AI-powered portfolio review assistant that helps early-career developers strengthen their professional portfolios.
PathReview analyzes GitHub profiles, resumes, and project repositories to generate structured, actionable feedback on portfolio completeness, project quality, skill gaps, and presentation improvements.
- Profile Ingestion — Upload a resume (PDF or Markdown), connect a GitHub profile, and link project repositories
- RAG-Powered Feedback — Retrieval-augmented generation produces specific, evidence-based feedback referencing your actual work
- Multi-Tool Agent — An AI agent orchestrates GitHub analysis, skill extraction, README scoring, and market comparison
- Safety Guardrails — Bias detection, content filtering, PII scrubbing, and prompt injection defense ensure feedback is constructive and safe
- Web Dashboard — View results, track improvement over time, and export shareable review summaries
Windows users: Use Git Bash to run these commands, not PowerShell. See docs/SETUP.md for Windows-specific setup including installing
make.
# Clone and enter the repo
git clone https://github.com/jamjamgobambam/pathreview.git
cd pathreview
# Configure environment (add your OPENROUTER_API_KEY to .env)
cp .env.example .env
# Start backing services — must be running before make setup
docker compose up -d
# Run first-time setup (installs deps, runs migrations, seeds DB, installs frontend)
make setup
# Start the application
make runThen open http://localhost:5173 in your browser.
For detailed setup instructions including platform-specific notes, see docs/SETUP.md.
PathReview is structured as a multi-service Python + React application with five major subsystems:
| Subsystem | Directory | Description |
|---|---|---|
| API Layer | api/ |
FastAPI REST API with authentication, validation, and rate limiting |
| Ingestion Pipeline | ingestion/ |
Document parsing, chunking, and embedding generation |
| RAG System | rag/ |
Hybrid retrieval, LLM-based review generation, and quality evaluation |
| Agent System | agent/ |
Multi-tool orchestration with planning, state management, and error handling |
| Safety Layer | safety/ |
Content filtering, bias detection, PII scrubbing, and prompt defense |
| Frontend | frontend/ |
React + TypeScript dashboard with Vite |
For a detailed architecture overview, see docs/ARCHITECTURE.md.
We welcome contributions! Please read docs/CONTRIBUTING.md before submitting a pull request.
make help # Show all available commands
make test-unit # Run unit tests (~30 seconds)
make check # Run linter + formatter + type checker
make run # Start the dev serversMIT