Laya for search and RAG
In retrieval pipelines Laya works best as a judge: is this passage relevant, does this evidence support the claim, should traversal continue. Projects use it to filter results and gate hallucinations. One published experiment found it is not a good general-purpose re-ranker.
88 projects
chat-seek-vscode
fstandhartinger
A VS Code extension searches chat archives and uses Laya to rerank matches
laya-jev-GraphRAG
bodepudimuneendra-netizen
Builds graph-based retrieval pipelines with swappable local Laya and cloud Jev decisions
laya-codex
pilotspace
Ranks repository code for Claude Code using the Laya re-ranker, hooks, and an MCP server
clinguard-laya-rag
saberfazliahmadi
Demonstrates a calibrated Laya decision layer for on-premises healthcare retrieval-augmented generation
jev-as-quant
jiayylu
Combines Laya and Jev with Claude in a quantitative research stack and evaluates trading experiments
laya-ara-rag
Wouze
Fine-tunes Laya multilingual for Arabic information retrieval and document reranking
laya-code
tindang
A Laya fine-tune that reranks code chunks by relevance to a task description
duckdb-jev-spatial
mraad
Adds DuckDB Jev-style SQL functions backed by a local Laya model for spatial examples
vi-law-laya
duclvQ
Reranks Vietnamese legal passages with a Laya-based relevance model fine-tuned for query answering
laya-kannaka-evidence-gate
flaukowski
Fine-tunes Laya to assess whether memory excerpts contain evidence needed to answer a question
laya-ara
ASNB-Smart-Solutions
Fine-tunes Arabic Laya models for NLU classification and short-list RAG
laya-needle
50bbx
Finds semantically relevant webpage passages with a locally running Laya model
laya-search
giaphutran12
Searches YC companies using local Laya inference or the TypeSafe Jev API
Cascade_Router
EllroyOfficial
Routes requests through a three-stage cascade using Laya decisions, RAG checks, and output safeguards
ownd-laya-search
ParkJH09
Fine-tunes Laya for semantic search-condition judgments across Korean sports-facility criteria
layaAsRagJudge
vishalmysore
Verifies RAG claims in the browser using Laya decisions and evaluates accuracy against labeled claims
laya-main
bill9924
Maps patent texts to OpenAlex concepts using TF-IDF retrieval and a Laya decision model
laya-reader
msudars
Ranks new arXiv papers against a reader profile using the local Laya model
jev-search
AnthonyDavidAdams
A Python library and CLI run decision-driven search with Jev or a local Laya backend
laya-compactor
Gjusev
Compacts RAG context by scoring and removing less relevant retrieved documents with Laya
laya-graph-harness
FMsongX2
Integrates a trained Laya model with Cognee and Neo4j for evidence-backed graph selection
DevPulse
CarlosGaubert
Aggregates technology news and uses Laya to classify relevance, topics, and impact
Nekomimi-Waifu-Seeker
CooLguNxDD
Uses Laya to guess anime and other fictional characters through typed decisions
opencode-memory
pedroteste00000008-stack
Adds long-term memory to OpenCode using Laya decisions, embeddings, reranking, and a local vector store
Filter and verify search results
zero-api-key-web-search searches the web without API keys and can add a local Laya relevance sieve:
pip install "zero-api-key-web-search[laya]" # pulls laya + torch
zero-search "react state management" --laya --laya-threshold 0.6 --json
zero-verify "Python 3.13 is the latest stable release" --laya --json
Without Laya installed, it falls back to a lexical verifier.
RAG claim checking
layaAsRagJudge runs the whole pipeline in the browser: chunking, MiniLM embeddings, top-k retrieval, then a Laya question asking whether the evidence supports the claim. An evaluation page scores 72 labelled claims.
GraphRAG
laya-jev-GraphRAG uses score, noul and choice questions for edge verification, entity disambiguation, A* traversal and a hallucination gate. It works across Neo4j, Memgraph, Apache AGE and Kùzu, with local Laya or cloud Jev.
Code retrieval
laya-codex ranks code for Claude Code with tree-sitter, BM25 and a Laya re-ranker (tindang/laya-code).
Long documents
laya-multilingual reads up to 8,192 tokens with max_len=8192. The core README reports 16 to 18 of 20 requests correct with up to about 4,000 tokens of text, and more variable results beyond that.
result = router.predict(long_document, questions, model="multilingual", max_len=8192)
Caveat: re-ranking
ai-experiments (nadeem4) re-ranked BM25 results for all 323 BEIR NFCorpus test queries. Jev improved nDCG@10 by +0.0347 and a MiniLM cross-encoder by +0.0204, while both Laya checkpoints ranked worse than doing nothing. Use Laya for yes/no relevance gates and claim checks. Measure before using it to reorder a ranked list.
More ways to use Laya