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Product API smoke tests (local 0.0.0.0:8001)

Source: MemTensor#518

Prerequisites

  • Service is running: python -m uvicorn memos.api.server_api:app --host 0.0.0.0 --port 8001
  • .env is configured for Redis, embeddings, and the vector DB (current test setup: Redis reachable, Qdrant Cloud connected).

1) /product/add

  • Purpose: Write a memory (sync/async).

  • Example request (sync):

    curl -s -X POST http://127.0.0.1:8001/product/add \
  -H 'Content-Type: application/json' \
  -d '{
        "user_id": "tester",
        "mem_cube_id": "default_cube",
        "memory_content": "Apple is a fruit rich in fiber.",
        "async_mode": "sync"
      }'

  • Observed result: 200, message: "Memory added successfully", returns the written memory_id and related info.

2) /product/get_all

  • Purpose: List all memories for the user/type to confirm writes.

  • Example request:

    curl -s -X POST http://127.0.0.1:8001/product/get_all \
  -H 'Content-Type: application/json' \
  -d '{
        "user_id": "tester",
        "memory_type": "text_mem",
        "mem_cube_ids": ["default_cube"]
      }'

  • Observed result: 200, shows the recently written apple memories (WorkingMemory/LongTermMemory/UserMemory present, vector_sync=success).

3) /product/search

  • Purpose: Vector search memories.

  • Example request:

    curl -s -X POST http://127.0.0.1:8001/product/search \
  -H 'Content-Type: application/json' \
  -d '{
        "query": "What fruit is rich in fiber?",
        "user_id": "tester",
        "mem_cube_id": "default_cube",
        "top_k": 5,
        "pref_top_k": 3,
        "include_preference": false
      }'

  • Observed result: previously returned 400 because payload indexes (e.g., vector_sync) were missing in Qdrant. Index creation is now automatic during Qdrant initialization (memory_type/status/vector_sync/user_name).

  • If results are empty or errors persist, verify indexes exist (auto-created on restart) or recreate/clean the collection.

Notes / Next steps

  • /product/add and /product/get_all are healthy.
  • /product/search still returns empty results even with vectors present; likely related to search filters or vector retrieval.
  • Suggested follow-ups: inspect SearchHandler flow, filter conditions (user_id/session/cube_name), and vector DB search calls; capture logs or compare with direct VecDBFactory.search calls.