An intelligent tool that analyzes a candidate's resume and a job description to evaluate compatibility and automatically generate a tailored cover letter. Ideal for personal use to check whether you fit a particular role and easily get a tailored cover letter.
- 🔍 Resume Parsing: Extracts skills, experience, education, and achievements from the uploaded resume.
- 🧠 Job Matching: Compares parsed resume data against a job description to assess relevance.
- ✍️ Cover Letter Generation: Produces a personalized cover letter using AI based on the user's qualifications and the job role.
- 📊 Skill & Domain Analysis: Highlights key technical skills and domain expertise.
- 🧾 Streamlit Interface: Simple web UI to interactively upload resumes, input job descriptions, and get results instantly.
- Ollama : Advanced language model for natural language processing and AI-driven analysis.
- Streamlit : Modern web framework for building interactive user interfaces.
- Swarm Framework : Coordination of specialized AI agents for modular task execution.
- Python : Core programming language for backend logic and AI integration.
Frontend :
- Built with Streamlit, allowing users to upload resumes and input job descriptions.
- Displays results in a tabbed interface, including analysis, job matches, screening scores, and recommendations.
Backend:
- Orchestrator Agent: Coordinates the workflow by delegating tasks to specialized agents.
- Extractor Agent: Extracts structured data from resumes.
- Analyzer Agent: Analyzes the extracted data for skills, experience, and qualifications.
- Matcher Agent: Matches the candidate's profile with the provided job description using Ollama.
- Recommender Agent: Generates the tailored cover letter
AI Integration:
- Uses Ollama to process natural language inputs and generate results such as job matching analysis and cover letters.
- app.py: Main Streamlit application file.
- agents: Contains specialized AI agents for extraction, analysis, matching, and recommendation.
- utils: Utility modules for logging, error handling, and file management.
- uploads: Directory for storing uploaded resumes.
- results: Directory for saving analysis outputs.
- Upload Resume: Users upload a PDF resume via the Streamlit interface.
- Input Job Description: Users paste a job description into the provided text area.
AI Processing:
- The resume is parsed, and the job description is analyzed.
View Results :
- Users can view skills analysis, job matches, screening scores, and a tailored cover letter.
- Save Results: Analysis outputs are saved in the results directory for future reference.
- Clone the repository.
- Install dependencies using pip install -r requirements.txt.
- Run the application with streamlit run app.py.
- Upload a resume and input a job description to get started!
- Improve job matching accuracy with advanced NLP techniques.
- Allow editing of given resume in latex to fit job description for better chances