oracle-ai-developer-hub

Oracle Agent Spec × Memory × CopilotKit

A personal travel concierge that shows how to use three things together — it searches flights, renders generative UI (flight cards, boarding-pass ticket), and remembers you across sessions:

Tell the concierge your travel preferences, come back in a brand-new session, and it still knows them — recalled from Oracle AI Database, not the current chat.

🌐 Try it live: hosted demo on Railway 📖 Full write-up: ../cookbook.md

How it works

Next.js + CopilotKit (V2) ──/api/copilotkit──▶ CopilotRuntime (HttpAgent)
                                                    │  AG-UI (SSE)
                                                    ▼
                                  Agent Spec JSON → ag_ui_agentspec (LangGraph)
                                     recall_memory · search_flights · book_flight (HITL ClientTool)
                                                    │  recall + persist
                                                    ▼
                                        oracleagentmemory → Oracle AI Database

The agent is defined once in Agent Spec (agent/concierge/agent.py) and run on LangGraph via the ag_ui_agentspec adapter. recall_memory pulls durable preferences from Oracle Agent Memory before planning; each turn is persisted so new preferences are extracted for next time, and a reconcile pass supersedes outdated facts so an updated preference wins on the next recall. CopilotKit consumes the AG-UI endpoint with an HttpAgent, so the agent owns the LLM call.

Prerequisites

Heads-up: the frontend uses CopilotKit V2 prerelease builds so Agent Spec’s human-in-the-loop renders, and the ag_ui_agentspec adapter is installed from the ag-ui repo (not PyPI). Both are pinned in the manifests.

Quickstart

1. Start Oracle AI Database (run from this demo/ directory)

docker compose up -d
docker compose logs -f oracle-db   # wait for "DATABASE IS READY TO USE"
./db/setup-db.sh                   # create the cookbook DB user (idempotent)

First boot takes a few minutes. The container-registry.oracle.com/database/free image includes AI Vector Search, which oracleagentmemory uses for semantic recall.

2. Run the agent

cd agent
cp .env.example .env          # add your OPENAI_API_KEY
uv sync
uv run uvicorn concierge.server:app --reload --port 8000

Health check: curl localhost:8000/health → {"status":"ok"}.

3. Run the frontend

cd frontend
cp .env.local.example .env.local   # optional; defaults to localhost:8000/run
npm install
npm run dev

Open http://localhost:3000.

Try it

  1. Tell it: “I’m vegetarian, I fly from SFO, and I prefer an aisle seat.”
  2. Click ”+ New thread” in the left sidebar, then ask: “Find me a flight to Amsterdam.”
  3. It recalls your preferences from Oracle (home airport SFO, aisle seat, vegetarian meal) and surfaces flights like AMS-001 — KLM KL606, nonstop, $740 as clickable flight cards — driven by what it remembered, not what you said in this thread.

Book it: select a flight from the cards (or ask “Book me flight AMS-001 to Amsterdam”), then click Confirm & book on the confirmation card to get the boarding pass. book_flight is a CopilotKit ClientTool so the confirm→book step resolves in one agent run. Multi-turn follow-ups in the same thread work too, via a server-side workaround — see Notes below.

Tests

End-to-end Playwright tests drive the real chat UI against the live agent + Oracle AI Database and record video. See frontend/e2e/README.md:

cd frontend && npm run test:e2e

Notes