Files
serverAppConfigs/scripts/deep-probe.py
T
Frank 7c77326c33 llm: complete the Protoss rename on the wire — served ids frank-archon/dragoon/zealot
The 2026-10-08 rename moved the harness model ids and the homepage cards;
the served aliases on the wire stayed frank-primary/frank-large/
frank-secondary. This closes the gap: the alias each endpoint announces is
now the family name, while the services, units, scripts, env files and
runbooks keep the old names (container identity stays stable).

- scripts/frank-secondary.env ALIAS, scripts/frank-large.env
  HALOGEN_MODEL_ID, scripts/frank-primary.env FRANK_PRIMARY_SERVED_NAME
  (+ the two serve-script defaults/gate messages)
- seams re-pinned: frank_secondary/frank_large/frank_primary unit bats
- fleet harnesses retargeted: bench-probe, deep-probe, calib-push,
  fleet-probes-swift15, autoresearch(+measure), bench-threads-batch-http,
  bench-decode
- shared/homepage/docs.html: api-id annotations and the "switchover will
  rename the ids" footnote removed — the page's names are now the ids;
  opencode/Pi/curl examples send frank-zealot
- dankclaw/hermes/config.yaml.example: frank-large -> frank-dragoon and the
  live 262144 context (Hermes routes by served id; see Hermes.md)

Consumers with live state re-keyed out-of-band in the same window:
OpenWebUI (model row, access_grant, openai.api_configs model_ids) and the
Hermes config.yaml.
2026-10-09 16:47:19 -07:00

56 lines
2.2 KiB
Python
Executable File

#!/usr/bin/env python3
"""deep-probe.py — one chat completion at ~43.6k prompt tokens, temp 0, 512
generated, streamed; decode = completion_tokens / (total - ttft)."""
import json, time, urllib.request
TARGET_BYTES = int(43600 * 3.8)
def build():
parts, n = [], 0
with open("/home/dank/corpora/out/calib.jsonl") as f:
for line in f:
p = json.loads(line)["prompt"]
parts.append(p)
n += len(p.encode())
if n >= TARGET_BYTES:
break
return "".join(parts)
def main(salt):
body = json.dumps({
"model": "frank-archon",
"messages": [{"role": "user", "content": f"[probe {salt}] Continue and summarize this material in English, 400 words.\n\n" + build()}],
"temperature": 0.0, "max_tokens": 512,
"stream": True, "stream_options": {"include_usage": True},
}).encode()
req = urllib.request.Request("http://localhost:7770/v1/chat/completions",
data=body, headers={"Content-Type": "application/json"})
t0 = time.time(); ttft = None; ctok = 0; usage = {}
with urllib.request.urlopen(req, timeout=2400) as r:
for raw in r:
line = raw.decode().strip()
if not line.startswith("data:"):
continue
d = line[5:].strip()
if d == "[DONE]":
break
j = json.loads(d)
if j.get("usage"):
usage = j["usage"]
for ch in j.get("choices", []):
delta = (ch.get("delta") or {})
piece = delta.get("content") or delta.get("reasoning_content") or ""
if piece and ttft is None:
ttft = time.time() - t0
ctok += 1
total = time.time() - t0
gen = usage.get("completion_tokens") or ctok
dec = gen / (total - (ttft or 0)) if total > (ttft or 0) else 0
print(json.dumps({"salt": salt, "prompt_tokens": usage.get("prompt_tokens"),
"completion_tokens": gen, "ttft_s": round(ttft or 0, 2),
"total_s": round(total, 1), "decode_tps": round(dec, 2)}))
if __name__ == "__main__":
import sys
main(sys.argv[1] if len(sys.argv) > 1 else "x")