酱牛肉 fd6aed42c9 feat(meta-reme): add dataset preparation layer with YAML-driven workspace init ... - Add meta-reme/run.py entry point loading a single --config YAML and preparing the workspace via the data_preparation module. - Add meta-reme/data_preparation/ (basic, lme, beam) normalizing BEAM and LongMemEval training cases into the shared CaseSpec/SessionSpec/QuerySpec contracts with reproducibility manifests and read-only case files. - Add per-benchmark config_meta_reme.yaml and run_meta.py launchers for beam and longmemeval that forward to the unified entry point. - Add tests/unit_sandbox/test_meta_reme_run.py covering case selection, read-only writes, empty-dir init, BEAM variant/time-anchor parsing, and config loading. - Update meta-reme/design.md to reflect the single-config CLI and the renamed data_preparation/ structure.		2026-08-07 02:06:06 +08:00
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beam	feat(meta-reme): add dataset preparation layer with YAML-driven workspace init	2026-08-07 02:06:06 +08:00
longmemeval	feat(meta-reme): add dataset preparation layer with YAML-driven workspace init	2026-08-07 02:06:06 +08:00
toolmemory	docs(benchmark): add toolmemory archive (#413)	2026-08-05 16:03:03 +08:00