An intelligent resume-to-job-description matcher that uses RAG (Retrieval-Augmented Generation) to analyze candidate fit and provide actionable insights.
RESMATCH goes beyond simple keyword matching. By leveraging LLMs and RAG workflows, it compares resumes against specific job descriptions to extract skills, identify gaps, and even suggest rewrites to better align with the role.
- RAG-Powered Analysis: Uses a retrieval-based approach to contextualize resume data against job requirements.
- Streamlit Interface: A clean, interactive UI for uploading resumes and viewing analysis results.
- Skill Extraction: Automatically parses and categorizes candidate skills from
PDFandCSVsources. - Automated Rewriting: Suggests improvements to help candidates tailor their profiles for specific JD requirements.
- Language: Python
- LLM Orchestration: [LANGCHAIN,FAISS,OPENAI]
- Frontend: Streamlit
- Data Handling: Pandas, JSON
rag-hat.py: The core logic for the RAG-based matching system.final_code.py: The Streamlit application entry point.resume_pipeline.py: The data processing pipeline for resume parsing.groundtruth.py: Evaluation scripts to ensure matching accuracy.
- Clone the repo:
git-clone [https://github.com/16GB-Analyzer/RESMATCH.git](https://github.com/16GB-Analyzer/RESMATCH.git)