## Documentation Index

Fetch the complete documentation index at: [/llms.txt](https://docs.mem0.ai/llms.txt)

Use this file to discover all available pages before exploring further.

Nora runs a travel service. When she stored all memories in one bucket, a recruiter’s nut allergy accidentally appeared in a traveler’s dinner reservation. Let’s fix this by properly separating memories for different users, agents, and applications.

**Time to complete:** ~15 minutes · **Languages:** Python

## Setup

```python
from mem0 import MemoryClient

client = MemoryClient(api_key="m0-...")
```

Grab an API key from the [Mem0 dashboard](https://app.mem0.ai/?utm_source=oss&utm_medium=cookbook-entity-partitioning) to get started.

## Store and Retrieve Scoped Memories

Let’s start by storing Cam’s travel preferences and retrieving them:

```python
cam_messages = [\
    {"role": "user", "content": "I'm Cam. Keep in mind I avoid shellfish and prefer boutique hotels."},\
    {"role": "assistant", "content": "Noted! I'll use those preferences in future itineraries."}\
]

result = client.add(
    cam_messages,
    user_id="traveler_cam",
    agent_id="travel_planner",
    run_id="tokyo-2025-weekend",
    app_id="concierge_app"
)
```

The memory is now stored. Let’s retrieve those memories with the same identifiers:

```python
user_scope = {
    "AND": [\
        {"user_id": "traveler_cam"},\
        {"app_id": "concierge_app"},\
        {"run_id": "tokyo-2025-weekend"}\
    ]
}
user_memories = client.search("Any dietary restrictions?", filters=user_scope)
print(user_memories)

agent_scope = {
    "AND": [\
        {"agent_id": "travel_planner"},\
        {"app_id": "concierge_app"}\
    ]
}
agent_memories = client.search("Any dietary restrictions?", filters=agent_scope)
print(agent_memories)
```

**Output:**

```
# User scope returns user's memory
{'results': [{'memory': 'avoids shellfish and prefers boutique hotels', ...}]}
# Agent scope returns agent's own memory
{'results': [{'memory': 'Cam prefers boutique hotels and avoids shellfish', ...}]}
```

Memories can be written with several identifiers, but each search resolves one entity boundary at a time. Run separate queries for user and agent scopes, as shown above, rather than combining both in a single filter.

## When Memories Leak

When Nora adds a chef agent, Cam’s travel preferences leak into food recommendations:

```python
chef_filters = {"AND": [{"user_id": "traveler_cam"}]}

collision = client.search("What should I cook?", filters=chef_filters)
print(collision)
```

**Output:**

```
['avoids shellfish and prefers boutique hotels', 'prefers Kyoto kaiseki dining experiences']
```

The travel preferences appear because we only filtered by `user_id`. The chef agent shouldn’t see hotel preferences.

## Fix the Leak with Proper Filters

First, let’s add a memory specifically for the chef agent:

```python
chef_memory = [\
    {"role": "user", "content": "I'd like to try some authentic Kyoto cuisine."},\
    {"role": "assistant", "content": "I'll remember that you prefer Kyoto kaiseki dining experiences."}\
]

client.add(
    chef_memory,
    user_id="traveler_cam",
    agent_id="chef_recommender",
    run_id="menu-planning-2025-04",
    app_id="concierge_app"
)
```

Now search within the chef’s scope:

```python
safe_filters = {
    "AND": [\
        {"agent_id": "chef_recommender"},\
        {"app_id": "concierge_app"},\
        {"run_id": "menu-planning-2025-04"}\
    ]
}

chef_memories = client.search("Any food alerts?", filters=safe_filters)
print(chef_memories)
```

**Output:**

```
{'results': [{'memory': 'prefers Kyoto kaiseki dining experiences', ...}]}
```

Now the chef agent only sees its own food preferences. The hotel preferences stay with the travel agent.

## Separate Apps with app_id

Nora white-labels her travel service for a sports brand. Use `app_id` to keep enterprise data separate:

```python
enterprise_filters = {
    "AND": [\
        {"app_id": "sports_brand_portal"}\
    ],
    "OR": [\
        {"user_id": "*"},\
        {"agent_id": "*"}\
    ]
}

page = client.get_all(filters=enterprise_filters, page=1, page_size=10)
print([row["user_id"] for row in page["results"]])
```

**Output:**

```
['athlete_jane', 'coach_mike', 'team_admin']
```

Wildcards (`"*"`) only match non-null values. Make sure you write memories with explicit `app_id` values.

When the sports brand offboards, delete all their data:

```python
client.delete_all(app_id="sports_brand_portal")
```

**Output:**

```
{'message': 'Memories deleted successfully!'}
```

## Production Patterns

```python
# Nightly audits - check all data for an app
def audit_app(app_id: str):
    filters = {
        "AND": [{"app_id": app_id}],
        "OR": [{"user_id": "*"}, {"agent_id": "*"}]
    }
    return client.get_all(filters=filters, page=1, page_size=50)

# Session cleanup - delete temporary conversations
def close_ticket(ticket_id: str, user_id: str):
    client.delete_all(user_id=user_id, run_id=ticket_id)

# Compliance exports - get all data for one tenant
export = client.get_memory_export(filters={"AND": [{"app_id": "sports_brand_portal"}]})
```

## Complete Example

Putting it all together - here’s how to properly scope memories:

```python
# Store memories with all identifiers
client.add(
    [{"role": "user", "content": "I need a hotel near the conference center."}],
    user_id="exec_123",
    agent_id="booking_assistant",
    app_id="enterprise_portal",
    run_id="trip-2025-03"
)

# Retrieve with the same scope
filters = {
    "AND": [\
        {"user_id": "exec_123"},\
        {"app_id": "enterprise_portal"},\
        {"run_id": "trip-2025-03"}\
    ]
}

# Alternative: Use wildcards if you're not sure about some fields
# filters = {
#     "AND": [\
#         {"user_id": "exec_123"},\
#         {"agent_id": "*"},  # Match any agent\
#         {"app_id": "enterprise_portal"},\
#         {"run_id": "*"}      # Match any run\
#     ]
# }

results = client.search("Hotels near conference", filters=filters)

# Debug: Print the filter you're using
print(f"Searching with filters: {filters}")

# If no results, try a broader search to see what's stored
if not results["results"]:
    print("No results found! Trying broader search...")
    broader = client.get_all(filters={"user_id": "exec_123"})
    print(broader)

print(results["results"][0]["memory"])  
```

**Output:**

```
I need a hotel near the conference center.
```

## When to Use Each Identifier

| Identifier | When to Use | Example Values |
| --- | --- | --- |
| `user_id` | Individual preferences that persist across all interactions | `cam_traveler`, `sarah_exec`, `team_alpha` |
| `agent_id` | Different AI roles need separate context | `travel_agent`, `concierge`, `customer_support` |
| `app_id` | White-label deployments or separate products | `travel_app_ios`, `enterprise_portal`, `partner_integration` |
| `run_id` | Temporary sessions that should be isolated | `support_ticket_9234`, `chat_session_456`, `booking_flow_789` |

## Troubleshooting Common Issues

### My search returns empty results!

**Problem**: Using `AND` with exact matches but some fields might be `null`.

**Solution**:

```python
# If this returns nothing:
filters = {"AND": [{"user_id": "u1"}, {"agent_id": "a1"}]}

# Try using wildcards:
filters = {"AND": [{"user_id": "u1"}, {"agent_id": "*"}]}

# Or don't include fields you don't need:
filters = {"AND": [{"user_id": "u1"}]}
```

### OR gives results but AND doesn’t

This confirms you have a **field mismatch**. The memory exists but some identifier values don’t match exactly.

**Always check what’s actually stored:**

```python
# Get all memories for the user to see the actual field values
all_mems = client.get_all(filters={"user_id": "your_user_id"})
print(json.dumps(all_mems, indent=2))
```

## Best Practices

1. **Use consistent identifier formats**

```python
# Good: consistent patterns
user_id = "cam_traveler"
agent_id = "travel_agent_v1"
app_id = "nora_concierge_app"
run_id = "tokyo_trip_2025_03"

# Avoid: mixed patterns
# user_id = "123", agent_id = "agent2", app_id = "app"
```

2. **Print filters when debugging**

```python
filters = {"AND": [{"user_id": "cam", "agent_id": "chef"}]}
print(f"Searching with filters: {filters}")  # Helps catch typos
```

3. **Clean up temporary sessions**

```python
# After a support ticket closes
client.delete_all(user_id="customer_123", run_id="ticket_456")
```

## Summary

You learned how to:

- Store memories with proper entity scoping using `user_id`, `agent_id`, `app_id`, and `run_id`
- Prevent memory leaks between different agents and applications
- Clean up data for specific tenants or sessions
- Use wildcards to query across scoped memories

## Next Steps

[**Deep Dive: Memory Filters v2**](https://docs.mem0.ai/platform/features/v2-memory-filters)

[**Control Memory Ingestion**](https://docs.mem0.ai/cookbooks/essentials/controlling-memory-ingestion)