Introducing wrapture, a new Python library from Graham Dumpleton that extends the monkeypatching concepts of wrapt to support both testing and tracing simultaneously. It allows developers to wrap any function or method so that all accesses can be traced or overridden, serving as an alternative to unittest.mock and enabling observation of code without altering its behavior. Wrapture includes OpenTelemetry support and offers a configuration-based approach for adding tracing to existing projects, with the entire project and its documentation created under AI assistance.
Stealing Reasoning Traces from Proprietary LLM APIs A vanity domain name ( stolen-thoughts. com ) for a neat paper : Anthropic, OpenAI, and Google return encrypted chain-of-thought blocks to clients that can be replayed across sessions, users, and models.
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 introduces Hy4 Preview, a new large language model from Tencent featuring 770 B total parameters, 49 B active parameters, a 1 M token context window, and 1.56 TB of storage on Hugging Face. The release marks a significant increase over Hy3, which had 295 B total parameters, 21 B active parameters, a 256 k token context window, and 598 GB of storage. Willison also shares the model’s chat template, highlighting two reasoning effort levels—‘high’ (default) and ‘no_think’—and demonstrates a sample prompt that showcases the model’s reasoning trace. whyItMatters":"The article provides concrete details on Hy4’s scale and configuration, illustrating Tencent’s advancement in large‑language‑model capabilities and offering practical insights into its usage through the chat template and reasoning settings."
The article recounts a challenging debug session that was significantly aided by an AI assistant. Despite the AI initially claiming the problem was unsolvable and suggesting a report be written instead, it persisted, adding debug code and analyzing it as the author pushed forward. Ultimately, the author credits the AI with writing the commit message for the fix.
Release: alchemy-utils 0. 1a0 I've long pondered what a database agnostic version of my sqlite-utils Python library and CLI utility might look like.
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.
Release: llm-gemini 0. 33 It's been a while since the last llm-gemini release.
EVE Online is beginning its transition to Python 3, a move that will involve using the futurize script on 2.4 million lines of code and a manual review of about 20,000 differences between Python 2 and Python 3. The company has historically run on Stackless Python since 2003, with the last major upgrade in 2010 to Stackless Python 2.7. While the announcement does not detail how Stackless will be replaced, the team previously showcased a shift away from Stackless in their Carbon engine for EVE Frontier, leveraging the open‑source carbonengine/scheduler library.
Introducing Muse Glimmer Meta are back in the open weights game! Muse Glimmer is a brand new 30B model under a clean Apache 2.
Research: smolmachines / smolvm as a sandbox for untrusted Python & JavaScript I tasked Claude Fable 5 running in Claude Code for web with the following research task: Put https://smolmachines. com through its paces as a fast secure sandbox.
But then users start to report a weird bug. It's the 4th time your team has been trying to fix it.
The article reports that rumors of bugs in open‑source projects now trigger rapid security exploits, with automated agents probing for vulnerabilities within minutes of a patch being discussed. Anil Madhavapeddy demonstrates how modern coding agents can exploit even minimal hints, and rclone maintainer Nick Craig‑Wood notes a dramatic spike in security disclosures and delayed CVE assignments. The post highlights the need for new processes to protect open‑source communities from swift exploitation.