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LLM Answers & Content Strategy
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Loa Laplas: An Orchestration Engine for Compiling AI Compositions into Executable Agent Workflows
This article introduces the Loa Laplas project, an orchestration tool designed for the Loa engine. It can compile high-level AI composition descriptions into executable, gate-controlled agent workflows, providing a new solution for the development and deployment of complex AI applications.
NDH Unified Cognitive Engine: An Innovative Reasoning Framework Based on Conceptual Quantum Computing
This article introduces the NDH Unified Cognitive Engine project, a unique conceptual quantum computing framework that uses conceptual qubits, tensor computing, and multi-dimensional harmonics to model complex reasoning processes, providing a novel theoretical perspective and technical tools for understanding and simulating high-complexity cognitive systems.
LLM Inference Engine Implemented Purely in Zig: A High-Performance, Lightweight Open-Source Alternative
This article introduces the SMC17/inference project, an LLM inference engine implemented from scratch using the Zig language. It supports modern optimization techniques such as paged attention, BF16 kernels, and persistent thread pools, providing developers who pursue extreme performance and controllability with a new alternative outside the Python ecosystem.
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White-box Adversarial Attacks Reveal Social Bias Vulnerabilities in Large Multimodal Models
This article introduces a white-box adversarial attack study targeting social bias issues in Large Multimodal Models (LMMs). The project provides complete code implementations, including targeted PGD attacks, universal adversarial perturbations, defense evaluation, and noise similarity analysis, serving as an important tool for AI safety research.
Hands-On Multi-Modal RAG System: A Local Document Intelligent Q&A Solution Based on Qwen2-VL and CLIP
This article introduces an open-source multi-modal Retrieval-Augmented Generation (RAG) system that combines the Qwen2-VL vision-language model and CLIP encoder. It supports mixed text-image retrieval for PDF documents and provides a complete technical solution for building localized, privacy-controllable intelligent document Q&A systems.
Building a DNA Large Language Model from Scratch: An Exploration of the Fusion of Bioinformatics and Deep Learning
A complete implementation of a DNA sequence large language model, covering the entire workflow from tokenizer construction, BPE algorithm, embedding layer design, Transformer architecture to prediction and evaluation.
Claude Workflow: An Agent Workflow Engine Based on YAML State Machines
This article introduces a plugin designed for Claude Code that uses YAML-defined state machines to drive AI agents in executing complex tasks, supporting state tracking, conditional guards, nested sub-workflows, and a visual dashboard.
A Lightweight Validation Framework for Trustworthiness Assessment of Open-Source Large Language Models
This article introduces a trustworthiness assessment framework for open-source large language models (LLMs), which constructs a lightweight and reproducible evaluation system from three dimensions: security, authenticity, and consistency, supporting local deployment and low-cost validation.
n8n Dependency EOL Firewall: A Multi-Agent Automated Dependency Governance Solution
This article introduces an n8n-based multi-agent workflow system that monitors the health status of code repository dependencies, automatically detects risks such as deprecation, end-of-life (EOL), and version lag, and generates migration PRs automatically.
LLM Playground: An Interactive Experimental Platform for Large Language Model Behavior
This article introduces an interactive application for experimenting with and exploring the behavior of large language models (LLMs). It supports features like temperature adjustment, context management, token usage monitoring, and API inference, helping developers gain an in-depth understanding of LLM response characteristics.
Application of Agentic AI in Football Research: How Multi-Agent Systems Revolutionize Sports Data Analysis
Explore how the agentic-football-ai project combines large language models (LLMs), RAG, vector databases, and multi-agent workflows to bring a new paradigm of intelligent analysis to the field of football research.
Tokamak: A Minimalist LLM Inference Engine Built from Scratch
Tokamak is a lightweight LLM inference engine implemented from scratch using PyTorch. It fully incorporates core optimization techniques such as KV caching, paged attention, continuous batching, and speculative decoding, and has undergone performance benchmarking against vLLM.
disp8ch: A Local-First AI Workspace That Turns Conversations into Visual Multi-Agent Workflows
disp8ch is a self-hosted AI workspace that upgrades the traditional chat interface into a system for visual workflow orchestration, multi-agent collaboration, and auditable automation. It supports full local operation, requires no API keys, and all data is stored locally.
Efficient LLM Inference Research Assistant: RAG-based Academic Paper Retrieval and Q&A System
A retrieval-augmented generation system targeting the field of efficient LLM inference (quantization, KV cache optimization, speculative decoding), built on approximately 30 arXiv papers, capable of generating evidence-based answers based on retrieved paper fragments.
GreatAegis: Post-Quantum Secure Enterprise AI Gateway Integrating PQC Encryption and AMD ROCm Acceleration
An open-source AI gateway for enterprise deployment, integrating post-quantum cryptography (PQC) encryption, dynamic hybrid workload routing, and AMD ROCm-based isolated open-source large model inference, providing dual guarantees for AI security and performance.
GitHub Issue Workflow Automation: A Lightweight AI Agent Integration Solution
A lightweight GitHub Issue automation workflow project that helps development teams easily integrate AI agents to automate Issue handling and provides a clear execution tracking mechanism.
LLM Memory Visualization Tool: Understand the Memory Mechanisms of Large Model Inference via 3D Interactive Lessons
An open-source interactive 3D visualization project that helps developers understand the memory management mechanisms in LLM inference from first principles, including core concepts like KV caching, pagination, quantization, and shared security.
Implementing Qwen 3.5 Inference from Scratch: A Deep Learning Project on CUDA and LLM Principles
An educational open-source project that helps developers gain an in-depth understanding of CUDA programming and the working principles of large language models by implementing the inference engine for Qwen 3.5's dense architecture from scratch.
LLM Judge AI: A Multi-Model Intelligent Evaluation Platform That Uses AI to Judge AI
An innovative multi-model comparison platform that simultaneously calls multiple large language models via OpenRouter and uses an AI Judge to automatically evaluate response quality, helping users find the most suitable model for specific tasks.
Delegator MCP: Asynchronous Task Orchestration for Multi-Agent Workflows and MCP Server
Delegator MCP is a TypeScript-based MCP server and asynchronous task orchestrator designed specifically for multi-agent workflows, offering AGY/Codex adapters, an Apple-style dashboard, and production-grade packaging support.
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