Prompts as WASM Programs
AICI is a proposed common interface between LLM inference engines (llama.cpp, vLLM, HF Transformers, etc.) and "controllers" - programs that can constrain the LLM output according to regexp, grammar, or custom logic, as well as control the generation process (forking, backtracking, etc.). AICI is based on Wasm, and is designed to be fast (runs on CPU while GPU is busy), secure (can run in multi-tenant cloud deployments), and flexible (allow libraries like Guidance, LMQL, Outlines, etc. to work on top of it). We (Microsoft Research) have released it recently, and would love feedback on the…
In plain words
AICI is a standardized interface that connects large language model inference engines like llama.cpp and vLLM with controller programs written in WebAssembly. These controllers constrain LLM output using regular expressions, grammars, or custom logic, and can manage the generation process through forking and backtracking. Developed by Microsoft Research, AICI is designed to execute efficiently on CPUs while GPUs handle inference, operate securely in shared cloud environments, and enable libraries like Guidance and Outlines to build on top of it.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
AICI is a proposed common interface between LLM inference engines (llama.cpp, vLLM, HF Transformers, etc.) and "controllers" - programs that can constrain the LLM output according to regexp, grammar, or custom logic, as well as control the generation process (forking, backtracking, etc.). AICI is based on Wasm, and is designed to be fast (runs on CPU while GPU is busy), secure (can run in multi-tenant cloud deployments), and flexible (allow libraries like Guidance, LMQL, Outlines, etc. to work on top of it). We (Microsoft Research) have released it recently, and would love feedback on the design of the interface, as well as our Rust AICI runtime. I'm the lead developer on this project and happy to answer any questions!
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