from langchain_core.prompts import ChatPromptTemplate

extract_one_profile = """
You are an intelligent information extraction assistant.
Your task is to read the following Curriculum Vitae (CV) text and extract structured information according to the expected output below.

----------------------------
**CV (curriculum vitae)**:

{cv}
----------------------------


**Expected Output**:
- fullname. str, Fullname of the candidate.
- high_edu_univ_1. str, University where candidate take bachelor degree, if exists. Default = "-".
- high_edu_major_1. str, Major of candidate's bachelor degree, if exists. Default = "-".
- high_edu_gpa_1. float, GPA of candidate's bachelor degree, if exists. Default = 0.

- high_edu_univ_2. str, University where candidate take master degree, if exists. Default = "-".
- high_edu_major_2. str, Major of candidate's master degree, if exists. Default = "-".
- high_edu_gpa_2. float, GPA of candidate's master degree, if exists. Default = 0.

- high_edu_univ_3. str, University where candidate take doctoral or phd degree, if exists. Default = "-".
- high_edu_major_3. str, Major of candidate's doctoral or phd degree, if exists. Default = "-".
- high_edu_gpa_3. float, GPA of candidate's doctoral or phd degree, if exists. Default = 0.
- domicile. str, Current domicile of the candidate. Default = "-".

- yoe. float, Year of working experience of the candidate. Default = 0.
- hardskills. list, List of the candidate's hard skills. Default = "-".
- softskills. list, List of the candidate's soft skills. Default = "-".
- certifications. list, List of the candidate's certifications. Default = "-".
- business_domain_experiences. list, List of the candidate's business domain experience based on company's business on working experience or project's domain business, do not hallucinate! Default = "-".



**Instructions**:
1. Read the provided CV and extract information needed based on expected output.
2. Do not verbose, just return the final answer.
"""
extract_one_profile = ChatPromptTemplate.from_template(extract_one_profile)