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feat(llm): upgrade web-llm to 0.2.86 and default to Gemma 4 E2B - #30
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- Pin web-llm 0.2.86 in llm-rag.js and llm-worker.js - Re-audit downloadBytes for all 22 models against the rebuilt v0_2_86 WASM libraries (weights and VRAM are unchanged) - Add gemma-4-E2B-it-q4f16_1-MLC as a direct, limited-RAG-tier option with its 4K prebuilt context; document the size formula - Test that the main thread and worker pin the same web-llm build
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- Gemma 4 E2B moves to the recommended group and RAG tier as the only isDefault model; Llama 3.2 3B stays in the recommended group - New installs persist their config on first read. An install that already downloaded models but never saved a setting is pinned to the previous default (Llama 3.2 3B), and saved configs are not migrated, so no existing user gets a surprise 2.84 GB download
arminpasalic
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October 24, 2026 13:33
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Upgrades web-llm 0.2.84 → 0.2.86 and makes Gemma 4 E2B (
gemma-4-E2B-it-q4f16_1-MLC) the default model for new installs.Upgrade
llm-rag.js,llm-worker.js) now pin 0.2.86. A new test keeps the two in step.v0_2_86), so I re-measured everydownloadBytes(each +0.7–1.0 MB). The formula is now documented inmodel-constraints.jsand reproduces the previous audit byte for byte.Gemma 4 E2B as the default
recommendedRAG tier, the onlyisDefaultmodel.context_window_size.q4f32_1skipped).model_manifestpath.Existing users keep their model (new installs only)
STORAGE_VERSIONbump: saved configs on Llama 3.2 3B are not migrated.model_id, so it would have switched silently.getConfig()now handles the first read without a stored config. Ifvectoria_models_readyorvectoria_models_cachedis set, it pins Llama 3.2 3B. It always saves the result, so a new install can't later look like an old one.Verification
npm run check: 233 unit tests (new tests cover the default and the new-installs-only behaviour), 16 wasm tests, build, stamp checknpm audit(root and mcp-server): 0 vulnerabilitiesDEFAULT_CONFIGand the catalog agree on the defaultDraft until the browser test is done.