indifferentketchup
c935687725
Drop 9 batch proposals that are superseded by the boocode-lift-analysis (boocontext-audit, conductor upgrades, self-healing/verify-gate skills): add-3tier-memory, import-llm-evaluator, import-pregel-engine, plugin-platform, conductor-evolution, code-intelligence-upgrade, dev-workflow, ui-overhaul, agent-reliability. Delete 11 stub archive files (49-66B each, 'Status: Shipped. Archived.' only) that provide zero documentation value over the existing CHANGELOG.md + git tags.
63 lines
2.9 KiB
Markdown
63 lines
2.9 KiB
Markdown
# llama-cache-and-spec — KV cache quantization + ngram speculative decoding
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## Why
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BooCode's llama-sidecar runs llama-server with bare-minimum base args:
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`-ngl 999 -c 32768 --flash-attn on --no-mmap`. Two high-impact llama.cpp
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features are available but not enabled:
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1. **KV cache quantization** (`--cache-type-k q4_0`) — stores the KV cache
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in 4-bit instead of f32. ~4× VRAM reduction for the cache, which
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dominates memory usage at 32K context. No quality impact for most models.
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2. **Ngram speculative decoding** (`--spec-type ngram-mod`) — uses a
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lightweight rolling-hash ngram model (~16MB) to predict tokens ahead of
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the main model. The main model verifies them in batch. 2-3× tok/s
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speedup on repetitive/code tasks with no accuracy loss and no separate
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draft model to load.
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Both are disabled because they're in the **shadowing lists** of both
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validators (`llama-args-validator.ts` + sidecar `validator.go`), which
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auto-strip them from agent `llama_extra_args`. The fix is to either:
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(A) remove them from the shadow lists, or (B) add them directly to the
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sidecar's `BASE_ARGS` (which skips validation entirely).
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## What Changes
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- Sidecar base args gain the full set:
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- `--cache-type-k q4_0` — KV cache quantization (~4× VRAM savings)
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- `--cache-reuse 256` — KV cache reuse across turns (prompt caching)
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- `--slot-save-path /tmp/llama-slots` — disk-persistent KV cache
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- `--cache-idle-slots` — auto-save idle slot caches to disk
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- `--spec-type ngram-mod --spec-ngram-mod-thsh 2` — spec decoding
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- `--ctx-checkpoints 32` — context overflow protection
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- `--sleep-idle-seconds 600` — GPU memory reclaim when idle
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- `--metrics` — Prometheus metrics endpoint
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- Both validators keep existing shadow lists (correct as-is)
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- `/tmp/llama-slots` created for slot KV cache persistence
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## Dependencies
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- llama-sidecar repo (separate git tree, `/opt/forks/llama-sidecar/`)
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- BooCode server (`llama-args-validator.ts`, `provider.ts`)
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## Routing Change
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Previously, the llama-sidecar was only used when an agent had `llama_extra_args`
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set in its AGENTS.md frontmatter. The default path was llama-swap (no cache
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quant, no spec decoding, no slot save).
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Now, when `LLAMA_SIDECAR_URL` is configured (it is in docker-compose.yml),
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ALL inference requests route through the sidecar by default, regardless of
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whether the agent has `llama_extra_args`. This means:
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- Every request gets KV cache quantization, spec decoding, prompt caching
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- Agents with explicit `llama_extra_args` still get their overrides on top
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- If `LLAMA_SIDECAR_URL` is unset, falls back to llama-swap (backward compat)
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## Risk
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- `ngram-mod` spec decoding adds ~16MB memory. Trivial vs the 35B model.
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- KV cache quant to q4_0 is lossy vs f32 — undetectable on code tasks.
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- Both well-tested in llama.cpp ecosystem. No known regressions.
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- If issues, remove from base args and restart — no code change needed.
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