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Test Log: 10_demo

cookbook/08_learning/10_demo/TEST_LOG.md

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Test Log: 10_demo

2026-06-12

seed.py

Status: PASS

Description: Ran the full seed end to end with a live OPENAI_API_KEY against the pgvector container. All scripted conversations completed and every store populated: user profiles and user memories for both users, session context for all three sessions, 7 global entity memories (Postgres Cluster with 4 facts, Marcus Lee, Sarah Kim, Northwind, Vantage Labs, Design System, PostgreSQL), 4 decision logs, and 5 learned-knowledge entries in the vector table including the explicit "rehearse the cutover on a clone" rule that transfers from Alice to Ben.

Result: 18 rows in ai.agno_learnings across all five learning types, 5 entries in ai.learning_demo_knowledge. Knowledge transfer beat works.


run.py (live server)

Status: PASS

Description: With the server running on port 7777, exercised the full /learnings API against the seeded data: list with pagination, learning_type and user_id filters, GET /learnings/users (both users indexed), GET by deterministic identity id ([email protected]), then a full CRUD cycle on a throwaway decision_log record: POST (201, UUID id), PATCH content and metadata, DELETE (204), GET after delete (404). Seeded data unaffected.

Result: All endpoints respond correctly; CRUD round-trip verified.


agents.py / run.py (offline smoke)

Status: PASS

Description: Imported the demo agent against Postgres + pgvector, confirmed all six stores initialize (user_profile, user_memory, session_context, entity_memory, learned_knowledge, decision_log), built the AgentOS app, and exercised the learnings endpoints with a FastAPI TestClient.

Result: App builds and the /learnings endpoints respond with paginated results.