].append([transcript[-1]])
         else:
-            new_transcripts["behavioral"].append(transcript)
-            new_transcripts["technical"].append([])
+            new_transcripts["comp_beha"].append(competences[i])
+            new_transcripts["behavioral"].append(transcript[1:])
+            # new_transcripts["technical"].append([])
     
     return new_transcripts