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wtf is lilo?

facebookresearch/lilo — explained in plain English

Analysis updated 2026-07-17 · repo last pushed 2026-05-12

★ 12PythonAudience · researcherComplexity · 4/5MaintainedSetup · moderate

TL;DR

A Bayesian optimization tool that uses an LLM's plain-English judgments of candidate solutions to automatically find the option that best matches your stated preferences.

Mindmap

mindmap
  root((lilo))
    What it does
      Compares candidates via LLM
      Learns preferences from feedback
      Suggests next best options
    Tech stack
      Python
      LLM API
      YAML config
    Use cases
      Tune ML hyperparameters
      Optimize summarizer settings
      Compare design candidates
    Audience
      ML researchers
      Product teams
    Setup
      Bring your own LLM key
      Use synthetic test envs
      Configure via YAML

Code map

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filefunction / class

Why would anyone build with this?

REASON 1

Tune machine learning hyperparameters using natural-language feedback instead of manual scoring functions.

REASON 2

Optimize a text summarizer's tradeoffs between accuracy, length, and readability by describing preferences in words.

REASON 3

Compare candidate designs (like product settings) by having an LLM judge which one better fits your stated goals.

What's in the stack?

PythonYAML

How it stacks up

facebookresearch/liloaim-uofa/reasonmatchairbone42/360-data-athlete
Stars121212
LanguagePythonPythonPython
Last pushed2026-05-12——
MaintenanceMaintained——
Setup difficultymoderatehardhard
Complexity4/55/54/5
Audienceresearcherresearchergeneral

Figures from each repo's GitHub metadata at analysis time.

How do you spin it up?

Difficulty · moderate Time to first run · 1h+

Requires bringing your own LLM API key (OpenAI, Anthropic, etc.) to run experiments.

Yoink these prompts

Prompt 1
Help me plug my Anthropic API key into LILO's LLM template so I can run its optimization loop.
Prompt 2
Explain how LILO turns pairwise LLM comparisons into a model that predicts what I care about.
Prompt 3
Set up a LILO YAML config to optimize hyperparameters for my machine learning model.

Frequently asked questions

wtf is lilo?

A Bayesian optimization tool that uses an LLM's plain-English judgments of candidate solutions to automatically find the option that best matches your stated preferences.

What language is lilo written in?

Mainly Python. The stack also includes Python, YAML.

Is lilo actively maintained?

Maintained — commit in last 6 months (last push 2026-05-12).

How hard is lilo to set up?

Setup difficulty is rated moderate, with roughly 1h+ to a first successful run.

Who is lilo for?

Mainly researcher.

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