📋 MedSecure Portfolio Project - Complete File Index

🚀 START HERE

First, read these in order:

1. PROJECT_COMPLETE.md ← You are here
2. PORTFOLIO_SETUP.md ← Quick-start guide
3. EXECUTION_PIPELINE.md ← 10-phase roadmap

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📚 Documentation Files

Primary Documentation

• PROJECT_COMPLETE.md — This file. Project completion status, file manifest, success criteria
• PORTFOLIO_SETUP.md — Quick-start guide, API examples, environment setup
• EXECUTION_PIPELINE.md — Complete 10-phase development roadmap with detailed instructions
• DEVELOPMENT_NOTES.md — Architecture decisions, design patterns, best practices
• README.md — Technical overview and project structure

Configuration

• .env.example — Environment variable template (copy to .env)
• requirements.txt — Python dependencies (18 packages)

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🎯 Application Core (FastAPI)

Entry Point

• app/main.py — FastAPI app initialization, router mounting

API Layer

• app/api/__init__.py — Package marker
• app/api/routes.py — Two endpoints (POST/GET summaries) with RBAC

Data Models

• app/schemas/__init__.py — Package marker
• app/schemas/models.py — Pydantic SummaryRequest/SummaryResponse models

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🔐 Core Infrastructure

Configuration & Settings

• app/core/__init__.py — Package marker
• app/core/config.py — Settings class, environment loading
• app/core/logging.py — Loguru setup, @log_call decorator
• app/core/security.py — RBAC require_role() decorator, role enforcement

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🧠 Services (Pipeline Components)

Pipeline Services

• app/services/__init__.py — Package marker
• app/services/pipeline.py — Main orchestrator (runs all steps in sequence)
• app/services/pii_masking.py — PII detection & masking (regex-based)
• app/services/ner.py — Named Entity Recognition (spaCy integration)
• app/services/summarizer.py — Text summarization (Llama-3 placeholder)
• app/services/verification.py — Hallucination detection (verification agent)
• app/services/storage.py — MongoDB CRUD operations

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🤖 Machine Learning

ML & Training

• app/ml/__init__.py — Package marker
• app/ml/finetune.py — PEFT/LoRA fine-tuning stub (Llama-3 ready)
• app/ml/evaluation.py — Evaluation metrics & quality checks stub

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🐳 Deployment & DevOps

Containerization

• Dockerfile — Docker image build (Python 3.11 slim + dependencies)
• docker-compose.yml — Local dev stack (API + MongoDB volumes)

CI/CD

• .github/workflows/ci.yml — GitHub Actions (Bandit + pip-audit + pytest)

Infrastructure

• infra/README.md — Azure ML integration notes & deployment placeholders

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🧪 Testing

Test Suite

• tests/__init__.py — Package marker (auto-created)
• tests/test_masking.py — Unit test for PII masking

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⚙️ VS Code Integration

Development Environment

• .vscode/tasks.json — Three tasks:
  1. "Run MedSecure API" (Ctrl+Shift+B) — Start dev server
  2. "Run Tests" — pytest execution
  3. "Security Scan" — Bandit security check

GitHub Copilot

• .github/copilot-instructions.md — Workspace-specific Copilot instructions

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🔧 Utilities

Setup & Validation

• quickstart.py — Environment validation script
  • Checks dependencies
  • Verifies MongoDB
  • Runs pipeline test
  • Prompts to start API

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📊 File Statistics

Category	Count	Files
Documentation	6	.md files + .env.example
Application Code	12	Core FastAPI app
ML/Infrastructure	4	Services + training stubs
DevOps	4	Docker + GitHub Actions + tasks
Testing	2	Test suite
Utilities	1	quickstart.py
TOTAL	29	Files

Lines of Code

• Core App: ~300 LOC
• Documentation: ~1500 LOC
• Configuration: ~50 LOC
• Tests: ~20 LOC

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🎯 How to Use This Index

For Understanding Architecture

1. Read PORTFOLIO_SETUP.md (overview)
2. Read app/services/pipeline.py (core flow)
3. Read app/api/routes.py (endpoints)
4. Read DEVELOPMENT_NOTES.md (design decisions)

For Development

1. Check EXECUTION_PIPELINE.md (which phase?)
2. Find relevant service file in app/services/
3. Update code
4. Run tests: pytest -v tests/
5. Security check: bandit -r app

For Deployment

1. Read docker-compose.yml (local testing)
2. Read Dockerfile (container build)
3. Read infra/README.md (Azure deployment)
4. Read .github/workflows/ci.yml (CI/CD setup)

For Portfolio

1. Share GitHub repo link
2. Point to README.md (overview)
3. Show EXECUTION_PIPELINE.md (10-phase roadmap)
4. Explain DEVELOPMENT_NOTES.md (architecture)

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🚀 Quick Navigation

"How do I..."

Question	File
Start the API?	See PORTFOLIO_SETUP.md § Quick Start
Understand the architecture?	Read DEVELOPMENT_NOTES.md § Architecture Overview
See the phases?	Check EXECUTION_PIPELINE.md (phases 1-10)
Run tests?	Use VS Code task or run pytest -v tests/
Deploy to Docker?	Follow EXECUTION_PIPELINE.md § Phase 8
Build Phase 1?	Read EXECUTION_PIPELINE.md § Phase 2.1
Check security?	Run Bandit: bandit -r app
Validate setup?	Run python quickstart.py
Configure environment?	Copy .env.example to .env
Understand RBAC?	Read app/core/security.py
See all endpoints?	Visit http://localhost:8000/docs (after starting API)

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📦 Project Dependencies

See requirements.txt for full list. Key packages:

• FastAPI — REST framework
• Uvicorn — ASGI server
• Pydantic — Data validation
• PyMongo — MongoDB driver
• Transformers — HuggingFace models
• spaCy — NLP library
• PEFT — LoRA fine-tuning
• Loguru — Structured logging
• Bandit — Security scanning
• pytest — Testing framework

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✅ Verification Checklist

• All files created and syntactically valid
• Python imports verified (no circular dependencies)
• Docker files ready for build
• GitHub Actions CI/CD configured
• Documentation complete and linked
• Environment configuration templated
• VS Code tasks set up
• Tests framework ready
• Quick-start script working
• Project structure clean and organized

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🎓 Portfolio Talking Points

When showcasing this project:

1. "Architecture" — Explain the 7-step pipeline (masking → NER → summarization → verification → storage → RBAC)
2. "Security" — Highlight RBAC, encryption hooks, CI/CD scanning
3. "NLP/ML" — Discuss NER integration, PEFT/LoRA fine-tuning approach, hallucination detection
4. "DevOps" — Show Docker setup, GitHub Actions, environment management
5. "Code Quality" — Point out decorators, type hints, structured logging

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📞 Getting Help

If you get stuck:

1. Check PORTFOLIO_SETUP.md § Troubleshooting
2. Run python quickstart.py to diagnose issues
3. Read relevant section in DEVELOPMENT_NOTES.md
4. Check file syntax: python -m pytest tests/ -v

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🎉 You're Ready!

Next Steps:

1. ✅ You have the complete project (this file)
2. 📖 Read PORTFOLIO_SETUP.md
3. 🧪 Run python quickstart.py
4. 🚀 Start uvicorn app.main:app --reload
5. 🎯 Begin Phase 1 (EXECUTION_PIPELINE.md)

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Status: ✅ Project Complete and Ready for Development Version: 1.0 Last Updated: February 2026