InfiAgent Model Card
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InfiAgent Model Card
| Field | Value |
|---|---|
| Repository | InfiAgent/InfiAgent |
| Category | Framework for Self-Improving Agent Loops |
| Stars / forks snapshot | 1900 / 235 |
| Language | Python |
| License | MIT |
| Raw capture | raw-github/infiagent_infiagent.md |
| Updated by | hourly public metadata update, 2026-05-29 16:12 +0800 |
1. Role in Self Evolve
InfiAgent presents an open-source framework aimed at self-improving AI agent loops with planner/executor/reflection style workflows. It matters because self-evolving agents need repeatable harness control, measurable feedback loops, and reusable skill procedures before claiming stable improvement.
2. Working Principle
break complex goals into planner-executor-reflection stages -> execute tasks with tool-use traces -> distill successful trajectories into reusable policies -> iterate to improve completion quality over time
3. Evidence Path
web-observed GitHub page showed 1.9k stars, 235 forks, 12 commits, MIT license, and README framing around self-improving agent workflows. Shell GitHub API access remained blocked by DNS and local gh auth was invalid, so this card treats the snapshot as web-observed rather than API-verified.
4. Teaching Use
Use this card to explain Framework for Self-Improving Agent Loops: it shows how harness/runtime/benchmark layers convert agent behavior into reproducible and auditable engineering workflows.
5. Limits
The repository was not cloned in this iteration; no benchmark run, plugin install, workflow execution, or agent loop experiment was executed. Counts and claims are visible public-page/search signals unless independently revalidated later.