egutierrez
faac610745
Extrae al registry funciones del proyecto interno footprint_aurgi: - core (6): slugify_ascii, normalize_for_join, cp_provincia_es, infer_provincia_from_cp, safe_read_csv_fallback, csv_to_parquet_duckdb - geo puras (7): haversine_km, point_in_ring, point_in_polygon, point_in_polygons_bbox, polygon_bbox, extent_with_padding, distance_bucket - geo I/O (4): load_geojson_polygons, load_boundary_gdf, add_basemap_osm, add_basemap_with_timeout - valhalla client (4): valhalla_route, valhalla_isochrone, valhalla_isochrones_async, valhalla_matrix_1_to_n - datascience stats (7): trimmed_mean, geometric_mean, detect_distribution_type, best_central_tendency, summary_stats, kde_density_levels, alpha_shape_concave_hull - datascience fuzzy (3): fuzzy_merge_adaptive (rapidfuzz), words_to_dataset, remove_words_from_column - datascience viz (2): plot_kde_2d, plot_heatmap_log - infra (4): compress_pdf_ghostscript, render_table_page_pdfpages, add_header_logo, osm2pgsql_ingest - pipelines (4): setup_geo_stack_docker, compute_centers_reachability, generate_isochrones_by_zone, count_points_per_zone - types geo (4): LonLat, BBox, IsochroneRequest, Centro Incluye: - apps/footprint_geo_stack/ (PostGIS + Martin + Valhalla via docker-compose) - 131/132 tests pasan (1 skip esperado: osm2pgsql en PATH) - Issue tracker dev/issues/0052-footprint-aurgi-extraction.md - Atribucion uniforme: source_repo internal:footprint_aurgi, source_license internal-aurgi - Build con 9 agentes en paralelo (8 wave 1 + 1 wave 2 pipelines) Tambien commitea trabajo previo no commiteado: aggregate_extraction_results, chunk_with_overlap, clean_pdf_text, merge_entity_aliases, extract_graph_gliner2, extract_relations_mrebel, extract_triples_spacy_es, gliner2/mrebel/marianmt/rebel/spacy_es load_model, parse_rebel_output, translate_es_to_en, issue 0050/0051. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
41 lines
1.2 KiB
Python
41 lines
1.2 KiB
Python
"""Carga (y cachea) un modelo spaCy en castellano para NER y OpenIE.
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LICENSE: spaCy = MIT. Modelo es_core_news_md = CC BY-SA 4.0 (datos CoNLL-2002).
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"""
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from __future__ import annotations
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from typing import Any
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# Cache global: model_name -> instancia spaCy nlp
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_MODEL_CACHE: dict[str, Any] = {}
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def spacy_es_load_model(model_name: str = "es_core_news_md") -> Any:
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"""Load (and cache) a spaCy Spanish language model.
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The model provides dependency parsing, POS tagging and NER (PER, ORG, LOC, MISC).
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Used by extract_triples_spacy_es for schema-less OpenIE in Spanish.
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LICENSE: spaCy = MIT. es_core_news_md = CC BY-SA 4.0 (CoNLL-2002 corpus).
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Args:
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model_name: Name of the spaCy model. Default: es_core_news_md.
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Alternatives: es_core_news_sm (smaller), es_core_news_lg (larger).
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Returns:
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spaCy Language instance cached by model_name.
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Raises:
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OSError: If the model is not installed. Install with:
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python -m spacy download es_core_news_md
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"""
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if model_name in _MODEL_CACHE:
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return _MODEL_CACHE[model_name]
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import spacy # type: ignore[import]
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nlp = spacy.load(model_name)
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_MODEL_CACHE[model_name] = nlp
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return nlp
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