Ross ROSS = Recommend OSS · open-source software intelligence for agents

OpenBMB/ChatDev

ChatDev 2.0: Dev All through LLM-powered Multi-Agent Collaboration observed · 2026-08-28

github.com/OpenBMB/ChatDev · homepage · Python · Apache-2.0 (permissive) observed · 2026-08-28

Health v2 · maintenance only

80/100

  • Activity 94
  • Release rhythm 63
  • Longevity 78
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: 59
  • age_days: 1102
  • days_rel: 164
  • days_push: 40
  • n_releases_24m: 4

Full methodology

Adoption not part of the score

34126 stars · 4266 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

ChatDev 2.0 (DevAll) is a zero-code multi-agent orchestration platform where users configure agents, workflows, and tasks to build LLM-powered collaborative systems without coding. Its legacy version (ChatDev 1.0) simulated a virtual software company with role-playing agents automating the software development life cycle.

Use cases

  • orchestrate multiple LLM agents to complete complex tasks
  • build multi-agent workflows without writing code
  • automate software development with AI agents acting as CEO, CTO, and programmers
  • run deep research or data visualization pipelines via agent collaboration
  • experiment with communicative agent collaboration paradigms from research
  • generate 3D content or reports through configured agent teams

When to choose

  • you want a configurable, zero-code platform for multi-agent LLM systems
  • you're researching multi-agent collaboration and orchestration strategies
  • you want to automate end-to-end software development with role-playing agents
  • you need an open-source, well-cited academic agent framework

When to avoid

  • you need a production-grade single-agent chatbot with simple API integration
  • you require fine-grained programmatic control over agent internals rather than configuration
  • your project needs minimal LLM token costs, since multi-agent pipelines are token-intensive
  • you need a framework with broad third-party plugin ecosystem support

Facets

framework · maturity active

agent-framework llm-inference workflow-automation prompt-engineering artificial-intelligence large-language-models developer-tools python cross-platform multi-agent llm-agents zero-code orchestration software-development-agents chatdev ai-agents automation docker

6 sources

Member repositories

RepositoryRoleHealth v2
OpenBMB/ChatDevmain80

For agents

markdown · JSON · MCP: product_card(name="OpenBMB/ChatDev")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem