#api-integration

#api-integration

The BoxLang AI module provides a unified interface to work with multiple different AI providers, simplifying the technical aspect of switching between services.

Imagine having the fastest, most knowledgeable assistant immediately available for any type of work at your request. That is exactly what AI agents are designed to be capable of.

The Next.js applications are configured to run on the same IP address, with one accessible from the root and the other at a specific branch path.

Richi Hartmann highlighted that the aim is to ensure a consistent set of APIs and a uniform JSON data schema for simple integration of Grafana dashboards across multiple applications.

Building LLM-powered applications is comparable to developing modern cloud-native applications, requiring notable support for REST and RPC protocols, where Go excels.

The currency converter application will empower users to easily convert amounts between different currencies using real-time exchange rates.

Scaling AI models from local tests to production involves managing significant resource requirements, with models needing up to 40GB of GPU memory for handling multiple requests efficiently.

TypeScript’s design enforces type safety from the start of the ETL process, reducing runtime errors from unexpected data types.

The advancements in deploying smaller-scale Large Language Models (LLMs) on edge devices face challenges like memory limitations but initiatives like MLC LLM allow compatibility across various hardware.

At WSO2Con in Barcelona, the company appears to have plenty of updates around Identity and Access Management in store.

This tutorial simplifies the integration with Microsoft 365 APIs by providing straightforward code examples to automate Outlook, Calendar, and SharePoint, streamlining complex processes.

Creating a Telegram bot can sound intimidating at first, but it's easier than you think. In this article, I'll guide you through the process of building a basic Telegram bot using Node.js.