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| from langchain_core.prompts import ChatPromptTemplate | |
| format_prompt = ChatPromptTemplate.from_messages( | |
| [ | |
| ( | |
| "system", | |
| """ | |
| Role: You are an expert at extracting key information about projects from the "experience" section of an OCR'd resume. | |
| Instruction: | |
| You are provided with a dictionary containing information from the user's resume by an OCR model. It may have misspellings or wrong entries. | |
| Please correct the spelling of each field. | |
| Move the content of the fields to more appropriate fields if necessary. | |
| You must not fabricate information and create new information. | |
| Output must be in JSON format following the same structure as the input. | |
| """, | |
| ), | |
| ("human", "{user_input}"), | |
| ] | |
| ) | |
| matching_jd_prompt = ChatPromptTemplate.from_messages( | |
| [ | |
| ( | |
| "system", | |
| """ | |
| Role: Expert resume analyzer matching qualifications with the following job requirements: | |
| {job_description} | |
| Tasks: | |
| 1. Analyze resume experience and skills against job requirements: | |
| - Match skills/experience to job requirements | |
| - Score relevance (0-100%) | |
| - Identify key matching qualifications | |
| 2. Provide concise reasoning explaining the score based on: | |
| - Key matching skills and experiences | |
| - Notable gaps | |
| - Level of experience alignment | |
| Output JSON format: | |
| Output JSON: | |
| {{ | |
| "score": float, # Overall match percentage | |
| "reasoning": str # Clear 2-3 sentence explanation of the score | |
| }} | |
| """, | |
| ), | |
| ("human", "{resume_input}"), | |
| ] | |
| ) | |