| """ |
| Parse free-form model text into a typed JewelryAction. |
| |
| Mirrors inference.py:get_action_from_text so the action surface during |
| training matches what was used during evaluation. |
| """ |
| from __future__ import annotations |
|
|
| from typing import Tuple |
|
|
| try: |
| from ..models import JewelryAction |
| except ImportError: |
| from models import JewelryAction |
|
|
|
|
| def parse_model_text_to_action(phase: str, text: str) -> Tuple[JewelryAction, str]: |
| """Return (action, normalised_text) for the current phase. |
| |
| Robust against typical LLM output noise: backticks, quotes, leading/trailing |
| whitespace. Falls back to safe defaults so a single bad token never breaks |
| the rollout. |
| """ |
| text = (text or "").strip().replace("`", "").strip(" \t\n\r\"'") |
|
|
| if phase == "market": |
| lower = text.lower() |
| if lower.startswith("buy"): |
| qty_str = lower.replace("buy", "").strip() |
| try: |
| qty = float(qty_str) |
| except ValueError: |
| qty = 1.0 |
| return JewelryAction(market_action="buy", gold_qty=qty), f"buy {qty}" |
| if "wait" in lower: |
| return JewelryAction(market_action="wait"), "wait" |
| try: |
| qty = float(text) |
| return JewelryAction(market_action="buy", gold_qty=qty), f"buy {qty}" |
| except ValueError: |
| return JewelryAction(market_action="wait"), "wait" |
|
|
| if phase == "warehouse": |
| lower = text.lower() |
| for product in ("necklace", "bracelet", "ring"): |
| if product in lower: |
| return JewelryAction(product_choice=product), product |
| return JewelryAction(product_choice="ring"), "ring" |
|
|
| if phase == "showroom": |
| return JewelryAction(message=text), text |
|
|
| return JewelryAction(), text |
|
|
