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:
Orchestrationcurrently reaches73/100onSWE-bench Verified 100, with96runs finishing incompletedstate and4ending infailed.Normalmode currently reaches72/100onSWE-bench Verified 100, with97runs finishing incompletedstate and3ending infailed.- Token usage is reported directly in the table so model IO and tool activity can be compared without deriving cost assumptions.
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 .
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.
1 maintainer
Metadata
1 maintainer
Release files for cool-play-agent-teams 0.0.3.20260327033309
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Built distribution (wheel)
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|---|---|---|---|---|
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Total release size: 1.0 MB
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