---
title: Direct Import
description: 'Bypass the memory deduction phase and directly store pre-defined memories for efficient retrieval'
---

## How to Use Direct Import

The Direct Import feature allows users to skip the memory deduction phase and directly input pre-defined memories into the system for storage and retrieval. To enable this feature, set the `infer` parameter to `False` in the `add` method.


<CodeGroup>


```python Python
messages = [
    {"role": "user", "content": "Alice loves playing badminton"},
    {"role": "assistant", "content": "That's great! Alice is a fitness freak"},
    {"role": "user", "content": "Alice mostly cooks at home because of her gym plan"},
]


client.add(messages, user_id="alice", infer=False)
```

```markdown Output
[]
```
</CodeGroup>

You can see that the output of the add call is an empty list.

<Note>Only messages with the role "user" will be used for storage. Messages with roles such as "assistant" or "system" will be ignored during the storage process.</Note>

<Warning>
Direct import skips the inference pipeline, so it also skips duplicate detection. If you later send the same fact with `infer=True`, Mem0 will store a second copy. Pick one mode per memory source unless you truly want both versions.
</Warning>

## How to Retrieve Memories

You can retrieve memories using the `search` method.

<CodeGroup>

```python Python
client.search("What is Alice's favorite sport?", filters={"user_id": "alice"})
```

```json Output
{
  "results": [
    {
      "id": "19d6d7aa-2454-4e58-96fc-e74d9e9f8dd1",
      "memory": "Alice loves playing badminton",
      "user_id": "pc123",
      "metadata": null,
      "categories": null,
      "created_at": "2024-10-15T21:52:11.474901-07:00",
      "updated_at": "2024-10-15T21:52:11.474912-07:00"
    }
  ]
}
```

</CodeGroup>

## How to Retrieve All Memories

You can retrieve all memories using the `get_all` method.

<Callout type="warning" title="Filters Required">
`get_all()` now requires filters to be specified.
</Callout>

<CodeGroup>

```python Python
client.get_all(filters={"AND": [{"user_id": "alice"}]})
```

```json Output
{
  "results": [
    {
      "id": "19d6d7aa-2454-4e58-96fc-e74d9e9f8dd1",
      "memory": "Alice loves playing badminton",
      "user_id": "pc123",
      "metadata": null,
      "categories": null,
      "created_at": "2024-10-15T21:52:11.474901-07:00",
      "updated_at": "2024-10-15T21:52:11.474912-07:00"
    },
    {
      "id": "8557f05d-7b3c-47e5-b409-9886f9e314fc",
      "memory": "Alice mostly cooks at home because of her gym plan",
      "user_id": "pc123",
      "metadata": null,
      "categories": null,
      "created_at": "2024-10-15T21:52:11.474929-07:00",
      "updated_at": "2024-10-15T21:52:11.474932-07:00"
    }
  ]
}
```

</CodeGroup>

If you have any questions, please feel free to reach out to us using one of the following methods:

<Snippet file="get-help.mdx" />
