pyr0ball
33a5cdec37
- cloud_session.py: CLOUD_AUTH_BYPASS_IPS with CIDR support; X-Real-IP for Docker bridge NAT-aware client IP resolution; local-dev DB path under CLOUD_DATA_ROOT for bypass sessions - compose.cloud.yml: thread CLOUD_AUTH_BYPASS_IPS from shell env; document Docker bridge CIDR requirement in .env.example - nginx.cloud.conf + nginx.conf: client_max_body_size 20m for barcode uploads - barcode_scanner.py: EXIF orientation correction (PIL ImageOps.exif_transpose) before cv2 decode; rotation coverage extended to [90, 180, 270, 45, 135] to catch sideways barcodes the 270° case was missing - llm_recipe.py: CF-core VRAM lease acquire/release wrapping LLMRouter calls - tasks/runner.py + config.py: COORDINATOR_URL + recipe_llm VRAM budget (4GB) - recipes.py: per-request Store creation inside asyncio.to_thread worker to avoid SQLite check_same_thread violations - download_datasets.py: HF_PARQUET_FILES strategy for repos without dataset builders (lishuyang/recipepairs direct parquet download) - derive_substitutions.py: use recipepairs_recipes.parquet for ingredient lookup; numpy array detection; JSON category parsing - test_build_flavorgraph_index.py: rewritten for CSV-based index format - pyproject.toml: add Pillow>=10.0 for EXIF rotation support
39 lines
1.5 KiB
Python
39 lines
1.5 KiB
Python
import csv
|
|
import tempfile
|
|
from pathlib import Path
|
|
|
|
|
|
def _write_csv(path: Path, rows: list[dict], fieldnames: list[str]) -> None:
|
|
with open(path, "w", newline="") as f:
|
|
w = csv.DictWriter(f, fieldnames=fieldnames)
|
|
w.writeheader()
|
|
w.writerows(rows)
|
|
|
|
|
|
def test_parse_flavorgraph_node():
|
|
from scripts.pipeline.build_flavorgraph_index import parse_ingredient_nodes
|
|
|
|
with tempfile.TemporaryDirectory() as tmp:
|
|
nodes_path = Path(tmp) / "nodes.csv"
|
|
edges_path = Path(tmp) / "edges.csv"
|
|
|
|
_write_csv(nodes_path, [
|
|
{"node_id": "1", "name": "beef", "node_type": "ingredient"},
|
|
{"node_id": "2", "name": "pyrazine", "node_type": "compound"},
|
|
{"node_id": "3", "name": "mushroom", "node_type": "ingredient"},
|
|
], ["node_id", "name", "node_type"])
|
|
|
|
_write_csv(edges_path, [
|
|
{"id_1": "1", "id_2": "2", "score": "0.8"},
|
|
{"id_1": "3", "id_2": "2", "score": "0.7"},
|
|
], ["id_1", "id_2", "score"])
|
|
|
|
ingredient_to_compounds, compound_names = parse_ingredient_nodes(nodes_path, edges_path)
|
|
|
|
assert "beef" in ingredient_to_compounds
|
|
assert "mushroom" in ingredient_to_compounds
|
|
# compound node_id "2" maps to name "pyrazine"
|
|
beef_compounds = ingredient_to_compounds["beef"]
|
|
assert any(compound_names.get(c) == "pyrazine" for c in beef_compounds)
|
|
mushroom_compounds = ingredient_to_compounds["mushroom"]
|
|
assert any(compound_names.get(c) == "pyrazine" for c in mushroom_compounds)
|