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π Interview Prep Platform v1.0.0
A desktop application for LeetCode and ML System Design interview preparation with AI-powered feedback.
β¨ Features
- Practice Modes: LeetCode coding problems and ML System Design questions
- Code Execution: Docker-based sandboxed execution for Python, Java, and C++
- AI Feedback: Local LLM support (Ollama, vLLM, llama.cpp) with OpenAI-compatible API
- Mock Interviews: Timed 30-minute interview sessions
- Progress Tracking: Submission history, statistics, and performance analytics
- Rich Editors: Monaco code editor with syntax highlighting, React Flow diagram editor
- 50+ Questions: Curated interview questions focused on Meta/Atlassian interviews
π Bug Fixes
- Fixed Submit button feedback generation failing silently
- Corrected database field name mismatch (question_id vs questionId)
- Added proper error handling and user feedback notifications
- Improved diagnostic logging for debugging
π οΈ Technical Stack
- Frontend: Electron 28+, React 18, TypeScript, TailwindCSS
- Backend: Node.js, SQLite (better-sqlite3)
- Code Execution: Docker containers with resource limits
- AI Integration: OpenAI-compatible API (Ollama, vLLM, llama.cpp, OpenAI, Claude)
- Editors: Monaco Editor, React Flow
π¦ Installation
# Clone repository
git clone https://github.com/pitcany/interview-prep-platform.git
cd interview-prep-platform
# Install dependencies
npm install
# Set up Python service
cd python-service && pip install -r requirements.txt && cd ..
# Initialize database
npm run db:init
sqlite3 ~/.config/interview-prep-platform/interview-prep.db < database/seed_complete.sql
# Configure LLM (see .env.example)
cp .env.example .env
# Edit .env to set LLM_PROVIDER=local and LLM_BASE_URL
# Start Ollama (for local LLM)
ollama serve
ollama pull llama3.1:8b
# Run application
npm run devπ Documentation
See CLAUDE.md for comprehensive development documentation.
π Acknowledgments
Built with Claude Code assistance.
Full Changelog: https://github.com/pitcany/interview-prep-platform/commits/v1.0.0