> ## Documentation Index
> Fetch the complete documentation index at: https://docs.memoryo.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# General Engine

The General Engine is the default. It works for most AI products — chatbots, coding agents, productivity copilots, SaaS personalization, internal knowledge tools — anything that needs persistent user memory without an industry-specific schema.

## Memory categories

| Category       | Example                                            |
| -------------- | -------------------------------------------------- |
| `preference`   | User prefers concise answers with Python examples. |
| `fact`         | User works in a B2B SaaS support team.             |
| `goal`         | User is preparing to launch an AI product.         |
| `procedure`    | User wants weekly summaries every Friday.          |
| `relationship` | User reports to the Head of Product.               |
| `expertise`    | User is comfortable with FastAPI and PostgreSQL.   |

## Write

`add()` authenticates the tenant, resolves `external_user_id`, runs the quality gate, queues extraction, resolves conflicts, stores memories, and indexes vectors — then returns a job result. Extraction is async.

```python theme={null}
result = mem.add(
    messages=[
        {
            "role": "user",
            "content": "Remember that I prefer concise technical explanations with Python examples.",
        }
    ],
    external_user_id="user_123",
)
```

Possible outcomes:

| Status        | What to do                                       |
| ------------- | ------------------------------------------------ |
| `queued`      | Continue normally                                |
| `passthrough` | Skip memory context, still call the LLM          |
| `L1`          | Per-user rate limit — retry later                |
| `L2`          | Low-quality input — don't retry the same message |
| `L3`          | Near-duplicate — avoid repeated writes           |
| `L4`          | Budget block — wait for reset or upgrade         |

<Tip>Blocking add() should not affect LLM calls.</Tip>

## Retrieve

Call `get()` before the model call. MemoryOS ranks memories by semantic relevance, importance, recency, and hot-tier signals, then returns `system_prompt_addition` ready to prepend.

```python theme={null}
memories = mem.get(
    query="answer this user's integration question",
    external_user_id="user_123",
    limit=5,
    context_max_tokens=500,
)

system_prompt = "You are a helpful assistant."
if memories.has_context:
    system_prompt = f"{system_prompt}\n\n{memories.system_prompt_addition}"
```

Use a query that describes the current task. `"answer this user's question"` retrieves better than `"preferences"` or `"memory"`.

## When to switch to a domain schema

The General Engine is the right default. Move to a domain schema when your product needs structured domain memory:

* **EdTech** — student profiles, weak topics, exams, forgetting stages
* **Support** — customer issue history, support type, sentiment, escalation risk

## Related pages

* [Cookbook: general AI memory](/cookbooks/general-ai-memory)
* [Domain schemas](/concepts/domain-schemas)
* [POST /v1/memories/add](/api-reference/add)
* [POST /v1/memories/retrieve](/api-reference/retrieve)