MoonEmbed

MoonEmbed is a MoonBit-first library for working with word embeddings locally.

Repository links:

• GitHub: https://github.com/wskwsk68/MoonEmbed
• GitLink: https://gitlink.org.cn/wskwsk68/MoonEmbed

What it does

• Load word2vec text embeddings
• Load GloVe-style text embeddings
• Load word2vec binary embeddings
• Normalize vectors for cosine search
• Search with a tiny bucketed approximate index and exact fallback
• Provide a small CLI demo and test coverage

Why this shape

The contest page encourages a public repository, clear README, runnable example, CI, tests, and an OSI license. MoonEmbed stays focused on one practical niche: semantic word lookup without depending on Python or a database.

Contest readiness:

• single contributor
• commit history expanded into multiple meaningful steps
• public-source-only implementation
• clear source notes and OSI license

I deliberately kept it narrower than a general vector database so it does not overlap too closely with existing MoonBit ecosystem work such as broader ANN/vector DB packages.

Repository layout

• MoonEmbed.mbt library code
• MoonEmbed_test.mbt tests
• cmd/main/main.mbt CLI demo
• LICENSE Apache-2.0
• .github/workflows/ci.yml basic build/test CI

Usage

Build and test:

moon test
moon run cmd/main

Example API:

let corpus = EmbeddingCorpus::from_glove_text(
  "king 0.92 0.10 0.00\nqueen 0.90 0.14 0.00\n",
)
let index = MoonEmbedIndex::from_corpus(corpus, signature_bits=3)
let report = index.search_token("king", 3)
println(format_report(report))

Source notes

This repository is original MoonBit code written for the contest. If you later extend it with upstream data, ports, or borrowed algorithms, document the source, license, and porting scope clearly in this section before submission.

License

Apache-2.0