# ObsiGate — Optional dependencies for semantic search (#70)
#
# These are NOT required: the semantic search engine degrades gracefully to a
# dependency-free hashing embedder and a pure-Python cosine store when they are
# absent. Install this file to enable the full local model + fast vector index:
#
#   pip install -r backend/requirements-semantic.txt
#
# NOTE: sentence-transformers pulls in PyTorch (large download). If you only
# want the vector acceleration, install numpy + faiss-cpu and configure an
# external embedding endpoint instead (OBSIGATE_EMBEDDING_*).

# Local embedding model (all-MiniLM-L6-v2, ~80 MB, CPU)
sentence-transformers>=2.2.0

# Vector storage / similarity search
numpy>=1.24.0
faiss-cpu>=1.7.4