from utils.prompts import (
    basic_details_extraction_prompt,
    general_skils_extraction_prompt,
    specific_skills_comparison_prompt,
)

from utils.gpt import gpt_response

prompt_mapping = {
    "basic": basic_details_extraction_prompt,
    "general": general_skils_extraction_prompt,
    "specific": specific_skills_comparison_prompt,
}


def paired_critique(
    cv_contents: str, job_post_contents: str, response_type: str, API_KEY: str
) -> str:
    """Process CV contents, using Cohere"""

    # First, get the prompt from the prompt dict
    prompt = prompt_mapping.get(response_type)

    # Now, populate with the contents of the CV and job posting
    prompt = prompt.replace("<cv>", cv_contents).replace(
        "<job-posting>", job_post_contents
    )

    response = gpt_response(
        prompt=prompt,
        api_key=API_KEY,
    )

    return response


if __name__ == "__main__":
    with open("sample_data/meta_job.txt", "r") as file:
        post_contents = file.read()

    with open("sample_data/example_cv.txt", "r") as file:
        cv_contents = file.read()

    COHERE_API_KEY = ""

    output = paired_critique(post_contents, cv_contents, "specific", COHERE_API_KEY)
    print(output)