wehub-resource-sync
55 lines
1.4 KiB
Markdown
55 lines
1.4 KiB
Markdown
# <YYYY-MM-DD> — <benchmark-name>
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**Commit:** `<sha>`
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**Bench:** LongMemEval `_s` / coding-agent-life-v1 / ...
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**N:** 500 / 15 / ...
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**K:** 5
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**Hardware:** macos-15 / ubuntu-22.04 / ...
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**OpenAI model:** text-embedding-3-small
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**Anthropic model:** N/A (no LLM in retrieval loop)
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## Headline
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agentmemory-hybrid: **R@5 = XX.XX%**, P@5 = XX.XX%, p50 latency = XXms
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Beats grep baseline by +X.Xpt R@5, vector by +X.Xpt R@5.
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## Per-adapter
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| Adapter | P@5 | R@5 | Hit rate | p50 latency |
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|---|---|---|---|---|
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| grep | | | | |
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| vector | | | | |
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| agentmemory-hybrid | | | | |
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## Per-question-type
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| Type | grep R@5 | vector R@5 | agentmemory R@5 |
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|---|---|---|---|
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| single-session-bug | | | |
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| single-session-refactor | | | |
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| preference | | | |
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| multi-session-causal | | | |
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| temporal | | | |
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## Methodology
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- Sessions ingested via `POST /agentmemory/remember` with `type=eval-session`
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- Queries hit `POST /agentmemory/smart-search` with `limit=k*4`
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- No LLM in retrieval loop. Direct rank from hybrid scoring.
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- Ranks dedup by sessionId before truncating to K
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- Latency measured as init+query for LongMemEval (per-question fresh state), query-only for coding-life (shared state)
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## Reproduce
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```sh
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git checkout <sha>
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npm install --legacy-peer-deps
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OPENAI_API_KEY=sk-... AGENTMEMORY_BASE_URL=http://localhost:3111 \
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npm run eval:longmemeval -- --stratify 10
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```
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## Notes
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<what surprised, what regressed, what's load-bearing>
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