five-desks-code / source /scripts /calibrate.py
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Five Desks Code: tasks, calibration and source
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"""Play Qwen3.8-27B (thinking off) against a running server to measure per-task solve rates.
The HF token is read inside this process via huggingface_hub (HF_TOKEN_PATH selects the file);
it is never printed or written anywhere.
Usage: HF_TOKEN_PATH=... python scripts/calibrate.py --url http://localhost:8000 --episodes 4 --out reports/calibration/run1
"""
import argparse
import json
import random
import re
import sys
import threading
import time
import urllib.error
import urllib.request
from concurrent.futures import ThreadPoolExecutor
from pathlib import Path
from statistics import mean
sys.path.insert(0, str(Path(__file__).resolve().parents[1]))
sys.path.insert(0, str(Path(__file__).resolve().parent))
from huggingface_hub import get_token # noqa: E402
from pydantic import ValidationError # noqa: E402
from five_desks.models import DeskAction # noqa: E402
from five_desks.tasks import TASK_IDS # noqa: E402
from wsclient import Session # noqa: E402
ROUTER = "https://router.huggingface.co/v1/chat/completions"
FINISH_ACTION = {"tool": "submit", "answer": {}}
_decoder = json.JSONDecoder(strict=False)
def system_prompt(action_schema: dict) -> str:
return (
"You are an agent acting in an environment. Reply to every message with exactly one JSON object and "
"nothing else: an action that matches the action schema below, or {\"finish\": true} to end the episode.\n"
f"Action schema: {json.dumps(action_schema)}"
)
def first_json_object(text: str):
text = re.sub(r"<think>.*?</think>", "", text or "", flags=re.S)
for match in re.finditer(r"\{", text):
try:
obj, _ = _decoder.raw_decode(text[match.start():])
if isinstance(obj, dict):
return obj
except json.JSONDecodeError:
continue
return None
class Model:
def __init__(self, model: str, max_tokens: int, temperature: float, thinking: bool = False):
self.model, self.max_tokens, self.temperature, self.thinking = model, max_tokens, temperature, thinking
self._token = get_token()
if not self._token:
raise SystemExit("No Hugging Face token found (set HF_TOKEN_PATH).")
self.usage = {"prompt_tokens": 0, "completion_tokens": 0, "calls": 0}
self._lock = threading.Lock()
self.empty_examples = []
def chat(self, messages):
# Some provider responses come back with no content at all; retry those rather than score them.
for _ in range(3):
content, used, finish = self._chat_once(messages)
if content.strip() or finish == "length":
break
return content, used, finish
def _chat_once(self, messages):
body = {"model": self.model, "messages": messages, "max_tokens": self.max_tokens,
"temperature": self.temperature, "chat_template_kwargs": {"enable_thinking": self.thinking}}
for attempt in range(5):
req = urllib.request.Request(ROUTER, data=json.dumps(body).encode(), headers={
"Authorization": f"Bearer {self._token}", "Content-Type": "application/json"})
try:
with urllib.request.urlopen(req, timeout=180) as response:
data = json.load(response)
break
except urllib.error.HTTPError as exc:
if exc.code in (429, 500, 502, 503, 504) and attempt < 4:
time.sleep(2 ** attempt * 3)
continue
raise RuntimeError(f"inference HTTP {exc.code}: {exc.read().decode()[:200]}") from None
except (urllib.error.URLError, TimeoutError): # DNS hiccups and slow responses are retried too
if attempt < 4:
time.sleep(2 ** attempt * 3)
continue
raise
usage = data.get("usage") or {}
with self._lock:
self.usage["prompt_tokens"] += usage.get("prompt_tokens", 0)
self.usage["completion_tokens"] += usage.get("completion_tokens", 0)
self.usage["calls"] += 1
choice = data["choices"][0]
message = choice["message"]
content = message.get("content") or ""
if not content.strip():
with self._lock:
self.usage["empty_content"] = self.usage.get("empty_content", 0) + 1
self.empty_examples.append({k: v for k, v in message.items() if v})
return content, usage.get("completion_tokens", 0), choice.get("finish_reason")
def play(url, model, schema, task_id, completion_budget, context_budget):
messages = [{"role": "system", "content": system_prompt(schema)}]
episode = {"task_id": task_id, "turns": [], "end": None, "reward": 0.0}
completion_used = 0
with Session(url) as session:
episode["seed"] = random.SystemRandom().randrange(2**48)
data = session.reset(task_id=task_id, seed=episode["seed"])
obs = data["observation"]
while True:
obs_text = json.dumps({k: v for k, v in obs.items() if k != "metadata" or v})
messages.append({"role": "user", "content": obs_text})
if len(messages) > 2:
completion_used += len(obs_text) // 3 # later observations count against the budget
if completion_used >= completion_budget or sum(len(m["content"]) for m in messages) // 3 >= context_budget:
episode["end"] = "budget"
data = session.step(FINISH_ACTION)
break
reply, used, finish_reason = model.chat(messages)
completion_used += used
messages.append({"role": "assistant", "content": reply})
episode["turns"].append({"obs": obs_text[:4000], "reply": reply[:2000], "finish_reason": finish_reason, "tokens": used})
if finish_reason == "length":
episode["end"] = "truncated"
data = session.step(FINISH_ACTION)
break
action = first_json_object(reply)
if isinstance(action, dict) and set(action) == {"action"} and isinstance(action["action"], dict):
action = action["action"]
if action is None:
episode["end"] = "empty_reply" if not reply.strip() else "invalid_json"
data = session.step(FINISH_ACTION)
break
if action.get("finish") is True:
episode["end"] = "finish"
data = session.step(FINISH_ACTION)
break
try:
DeskAction.model_validate(action)
except ValidationError:
episode["end"] = "schema_invalid"
data = session.step(FINISH_ACTION)
break
data = session.step(action)
obs = data["observation"]
if data["done"]:
episode["end"] = "submitted" if action.get("tool") == "submit" else "out_of_steps"
episode["final"] = obs.get("output")
break
episode["reward"] = data.get("reward") or 0.0
episode["n_turns"] = len(episode["turns"])
episode["completion_tokens_est"] = completion_used
return episode
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--url", default="http://localhost:8000")
parser.add_argument("--model", default="Qwen/Qwen3.8-27B:deepinfra")
parser.add_argument("--episodes", type=int, default=4)
parser.add_argument("--tasks", default="", help="comma-separated task ids or prefixes (default: all)")
parser.add_argument("--workers", type=int, default=8)
parser.add_argument("--max-tokens", type=int, default=1024)
parser.add_argument("--temperature", type=float, default=1.0)
parser.add_argument("--completion-budget", type=int, default=8192)
parser.add_argument("--context-budget", type=int, default=16384)
parser.add_argument("--out", required=True)
args = parser.parse_args()
tasks = TASK_IDS
if args.tasks:
wanted = args.tasks.split(",")
tasks = [t for t in TASK_IDS if any(t.startswith(w) for w in wanted)]
with urllib.request.urlopen(f"{args.url}/schema", timeout=15) as response:
schema = json.load(response)["action"]
model = Model(args.model, args.max_tokens, args.temperature)
out = Path(args.out)
out.mkdir(parents=True, exist_ok=True)
jobs = [t for t in tasks for _ in range(args.episodes)]
started = time.monotonic()
results = []
with ThreadPoolExecutor(args.workers) as pool, open(out / "episodes.jsonl", "w") as log:
futures = [pool.submit(play, args.url, model, schema, t, args.completion_budget, args.context_budget) for t in jobs]
for fut in futures:
try:
ep = fut.result()
except Exception as exc: # infrastructure errors are excluded, not scored as 0
print("episode error:", exc, file=sys.stderr)
continue
results.append(ep)
log.write(json.dumps(ep) + "\n")
summary = {}
for task_id in tasks:
eps = [e for e in results if e["task_id"] == task_id]
if not eps:
continue
rewards = [e["reward"] for e in eps]
ends = {}
for e in eps:
ends[e["end"]] = ends.get(e["end"], 0) + 1
summary[task_id] = {"n": len(eps), "mean": round(mean(rewards), 3), "rewards": rewards,
"mixed": len(set(rewards)) > 1, "ends": ends,
"turns": round(mean(e["n_turns"] for e in eps), 1)}
report = {"model": args.model, "episodes": len(results), "seconds": round(time.monotonic() - started),
"usage": model.usage, "tasks": summary}
(out / "summary.json").write_text(json.dumps(report, indent=2) + "\n")
(out / "empty_examples.json").write_text(json.dumps(model.empty_examples[:20], indent=2) + "\n")
print(f"{'task':24s} {'mean':>5s} rewards ends")
for task_id, s in summary.items():
print(f"{task_id:24s} {s['mean']:5.2f} {str(s['rewards']):30s} {s['ends']}")
print("usage:", model.usage, "seconds:", report["seconds"])
if __name__ == "__main__":
main()