llm-openrouter 0.7
Release: llm-openrouter 0. 7 Now that this plugin is compatible with LLM 0.
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.
Release: llm-openrouter 0. 7 Now that this plugin is compatible with LLM 0.
Simon Willison comments on EmbeddingGemma 2, noting its Apache 2.0 license and expressing preference for open‑weight models over proprietary, hosted‑only options. He argues that embedding models are often used to generate and store large numbers of vectors, and a closed model could force costly re‑embedding if the vendor discontinues service. Willison prefers a hosted solution that allows him to switch to the open‑weight version if needed.
Simon Willison announces the release of the llm-openai-decisions 0.1a0 plugin, which interfaces with OpenAI’s new Jev-style Decisions API. The plugin, inspired by llm-typesafe, supports image and text input and offers the same three question types (yes/no, choices, scores) as Jev, with pricing at 10¢ per million input tokens. Installation is simple via `llm install llm-openai-decisions`, and an example query demonstrates image-based evaluation.
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 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.
Anthropic and OpenAI have introduced matching API credit benefits for their premium ChatGPT subscription plans. Subscribers paying $100, $200, or $500 per month receive an equivalent amount of expiring credits that can be applied to their respective APIs. The author, who holds subscriptions with both services, notes this allows for immediate use in public-facing demos without additional cost.
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 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 datasette-llm 0.1a9 introduces a small user‑experience improvement: the plugin now automatically detects the default LLM model, eliminating the need for users to manually configure a default model when running Datasette Agent. This change simplifies the setup process for users who previously had to specify a model with the `-s plugins.datasette-agent.default_model` option.
Anthropic has announced that it will donate the Agent Skills standard to the Agentic AI Foundation (AAIF), a Linux Foundation‑backed organization co‑founded with Block and OpenAI. The move follows Anthropic’s earlier declaration that skills would be an open standard and aligns with the AAIF’s recent role as the home of the Model Context Protocol (MCP). The donation is part of Anthropic’s commitment to keeping Agent Skills community‑driven and vendor‑neutral.
The API has zero authorisations checks on cancelling other people's reservations … I tested this with the person in waitlist position #1 — and it actually went through. So you've moved from #4 to #3 already.
The article explains how to create an inexpensive yet dependable model router using Jev, highlighting that model routing can now be considered a design decision rather than merely a system improvement. It outlines the steps and benefits of implementing this approach, emphasizing its practicality and cost-effectiveness. The piece serves as a guide for developers looking to integrate efficient model routing into their workflows.