Python · MIT
xingyaoww/code-act
Official Repo for ICML 2024 paper "Executable Code Actions Elicit Better LLM Agents" by Xingyao Wang, Yangyi Chen, Lifan Yuan, Yizhe Zhang, Yunzhu Li, Hao Peng, Heng Ji.
★ 1.7k
Stars
147 forks · 15 open issues
flat
Growth · measured
Stars counted between two of our own snapshots roughly a week apart. The repository page gives the exact span.
9.4
Momentum / 100
see the breakdown below
2y ago
Created
last push 2y ago
Star history
How this score was built
| Component | Weight | Earned | Why |
|---|---|---|---|
| Velocity | 55 | 0.0 | flat, log-scaled against a 750/day ceiling |
| Acceleration | 15 | 0.0 | needs 7-day and 30-day rates side by side |
| Freshness | 15 | 0.0 | last push 2y ago; decays to zero at 180 days |
| Scale | 15 | 9.4 | 1.7k stars, log-scaled against 150k — stops a 3-star repo topping the board |
| Momentum | 100 | 9.4 | sum of the above |
Detail
| Topics | llmllm-agentllm-finetuningllm-framework |
| Matched on | AI Agents (llm-agent) |
| Short window | +0 stars over 7 days = 0.0/day |
| Long window | +5 stars over 26 days = 0.2/day |
| Lifetime average | 1.67 stars/day over 1,027 days |
| First seen here | 2026-10-11 |
| Last read | 2d ago |