# Conversation Summarization & Pruning

Manages conversation history by summarizing long conversations and enforcing retention policies.

## Features

- **Automatic Summarization**: Summarize conversations when they exceed size limits
- **Message Pruning**: Keep recent messages, summarize older ones
- **Retention Policies**: Automatic deletion of old conversations
- **Privacy Controls**: User can delete specific sessions

## Usage

### Summarization

```python
from conversation.summarization.summarizer import get_summarizer

summarizer = get_summarizer()

# Check if summarization needed
messages = session.get_messages()
if summarizer.should_summarize(len(messages), total_tokens=5000):
    summary = summarizer.summarize(messages, agent_type="family")
    
    # Prune messages, keeping recent ones
    pruned = summarizer.prune_messages(
        messages,
        keep_recent=10,
        summary=summary
    )
    
    # Update session with pruned messages
    session.update_messages(pruned)
```

### Retention

```python
from conversation.summarization.retention import get_retention_manager

retention = get_retention_manager()

# List old sessions
old_sessions = retention.list_old_sessions()

# Delete specific session
retention.delete_session("session-123")

# Clean up old sessions (if auto_delete enabled)
deleted_count = retention.cleanup_old_sessions()

# Enforce maximum session limit
deleted_count = retention.enforce_max_sessions()
```

## Configuration

### Summarization Thresholds

- **Max Messages**: 20 messages (default)
- **Max Tokens**: 4000 tokens (default)
- **Keep Recent**: 10 messages when pruning

### Retention Policy

- **Max Age**: 90 days (default)
- **Max Sessions**: 1000 sessions (default)
- **Auto Delete**: False (default) - manual cleanup required

## Integration

### With Session Manager

The session manager should check for summarization when:
- Adding new messages
- Retrieving session for use
- Before saving session

### With LLM

Summarization uses LLM to create concise summaries that preserve:
- Important facts and information
- Decisions made or actions taken
- User preferences or requests
- Tasks or reminders created
- Key context for future conversations

## Privacy

- Users can delete specific sessions
- Automatic cleanup respects retention policy
- Summaries preserve context but reduce verbosity
- No external storage - all local

## Future Enhancements

- LLM integration for better summaries
- Semantic search over conversation history
- Export conversations before deletion
- Configurable retention per session type
- Conversation analytics