perf(agent): prune ARIA observations incrementally#55
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Track observation messages already scanned so pruning old ARIA payloads does not rescan the full transcript after every appended message. Reset the incremental state on compaction and run reset. Corrected eval on this branch: prune_aria_ms 174.4 ms to 120.5 ms with behavior hash preserved.
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@microsoft-github-policy-service agree company="Weco AI" |
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Summary
ruff.Benchmark
Deterministic micro-benchmark for
DefaultAgent._prune_old_observation_aria_snapshots, simulating 50 browser observations with ~20 KB ARIA payloads:prune_aria_msThat is a 30.9% reduction, with the behavior hash preserved:
37a80de01c7fdb4543e7ac82a1ad9e60a6b9d92965a2e14596edc2b81f4d17b4.Supplementary autoresearch: public dashboard.
Validation
uvx ruff check --fix .PYTHONPATH="$WT/src" uv run --with pytest pytest tests/unit/test_default_agent_aria_pruning.py tests/unit/test_tool_model_routing.py tests/unit/test_doctor.py -quvx ruff check src/webwright/agents/default.py tests/unit/test_default_agent_aria_pruning.pygit diff --check