Conversations

R2R Conversations enable multi-turn interactions between users and the system, storing messages and preserving context across interactions. They serve as containers for chat sessions, agent interactions, and collaborative discussions.

Refer to the conversations API and SDK reference for detailed examples for interacting with conversations.

Core Concepts

Conversations in R2R maintain context through three key mechanisms:

1. Message Threading - Messages are stored in chronological order with optional parent-child relationships, enabling threaded discussions and branching conversations.

2. Context Preservation - The system preserves conversation context across messages, allowing for coherent multi-turn interactions and advanced retrieval capabilities.

3. User Association - Each conversation is owned by a specific user and can be shared with other users, enabling both private and collaborative chat sessions.

Message Management

Creating Messages

Messages represent individual turns in a conversation. Each message includes:

• Content (the actual message text)
• Role (user, assistant, or system)
• Optional parent message reference
• Metadata for additional context

Messages can be added to conversations at any time, and the system maintains their chronological order while preserving threading relationships.

Updating Messages

The system allows for message editing while maintaining conversation integrity:

• Content can be updated
• Metadata can be modified or enriched
• Threading relationships remain intact
• Edit history is preserved in metadata

Conversation Features

Organization

Conversations can be organized and managed through:

• Custom naming and descriptions
• Filtering and search capabilities
• Metadata tags and annotations
• Chronological or threaded views

Access Control

R2R implements straightforward access controls for conversations:

• Private conversations visible only to their owner
• Shared conversations accessible to specified users
• Superuser access for system management

Integration with Agents

When used with agents, conversations enable:

• Persistent context for AI interactions
• Multi-turn query processing
• Knowledge graph integration
• Automated content analysis

Superuser Features

Superusers have access to additional conversation management capabilities:

• Bulk export of conversations
• Usage analytics and reporting
• System-wide conversation search
• Advanced filtering and organization

Data Management

The system provides tools for effective conversation management:

1. Retrieval - Fetch conversations by ID, filter by date, or search content
2. Updates - Modify conversation properties and message content
3. Deletion - Remove conversations while preserving system integrity
4. Export - Download conversation data in standard formats

Conclusion

R2R Conversations provide a robust foundation for managing multi-turn interactions. Through careful message threading, context preservation, and integration with other R2R systems, conversations enable sophisticated chat applications, agent interactions, and collaborative discussions.