Reading
Ankh.md is a framework that supports configuring multiple scoped Hermes Agents per project. It enables customized AI workflows through local configurations, skills, and tools, providing more granular control over agents.
Section 01
Ankh.md is a framework that supports configuring multiple scoped Hermes Agents per project. It enables customized AI workflows through local configurations, skills, and tools, providing more granular control over agents.
Section 02
The design philosophy of Ankh.md is to bind agents to specific projects rather than running them as global services. Each project can have:
This design brings several significant advantages:
Section 03
Agents deeply understand the project-specific codebase, documents, and conventions instead of relying on general knowledge.
Section 04
Configurations are version-controlled along with project code, ensuring team members use consistent agent settings.
Section 05
Sensitive projects and data do not need to be uploaded to cloud agent services and can run entirely locally.
Section 06
Avoid calling expensive cloud APIs for general queries; only use advanced models when necessary.
Section 07
Hermes Agents are the core execution units of Ankh.md, designed with inspiration from Hermes, the messenger god in Greek mythology—fast, flexible, and good at delivering information.
Section 08
Ankh.md supports configuring different types of Hermes Agents:
| Type | Responsibilities | Typical Application Scenarios |
|---|---|---|
| Code Assistant | Code generation, refactoring, review | Daily development tasks |
| Documentation Specialist | Document writing, updating, translation | Technical document maintenance |
| Test Engineer | Test case generation, coverage analysis | Quality assurance |
| Architecture Consultant | Design review, technology selection | Architecture decision support |
| DevOps Assistant | Deployment scripts, CI/CD configuration | Operation and maintenance automation |
Keep going with more reads from the same topic.
Splinter is a minimalist, high-performance key-value (KV) and vector storage system enabling zero-latency inter-process communication via shared memory and atomic operations. With only 766 lines of core code, it supports millions of operations per second and 768-dimensional vector storage, offering a new architectural approach for local LLM inference and data-intensive applications.
Folkering OS is the world's first AI-native bare-metal operating system, entirely written in Rust no_std without relying on Linux, POSIX, or libc. It can generate commands from scratch, compile them into WASM, and run them in 10 seconds, achieving true self-evolution.
This project explores how to use Large Language Models (LLMs) to detect logical vulnerabilities in Ethereum smart contracts, especially business logic flaws that are difficult for traditional static analysis tools to capture, such as economic manipulation and execution order errors.
This article details how to quickly deploy a virtual machine equipped with 4 NVIDIA V100 GPUs on Azure using Terraform to enable local inference of large language models with over 70B parameters. It covers a complete practical guide from infrastructure deployment, Ollama/vLLM dual-engine comparison testing, to cost optimization and actual performance data.