# ─── Python ───────────────────────────────────────────────────
__pycache__/
*.py[cod]
*.pyo
*.pyd
*.so
.Python
*.egg-info/
dist/
build/
*.egg

# ─── Virtual environments ──────────────────────────────────────
venv/
.venv/
env/
ENV/

# ─── Secrets & local config ────────────────────────────────────
.env
.env.*
*.key
secrets.json

# ─── Dev / IDE ─────────────────────────────────────────────────
.pytest_cache/
.mypy_cache/
.ruff_cache/
.coverage
htmlcov/
.DS_Store
Thumbs.db
*.swp
*.swo
.vscode/
.idea/

# ══════════════════════════════════════════════════════════════
# GENERATED RUNTIME FILES (re-created on each run)
# ══════════════════════════════════════════════════════════════

# Persistent cross-episode memory — auto-generated by reflection.py
memory_bank.json

# ══════════════════════════════════════════════════════════════
# TRAINING — large / generated files (DO NOT push to HF Spaces)
# Upload grpo_dataset.jsonl to HF Datasets Hub instead:
#   python training/generate_dataset.py --push
#   → https://huggingface.co/datasets/vssksn/intellicredit-grpo-dataset
# ══════════════════════════════════════════════════════════════

# Generated 2000-sample JSONL dataset (6.87 MB)
training/grpo_dataset.jsonl

# LoRA / QLoRA checkpoints after each GRPO stage (can be GBs)
training/checkpoints/

# Merged 16-bit model export (can be 15+ GB)
training/merged_model/

# Per-step training logs
training/logs/

# Miscellaneous training outputs
training/*.png
training/*.zip
training/*.safetensors
training/*.bin

# ══════════════════════════════════════════════════════════════
# EVALUATION — generated outputs (offline analysis artifacts)
# These are produced by evaluate.py / compare.py locally.
# Not needed in HF Spaces — the Space runs the live env API only.
# ══════════════════════════════════════════════════════════════

# Per-run JSON result files
evaluation/results/

# Matplotlib charts and ASCII chart text files
evaluation/charts/

# ══════════════════════════════════════════════════════════════
# MISC LARGE FILES
# ══════════════════════════════════════════════════════════════

# Jupyter notebook checkpoints
.ipynb_checkpoints/
*.ipynb

# Large data files
*.jsonl
*.parquet
*.arrow
*.feather
*.h5
*.hdf5
*.pkl
*.pickle

# BUT keep the project source JSONL fixtures if any are tiny
# (override the *.jsonl rule above for specific files if needed)docs/assets/*.png