platform/aiml/QUICK_RECOMMENDATIONS.md

Quick Recommendations for Working with the Repo

Goal	Suggested Starting Point
Run a simple Elizabeth chat	cd elizabeth/e-1-first_session && python elizabeth_chat (or elizabeth_full.py).
Inspect memory calls	Open elizabeth_memory_integration.py and follow calls to bloom_memory_api modules in bloom-memory/.
Run the full autonomous stack	cd mlops && python deploy_autonomous.py (ensure required env vars for DBs and vLLM are set).
Track an experiment	After running, open mlflow.db via the MLflow UI (mlflow ui --backend-store-uri sqlite:///mlflow.db).
Add a new tool for the LLM	1. Add a JSON entry in mlops/agents/tool_registry.json. 2. Implement the function in mlops/elizabeth_mlops_tools.py. 3. Update elizabeth_tool_demo.py to call it.
Scale memory services	Look at bloom-memory/deployment/ scripts (deploy.sh, DEPLOYMENT_GUIDE_212_NOVAS.md) to launch on a Kubernetes‑like environment.