llm-openrouter 0.7
Release: llm-openrouter 0. 7 Now that this plugin is compatible with LLM 0.
The release of llm-keys-ui 0.1 introduces a plugin that allows users to manage API keys on remote machines without pasting them into the ChatGPT app. By running a simple command, the plugin provides a local or Tailscale URL for an interface where additional keys can be saved, and later retrieved via a shell command. This streamlines key management for coding agents used in LLM projects.
Release: llm-openrouter 0. 7 Now that this plugin is compatible with LLM 0.
The release of llm 0.33 introduces several key updates: it upgrades to the OpenAI Python library 3.x and switches the HTTP client from httpx to httpx2, adds comprehensive key handling for embedding functions, allows repeated template usage to combine configurations, and adds a reasoning_summary option for reasoning-capable responses. These changes improve compatibility, flexibility, and usability of the llm tool.
My comment on MCP was always a bad idea? — Hacker News.This article entirely misses the value that MCP brings today. Sure, there's almost no reason to use MCPs if you are running a full-blown te...
Simon Willison released the llm-typesafe 0.1a0 plugin, adding support for TypeSafe AI’s Jev model to the LLM tool. Users install it with `llm install llm-typesafe`, set an API key, and can then ask Jev-model questions such as yes/no, choice, or scoring queries via the `llm -m jev` command. The release includes examples for each question type and references a README for further details.
The article announces the release of Datasette 1.0a40, which includes a security fix identical to that in version 0.65.5, new features such as the ability for plugins to launch and manage background tasks via the datasette.add_background_task() method, and a migration to httpx2 to support features like datasette.client.get(). The update also contains numerous bug fixes, many of which were addressed during a recent triage effort for the upcoming 1.0 stable release.
OpenAI launched ChatGPT Work on July 9, offering two distinct products: Work Cloud, accessed via chatgpt.com or the mobile apps, and Work Local, available through the desktop app that can run programs on a user’s computer. Work Cloud is a paid‑only feature for $20/month and up subscribers, providing advanced capabilities such as code execution with internet access, a headless Chrome browser, and a persistent filesystem across sessions. The author notes that while ChatGPT Work claims to be better for tasks with clear outcomes, many users find the distinction unnecessary and prefer the standard Chat interface for most use cases.
Stop Making TUIs Thomas Ptacek advocates for building real native user interfaces for even the smallest of personal tools, because coding agents have reduced the cost of getting a usable-enough GUI up and running to almost nothing. I wrote about my vibe-coded bandwidth and GPU monitoring macOS task bar apps back in March , and I'm still using both of those on a daily basis.
The release of llm 0.34 introduces a new feature that enhances log output by including response duration in both milliseconds and a human‑readable format. The short log view now contains a dedicated duration_ms field. Additionally, the update incorporates multiple bug fixes and a notable performance boost to llm logs, attributed to waveplate integration.
The release of llm‑anthropic 0.27 updates the Anthropic plugin for LLM to be compatible with the newly released anthropic v1.0.0 Python library, which has switched from httpx to httpx2. This mirrors a similar change made by OpenAI in their v3.0.0 release two weeks prior. The update includes a migration guide and a pull request that ensures tests pass after upgrading to anthropic>=1.
The release of llm 0.36 introduces new OpenAI models gpt-6-sol and gpt-6-luna, and adds support for model plugins to declare that they do not support conversations via supports_conversation = False. When such models receive assistant or tool history, llm raises a ConversationNotSupported error and the chat interface rejects them before starting a session. Additional changes include wrapping reasoning traces in Markdown output with <details> tags and bug fixes from five contributors.
Farid Zakaria’s trynix.dev lets users run any Nix package from the past 13 years inside a browser‑based x86_64 Linux VM powered by QEMU‑WASM. By providing URL‑addressable packages, a user can simply navigate to a link such as https://trynix.dev/?pkg=python3%403.6.2, click "Load," and obtain an interactive shell running that specific package. The platform is also integrated with GitHub Actions, enabling pull‑request reviews that launch the PR’s build directly in the browser via trynix-preview.
Release: llm 0. 32.