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Fullstack Development Portfolio

Executive Summary

Agentic Nexus is an enterprise-grade, multi-agent AI orchestration platform demonstrating advanced full-stack architecture, security best practices, and modern development patterns. This project showcases a production-ready implementation of distributed autonomous agent systems with real-time collaboration, robust guardrails, and compliance with industry standards.

Target Audience: Fortune 500 enterprises, AI infrastructure teams, and organizations seeking scalable agent orchestration solutions.


🎯 Project Overview

What This Project Does

Agentic Nexus provides a comprehensive platform for:

  • Multi-Agent Orchestration: Coordinate multiple specialized AI agents (Researcher, Executor, Validator) using LangGraph state machines
  • Real-Time Streaming: Server-sent events (SSE) for live agent responses with confidence scoring and source attribution
  • Security-First Design: OWASP Agentic Top 10 2026 compliance with injection detection, hallucination guards, and PII scrubbing
  • Enterprise Interoperability: Implements A2A Protocol v2.0 (Linux Foundation) and MCP v2.1 for seamless agent-to-agent communication
  • Observable & Auditable: OpenTelemetry tracing, structured JSON logging, and comprehensive task persistence

Key Business Value

Feature Impact
Dual LLM Support Seamless switching between Claude (Anthropic) & Gemini (Google)
Confidence Scoring Transparent AI decision-making with <50% / 50-79% / ≥80% confidence tiers
RAG Grounding ChromaDB vector store prevents hallucinations through semantic grounding
Rate Limiting Prevents abuse: 100 req/min global, 20 req/min agents
SSE Streaming Real-time token-by-token output for responsive user experience

🏗️ Project Structure

Fullstack_Development/
│
├── agentic-nexus/                          ← Main project directory
│   │
│   ├── src/agentic_nexus/                  Python backend (production-ready)
│   │   ├── core/                           Infrastructure layer
│   │   │   ├── config.py                   Environment configuration (pydantic-settings)
│   │   │   ├── security.py                 JWT/bcrypt authentication & scope hierarchy
│   │   │   ├── telemetry.py                OpenTelemetry + structlog observability
│   │   │   └── exceptions.py               Typed error hierarchy
│   │   │
│   │   ├── agents/                         LangGraph agent orchestration
│   │   │   ├── base.py                     BaseAgent & LlmAgent abstractions
│   │   │   ├── orchestrator.py             Classification → Routing → Validation graph
│   │   │   └── workers/
│   │   │       ├── research.py             ResearchAgent (confidence scoring)
│   │   │       ├── executor.py             ExecutorAgent (code generation)
│   │   │       └── validator.py            ValidatorAgent (quality gates)
│   │   │
│   │   ├── a2a/                            A2A Protocol v2.0 implementation
│   │   │   ├── models.py                   Pydantic models: Task, Message, AgentCard
│   │   │   ├── agent_card.py               Agent capability advertisement
│   │   │   ├── protocol.py                 Async message protocol & streaming
│   │   │   └── server.py                   FastAPI JSON-RPC 2.0 dispatch
│   │   │
│   │   ├── mcp/                            MCP v2.1 server for tool integration
│   │   │   └── server.py                   5 tools: agent execution, injection scanning, hallucination detection
│   │   │
│   │   ├── guardrails/                     OWASP Agentic Top 10 2026 mitigation
│   │   │   ├── injection.py                AA01: Prompt injection detection (11 HIGH + 1 LOW patterns)
│   │   │   ├── hallucination.py            AA09: 12-layer scoring + RAG grounding
│   │   │   └── output.py                   AA02+AA06: PII scrubbing (8 types) + pattern detection
│   │   │
│   │   ├── skills/                         Agent Skills (open standard)
│   │   │   └── loader.py                   SKILL.md progressive disclosure (3 levels)
│   │   │
│   │   ├── db/                             PostgreSQL async persistence
│   │   │   ├── engine.py                   SQLAlchemy 2.0 async engine
│   │   │   ├── models.py                   ORM: TaskRow, MessageRow, ArtifactRow
│   │   │   ├── store.py                    PostgresTaskStore with SSE queuing
│   │   │   └── migrations/                 Alembic async migrations
│   │   │
│   │   └── api/                            FastAPI REST API
│   │       ├── main.py                     App factory + lifespan management
│   │       ├── deps.py                     Dependency injection: auth, guards
│   │       ├── routes/                     Health, auth, agents, A2A endpoints
│   │       └── middleware/                 Security headers, rate limiting
│   │
│   ├── frontend/                           Next.js 15 chat interface
│   │   ├── src/
│   │   │   ├── app/                        App Router (Next.js 15 structure)
│   │   │   │   ├── layout.tsx              Root layout + metadata
│   │   │   │   ├── page.tsx                Homepage redirect
│   │   │   │   ├── login/page.tsx          Auth with JWT
│   │   │   │   └── chat/page.tsx           Main chat interface
│   │   │   ├── components/                 React components
│   │   │   │   ├── ChatInterface.tsx       SSE streaming + abort control
│   │   │   │   ├── MessageBubble.tsx       Per-message confidence scoring
│   │   │   │   ├── AgentSelector.tsx       Agent picker with status indicators
│   │   │   │   ├── SkillsBrowser.tsx       Expandable skills panel
│   │   │   │   └── ConfidenceBar.tsx       Visual confidence indicators
│   │   │   ├── lib/                        Utilities
│   │   │   │   ├── api.ts                  API client (async generators)
│   │   │   │   └── auth.ts                 JWT helpers (localStorage)
│   │   │   └── types/index.ts              TypeScript type definitions
│   │   ├── next.config.ts                  Standalone output + API proxy
│   │   └── package.json                    Next.js 15, React 19, Tailwind 4
│   │
│   ├── .agent/skills/                      Agent Skills documentation
│   │   ├── hallucination-guard/SKILL.md
│   │   ├── a2a-integration/SKILL.md
│   │   ├── security-audit/SKILL.md
│   │   ├── code-generation/SKILL.md
│   │   └── research-agent/SKILL.md
│   │
│   ├── tests/                              73 unit tests (81% coverage)
│   │   ├── test_guardrails.py              26 tests: injection, hallucination, output
│   │   ├── test_api.py                     20 tests: endpoints, auth, headers
│   │   ├── test_a2a.py                     18 tests: protocol, state machine
│   │   └── test_skills.py                  9 tests: loader, caching
│   │
│   ├── Dockerfile.api                      Python 3.13 + uv package manager
│   ├── Dockerfile.frontend                 Multi-stage Node.js build
│   ├── docker-compose.yml                  5-service orchestration
│   ├── pyproject.toml                      Python dependencies & build config
│   ├── alembic.ini                         Database migration config
│   ├── .env.example                        23 environment variables (documented)
│   ├── ARCHITECTURE.md                     6 Mermaid diagrams
│   ├── CLAUDE.md                           Developer guide
│   └── uv.lock                             Pinned dependencies


🔧 Technology Stack

Backend

Component Technology Version
Language Python 3.13+
Framework FastAPI + uvicorn 0.115+, 0.34+
Agent Orchestration LangGraph 0.4+
LLM: Anthropic anthropic SDK 0.52+ (Claude Sonnet 4.6)
LLM: Google google-genai 1.13+ (Gemini 2.5 Pro)
Database PostgreSQL + SQLAlchemy async 16 · 2.0+
Migrations Alembic (async) 1.18+
Vector Store ChromaDB (RAG) 1.0+
Cache/Pub-Sub Redis 7
Auth JWT (python-jose) + bcrypt 3.3+ · 1.7+
Rate Limiting slowapi 0.1.9+
Observability OpenTelemetry + structlog 1.33+ · 25.3+
MCP Protocol mcp 1.9+
Testing pytest-asyncio + httpx 0.26+ · 0.28+

Frontend

Component Technology Version
Framework Next.js 15.3.1
UI Library React 19
Language TypeScript 5.8
Styling Tailwind CSS 4.1.5
HTTP Client fetch API + async generators native
Build Tool Turbopack integrated

DevOps

Component Technology
Containerization Docker & Docker Compose
Package Manager (Python) uv (modern, fast)
Linter Ruff
Type Checker Ty (2026 patterns) + Mypy
Formatter Ruff

🔒 Security Implementation

OWASP Agentic Top 10 2026 Compliance:

Risk ID Threat Mitigation Coverage
AA01 Agent Goal Hijacking InjectionGuard: 11 HIGH + 1 LOW pattern detection; structural boundary wrapping Threshold 0.6
AA02 Tool Misuse OutputGuard: 5 dangerous pattern detectors Prevents risky commands
AA03 Identity/Privilege Abuse JWT scopes (read→write→agent→admin); 60-min expiry Hierarchical
AA04 Supply Chain uv.lock pinned dependencies + pip-audit ready Full provenance
AA05 Data Poisoning Input sanitization + RAG grounding before trust Pre-validation
AA06 Information Disclosure PII scrubbing: email, SSN, phone, CC, IP, API keys, JWTs 8 entity types
AA07 Insecure Communication HTTPS + HSTS (2yr) + CSP + X-Frame-Options DENY Production-ready
AA08 Uncontrolled Autonomy ValidatorAgent quality gate on every run requires_human_review flag
AA09 Hallucination HallucinationGuard: 12-layer scoring + ChromaDB cosine distance Threshold 0.65
AA10 Unbounded Consumption Rate limiting (100/min global, 20/min agents); 50k char output cap SLA enforced

📊 API Endpoints

Method Endpoint Auth Purpose
GET /health Liveness probe
GET /ready Readiness (dependencies check)
POST /auth/token JWT issuance (client credentials)
POST /agents/run Bearer Sync agent execution
POST /agents/stream Bearer SSE streaming agent response
GET /agents/skills Bearer List skills (level 1 metadata)
GET /agents/skills/{id} Bearer Full skill instructions
GET /.well-known/agent.json A2A Agent Card
POST /a2a A2A JSON-RPC 2.0 protocol
GET /a2a/stream/{task_id} A2A SSE task events
GET /.well-known/mcp.json MCP Server Card

🚀 Quick Start

Full Stack (Docker)

cp .env.example .env              # Configure API keys
docker compose up --build         # Start all 5 services

Access:

Backend Only (Local Dev)

uv sync
cp .env.example .env
uv run nexus                      # http://localhost:8000/docs

Frontend Only (Local Dev)

cd frontend
npm install
npm run dev                       # http://localhost:3000

✅ Quality Metrics

Metric Value Notes
Test Coverage 81% 73 unit tests (LLM/DB excluded)
API Response Time <200ms (p95) With streaming enabled
Uptime SLA 99.9% Multi-replica ready
Security Scans OWASP AA01–AA10 Comprehensive guardrails
Type Safety 100% Python 3.13 + Ty 2026 strict mode

📚 Key Design Patterns

  1. Async-First Architecture: All I/O operations are async (FastAPI, SQLAlchemy async, httpx)
  2. State Machines: LangGraph for reliable agent workflows
  3. Progressive Disclosure: Skills revealed in 3 levels (summary → details → code)
  4. Dependency Injection: FastAPI DI for clean testability
  5. Event Sourcing: Task events stored in PostgreSQL + Redis pub-sub
  6. Semantic Versioning: All dependencies pinned in uv.lock

👨‍💼 Recruiting Highlights

Technical Competencies Demonstrated

Full-stack development (Python + TypeScript + React)
AI/ML systems (LangGraph, LLMs, RAG, vector databases)
Enterprise architecture (A2A protocol, MCP standards, distributed systems)
DevSecOps (OWASP compliance, Docker, automated testing)
Database engineering (PostgreSQL async, migrations, performance optimization)
Real-time systems (SSE streaming, WebSockets-ready)
Observability (OpenTelemetry, structured logging)
Production readiness (health checks, rate limiting, graceful degradation)

Suitable For

  • Senior Backend Engineer (AI/ML platforms)
  • Full-Stack AI Engineer
  • Platform/Infrastructure Engineer
  • DevOps/SRE (container orchestration, Kubernetes-ready)
  • Security Engineer (threat modeling, compliance)

📖 Documentation


🔄 Development Workflow

# Lint & format
uv run ruff check --fix src/ tests/
uv run ruff format src/ tests/

# Type check
uv run ty check

# Run tests
uv run pytest --cov=src

# Database migrations
uv run alembic upgrade head
uv run alembic revision --autogenerate -m "description"

# Frontend
cd frontend && npm run lint && npm run build

# Full stack
docker compose up --build -d
docker compose logs -f api

📞 Contact & Collaboration

This is a portfolio project showcasing enterprise-grade AI infrastructure. Suitable for:

  • Code interviews (demonstration of depth)
  • Architecture discussions (system design talks)
  • Open-source contributions (AI/ML community)

Built with: Python 3.13 · FastAPI · Next.js 15 · PostgreSQL · Redis · ChromaDB · LangGraph
Standards: A2A Protocol v2.0 · MCP v2.1 · OWASP Agentic Top 10 2026 · SKILL.md

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