Ruslan Magana Vsevolodovna, esperta in Intelligenza Artificiale, Data Science, Machine Learning e sviluppo cloud, con tutorial su sistemi multi-agente e Watsonx.
23 articles from this blog
Tutorial on adding persistent memory to LangChain, LangGraph, and CrewAI using Matrix Context for document retrieval.
Build a chatbot with memory using Matrix Context in Python, no API keys needed, with local-first open-source engine.
Explores the concept of typed, budgeted, and auditable memory for AI agents, moving beyond flat retrieval to structured context management.
AutoSelf introduces self-consistency as a reliability primitive for autonomous multi-robot operations in remote environments like Mars.
Explores Mixture of Experts (MoE) in AI models, its sparse routing principle, and how it enables large model capacity with low compute cost per token.
Learn how to build a Python email triage agent using the ReAct (Reason + Act) pattern for step-by-step reasoning and tool use.
Tutorial on building a multi-agent email triage system in Python using AutoGen, with agents for analysis, reputation checking, and decision-making.
Tutorial on building a semantic search engine in Python using Sentence Transformers, FAISS, and embeddings for meaning-based document retrieval.
Step-by-step guide to deploying AI agents to production using Docker, FastAPI, and LangGraph with best practices.
Build an AI email triage agent using LangChain, LangGraph, and OpenAI in under 100 lines of Python code.
Introduces Agent-Matrix, an open-source OS for managing autonomous AI agents as living systems, aiming to eliminate maintenance.
A tutorial on building multi-agent systems using the universal-a2a-agent framework, covering HTTP endpoints, provider-agnostic design, and LangGraph integration.
A tutorial on building a multi-agent AI system with specialized agents using IBM's Watsonx Orchestrate platform and Docker.
A tutorial on building an AI agent with Watsonx.ai and integrating it using the Model Context Protocol (MCP) Gateway for seamless tool communication.
A tutorial on integrating IBM watsonx.ai models into Langflow to build visual RAG applications and AI workflows.
A tutorial on building a Retrieval-Augmented Generation (RAG) server using IBM Watsonx.ai, ChromaDB, and the Model Context Protocol (MCP) Python SDK.
A tutorial on building a production-ready chatbot server using IBM Watsonx.ai and the Model Context Protocol (MCP) Python SDK.
A guide to building a production-ready, vendor-neutral AI agent using IBM watsonx.ai, MatrixHub, and MCP Gateway, focusing on decoupled architecture.
Explains a neuro-symbolic system using a theorem prover to prevent GenAI hallucinations in enterprise actions, ensuring logical constraints are met.
Introducing Physica, a Physics World Model AI that enforces physical laws to prevent errors in AI-generated simulations, moving beyond token fluency.
