Docker is making it easier for developers to run and test AI Large Language Models (LLMs) on their PCs with the launch of Docker Model Runner, a new beta feature in Docker Desktop 4.40 for Apple silicon-powered Macs. It also integrates the Model Context Protocol (MCP) for streamlined connections between AI agents and data sources.
A repository containing extracted system prompts and tools for various AI models including FULL v0, Cursor, Manus, Same.dev, Lovable, Devin, Replit Agent, Windsurf Agent, and VSCode Agent. It offers insights into the structure and functionality of these models and includes a security notice for AI startups.
Bethere.ai: The author introduces bethere.ai, a platform built to natively support both flows and state machines for building hybrid conversational experiences.
SWE-agent is an agent that uses a language model (like GPT-4) to automatically fix GitHub issues, perform web tasks, solve cybersecurity challenges, or execute custom tasks through configurable agent-computer interfaces.
SWE-agent is an open-source tool that utilizes large language models (LLMs) like GPT-4o and Claude Sonnet 3.5 to autonomously fix bugs in GitHub repositories, solve cybersecurity challenges, and perform complex tasks. It features a mode called EnIGMA for offensive cybersecurity and prioritizes simplicity and adaptability.
This article details building a Retrieval-Augmented Generation (RAG) system to assist with research paper tasks, specifically question answering over a PDF document. It covers document loading, splitting, embedding with Sentence Transformers, using ChromaDB as a vector database, and implementing a query interface with LangChain.
This article details new prompting techniques for ChatGPT-4.1, emphasizing structured prompts, precise delimiting, agent creation, long context handling, and chain-of-thought prompting to achieve better results.
Solo.io donated Kagent, its open source framework for AI agents in Kubernetes, to the CNCF, and introduced MCP Gateway. They also unveiled automated zero-downtime migration and cost-analysis tools for Ambient Mesh.
This tutorial demonstrates how to integrate Google’s Gemini 2.0 with an in-process Model Context Protocol (MCP) server using FastMCP, creating tools for weather information and integrating them into Gemini's function calling workflow.
This paper proposes the Knowledge Graph of Thoughts (KGoT) architecture for AI assistants, integrating LLM reasoning with dynamically constructed knowledge graphs to reduce costs and improve performance on complex tasks like the GAIA benchmark.
