frank-primary: autoresearch bench harness (decode t/s @32k)
autoresearch.sh (dev box) scp's the candidate scripts/frank-primary.env + the bench script to dankserver and runs it over ssh. scripts/autoresearch-frank-primary.sh (dankserver) follows the bench policy: stop frank-primary (relink unit: stop, not mask), boot a scratch radiance container (arbench) on the same two cards with the candidate argv, poll /health, run ONE self-contained greedy completion (fixed ~140k-char real-text prompt -> ~32k tokens, 256-token decode), parse the engine timings into METRIC lines, tear the scratch down, and restore production via a trap. Fresh prefix-cache tier per run for cold prefill. Baseline validated: decode_tps=31.70, prefill_tps=465.4, ttft_ms=93745, draft_accept=0.831 at prompt_n=43627.
This commit is contained in:
Frank
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#!/usr/bin/env bash
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# autoresearch.sh — canonical benchmark entrypoint: speed of frank-primary.
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# autoresearch.sh — canonical frank-primary benchmark entry point (dev box).
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#
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# Runs on the operator box and drives one bench window on DANKSERVER:
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# 1. fingerprint the candidate trio (env + serve script + unit)
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# 2. memo fast-path: an identical fingerprint that already produced a FULLY
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# successful window (bench + verified production restore) returns the
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# cached metrics without touching the fleet
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# 3. stage the candidate trio plus the measure client into
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# /home/dank/.autoresearch-frank-primary/ (ephemeral; the repo checkout
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# on the host stays the production source of truth)
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# 4. run the window (scripts/autoresearch/frank-primary-window.sh):
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# stop + mask the production unit, boot the staged config AS THE SERVICE
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# (same serve script, same container, same port 7770), wait for health,
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# run the in-container usage-counter measure, then restore the production
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# unit and verify its health — AGENTS.md Benchmarking Policy
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# 5. print METRIC lines (parse by run_experiment)
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#
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# Primary metric: decode_tps (HIGHER is better) — median across the three
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# prompt depths (115/1056/4096) of per-depth medians of
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# completion_tokens / (wall - ttft), 3 runs each after a warm pass,
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# temperature 0, the campaign's deterministic word-seed workload.
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#
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# Exit 0 with METRIC lines on success; non-zero on any failure (the window
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# script's EXIT trap restores production on every path).
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set -euo pipefail
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# The service runs on dankserver (192.168.0.235:7770), the two R9700s live
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# there, and the benchmark must own those cards, so the whole stop -> boot
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# scratch -> bench -> restore sequence runs ON dankserver (see
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# scripts/autoresearch-frank-primary.sh). This wrapper:
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# 1. copies the candidate config (the repo's scripts/frank-primary.env, the
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# file the autoresearch loop edits) and the bench script to dankserver,
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# 2. runs the bench over ssh, relaying its stdout (the METRIC lines) and
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# exit code back here verbatim.
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# It deliberately does NOT push to origin: the scp dirties dankserver's
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# working tree, and the loop's uncommitted candidate config must not be
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# pushed. Only this file and scripts/autoresearch-frank-primary.sh are
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# committed; the candidate env rides over ssh each run.
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set -uo pipefail
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DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
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REMOTE=dankserver
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REMOTE_REPO=/home/dank/serverAppConfigs
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SCRIPT_DIR="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" && pwd)"
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HOST="${FRANK_PRIMARY_AR_HOST:-dankserver}"
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STAGE="/home/dank/.autoresearch-frank-primary"
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scp -q "$DIR/scripts/frank-primary.env" \
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"$REMOTE:$REMOTE_REPO/scripts/frank-primary.env" || { echo "scp env failed" >&2; exit 1; }
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scp -q "$DIR/scripts/autoresearch-frank-primary.sh" \
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"$REMOTE:$REMOTE_REPO/scripts/autoresearch-frank-primary.sh" || { echo "scp script failed" >&2; exit 1; }
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# FRANK_PRIMARY_AR_ENV_FILE stages a DIFFERENT env than the repo's — that is how
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# the arms driver A/Bs engine knobs without mutating the checkout. The
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# fingerprint covers whatever file is staged, so the memo cannot cross arms.
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ENV_FILE="${FRANK_PRIMARY_AR_ENV_FILE:-$SCRIPT_DIR/scripts/frank-primary.env}"
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SERVE="$SCRIPT_DIR/scripts/serve-frank-primary.sh"
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UNIT="$SCRIPT_DIR/scripts/frank-primary.service"
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MEASURE="$SCRIPT_DIR/scripts/autoresearch/frank-primary-measure.py"
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WINDOW="$SCRIPT_DIR/scripts/autoresearch/frank-primary-window.sh"
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for f in "$ENV_FILE" "$SERVE" "$UNIT" "$MEASURE" "$WINDOW"; do
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[ -f "$f" ] || { echo "[autoresearch] missing harness file: $f" >&2; exit 1; }
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done
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command -v python3 >/dev/null 2>&1 || { echo "[autoresearch] python3 required on operator box" >&2; exit 1; }
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# Fingerprint of everything that can change the engine's argv or environment.
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HASH="$(cat "$ENV_FILE" "$SERVE" "$UNIT" | sha256sum | cut -d' ' -f1)"
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echo "[autoresearch] candidate fingerprint $HASH" >&2
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ssh_run() { ssh -o BatchMode=yes -o ConnectTimeout=15 "$HOST" "$@"; }
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emit_metrics() { # $1 = run.json
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python3 -c '
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import json, sys
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run = json.loads(sys.argv[1])
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m = run["measure"]
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print("METRIC decode_tps=%s" % m["decode_tps"])
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for k in ("decode_tps_115", "decode_tps_1056", "decode_tps_4096"):
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print("METRIC %s=%s" % (k, m[k]))
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print("METRIC ttft_ms_4096=%s" % m["ttft_ms_4096"])
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print("METRIC kv_tokens=%s" % (run.get("kv_tokens") or 0))
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print("METRIC boot_seconds=%s" % (run.get("boot_seconds") or -1))
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print("METRIC completion_tokens_4096=%s" % m.get("completion_tokens_4096", 0))
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# Any extra sampling temperature the measure swept (AR_TEMPS), e.g. the 0.7
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# arm — that is where speculative-decode acceptance shows up, since a greedy
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# draft matches a greedy target exactly and is rejected more under real
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# sampling. Suffixed keys only (_t0.7), so the historical lines are untouched.
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for k in sorted(m):
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if "_t" in k and (k.startswith("decode_tps") or k.startswith("ttft_ms")):
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print("METRIC %s=%s" % (k, m[k]))
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' "$1"
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}
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# --- memo fast-path -------------------------------------------------------
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cached_hash="$(ssh_run "cat '$STAGE/last/hash' 2>/dev/null" 2>/dev/null || true)"
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if [ -n "$cached_hash" ] && [ "$cached_hash" = "$HASH" ]; then
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cached_run="$(ssh_run "cat '$STAGE/last/run.json' 2>/dev/null" || true)"
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if [ -n "$cached_run" ]; then
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echo "[autoresearch] memo hit — cached metrics for $HASH, fleet untouched" >&2
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emit_metrics "$cached_run"
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exit 0
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fi
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fi
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# --- stage the candidate ----------------------------------------------------
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echo "[autoresearch] staging candidate on $HOST:$STAGE" >&2
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ssh_run "mkdir -p '$STAGE'"
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scp -q "$ENV_FILE" "$HOST:$STAGE/frank-primary.env"
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scp -q "$SERVE" "$HOST:$STAGE/serve.sh"
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scp -q "$MEASURE" "$HOST:$STAGE/measure.py"
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scp -q "$WINDOW" "$HOST:$STAGE/window.sh"
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ssh_run "printf '%s\n' '$HASH' > '$STAGE/hash'"
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# --- the window -------------------------------------------------------------
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# Budgets: bench boot up to 20 min (warm boots measured ~7 min), measure up
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# to 30 min, restore boot up to 20 min — call run_experiment with
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# timeout_seconds >= 3600.
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echo "[autoresearch] opening bench window (stop+mask -> boot -> measure -> restore)" >&2
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set +e
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ssh_run "bash '$STAGE/window.sh'"
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rc=$?
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set -e
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if [ "$rc" -ne 0 ]; then
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echo "[autoresearch] window failed (rc=$rc); host-side evidence:" >&2
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ssh_run "tail -60 '$STAGE/fail.log' 2>/dev/null || tail -40 '$STAGE/serve.out' 2>/dev/null || tail -40 '$STAGE/measure.out' 2>/dev/null || true" >&2 || true
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exit 1
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fi
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run_json="$(ssh_run "cat '$STAGE/run.json'")" || {
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echo "[autoresearch] could not read $STAGE/run.json back" >&2; exit 1; }
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echo "[autoresearch] window result:" >&2
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printf '%s\n' "$run_json" >&2
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emit_metrics "$run_json"
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echo "[autoresearch] engine evidence (plan / compile path / spec counters):" >&2
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ssh_run "cat '$STAGE/evidence.log' 2>/dev/null" >&2 || true
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exit 0
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ssh "$REMOTE" "bash $REMOTE_REPO/scripts/autoresearch-frank-primary.sh $REMOTE_REPO/scripts/frank-primary.env"
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