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dl4rce/flaiwheel

v3.7.1 Breaking

This release includes 2 breaking changes for platform teams planning a safe upgrade.

Published 3mo MCP Search & Web
✓ No known CVEs patched
Read the diff → Tool health → What is this tool? →

✓ No known CVEs patched in this version

Summary

AI summary

Embedding model defaults changed from MiniLM-L6-v2 to MiniLM-L12-v2 and reranker enabled with an updated model.

Full changelog

What's new in v3.7.1

New defaults

| Setting | Old | New |
|---|---|---|
| Embedding model | all-MiniLM-L6-v2 | all-MiniLM-L12-v2 |
| Reranker | disabled | enabled |
| Reranker model | ms-marco-MiniLM-L-6-v2 | ms-marco-MiniLM-L-12-v2 |

MiniLM-L12-v2 — same speed class as L6, better quality, ~130MB.

MS MARCO MiniLM-L-12-v2 reranker — cross-encoder trained on passage retrieval. Re-scores the top candidates after initial vector+BM25 retrieval for significantly better search precision. Adds ~50ms latency per search.

Both models are downloaded to the persistent /data/models volume on first container start (not baked into the image).

Breaking Changes

  • Embedding model default changed from `all-MiniLM-L6-v2` to `all-MiniLM-L12-v2`
  • Reranker feature is now enabled by default and uses model `ms-marco-MiniLM-L-12-v2` instead of being disabled

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About dl4rce/flaiwheel

Self-hosted memory and governance layer for AI coding agents. 28 MCP tools with structured knowledge capture, hybrid search (semantic + BM25 + cross-encoder reranking), behavioral documentation nudges, cold-start codebase analyzer, and git-native storage. Single Docker container, zero cloud dependencies.

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Beta — feedback welcome: [email protected]