Tools/facebookresearch/HyperAgents

HyperAgents

Self-referential self-improving agents that can optimize for any computable task

2.7k+10/wkemergingPythonCC-BY-NC-SA-4.0new this week

The Lens

By Erik Loyd, SaaS CEO and former COO/CFO of an AWS Premier Partner.

Updated Mar 2026

A 'meta agent' modifies the 'task agent' and can also modify itself. It's agents all the way down.

The architecture combines a task agent (solves the problem) and a meta agent (optimizes both the task agent and its own optimization strategy) into a single editable Python repository. The meta agent can modify any file, including its own source code. In benchmarks, this self-referential loop outperforms agents without self-improvement, and the meta-level improvements transfer across domains.

This is from the paper 'Hyperagents' (arxiv 2603.19461). The catch: this is a research project, not a production tool. The license says 'Other' which likely means Meta's research license. Check before using commercially. Running self-modifying agents requires serious compute (the paper uses multiple LLM calls per iteration) and serious trust in the guardrails. Fascinating research. Not something you deploy to production tomorrow.

Free vs Self-Hosted vs Paid

fully free

Research code released under Meta's license (check LICENSE.md, likely non-commercial research use). No paid tier, no hosted version. You need your own GPU compute and LLM API access to run experiments.

Free for research. Check license for commercial use. You pay for compute and LLM APIs.

Self-hosting ops:heavy
View pricing page →

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70/100 · B+
Adoption17/30
Maintenance21/25
Community7/20
License15/15
Analysis10/10

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Growing adoption: 2,301 stars

License: CC-BY-NC-SA-4.0

Corrected from MIT: GitHub API mis-detected; raw LICENSE is Creative Commons Attribution-NonCommercial-ShareAlike 4.0 (non-commercial). Lens already flags research/non-commercial use (editorial 2026-06-14)

Commercial use: ✗ Restricted

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