# Python Environment 
__pycache__/
*.py[cod]
*$py.class
venv/
env/
.env
.venv
pip-log.txt

# Trained ML models (XGBoost classifiers — proprietary)
models/*.pkl
models/*.joblib
models/*.bin
**/models/*.pkl
**/models/*.joblib
**/models/*.bin
**/models/*.json
!models/.gitkeep
!**/models/.gitkeep

# Adversarial FAISS index (trained corpus — proprietary)
storage/faiss_adversarial.index
storage/faiss_adversarial.meta
storage/*.json
!storage/__init__.py

# Raw and labeled training datasets
data/datasets/
data/labeled/

# Training results and metrics 
data/training_results.json
data/eval_results*.json
data/eval_results*.jsonl
data/seeds/
data/jbb_results/
data/jbb_tier1/

# PAIR classifier training corpus
data/pair_training/

# Adversarial evaluation data 
data/adversarial_eval_set.jsonl
data/eval_new_attacks_results.json
data/eval_new_attacks.py

# VEXR collaboration research data 
data/vexr/

# Distribution builds — published via PyPI, not git
dist/

# Notebook research output 
notebooks/comparison_plots/
notebooks/pair_classifier_plots/
notebooks/*.png
notebooks/*.jpg

# Benchmark evaluation output 
notebooks/benchmark_figures/
notebooks/benchmark_results/
notebooks/*.csv

# VEXR collaboration research 
notebooks/vexr_*.ipynb
notebooks/vexr_*.txt
notebooks/vexr_*.csv
paper/
README_files/


# Evaluation framework (local research only — never push)
evaluation/

# END PRIVATE
results/

#Jupyter checkpoints 
.ipynb_checkpoints/
**/.ipynb_checkpoints/

#HuggingFace local dataset downloads 
*.arrow
*.parquet
datasets/

# Failure Intelligence Storage 
failures.json

# VS Code & IDEs 
.vscode/
.idea/
*.swp
*.bak

# Testing & Reports 
.pytest_cache/
.coverage
htmlcov/
nosetests.xml
*.log

#Streamlit
.streamlit/config.toml
static/
docs/
