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Multi-Agent Systems

Designing Multi-Agent Systems

Designing Multi-Agent Systems is a public Python repository accompanying a book about designing and implementing LLM-enabled agents. It contains PicoAgents, a framework built from scratch for teaching agent internals and orchestration, plus examples and a progressive code-along.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Designing Multi-Agent Systems — OpenViST project profile in Multi-Agent Systems.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it when learning or prototyping agent systems and you want companion code that exposes implementation details rather than only framework-level abstractions.

Who it is for

  • Developers learning agent architecture through implementation
  • Readers of the accompanying book who want its code examples
  • Teams prototyping LLM-enabled agent or multi-agent application patterns

Documented uses

  • Study how an agent loop is structured and extended with tools, memory and streaming.
  • Explore coordination and orchestration patterns for multi-agent applications.
  • Use examples to examine capabilities such as middleware, structured output, observability, human approval and browser automation.
  • Prepare a local PicoAgents environment or explore examples through browser-based notebooks.
Before you choose

Requirements & limits

The repository is public and lists an Apache-2.0 license. Its README describes browser notebooks, GitHub Codespaces and local installation paths.

  • PicoAgents is presented as a teaching framework built from scratch; the repository also describes its core patterns as framework-agnostic.
  • The local quick-start uses an OpenAI client and API key, while the README says other providers use different client classes and credentials.
  • The local installation offers optional extras for web UI, MCP, persistence, computer use and examples.
  • Interactive notebooks are presented as a browser-based route that requires no installation.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Set up PicoAgents locally

Install the repository’s PicoAgents package and prepare an API credential for the README’s agent example.

Before you start

  • Python environment
  • Git
  • API credential for a supported model provider; the quick-start example uses OpenAI

Steps

  1. Clone the repository and change into its picoagents directory.

  2. Create and activate a virtual environment, following the commands for your operating system.

  3. Install the package with pip install -e .

  4. Set the provider API key in the environment, then consult the README’s quick-start example and model-client setup for the next stage.

Expected outcome

PicoAgents is installed locally and the environment has a provider credential configured for continuing with the documented example.

Guide limitations

  • This is a setup recipe; it does not claim the example was executed.
  • Optional features such as the web interface or computer use require their corresponding installation extras.
  • The repository notes that provider setup varies by client.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
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Sources checked
15 October 2026
Original website title
victordibia/designing-multiagent-systems · Official homepage title · retained in its source language
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