GuideIntermediate

Multi Agent Orchestration

This guide is the direct continuation of the Agent Fundamentals and Tool Calling Guide: it takes Reservo's single agent and turns it into a system of several specialized agents working together — with no orchestration framework (LangGraph, CrewAI, AutoGen), built by hand with Python 3.14 and its standard library. The entire first module is a decision framework, measured for real — counting concept-level model calls and message "hops" — for when sub-tasks are genuinely separable with distinct expertise (multi-agent) versus when a single agent with more tools is already enough; the bar to clear isn't "I can implement the pattern," it's "I can decide whether it's needed." From there, the guide covers five coordination patterns, each in its own fully executed module: supervisor/router, sequential pipeline, parallel fan-out with aggregation whose result never depends on thread completion order, handoff/delegation mid-task, and shared state via a blackboard. The driving case is three Reservo specialists with genuinely distinct tools — `booking_agent`, `policy_agent` (over a minimal policy-search stub), and `pricing_agent` — coordinated by a supervisor. The orchestration itself — the router, message passing, the blackboard, fan-out and its aggregation — actually runs and its real output is cited; each agent's decision remains a concept, as throughout the rest of the ecosystem. It doesn't cover memory that persists across sessions, fine-grained context-window budgeting per agent, exposing tools over MCP, or security hardening — all of that is named and pointed to the matching sibling guide.