Learning Cookbooks Test Log

Last updated: 2026-06-12

2026-06-12: Cookbook refresh and AgentOS demo

Changes in this pass:

1. Unified all examples on gpt-5.5 (was gpt-5.2, plus two OpenAIChat/gpt-4o stragglers in 09_decision_logs/)
2. Bumped the Claude quick test to claude-sonnet-4-6
3. README: complete structure tree (was missing 4 folders), added Decision Log store section, added "View Learnings in AgentOS" section
4. Added 10_demo/: AgentOS demo with all six learning stores enabled on Postgres + pgvector, a seed script, and the Learning UI walkthrough

Verified in this pass:

10_demo (agents.py / run.py)

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 GET /learnings, GET /learnings/users, and learning_type filtering with a FastAPI TestClient.

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

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Model unification (all folders)

Status: PENDING (live re-run)

Description: Model id swap is mechanical; imports verified. Live extraction runs with gpt-5.5 still need a full pass (requires OPENAI_API_KEY and the pgvector container for Postgres-based examples).

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2026-01-27: Previous full pass

Test Environment

• Database: PostgreSQL with PgVector at localhost:5532
• Python: .venvs/demo/bin/python
• Model: gpt-5.2 (OpenAI)

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Priority 1: Directly Affected by Recent Changes

05_learned_knowledge/01_agentic_mode.py

Status: PASS

Description: Tests AGENTIC mode for LearnedKnowledgeStore with the restructured prompt (Rules 1-4 consolidated in CRITICAL RULES section).

Result: Agent correctly:

• Searched before answering substantive questions (Rule 1)
• Saved team goal when user said "we're trying to reduce cloud egress costs" (Rule 4)
• Retrieved and applied learnings in subsequent session

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05_learned_knowledge/02_propose_mode.py

Status: PASS

Description: Tests PROPOSE mode where agent proposes learnings for user approval before saving.

Result: Agent correctly:

• Proposed a learning with title/context/insight format (no emoji - fix verified)
• Did NOT save when user said "No, don't save that"
• Searched for existing learnings

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06_quick_tests/02_learning_true_shorthand.py

Status: PASS

Description: Tests the learning=True shorthand which now enables both UserProfile and UserMemory stores by default.

Result:

• LearningMachine created with both stores: ['user_profile', 'user_memory']
• UserProfileStore extracted: Name "Charlie Brown", Preferred Name "Chuck"
• UserMemoryStore extracted: "User's name is Charlie Brown; friends call him Chuck"
• Session 2 correctly recalled "Chuck"

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Priority 2: Smoke Tests

00_quickstart/01_always_learn.py

Status: PASS

Description: Basic ALWAYS mode learning with automatic extraction.

Result: Agent learned user info (Alice, Anthropic research scientist, prefers concise responses) and recalled it in session 2.

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00_quickstart/02_agentic_learn.py

Status: PASS

Description: Basic AGENTIC mode where agent has tools to update memory.

Result: Agent used update_user_memory tool and correctly recalled user info.

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00_quickstart/03_learned_knowledge.py

Status: PASS

Description: Tests learned knowledge sharing across users.

Result:

• User 1 saved "reduce cloud egress costs" goal
• User 2 received advice that incorporated the egress cost consideration ("Given your org goal to reduce egress costs, this should be a top discriminator")

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Priority 3: User Profile/Memory

01_basics/1a_user_profile_always.py

Status: PASS

Description: UserProfileStore with ALWAYS mode extraction.

Result: Extracted profile (Alice Chen / Ali) and recalled correctly in session 2.

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01_basics/2a_user_memory_always.py

Status: PASS

Description: UserMemoryStore with ALWAYS mode extraction.

Result: Extracted memories about user's work and preferences, applied them in session 2 response.

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Priority 4: Other Stores

01_basics/3a_session_context_summary.py

Status: PASS

Description: SessionContextStore tracking conversation state.

Result: Maintained session summary across turns, correctly summarized the API design discussion when asked "What did we decide?"

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01_basics/4_learned_knowledge.py

Status: PASS

Description: Basic LearnedKnowledgeStore functionality.

Result: Agent searched learnings, incorporated egress cost goal into cloud provider recommendations.

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Summary

Category	Tests	Passed	Failed
Priority 1 (Recent Changes)	3	3	0
Priority 2 (Smoke Tests)	3	3	0
Priority 3 (User Profile/Memory)	2	2	0
Priority 4 (Other Stores)	2	2	0
Total	10	10	0

All tests passing after the following changes:

1. learning=True now enables both user_profile and user_memory by default
2. LearnedKnowledgeStore prompt restructured with Rules 1-4 in CRITICAL RULES section
3. Added Rule 3 (explicit save requests) and Rule 4 (org goals/constraints/policies)
4. Removed emoji from PROPOSE mode
5. Fixed learning_saved state reset bug
6. Simplified tool docstrings (removed redundant "when to save" criteria)
7. Updated extraction prompt with clearer two-category structure