A.R.T.E.M.I.S: LangGraph Supervisor v2 for multi-agent RAG (FastAPI + Docker)—feedback/PRs?

Hey LangChain community—I've built A.R.T.E.M.I.S as a modular foundation for dynamic agent systems, starting with RAG workflows. This is surface-level MVP #1: a **LangGraph Supervisor v2** that intelligently routes between specialized agents (rag_search, ingestion, collection mgmt) via a clean FastAPI backend.

Current stack (plug-and-play):

- **LangGraph Supervisor** for routing (handles multi-turn, direct API calls)

- FastAPI endpoints (/health, /query), Docker-compose, Postman collection

- Qdrant vector store, Groq/OpenAI LLMs

- Full docs, tests, deploy guide—clone & run in minutes

Live demo: http://54.87.62.83:8000/health (try /query for agent flows)

**The vision**: Fully dynamic agents that auto-generate around APIs/tools/use cases. Right now it's RAG-focused but built modular.

**Check it out**: Repo + open issues (e.g. #8: E2E tests): https://github.com/Anshumanv28/A.R.T.E.M.I.S

**Feedback/PRs** on routing patterns, integrations, observability? All welcome—let's iterate together!

Example: "Ingest these docs → query with history" → auto-routes ingestion → rag agent.