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efe9b39 92405d9 efe9b39 92405d9 efe9b39 92405d9 efe9b39 | 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 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 | """Shared helpers for latincy-lexicon demo pages (11, 12, 13)."""
from __future__ import annotations
import tempfile
from pathlib import Path
import streamlit as st
DEFAULT_SENTENCE = "Poeta bonus carmina pulchra scribit."
@st.cache_resource(show_spinner="Building Whitaker's Words data (first load only)…")
def build_lexicon_artifacts() -> tuple[Path, Path]:
"""Build lexicon.json + analyzer.json once per session.
Artifacts are cached under a temp directory. First call takes
~5–10s; subsequent calls short-circuit via Streamlit's
cache_resource and are instant.
"""
from latincy_lexicon.build import build
output_dir = Path(tempfile.gettempdir()) / "latincy-dashboard-lexicon"
output_dir.mkdir(parents=True, exist_ok=True)
lexicon_path = output_dir / "lexicon.json"
analyzer_path = output_dir / "analyzer.json"
if not (lexicon_path.exists() and analyzer_path.exists()):
build(output_dir=output_dir)
return lexicon_path, analyzer_path
@st.cache_resource(show_spinner="Loading LatinCy pipeline…")
def load_lexicon_pipeline(model_name: str):
"""Load a LatinCy model with whitakers_words + paradigm_generator attached.
Cached per model_name — all three lexicon demo pages share the same
pipeline instance, so switching pages is instant after the first
load.
"""
import spacy
nlp = spacy.load(model_name)
lexicon_path, analyzer_path = build_lexicon_artifacts()
nlp.add_pipe(
"whitakers_words",
config={
"lexicon_path": str(lexicon_path),
"analyzer_path": str(analyzer_path),
},
last=True,
)
nlp.add_pipe(
"paradigm_generator",
config={"analyzer_path": str(analyzer_path)},
last=True,
)
return nlp
def sentence_picker(key: str) -> str:
"""Render a free-text area prefilled with a simple example sentence."""
return st.text_area(
"Latin text:",
value=DEFAULT_SENTENCE,
height=100,
key=f"text_{key}",
)
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