Building a RAG Pipeline with llama.cpp in Python
Using llama. Source link
Using llama. Source link

In this notebook, we demonstrate how to build a fully in-memory “sensor alert” pipeline in Google Colab using FastStream, a high-performance, Python-native stream processing framework, and its integration with RabbitMQ. By leveraging faststream.rabbit’s RabbitBroker and TestRabbitBroker, we simulate a message…
This post is divided into three parts; they are: • Building a Semantic Search Engine • Document Clustering • Document Classification If you want to find a specific document within a collection, you might use a simple keyword search. Source…

Serverless computing has significantly streamlined how developers build and deploy applications on cloud platforms like AWS. However, debugging and managing complex architectures—comprising services such as Lambda, DynamoDB, API Gateway, and IAM—often requires developers to jump between logs, dashboards, and local…

In this Colab‑ready tutorial, we demonstrate how to integrate Google’s Gemini 2.0 generative AI with an in‑process Model Context Protocol (MCP) server, using FastMCP. Starting with an interactive getpass prompt to capture your GEMINI_API_KEY securely, we install and configure all…

As the deployment of artificial intelligence accelerates across industries, a recurring challenge for enterprises is determining how to operationalize AI in a way that generates measurable impact. To support this need, OpenAI has published a comprehensive, process-oriented guide titled “Identifying…