| Enable options for AlphaGeometry | |
| This document describes how to enable the four deployment options described in | |
| the architecture: Demo (fallbacks), Local infra (Neo4j/FAISS via Docker), Hosted | |
| services, and Full production (Kubernetes/Ray/CI). | |
| 1) Option 1 — Fast demo (no external infra) | |
| - Create a virtualenv and install requirements-merged.txt | |
| - Run the demo app locally: python -m backend.run_demo | |
| - Use the API to create universes and attempt proofs (NeuroSymbolicCore uses fallbacks) | |
| 2) Option 2 — Local infra (Neo4j + FAISS) | |
| - Install Docker Desktop. | |
| - Start Neo4j using provided compose file: | |
| docker compose -f docker-compose.neo4j.yml up -d | |
| - Install FAISS (CPU): pip install faiss-cpu | |
| - Configure backend/adapters/graph_adapter.Neo4jAdapter connection parameters or use env vars | |
| 3) Option 3 — Hosted services | |
| - Provide connection strings for hosted Neo4j and hosted vector DB in a secure manner (secrets manager) | |
| - Configure adapters to point to these endpoints (see backend/adapters/*) | |
| 4) Option 4 — Full production | |
| - Build docker images and push to registry | |
| - Deploy to Kubernetes using manifests in deploy/k8s or Helm using deploy/values.example.yaml | |
| - Provision Ray or Kubernetes jobs for heavy compute and configure autoscaling | |
| Security notes: | |
| - Use a secrets manager for tokens and DB credentials. Replace TokenAuth with a proper IAM/OAuth flow in production. | |