Google has released the MCP Toolbox for Databases, a new open-source module under its GenAI Toolbox aimed at simplifying the integration of SQL databases into AI agents. The release is part of Google’s broader strategy to advance the Model Context Protocol (MCP), a standardized approach that allows language models to interact with external systems—including tools,…
In this advanced tutorial, we aim to build a multi-agent task automation system using the PrimisAI Nexus framework, which is fully integrated with the OpenAI API. Our primary objective is to demonstrate how hierarchical supervision, intelligent tool utilization, and structured outputs can facilitate the coordination of multiple AI agents to perform complex tasks, ranging from…
Osmosis AI has open-sourced Osmosis-Apply-1.7B, a fine-tuned variant of Qwen3-1.7B, designed to perform highly accurate and structured code merge tasks. Drawing inspiration from IDE agents like Cursor’s “instant apply,” Osmosis-Apply-1.7B is optimized for context-sensitive, function-level code edits. The model achieves strong performance with fewer parameters compared to much larger foundation models by leveraging code-specific formatting…
ByteDance, the Chinese tech giant behind TikTok and other global platforms, has officially released Trae Agent, a general-purpose software engineering agent powered by large language models (LLMs). Designed to execute complex programming tasks via natural language prompts, Trae Agent offers a highly capable and extensible Command-Line Interface (CLI), redefining how developers can interact with their…
The Agent Communication Protocol (ACP) is an open standard designed to enable seamless communication between AI agents, applications, and humans. As AI systems are often developed using diverse frameworks and infrastructures, they can end up isolated and incompatible, limiting their ability to collaborate. ACP addresses this fragmentation by offering a unified RESTful API that facilitates:…
Introduction: What is Context Engineering? Context engineering refers to the discipline of designing, organizing, and manipulating the context that is fed into large language models (LLMs) to optimize their performance. Rather than fine-tuning the model weights or architectures, context engineering focuses on the input—the prompts, system instructions, retrieved knowledge, formatting, and even the ordering of…
In this tutorial, we implement the BioCypher AI Agent, a powerful tool designed for building, querying, and analyzing biomedical knowledge graphs using the BioCypher framework. By combining the strengths of BioCypher, a high-performance, schema-based interface for biological data integration, with the flexibility of NetworkX, this tutorial empowers users to simulate complex biological relationships such as…
Together AI has released DeepSWE, a state-of-the-art, fully open-sourced software engineering agent that is trained entirely through reinforcement learning (RL). Built on top of the Qwen3-32B language model, DeepSWE achieves 59% accuracy on the SWEBench-Verified benchmark and 42.2% Pass@1, topping the leaderboard among open-weight models. This launch represents a significant shift for Together AI, from…
In this tutorial, we walk you through the seamless integration of AutoGen and Semantic Kernel with Google’s Gemini Flash model. We begin by setting up our GeminiWrapper and SemanticKernelGeminiPlugin classes to bridge the generative power of Gemini with AutoGen’s multi-agent orchestration. From there, we configure specialist agents, ranging from code reviewers to creative analysts, demonstrating…
Rare diseases impact some 400 million people worldwide, accounting for over 7,000 individual disorders, and most of these, about 80%, have a genetic cause. Notwithstanding their incidence, diagnosing rare diseases is notoriously difficult. Patients already suffer through lengthy diagnostic processes that average more than five years, often resulting in sequential misdiagnoses and invasive procedures. All…