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Multi-Agent System Pattern

Python 3.11 LangGraph pytest Vercel

Part 4 of 5 — orchestrator + specialists with reviewer gates. Used in VAP Platform.

▶ Live demo · Architecture · Portfolio · VAP case study

What this is

Production reference for multi-agent collaboration — specialized roles, delegation, coordinated handoffs.

How we solve it

Orchestrator-controlled routing with critic/reviewer gates before final output; live trace UI for interviews and teaching.

Case study & tradeoffs

venkat-ai.com/work · Tradeoffs in docs/ARCHITECTURE.md.


Org skills: vpeetla-ai-skills. This repo includes .cursor/skills/, AGENTS.md, and CONTEXT.md.

git clone https://github.com/vpeetla-ai/vpeetla-ai-skills.git
./vpeetla-ai-skills/scripts/install.sh --cursor --codex --project .

Implementation status

Component Status Notes
Pattern demo + trace UI Live Vercel demo
Core agent loop Reference implementation
LangGraph production graph 🟡 Teaching scope — compose into VAP for fleet use
MCP tool bridge See LoopForge / VAP MCP docs
AegisAI gateway No side effects in pattern demo
Pytest regression pytest -q in repo

Live Demo Part of Production Agent Patterns License: MIT

Part 4 of 5 in the Production Agent Patterns series.

Production-grade reference implementation of the Multi-Agent System pattern — specialized roles, delegation, and coordinated handoffs between agents.

# Pattern Repository Use when
1 ReAct react-agent-pattern Tool use + reasoning loops
2 Reflection reflection-agent-pattern Self-critique and improve output
3 Plan-Execute plan-execute-agent-pattern Decompose goals into steps
4 Multi-Agent this repo Specialized role delegation
5 Swarm swarm-agent-pattern Parallel autonomous agents

▶ Live demo · 📖 Full series roadmap · 🚀 See in production — AI Content Factory


What you'll learn

  • Role-specialized agents (researcher, writer, reviewer) with clear contracts
  • Orchestrator delegates tasks and merges outputs
  • Shared state vs. message-passing tradeoffs
  • Boundaries that map to LangGraph / production service splits

Quick start

python -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"
python -m multi_agent_system_pattern
pytest

Runs without external API keys using deterministic stubs.

cp .env.example .env

See docs/LOCAL_DEVELOPMENT.md and docs/ARCHITECTURE.md.

See it in production

AI Content Factory uses this pattern at scale: Research → Content → SEO/Visual → HITL → Publisher agents on LangGraph.

▶ Live demo

Related

⭐ Star the repo if this pattern helps your work.

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