requirements.txt

# Runtime deps ONLY -- what `uvicorn backend.main:app` needs to serve.
# Deliberately excludes torch: the serving process reads a precomputed novelty
# score (artifacts/novelty.csv) and never imports torch, whose ~500MB resident
# set does not fit a 512MB instance. Training deps are in requirements-train.txt.
fastapi==0.116.1
uvicorn[standard]==0.35.0
pandas==2.3.3
numpy==2.2.4
networkx==3.3
scikit-learn==1.7.0
shap==0.48.0
joblib==1.5.1

# Removed from the original Neo4j-backed design:
#   neo4j  -- the graph is built in-process from the CSVs; the Aura instance in
#             .env no longer resolves and nothing queries Cypher any more.
#   dgl    -- the GCN it backed was loaded but never called, and DGL publishes no
#             wheel for this Python/torch pair on Windows. models/classifier.py
#             replaces it with a gradient-boosted tree over the same graph
#             features (held-out macro-F1 0.90).