The AI Career Guide is an integrated web-based toolkit designed to assist users in their career development journey. It includes modules for resume analysis, job-role matching, and a chatbot for interview preparation — all powered by artificial intelligence.
- Parses uploaded resumes.
- Extracts skills, experience, and education details.
- Matches resumes to suitable job roles.
Main file: app.py
- Matches user profiles/resumes with appropriate job roles.
- Uses similarity scoring between resume content and job descriptions.
Main file: job_matcher.py
- Simulates mock interview sessions using pre-defined question datasets.
- Responds with feedback and tips based on AI prompts.
Main file: interview_chatbot.py
AI_Career_Guide/
│
├── app.py # Resume analyzer backend
├── resume_parser.py # Resume analyzer backend support
├── job_matcher.py # Job-role matching backend
├── interview_chatbot.py # Interview chatbot backend
│
├── Career QA Dataset.csv # Q&A dataset for the chatbot
├── customSmalltalkResponses_en.csv # Chatbot's smalltalk responses
├── Mock-Interview-Questions.csv # Interview questions dataset
├── job_roles.csv # Job roles with skill requirements
├── jobs_resume.csv # Sample resume-job mappings
│
├── requirements.txt # Python dependencies
│
├── *.html # Web interfaces for each module
│
└── Interview preparation chatbox_files/
└── * # Assets for the chatbot web UI
Make sure Python 3.8+ is installed, then run:
pip install -r requirements.txtpython app.py
python interview_chatbot.py
python job_matcher.pyThen, open the relevant HTML files in your browser (e.g., Resume analyzer.html, Job matching.html, etc.).
- Career QA Dataset.csv – Used for the interview chatbot's knowledge base.
- Mock-Interview-Questions.csv – Contains a variety of interview questions.
- jobs_resume.csv – Mapping between resumes and job titles.
- job_roles.csv – Job titles and their associated skills.
- Students preparing for job interviews.
- Job seekers refining their resumes.
- Career coaches aiding clients with mock interviews and job-role targeting.
- Python
- Natural Language Processing (NLP)
- Flask
- HTML/CSS/JavaScript
Contributions and feature enhancements are welcome! Please open an issue or submit a pull request.
This project is open-source and available under the MIT License.