Co-Pilot / 辅助式
更新于 a month ago

labs

Hhashintel
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hashintel/labs
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💡 摘要

该存储库托管用于基于代理建模和仿真工具的实验代码片段和应用程序。

🎯 适合人群

寻找仿真工具的数据科学家对基于代理建模感兴趣的开发人员人工智能和机器学习领域的研究人员开源贡献者学习仿真框架的学生

🤖 AI 吐槽:看起来很能打,但别让配置把人劝退。

安全分析中风险

风险:Medium。建议检查:是否执行 shell/命令行指令;是否发起外网请求(SSRF/数据外发);文件读写范围与路径穿越风险。以最小权限运行,并在生产环境启用前审计代码与依赖。

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Labs

A public laboratory for HASH's experiments 🧪

This repository contains code snippets, examples and experimental work made public. Projects from our private internal-labs (🔒) monorepo for experiments will be moved here and published when safe and practical to do so, in line with our commitment to open-source.

Apps

The apps directory contains the source-code and/or content for a number of runnable applications.

Simulation Tools

The HASH app seeks to enable its users to make better decisions by utilizing all of the information available to them. Generative simulation is a core part of realizing this vision. In anticipation of integrating these capabilities, we have developed a variety of standalone tools for agent-based modeling. These simulation tools remain experimental, but we are open to accepting contributions to these in line with our repository guidelines.

  • sim-core is an open-source, locally-runnable version of HASH Core
  • sim-core-plugins contains an example external plugin developed for hCore, which provides a visual interface for process modeling
  • sim-engine contains HASH Engine, a versatile agent-based simulation engine written in Rust (with support for TypeScript & Python sims)

Libs

Block Protocol Libraries

POCs

The pocs folder contains proof of concepts and other one-off experiments.

  • distributed_collab - Distributed Collab: a BEAM VM based system for publishing/subscribing to JSON Patches with core logic implemented in Rust
  • hash-agents - HASH Agents: an experimental setup for writing Python-based 'agents' that interface with LLMs
  • hash_helm_chart - HASH Helm Charts: An experimental Helm chart for deploying (now outdated, legacy) instances of HASH on Kubernetes

A number of older POCs can be found in our hasharchives organization, including:

五维分析
清晰度7/10
创新性8/10
实用性8/10
完整性6/10
可维护性7/10
优缺点分析

优点

  • 提供多种实验工具
  • 鼓励社区贡献
  • 专注于基于代理的建模

缺点

  • 实验工具可能缺乏稳定性
  • 某些组件的文档有限
  • 并非所有功能都已完全开发

相关技能

pytorch

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免责声明:本内容来源于 GitHub 开源项目,仅供展示和评分分析使用。

版权归原作者所有 hashintel.