PipesHub brings together data from Slack, Jira and GitHub for internal search and AI agents. Version 1.0.0 adds code graphs ...

Vector stores have been part of the Python experience in Semantic Kernel for some time. With Microsoft Agent Framework, we have ported that work forward rather than starting over. This post focuses on ...

While development using cloud-based generative AI APIs is becoming common, the demand for "local LLMs"—running models on internal infrastructure or local machines—is rapidly increasing to ensure the ...

Qdrant is an open-source and fully managed high-performance Vector Database. The vector search engine provides a production-ready service with a convenient API to store, search, and manage vectors ...

A real AI pipeline rarely runs on a single model. This article shows how to serve an SLM, an OCR model, an NER model, a reranker, and an object detector, through a serving layer on a single GPU. Small ...

Aggy is a veteran writer and editor in the technology and gaming space. Having served as a Managing Editor for high-traffic digital publications, alongside being an editor and consultant for over a ...

Hermes Agent already remembers across sessions. The open-source agent from Nous Research ships with curated memory files and full-text session search. But a new community project argues that built-in ...

Hermes Agent is an open-source, self-improving AI agent framework built by Nous Research — the same lab behind the Hermes, Nomos, and Psyche model families. Launched on February 25, 2026, it ...

AI WEEK brings together over 700 international speakers, 250+ AI Exhibitors and 25,000 +attendees across 10 stages, uniting managers, entrepreneurs, engineers, researchers, and innovators shaping the ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

In this tutorial, you build a retrieval-augmented generation (RAG) pipeline over documents stored in Azure Files. The pipeline uses LlamaIndex for orchestration and Qdrant as the vector database.