mem0/docs/api-reference/memory/search-memories.mdx

---
title: 'Search Memories'
description: "Search memories with hybrid retrieval (semantic + BM25 + entity matching) and advanced filtering using logical and comparison operators."
openapi: post /v3/memories/search/
---

Relevance-ranked hybrid search across stored memories. V3 uses multi-signal retrieval — semantic, BM25 keyword, and entity matching scored in parallel and fused. The returned `score` is a combined `[0, 1]` value.

Entity IDs (`user_id`, `agent_id`, `app_id`, `run_id`) **must** be passed inside the `filters` object — top-level entity IDs are rejected with 400. At least one entity ID is required.

The `filters` object supports complex logical operations (AND, OR, NOT) and comparison operators:
- `in`: Matches any of the values specified
- `gte`: Greater than or equal to
- `lte`: Less than or equal to
- `gt`: Greater than
- `lt`: Less than
- `ne`: Not equal to
- `icontains`: Case-insensitive containment check
- `*`: Wildcard character that matches everything

## Temporal fields in V3 responses

When Temporal Reasoning is enabled for a query, search results can include additional **top-level** fields such as:

- `memory_type`
- `event_date`
- `event_start`
- `event_end`
- `plan_status`
- `effective_plan_status`
- `time_precision`
- `temporal_surface`
- `reference_date_used`
- `score_breakdown.temporal_boost`

### Search parameter defaults

| Parameter | V1/V2 | V3 |
| --- | --- | --- |
| `top_k` | Supported (default 10) | Supported (1-1000, default 10) |
| `threshold` | No default | Default `0.1` (pass `0.0` to disable) |
| `rerank` | Default `true` | Default `false` (pass `true` to enable) |

<CodeGroup>
```python Platform API Example
related_memories = client.search(
    query="What are Alice's hobbies?",
    filters={
        "OR": [
            {
              "user_id": "alice"
            },
            {
              "agent_id": {"in": ["travel-agent", "sports-agent"]}
            }
        ]
    },
)
```

```json Output
{
  "results": [
    {
      "id": "ea925981-272f-40dd-b576-be64e4871429",
      "memory": "Likes to play cricket and plays cricket on weekends.",
      "user_id": "alice",
      "metadata": {
        "category": "hobbies"
      },
      "score": 0.82,
      "score_breakdown": {
        "semantic": 0.79,
        "bm25": 0.0,
        "entity": 0.0,
        "temporal_boost": 0.0
      },
      "created_at": "2024-07-26T10:29:36.630547-07:00",
      "updated_at": null,
      "categories": ["hobbies"]
    }
  ]
}
```
</CodeGroup>

### Temporal example

<CodeGroup>
```python Platform API Example
results = client.search(
    query="what did I do last week?",
    filters={"user_id": "alice"},
    reference_date="2025-03-21T00:00:00Z",
)
```

```json Output
{
  "results": [
    {
      "id": "9b59b0fd-0b31-4a0b-a3ad-7f26bb4f1f8d",
      "memory": "Finished the Q1 product review on March 10, 2025.",
      "user_id": "alice",
      "score": 0.91,
      "score_breakdown": {
        "semantic": 0.84,
        "bm25": 0.0,
        "entity": 0.0,
        "temporal_boost": 0.07
      },
      "memory_type": "event",
      "event_date": "2025-03-10",
      "event_start": "2025-03-10",
      "event_end": "2025-03-10",
      "plan_status": null,
      "effective_plan_status": null,
      "time_precision": "day",
      "temporal_surface": "Mar 10, 2025",
      "reference_date_used": "2025-03-21",
      "metadata": {},
      "categories": [],
      "created_at": "2025-03-10T00:00:00Z",
      "updated_at": "2025-03-10T00:00:00Z"
    }
  ]
}
```
</CodeGroup>

<Note>
  Temporal fields are most useful on `search`. The paginated `get_all` endpoint remains a broader retrieval surface and does not mirror the full time-aware search result shape.
</Note>

<CodeGroup>
```python Wildcard Example
# Using wildcard to match all run_ids for a specific user
all_memories = client.search(
    query="What are Alice's hobbies?",
    filters={
        "AND": [
            {
                "user_id": "alice"
            },
            {
                "run_id": "*"
            }
        ]
    },
)
```
</CodeGroup>

<CodeGroup>
```python Categories Filter Examples
# Example 1: Using 'contains' for partial matching
finance_memories = client.search(
    query="What are my financial goals?",
    filters={
        "AND": [
            { "user_id": "alice" },
            {
                "categories": {
                    "contains": "finance"
                }
            }
        ]
    },
)

# Example 2: Using 'in' for exact matching
personal_memories = client.search(
    query="What personal information do you have?",
    filters={
        "AND": [
            { "user_id": "alice" },
            {
                "categories": {
                    "in": ["personal_information"]
                }
            }
        ]
    },
)
```
</CodeGroup>