extractor_helper.py

def extract_technical(competences: list[str], transcripts: list[dict]):
    new_transcripts = {
        "comp_tech": [],
        "comp_beha": [],
        "behavioral": [],
        "technical": [],
    }
    # logger.info(competences)

    for i in range(len(competences)):
        # new_transcripts[i]= { "competence": competences[i] }


        transcript = transcripts[i]
        # logger.info(transcript)

        if transcript[0]["question"].startswith("TECHNICAL:"):
            # new_transcripts["behavioral"].append(transcript[0])
            new_transcripts["comp_tech"].append(competences[i])
            new_transcripts["technical"].append([transcript[-1]])
        else:
            new_transcripts["comp_beha"].append(competences[i])
            new_transcripts["behavioral"].append(transcript[1:])
            # new_transcripts["technical"].append([])
    
    return new_transcripts

def extract_competences_and_responses(competences: list[str], transcripts: list[dict]):
    responses = []

    for i in range(len(competences)):
        transcript = transcripts[i]

        response = ""
        for idx, chat in enumerate(transcript):
            # logger.info(chat)
            response += chat["answer"]

            if idx < len(transcript) - 1:
                response += "\n"
        
        responses.append(response)
    
    return competences, responses