Spaces:
Runtime error
Runtime error
| """Constants shared by production agents, the training package, and tests. | |
| Aspect keys are snake_case everywhere (API, DB JSON, features, labels). The | |
| natural-language phrase in :data:`ASPECT_PHRASES` is only used as the second | |
| sentence fed to the ABSA model. | |
| """ | |
| from __future__ import annotations | |
| from typing import Final, Literal | |
| #: Canonical, ordered aspect keys. ORDER IS PART OF THE FUSION FEATURE CONTRACT — | |
| #: never reorder without retraining the ensemble. | |
| EARBUD_ASPECTS: Final[tuple[str, ...]] = ( | |
| "sound_quality", | |
| "bass", | |
| "battery_life", | |
| "comfort", | |
| "fit", | |
| "build_quality", | |
| "connectivity", | |
| "microphone", | |
| "noise_cancellation", | |
| "value", | |
| ) | |
| #: Aspect key -> phrase given to the ABSA model as the aspect sentence. | |
| ASPECT_PHRASES: Final[dict[str, str]] = {key: key.replace("_", " ") for key in EARBUD_ASPECTS} | |
| #: Keyword pre-filter per aspect. Matched on word boundaries at the START of a | |
| #: word (so "isolat" matches "isolation" but "fit" does not match "benefit"). | |
| #: "cheap" is deliberately only under `value`: "cheap plastic" is still caught | |
| #: by `build_quality` through "plastic". | |
| ASPECT_KEYWORDS: Final[dict[str, tuple[str, ...]]] = { | |
| "sound_quality": ( | |
| "sound", | |
| "audio", | |
| "music", | |
| "clarity", | |
| "treble", | |
| "highs", | |
| "mids", | |
| "tinny", | |
| "muddy", | |
| ), | |
| "bass": ("bass", "low end", "boom", "thump", "sub-bass", "subwoofer"), | |
| "battery_life": ("battery", "charge", "charging", "playtime", "endurance", "hours of"), | |
| "comfort": ("comfort", "uncomfortable", "ear pain", "hurt", "wear", "wearing", "sore"), | |
| "fit": ("fit", "fits", "stay in", "stays in", "fall out", "falls out", "ear tip", "seal"), | |
| # Durability counts as build quality in the labeling protocol ("broke after a week", | |
| # "connector bent"), which the original 7 keywords missed (train-split recall 0.35). | |
| "build_quality": ( | |
| "build", | |
| "built", | |
| "construct", | |
| "durab", | |
| "sturd", | |
| "flims", | |
| "fragil", | |
| "well made", | |
| "well-made", | |
| "cheaply made", | |
| "poorly made", | |
| "plastic", | |
| "material", | |
| "hinge", | |
| "crack", | |
| "broke", | |
| "break", | |
| "snapped", | |
| "fell apart", | |
| "falling apart", | |
| "came apart", | |
| "cord", | |
| "cable", | |
| "wire", | |
| "jack", | |
| "connector", | |
| "stopped working", | |
| "quit working", | |
| "died", | |
| "defect", | |
| "peel", | |
| "wore out", | |
| "worn out", | |
| ), | |
| # "pair" / "range" were removed: "a pair of headphones" and "price range" made | |
| # connectivity precision 0.52 on the train split. | |
| "connectivity": ( | |
| "bluetooth", | |
| "connect", | |
| "disconnect", | |
| "reconnect", | |
| "pairing", | |
| "paired", | |
| "pair with", | |
| "pair to", | |
| "latency", | |
| "lag", | |
| "delay", | |
| "drops out", | |
| "dropped out", | |
| "dropout", | |
| "cuts out", | |
| "cutting out", | |
| "signal", | |
| "out of range", | |
| "sync", | |
| "stutter", | |
| "multipoint", | |
| ), | |
| "microphone": ("mic", "microphone", "calls", "phone call", "voice", "recording"), | |
| "noise_cancellation": ( | |
| "anc", | |
| "noise cancel", | |
| "noise-cancel", | |
| "passive isolation", | |
| "isolat", | |
| "block out", | |
| "blocks out", | |
| "transparency mode", | |
| ), | |
| "value": ("price", "value", "worth", "money", "cheap", "expensive", "cost", "budget"), | |
| } | |
| Sentiment = Literal["positive", "negative", "neutral", "not_mentioned"] | |
| #: Numeric encoding of aspect sentiment for fusion features (PRD §10.1). | |
| SENTIMENT_TO_NUMERIC: Final[dict[str, int]] = { | |
| "negative": -1, | |
| "neutral": 0, | |
| "positive": 1, | |
| "not_mentioned": 0, | |
| } | |
| #: Valid experience-score label values produced by the labeler (PRD §7.2). | |
| LABEL_SCORE_VALUES: Final[tuple[float, ...]] = (1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0) | |
| SCORE_MIN: Final[float] = 1.0 | |
| SCORE_MAX: Final[float] = 5.0 | |
| #: Largest possible distance on the 1–5 scale. | |
| SCORE_RANGE: Final[float] = SCORE_MAX - SCORE_MIN | |