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32030e4 | 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 | """Chat messages for single-turn and multi-step tasks (identical for every model)."""
from __future__ import annotations
import json
SYSTEM = ("You are an experienced thermal engineer. Answer from engineering judgement and "
"first-principles estimates; you cannot run simulations.")
def answer_instruction(output_schema: dict) -> str:
return ("Finish your reply with a single JSON object with exactly these fields: "
f"{json.dumps(output_schema)}. Write every interval as [low, high] numbers and every "
"confidence as a number between 0 and 1.")
def single_turn_messages(task: dict) -> list[dict]:
return [{"role": "system", "content": SYSTEM},
{"role": "user", "content": task["prompt"] + "\n\n" + answer_instruction(task["output_schema"])}]
def multi_step_messages(observation: dict) -> list[dict]:
"""``observation`` is ``StoredDataEnv.reset()``: prompt, tools, budget, output_schema."""
protocol = (
"You work in turns. To call a tool, reply with only a JSON object "
'{"tool": "<name>", "args": {...}}; the result comes back in the next message. '
"Make one tool call per reply and stop there: anything after it is ignored. "
f"Tools: {json.dumps(observation['tools'])}. Call budget: {json.dumps(observation['budget'])}. "
'When you are ready, reply with {"tool": "submit", "args": <answer>}, where <answer> has '
f"exactly these fields: {json.dumps(observation['output_schema'])}. "
"Write intervals as [low, high] numbers and confidence as a number between 0 and 1.")
return [{"role": "system", "content": SYSTEM},
{"role": "user", "content": observation["prompt"] + "\n\n" + protocol}]
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