📰 Story

LLM 0.32a0 is a major backwards-compatible refactor

I just released LLM 0.32a0 , an alpha release of my LLM Python library and CLI tool for accessing LLMs, with some consequential changes that I've been working towards for quite a while. Previous versions of LLM modeled the world in terms of prompts and responses. Send the model a text prompt, get back a text response. import llm model = llm . get_model ( "gpt-5.5" ) response = model . prompt ( "Capital of France?" ) print ( response . text ()) This made sense when I started working on the library back in April 2023. A lot has changed since then! LLM provides an abstraction over thousands of different models via its plugin system . The original abstraction - of text input that returns text output - was no longer able to represent everything I needed it to. Over time LLM itself has grown attachments to handle image, audio, and video input, then schemas for outputting structured JSON, then tools for executing tool calls. Meanwhile LLMs kept evolving, adding reasoning support and the ability to return images and all kinds of other interesting capabilities. LLM needs to evolve to better handle the diversity of input and output types that can be processed by today's frontier models. The 0.32a0 alpha has two key changes: model inputs can be represented as a sequence of messages, and model responses can be composed of a stream of differently typed parts. Prompts as a sequence of messages LLMs accept input as text, but ever since ChatGPT demonstrated the value of a two-way conversatio