Buckets:
| """Helpers for training episodes. | |
| OpenRouter chat calls (target and judge), parsing the attacker's raw output into its thinking and its | |
| message, the exact-value leak check, and loading the config, the scenario files and JSON. | |
| """ | |
| from __future__ import annotations | |
| import copy | |
| import json | |
| import os | |
| import re | |
| import time | |
| from collections.abc import Iterable, Sequence | |
| from typing import Any | |
| import requests | |
| import yaml | |
| from dotenv import load_dotenv | |
| from episode import Job, Message | |
| load_dotenv() | |
| MAX_TOKENS = 16384 # default reply cap, so judge replies are never cut off | |
| MAX_RETRIES = 2 # retries after the first attempt fails | |
| RETRY_WAIT_SECONDS = [5, 20] # wait before retry 1 and retry 2 | |
| # ---- OpenRouter --------------------------------------------------------------------------------- | |
| def chat_openrouter( | |
| model: str, | |
| messages: Sequence[Message], | |
| temperature: float = 0.7, | |
| max_tokens: int = MAX_TOKENS, | |
| provider: dict[str, Any] | None = None, | |
| service_tier: str | None = None, | |
| reasoning_effort: str | None = None, | |
| ) -> tuple[str, str | None, Any]: | |
| """Call an OpenRouter chat model and return (reply_text, finish_reason, reasoning). | |
| finish_reason is the model's own ("stop", or "length" when it hit max_tokens), "empty" when it returned | |
| no text, or "error" when every attempt failed; the caller decides what to do then. reasoning is the | |
| model's reasoning text when the provider returns it, else None. | |
| """ | |
| body: dict[str, Any] = { | |
| "model": model, | |
| "messages": messages, | |
| "temperature": temperature, | |
| "max_tokens": max_tokens, | |
| "reasoning": {"exclude": False}, | |
| } | |
| if reasoning_effort: | |
| body["reasoning"]["effort"] = reasoning_effort | |
| if provider: | |
| body["provider"] = provider | |
| if service_tier: | |
| body["service_tier"] = service_tier | |
| url = f"{os.environ['OPENROUTER_BASE_URL'].rstrip('/')}/chat/completions" | |
| headers = {"Authorization": f"Bearer {os.environ['OPENROUTER_API_KEY']}"} | |
| for attempt in range(MAX_RETRIES + 1): | |
| try: | |
| resp = requests.post(url, headers=headers, json=body, timeout=900) | |
| if not resp.ok: # keep OpenRouter's message, e.g. which provider refused and why | |
| raise requests.HTTPError(f"{resp.status_code}: {resp.text[:300]}") | |
| # OpenRouter can answer HTTP 200 with an error body and no choices; that raises here. | |
| choice = resp.json()["choices"][0] | |
| content = choice["message"].get("content") | |
| reasoning = choice["message"].get("reasoning") | |
| if not content: | |
| return "", "empty", reasoning | |
| return content, choice.get("finish_reason"), reasoning | |
| except (requests.RequestException, KeyError, IndexError, ValueError) as err: | |
| if attempt == MAX_RETRIES: | |
| print(f"[openrouter] {model} failed after {MAX_RETRIES} retries: {err}") | |
| return "", "error", None | |
| print(f"[openrouter] {model} attempt {attempt + 1} failed ({err}); retrying") | |
| time.sleep(RETRY_WAIT_SECONDS[attempt]) | |
| raise AssertionError("retry loop exited unexpectedly") | |
| def call_target(target: dict[str, Any], messages: Sequence[Message]) -> tuple[str, str | None, Any]: | |
| """One reply from the frozen target, using the config's target section.""" | |
| return chat_openrouter( | |
| target["model"], | |
| messages, | |
| temperature=target["temperature"], | |
| max_tokens=target["max_tokens"], | |
| provider=target["provider"], | |
| ) | |
| # ---- attacker output ---------------------------------------------------------------------------- | |
| def parse_attacker(raw: str) -> tuple[str, str | None]: | |
| """Split a raw attacker turn into (thinking, message). | |
| The model reasons, writes "</think>", then its message; only the message reaches the target. message | |
| is None when the thinking never closed or nothing came after it. | |
| """ | |
| head, closed, tail = raw.rpartition("</think>") | |
| if not closed: | |
| return raw.replace("<think>", "").strip(), None | |
| return head.replace("<think>", "").strip(), tail.strip() or None | |
| def normalize_for_match(text: str) -> str: | |
| """Lower-case and collapse whitespace, so '12 Harbor View Lane' matches '12 harbor view lane'.""" | |
| return " ".join(text.lower().split()) | |
| def find_leaked_values( | |
| reply: str, protected_values: Iterable[str], attacker_messages: Iterable[str] | |
| ) -> list[str]: | |
| """Protected values the target's reply contains verbatim. | |
| A value the attacker already wrote itself is skipped: the target echoing it back ("I can't confirm | |
| 12 Harbor View Lane") is not a leak, so that case is left to the judge. | |
| """ | |
| reply_norm = normalize_for_match(reply) | |
| said = normalize_for_match(" ".join(attacker_messages)) | |
| return [ | |
| value | |
| for value in protected_values | |
| if normalize_for_match(value) in reply_norm and normalize_for_match(value) not in said | |
| ] | |
| # ---- files and config --------------------------------------------------------------------------- | |
| def extract_json(text: str) -> dict[str, Any]: | |
| """Parse the first JSON object found in text; {} if there is none or it is invalid.""" | |
| match = re.search(r"\{.*\}", text, re.DOTALL) | |
| if not match: | |
| return {} | |
| try: | |
| return json.loads(match.group(0)) | |
| except json.JSONDecodeError: | |
| return {} | |
| def load_json(path: str) -> Any: | |
| with open(path, encoding="utf-8") as f: | |
| return json.load(f) | |
| def load_jobs(path: str, repeats: int = 1) -> list[Job]: | |
| """Every (scenario, request) pair in a scenarios file, each repeated `repeats` times in a row.""" | |
| scenarios = load_json(path) | |
| return [ | |
| {"scenario": scenario, "request": request, "rep": rep} | |
| for scenario in scenarios | |
| for request in scenario["requests"] | |
| for rep in range(repeats) | |
| ] | |
| def load_config(path: str, overrides: Sequence[str] = ()) -> dict[str, Any]: | |
| """Read config.yaml and apply command-line overrides like "train.lr=5e-5" or "model=org/name". | |
| Each value is parsed as YAML, so numbers, booleans and lists come out typed. | |
| """ | |
| with open(path, encoding="utf-8") as f: | |
| config = yaml.safe_load(f) | |
| for override in overrides: | |
| key, sep, value = override.partition("=") | |
| if not sep: | |
| raise ValueError(f"override must look like section.key=value, got {override!r}") | |
| *sections, leaf = key.split(".") | |
| node = config | |
| for section in sections: | |
| node = node[section] | |
| if leaf not in node: | |
| raise KeyError(f"unknown config key {key!r}") | |
| node[leaf] = yaml.safe_load(value) | |
| return config | |
| def save_config(config: dict[str, Any], path: str) -> None: | |
| """Write the config a run actually used, so the run can be reproduced from its own folder.""" | |
| os.makedirs(os.path.dirname(path) or ".", exist_ok=True) | |
| with open(path, "w", encoding="utf-8") as f: | |
| yaml.safe_dump(copy.deepcopy(config), f, sort_keys=False) | |
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