| from typing import Dict, List, Any |
|
|
| class JobMatcher: |
| def __init__(self): |
| |
| pass |
| |
| def find_matches(self, analysis_results: Dict[str, Any]) -> List[Dict[str, Any]]: |
| """ |
| Process the job matches already generated by the LLM |
| |
| In a real application, this module could: |
| 1. Connect to job databases or APIs |
| 2. Implement sophisticated matching algorithms |
| 3. Apply filters based on location, experience level, etc. |
| |
| For this implementation, we're using the matches already provided by the LLM |
| """ |
| job_matches = analysis_results.get("job_matches", []) |
| |
| |
| |
| |
| return job_matches |
| |
| def calculate_match_score(self, job_requirements: List[str], candidate_skills: List[str]) -> float: |
| """ |
| Calculate a match score between job requirements and candidate skills |
| |
| Args: |
| job_requirements: List of skills required for the job |
| candidate_skills: List of skills possessed by the candidate |
| |
| Returns: |
| A match score between 0 and 1 |
| """ |
| if not job_requirements: |
| return 0.0 |
| |
| matched_skills = [skill for skill in candidate_skills if any(req.lower() in skill.lower() for req in job_requirements)] |
| match_score = len(matched_skills) / len(job_requirements) |
| |
| return min(match_score, 1.0) |
| |