.gitignore

# Personal Claude Code workspace — per-developer scratchpad and memory.
# Each teammate may have their own .claude/ directory; none are shared.
.claude/

# Python
__pycache__/
*.py[cod]
*.egg-info/
.venv/
venv/
backend/venv/
.pytest_cache/
.mypy_cache/
.ruff_cache/

# Node / frontend
node_modules/
dist/
build/
.next/

# Environment / secrets
.env
.env*
.env.local
.env.*.local

# Editor / OS
.vscode/
.idea/
.DS_Store
Thumbs.db

# Pipeline artifacts
clips/videos/
backend/eval/reports/
*.cache

# SQLite runtime cache — clip_fact_checks.db is a per-process artifact
# that mutates every time the backend runs; the WAL/SHM sidecars churn
# even faster. Tracking them produces noisy diffs and merge conflicts.
backend/data/*.db
backend/data/*.db-shm
backend/data/*.db-wal

# Level 2b routing — combined_train.csv is committed (the data is
# the durable artifact). model.pkl is NOT committed because git over
# HTTPS chokes on the 32 MB pickle. Every contributor trains locally
# once after clone:
#   python -m backend.app.level2b_routing.classifier.train \
#       backend/app/level2b_routing/data/combined_train.csv \
#       --out backend/app/level2b_routing/classifier/model.pkl
# Pinned scikit-learn==1.8.0 + joblib==1.5.3 in requirements.txt so
# every local retrain produces a load-compatible artifact.
backend/app/level2b_routing/data/synthetic_train.csv
*.pkl