Skip to main content

Role-driven multi-agent framework with strong typing and tool-based collaboration.

Project description

cool-play-agent-teams

Role-driven multi-agent orchestration framework built with strong typing and tool-only collaboration flow. Runtime model execution uses pydantic_ai with OpenAI-compatible endpoints.

Evaluation Snapshot

Recent SWE-bench snapshots are archived under docs/evaluations/swebench/. Current snapshots cover only the first 100 items from SWE-bench Verified, not the full benchmark.

Using glm-5,Temperature: 0.7,Top P:0.95.

Mode Benchmark Pass Rate Passed Failed Mean Duration Input Tokens Cached Input Output Tokens Requests Tool Calls Report
Normal SWE-bench Verified 100 72.0% 72 28 369.2s 60,265,198 58,214,976 451,537 2,432 2,484 HTML
Orchestration SWE-bench Verified 100 73.0% 73 27 704.2s 103,016,077 95,659,776 1,886,195 6,026 7,171 HTML

Highlights:

  • Orchestration currently reaches 73/100 on SWE-bench Verified 100, with 96 runs finishing in completed state and 4 ending in failed.
  • Normal mode currently reaches 72/100 on SWE-bench Verified 100, with 97 runs finishing in completed state and 3 ending in failed.
  • Token usage is reported directly in the table so model IO and tool activity can be compared without deriving cost assumptions.

Web Interface

Agent Teams Web Interface

Start the server with uv run agent-teams server start and open http://127.0.0.1:8000 in your browser. Use uv run agent-teams server restart to restart the managed server, and uv run agent-teams server stop --force to force stop it. The web UI now includes a language toggle beside the settings button so you can switch between English and Simplified Chinese in-page.

Frontend assets are now decoupled under frontend/dist and served by the backend.

Quick start

1) Install dependencies

Use the setup script for your platform, install from PyPI, or install directly with uv.

Windows:

.\setup.bat

Linux/macOS:

sh setup.sh

Install from PyPI:

pip install cool-play-agent-teams

Direct install:

uv sync --extra dev
uv pip install -e .

For local development, prefer uv run --extra dev ... over raw python, pytest, or ruff so commands execute inside the repository environment instead of a system interpreter.

2) help

agent-teams --help

# for evals
agent-teams-evals --help

If the agent-teams command is still missing in a fresh local checkout, the project package was not installed into the active virtual environment. Run uv pip install -e . or use uv run python -m agent_teams --help as a fallback.

Examples:

uv run --extra dev pytest -q
uv run --extra dev ruff check --fix
uv run --extra dev basedpyright

Project details


Release history Release notifications | RSS feed

This version

0.0.4

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

cool_play_agent_teams-0.0.4.tar.gz (941.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

cool_play_agent_teams-0.0.4-py3-none-any.whl (1.2 MB view details)

Uploaded Python 3

File details

Details for the file cool_play_agent_teams-0.0.4.tar.gz.

File metadata

  • Download URL: cool_play_agent_teams-0.0.4.tar.gz
  • Upload date:
  • Size: 941.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for cool_play_agent_teams-0.0.4.tar.gz
Algorithm Hash digest
SHA256 d0c57187ce5b17505b03f05ed0c98b9cb4b6dfe6dd502af16dae9aa037d2a224
MD5 d5b2acafbe68dea333b836d497124798
BLAKE2b-256 a6650ec02d60691d5f8aa9be545e5dd67f3d05ff0166fbb848b15a4993397c95

See more details on using hashes here.

Provenance

The following attestation bundles were made for cool_play_agent_teams-0.0.4.tar.gz:

Publisher: release.yml on coolplayagent/agent-teams

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file cool_play_agent_teams-0.0.4-py3-none-any.whl.

File metadata

File hashes

Hashes for cool_play_agent_teams-0.0.4-py3-none-any.whl
Algorithm Hash digest
SHA256 2fcf256a6a72c051646342a9e5c9e6bc0fe97dccdc8e90f1d97b85899b6faf42
MD5 92df13c11e9e2f190719bb9e0c4cf031
BLAKE2b-256 7d327a40fc68e9f7caeec474bb474b1fa8b23444ae63f9cd501e8f1092da0664

See more details on using hashes here.

Provenance

The following attestation bundles were made for cool_play_agent_teams-0.0.4-py3-none-any.whl:

Publisher: release.yml on coolplayagent/agent-teams

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page