GitHub Radar

Building an LLM demo is easy compared with operating one. Once an application reaches users, teams need to know which model handled a request, how long it took, what it cost, whether the answer was useful and what changed after a prompt or provider update. TensorZero tries to bring those concerns into one open-source system. Its scope is ambitious: gateway, observability, evaluation, experimentation and optimization. That can reduce fragmentation, but it also creates a platform that must be designed and operated carefully. What TensorZero is TensorZero sits between an application and model providers. Requests pass through a common gateway that can route across supported services and self-hosted inference systems. The same platform records structured inference data, supports evaluations and experiments, and connects production feedback to later prompt or model improvements. The project is provider-agnostic rather than tied to one commercial API. This is useful when teams want fallback r...

Customer relationship management software tends to become infrastructure. Contacts, sales activity, email history, permissions and automation accumulate until moving to another platform becomes a major project. Twenty argues that this category should be more open: a modern CRM with APIs, customization and a path to self-hosting. That makes Twenty more interesting than a visual copy of Salesforce. It also means buyers need to evaluate the entire operational model, not only the interface. What Twenty is Twenty is an open-source CRM built with TypeScript, NestJS, PostgreSQL, Redis and React. It supports familiar CRM work such as contacts, companies, opportunities, views and workflows, while allowing teams to define custom objects and fields. Developers can work through REST and GraphQL APIs, webhooks and an application framework. The project’s positioning increasingly includes AI assistants and agents, but its core value remains a configurable system of record for customer data. Teams can...

Files are often the least convenient part of an AI workflow. A PDF may look clean to a reader but contain broken reading order. A PowerPoint deck can hide important text inside shapes. A spreadsheet mixes values, formulas and structure that do not translate naturally into a prompt. Microsoft’s MarkItDown approaches the problem with a practical target: convert supported documents into Markdown that software and language models can process. That goal makes MarkItDown useful, but it also defines its limits. It is a text-extraction and conversion tool, not a guarantee that every visual detail will survive. What MarkItDown does MarkItDown is a Python package and command-line tool for converting PDFs, Word documents, PowerPoint presentations, spreadsheets and other supported inputs into Markdown. The output can be searched, indexed, reviewed in version control or passed into retrieval and AI pipelines. The basic command is deliberately simple: point the tool at a file and redirect or sav...

CapCut proved that video editing could feel approachable without looking like a simplified toy. It also pushed many creators toward a product whose most useful features, cloud services, and platform decisions are controlled by one company. OpenCut takes the opposite approach: build an editor in public, keep it free and open source, and move as much of the editing workflow as possible onto the user's device. That makes OpenCut one of the most interesting open creator tools on GitHub. It does not, however, make it a complete CapCut replacement today. What OpenCut is OpenCut is an MIT-licensed video editor for the web, with desktop and mobile ambitions. Its current architecture combines a Next.js application with a growing Rust core. GPU compositing, effects, masks, timing, and WebAssembly bindings are being moved into Rust so the same foundation can eventually support browser, desktop, automation, and plugin use cases. The hosted editor is the easiest way to try it. Developers c...

GitHub's trending list moves quickly, but the most useful projects are not always the ones with the biggest one-day star count. For this edition of Weekly Radar, we looked for projects with a clear purpose, an identifiable licence, usable documentation, and enough technical substance to justify attention beyond the trend cycle. The result is a varied group: an ambitious virtual companion, a provider-neutral LLM library, a modular voice-agent stack, a local-first GIS platform, and a WebGPU building editor. All five are open source, but their maturity and operating costs differ significantly. 1. Project AIRI: an open digital companion with a very large roadmap Repository: https://github.com/moeru-ai/airi Licence: MIT Best for: developers experimenting with AI characters, real-time voice, avatars, and game integrations Pricing: open-source software; model, speech, and hosted API providers may charge separately Project AIRI aims to create a self-hosted digital companion that ca...