Open-source LLMs as LangChain Agents

Introducing Agents.js: Give tools to your LLMs using JavaScript

Introducing AnyLanguageModel: One API for Local and Remote LLMs on Apple Platforms

Understanding and Implementing Qwen3 From Scratch

A Detailed Look at One of the Leading Open-Source LLMs

Components of A Coding Agent

How coding agents use tools, memory, and repo context to make LLMs work better in practice

Consilium: When Multiple LLMs Collaborate

Seven Security Challenges in Cross-domain Multi-agent LLM Systems

arXiv:2505. 23847v5 Announce Type: replace-cross Abstract: Large language models (LLMs) are rapidly evolving into autonomous agents that cooperate across organizational boundaries, enabling joint disaster response, supply-chain optimization, and other tasks that demand decentralized expertise without surrendering data ownership.

Open-Source Text Generation & LLM Ecosystem at Hugging Face

Seven Security Challenges That Must be Solved in Cross-domain Multi-agent LLM Systems

arXiv:2505. 23847v4 Announce Type: replace-cross Abstract: Large language models (LLMs) are rapidly evolving into autonomous agents that cooperate across organizational boundaries, enabling joint disaster response, supply-chain optimization, and other tasks that demand decentralized expertise without surrendering data ownership.

CodeGemma - an official Google release for code LLMs

LLMs help robots understand vague instructions and focus on key details

To help robots do chores in places like homes and factories, a new approach from MIT uses one language model to clarify users’ instructions, then another to ignore irrelevant info.

Understanding Issues, Causes and Solutions in Open-Source LLM-based Multi-Agent Systems

The paper investigates challenges in open‑source large‑language‑model (LLM) based multi‑agent systems (MAS). By analyzing 944 issues extracted from 21 projects, it finds that orchestration and execution problems are most common, with workflow, tool integration, and memory issues as primary causes. The predominant remedy identified is optimizing workflow, and the study offers empirically grounded implications for improving orchestration, tool integration, and memory mechanisms in LLM‑based MAS.

Build an LLM Agent That Can Write and Run Code

A hands-on walkthrough of code execution with the OpenAI Agents SDK and Docker The post Build an LLM Agent That Can Write and Run Code appeared first on Towards Data Science .