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chore: import upstream snapshot with attribution
2026-07-13 12:24:24 +08:00

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# Benchmark configuration — single source of truth.
#
# All parameters aligned with the upstream evaluation reference so that
# benchmark numbers are directly comparable to published LoCoMo results.
# BenchmarkConfig reads this file on every run.
# --- EverOS server ---
cascade_timeout = 7200 # max seconds to wait for cascade + OME to complete
batch_size = 25 # messages per /add request (everos caps at 500)
# --- Search ---
methods = "agentic" # comma-separated: keyword, vector, hybrid, agentic
top_k = 10 # episodes to retrieve per question
eval_owner = "speaker_a" # which speaker's memory partition to query
# --- Answer LLM ---
answer_model = "gpt-4.1-mini" # LLM for generating answers from retrieved context
answer_temperature = 0.0 # deterministic answers
answer_max_tokens = 32768 # max output tokens per answer call
answer_timeout = 300.0 # per-request socket timeout (seconds)
answer_max_retries = 5 # retry budget (HTTP + empty-response retries)
# --- Judge LLM ---
judge_model = "gpt-4o-mini" # LLM judge for correctness evaluation
judge_temperature = 0.0 # deterministic judging
judge_timeout = 300.0 # per-request socket timeout (seconds)
judge_max_retries = 5 # retry budget
judge_runs = 3 # majority vote across N independent judge runs
# --- Concurrency ---
conversations_concurrency = 10 # how many conversations run at the same time
search_concurrency = 5 # concurrent /search requests per conversation
eval_concurrency = 20 # concurrent answer/judge LLM calls per conversation