requirements.txt

scrapy>=2.11.0
selenium>=4.15.0
python-dotenv>=1.0.0
webdriver-manager>=4.0.0
undetected-chromedriver>=3.5.5
setuptools>=70.0.0

# ── LLM personalisation (Gemma 3 4B-IT via PyTorch + Apple Metal MPS) ─────────
# Install with:  pip install torch transformers accelerate protobuf
#
# Apple Silicon (M1/M2/M3):
#   - PyTorch uses the MPS (Metal Performance Shaders) backend automatically
#   - Set PYTORCH_ENABLE_MPS_FALLBACK=1 if you hit unsupported ops
#
# Model: google/gemma-3-4b-it  (~2 GB, downloaded via Hugging Face Hub)
# Accept the Gemma 3 licence at: https://huggingface.co/google/gemma-3-4b-it
# Optional: huggingface-cli login  (or set HF_TOKEN in .env)
#
# jax-metal is also installed (future use / experimentation):
#   pip install jax-metal
torch>=2.0.0
transformers>=4.50.0
accelerate>=0.30.0
protobuf>=3.20.0
sentencepiece>=0.1.99
kagglehub>=0.2.0

# ── LLM personalisation — optional remote API providers ───────────────────────
# Select the backend via LLM_PROVIDER in config/.env: gemma_local (default),
# gemini, or openai. Only install what you actually use.
#
# Gemini (Developer API key OR Vertex AI project/billing — e.g. free credits):
#   pip install google-genai
google-genai>=0.3.0
#
# OpenAI (e.g. GPT-5 nano):
#   pip install openai
openai>=1.50.0