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CareerPilot AI: An Intelligent Career Planning System Based on Large Language Models

An open-source project integrating NLP, TF-IDF, cosine similarity, and Google Gemini AI to help job seekers analyze resumes, identify skill gaps, and generate personalized career advice

Career GuidanceResume AnalysisNLPGemini AIStreamlitTF-IDFATSJob MatchingPython
Published 2026-06-01 12:15Recent activity 2026-06-01 12:18Estimated read 5 min
CareerPilot AI: An Intelligent Career Planning System Based on Large Language Models
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Section 01

CareerPilot AI: Open-Source Intelligent Career Planning System (Introduction)

CareerPilot AI is an open-source smart career planning system developed by Krishna Yadav (a 3rd-year B.Tech CSE student) and hosted on GitHub. It integrates NLP, TF-IDF, cosine similarity, and Google Gemini AI to help job seekers analyze resumes, identify skill gaps, generate personalized career advice, and more. This post breaks down its core features, technical implementation, usage guide, and practical value.

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Section 02

Background & Problem Statement

In today's competitive job market, resumes are the first barrier between job seekers and recruiters. Many candidates lack clarity on their resume's ATS (Applicant Tracking System) performance or the skill gaps between their profile and target roles. CareerPilot AI addresses these pain points by providing data-driven insights and actionable guidance.

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Section 03

Core Features of CareerPilot AI

The system offers key functions:

  1. Resume upload & text extraction (PDF parsing via NLP)
  2. ATS compatibility scoring (resume-job description match analysis)
  3. Skill gap analysis (identifies existing/missing skills and improvement suggestions)
  4. Smart job matching (TF-IDF + cosine similarity for relevant position recommendations)
  5. Interview question generation (tech, HR, project-related questions via Gemini AI)
  6. Personalized career roadmap (learning plans, certifications, project recommendations)
  7. Data visualization (skill distribution, ATS score insights via Plotly)
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Section 04

Technical Architecture & Stack

Frontend: Streamlit (Python-based, no frontend experience needed, real-time reload) Backend: Python, Scikit-learn (ML), TF-IDF (NLP), Google Gemini API, Plotly (visualization), Pandas/NumPy (data processing) Core Algorithms: TF-IDF vectorization, cosine similarity, prompt engineering for Gemini Project Structure: Modular design with separate modules for ATS scoring, skill gap analysis, job matching, etc.

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Section 05

Deployment & Quick Start Guide

To use CareerPilot AI:

  1. Clone repo: git clone https://github.com/Krishna-Yadav500/CareerPilotAI.git
  2. Install dependencies: pip install -r requirements.txt
  3. Configure Gemini API key: Add GEMINI_API_KEY="your_key" to .streamlit/secrets.toml
  4. Run app: streamlit run app/app.py
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Section 06

Application Value & Impact

For Job Seekers: Optimize resumes for ATS, identify skill gaps, prepare for interviews, find matching jobs For Educational Institutions: Inspire student career guidance systems, course recommendation engines, skill assessment platforms

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Section 07

Future Directions & Learning Highlights

Future Plans: Resume ranking for enterprises, real-time job scraping, BERT-based semantic matching, user authentication, multi-language support Learning Value: Modular architecture, fusion of traditional ML and generative AI, Streamlit best practices

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Section 08

Summary

CareerPilot AI is a comprehensive, well-architected tool solving real job-seeking problems with AI. It's a practical resource for job seekers, a learning case for developers, and an AI application reference for edtech practitioners. Its open-source nature allows further customization.