| # AI-Powered Resume Analyzer and Enhancer | |
| This application is an AI-powered tool that analyzes and enhances resumes based on job descriptions. It uses advanced language models to provide detailed insights and improvements for job seekers. | |
| <p align="center"> <img src="architecture.png" alt="Image generated using Claude AI"> <br> <em>Image generated using Claude AI</em> </p> | |
| ## Features | |
| - Resume upload (DOCX format) | |
| - Job description input | |
| - Quick and in-depth resume analysis | |
| - Resume enhancement | |
| - Output in multiple formats (DOCX, HTML) | |
| ## Architecture | |
| The application follows this high-level flow: | |
| 1. Start Application | |
| 2. Upload DOCX Resume | |
| 3. Input Job Description | |
| 4. Input GROQ API Key | |
| 5. Choose Action (Analyze or Enhance) | |
| 6. If Analyze: | |
| - Choose Analysis Type (Quick or In-Depth) | |
| - Perform Analysis | |
| - Display Results | |
| 7. If Enhance: | |
| - Perform In-Depth Analysis | |
| - Enhance Resume | |
| - Generate Enhanced Outputs | |
| ## Key Components | |
| - **Streamlit**: For the web interface | |
| - **python-docx**: To process DOCX files | |
| - **GROQ API**: For accessing AI models | |
| - **LLaMA 3 70B**: Large language model for analysis and enhancement | |
| - **Graphviz**: For generating the architecture diagram | |
| ## Setup and Installation | |
| 1. Clone the repository | |
| 2. Install required packages: `pip install - r requirements.txt` | |
| 3. Set up a GROQ API account and obtain an API key from here (https://console.groq.com/keys?_gl=1*1ozbol6*_gcl_au*MTc1ODk5MDQ0Mi4xNzM2NTgwNTgx*_ga*NDM2OTA5NjI1LjE3MzY1ODA1ODA.*_ga_4TD0X2GEZG*MTczNjU4MDU4MC4xLjAuMTczNjU4MDU4MC42MC4wLjA.) | |
| ## Usage | |
| 1. Run the Streamlit app: `streamlit run main.py` | |
| 2. Upload your resume (DOCX format) | |
| 3. Enter the job description | |
| 4. Provide your GROQ API key | |
| 5. Choose to analyze or enhance your resume | |
| 6. View the results or download the enhanced resume | |
| ## Modules | |
| - `main.py`: Main Streamlit application | |
| - `prompts.py`: Prompts for handling resume parsing and formatting | |
| - `flowhchart.py`: Flow chart vizualization | |
| ## Dependencies | |
| - Streamlit | |
| - python-docx | |
| - groq | |
| - graphviz | |
| - docx2txt | |
| ## Note | |
| Ensure you have a valid GROQ API key and sufficient credits for using the LLaMA 3 70B model. The application's performance depends on the quality and availability of the AI model. | |