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ab62348 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 | """How an example becomes a prompt. Shared by every backend, so it imports no ML framework."""
from __future__ import annotations
LETTERS = "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
SYSTEM = ("You make decisions about a document under a policy. Read only what is written in the document. "
"Reply with the letter of the correct option and nothing else.")
ANSWERABLE = "Does the document state every fact that the policy needs in order to decide this case?"
YES_NO = [("yes", "yes"), ("no", "no")]
def option_lines(example):
"""(label, text shown) per option, in the example's order."""
if example["kind"] == "noul":
return [("true", "true"), ("false", "false")]
return [(o["name"], o["name"] if o["name"] == o["description"] else f"{o['name']}: {o['description']}")
for o in example["options"]]
def user_prompt(example, question, options):
listing = "\n".join(f"{LETTERS[i]}. {text}" for i, (_, text) in enumerate(options))
document = f"DOCUMENT\n{example['document']}\n\n" if example["document"] else "" # bare questions have none
return (f"POLICY\n{example['policy']}\n\n{document}"
f"QUESTION\n{question}\n\nOPTIONS\n{listing}")
def prompt_ids(tokenizer, user):
messages = [{"role": "system", "content": SYSTEM}, {"role": "user", "content": user}]
ids = tokenizer.apply_chat_template(messages, add_generation_prompt=True, enable_thinking=False)
return list(ids if isinstance(ids, list) else ids["input_ids"]) # some tokenizer versions return a mapping
def letter_token_ids(tokenizer):
ids = [tokenizer.encode(letter, add_special_tokens=False) for letter in LETTERS]
if any(len(i) != 1 for i in ids):
raise ValueError("Every option letter must be a single token for this tokenizer.")
return [i[0] for i in ids]
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