OpenRouter advertises automatic fallback and cost‑effective routing to the best backend provider for a single API endpoint. However, Mohamed Moustafa highlights that different providers use varied serving software, optimizations, and capabilities, leading to inconsistent behavior across the same endpoint. Users can mitigate this by specifying a provider with the provider.only option and checking available providers via the /endpoints method.
The article announces the release of version 0.7.1 of the llm-openrouter library. It highlights a performance fix that improves the loading of OpenRouter models. The release acknowledges a contribution from waveplate.
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.
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.
Release: llm 0. 32.
The article announces the release of llm version 0.35, which introduces a new OpenAI model named gpt-6-astra for GPT-6 Astra. It highlights the addition of this model to the llm library and tags the release with openai, llm, and gpt-6-astra.
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.
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 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.
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.
The article announces the release of Datasette 1.0a41, highlighting new OpenTelemetry support added by Alec Garcia and a refactor that consolidates all modal dialogs into a single Web Component, now documented for plugin use.
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.