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# Sleeptime Agents
Sleeptime agents run background processing to refine and organize memory between conversations.
## Enabling Sleeptime
```python
agent = client.agents.create(
model="anthropic/claude-sonnet-4-5-20250929",
embedding="openai/text-embedding-3-small",
memory_blocks=[
{"label": "persona", "value": "I am a helpful assistant."},
{"label": "human", "value": "User information."}
],
enable_sleeptime=True # Creates a background sleeptime agent
)
```
```typescript
const agent = await client.agents.create({
model: "anthropic/claude-sonnet-4-5-20250929",
embedding: "openai/text-embedding-3-small",
memory_blocks: [
{ label: "persona", value: "I am a helpful assistant." },
{ label: "human", value: "User information." }
],
enable_sleeptime: true
});
```
## How It Works
1. **Main agent** handles real-time conversations
2. **Sleeptime agent** runs in background between conversations
3. Sleeptime agent reviews conversation history and refines memory blocks
4. Both agents share the same memory blocks
```
User conversation
↓
Main Agent (real-time)
↓
Memory blocks updated
↓
[Time passes...]
↓
Sleeptime Agent (background)
↓
Memory blocks refined/organized
```
## Enabling on Existing Agent
```python
# Enable sleeptime on an existing agent
client.agents.update(
agent_id=agent.id,
enable_sleeptime=True
)
```
## When to Use Sleeptime
**Good for:**
- Personal assistants that learn over time
- Agents that need to consolidate information
- Long-running agents with many conversations
- Memory organization and deduplication
**Not needed for:**
- Stateless support bots
- Single-session interactions
- Agents where memory doesn't evolve
## Sleeptime Frequency
The sleeptime agent runs periodically based on conversation activity. You can configure frequency:
```python
client.agents.update(
agent_id=agent.id,
sleeptime_agent_frequency=5 # Run after every 5 conversations
)
```
## Monitoring Sleeptime
Check sleeptime agent activity in ADE:
1. Open your agent
2. Look for the sleeptime agent indicator
3. View memory block changes over time
## Example: Learning Assistant
```python
# Create an agent that learns and improves over time
agent = client.agents.create(
model="anthropic/claude-sonnet-4-5-20250929",
embedding="openai/text-embedding-3-small",
memory_blocks=[
{
"label": "persona",
"value": "I am a learning assistant. I remember what works and what doesn't."
},
{
"label": "human",
"value": "User preferences and learning style."
},
{
"label": "lessons_learned",
"value": "Insights from past interactions:"
}
],
enable_sleeptime=True
)
# After many conversations, the sleeptime agent will:
# - Consolidate repeated information
# - Organize the lessons_learned block
# - Update human block with patterns it notices
```