# =============================================================================
# requirements.txt — runtime dependencies for the FastAPI backend (slim).
# -----------------------------------------------------------------------------
# This file mirrors `[project.dependencies]` in pyproject.toml so that
# Docker builds and CI can `pip install -r requirements.txt` without needing
# the package source available.
#
# To regenerate from pyproject.toml later (recommended after Phase 1):
#   pip install pip-tools
#   pip-compile --extra=hf pyproject.toml -o requirements.txt
#
# All versions are pinned. Floating versions across TF + transformers + torch
# is the most common silent source of BLEU drift between runs and deploys.
# =============================================================================

# ---- Core ML framework -------------------------------------------------------
# CPU-only TF: deploy target is CPU HuggingFace Spaces. Pinned at 2.15 because
# 2.16+ ships Keras 3 by default, which breaks the IEEE notebook's
# `tf.keras.layers.TextVectorization` save/load semantics.
tensorflow-cpu==2.15.0

# ---- Numerics / data ---------------------------------------------------------
# NumPy <2.0 because TF 2.15 was built against the 1.x ABI.
numpy==1.26.4
pandas==2.2.2
pillow==10.3.0
pyyaml==6.0.1

# ---- Config & validation -----------------------------------------------------
pydantic==2.7.4
pydantic-settings==2.3.4

# ---- API server --------------------------------------------------------------
fastapi==0.111.0
uvicorn[standard]==0.30.1
python-multipart==0.0.9

# ---- Model artefact pull at startup ------------------------------------------
huggingface-hub==0.23.4

# ---- Logging / async / CLI ---------------------------------------------------
structlog==24.2.0
anyio==4.4.0
tqdm==4.66.4
click==8.1.7