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Topics: agents

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2 repositories by Attention Score · May 7, 2026 – Nov 2, 2026 (UTC)

Language: Ruby
Topic: agents
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1.crmne / ruby_llm

The Ruby AI framework.

llm
ruby
ai
anthropic
embeddings
gemini
+14 more

Ruby MIT4.5K total530 forks

+625 stars

from 3,865 · score 6.44

2.patterns-ai-core / langchainrb

Build LLM-powered applications in Ruby

artificial-intelligence
machine-learning
ml
rubyml
vector-search
agents
+1 more

Ruby MIT2K total270 forks

+41 stars

from 1,966 · score 3.74

Order: Attention Score

Most net stars gained in the window first. The score only puts this gain on a log scale, so the order is the order of the gain.

How the ranking works

Ranked by stars gained in the window. The score is the natural log of one plus that gain, so a repository's rank is exactly its star gain's rank.

score = log1p(net stars gained in the trailing T complete UTC days)

A repository is ranked only when its Star History covers every day of the window and its latest Observation is not missing.

The longest window is 180 days. Star History from the Repository Host goes back at most 180 days before a repository's first Observation. A longer window needs more days of Observations first. A repository younger than the window is not ranked in it.

The filters narrow the same eligible repositories. A repository matches the topics when it has any of them. Total stars is the count now. Last push and creation on the Repository Host count back from the start of today (UTC). The counts beside the languages, licenses, and topics include all ranked repositories in the window. A Tag holds the repositories that have it; see Tags.

Repositories enter the index from the Seed Dataset or by gaining stars faster than the published admission threshold, whatever their size. Admission is permanent, so an archived repository can still rank.

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