Memory Overview

Understanding Memory Systems

The Memory function represents a sophisticated approach to channel personalisation, combining manually curated information with machine learning capabilities. This dual-system approach creates an evolving knowledge base that enhances stream interactions through contextual awareness and viewer recognition.

Static Memory Architecture

The static memory component serves as the foundation of channel knowledge, comprising deliberately input information that remains consistent unless manually updated. Think of static memory as your channel’s reference library - a collection of essential facts and specifications that define your streaming environment. This includes detailed information about your streaming setup, carefully crafted descriptions of channel-specific emojis and their contextual usage, comprehensive performance statistics, and other fundamental channel characteristics.

When you input information into the static memory system, you’re essentially teaching the bot permanent facts about your channel. For instance, you might provide details about your gaming rig, document your speedrunning achievements, or outline specific community guidelines. This information forms a reliable foundation that the bot can consistently reference when interacting with viewers.

Dynamic Memory Evolution

In contrast to the structured nature of static memory, the dynamic memory system functions as an adaptive learning mechanism, continuously gathering and processing information from stream interactions. This system observes and records patterns in viewer behaviour, gaming preferences, and community interactions, building an ever-expanding understanding of your channel’s ecosystem.

The dynamic memory system excels at identifying recurring themes in chat discussions, memorable quotes from community members, and evolving viewer interests. For example, if certain games consistently generate enthusiastic chat responses, the system notes this pattern. Similarly, it recognises regular viewers’ communication styles and preferences, allowing for more personalised interactions over time.

Profile Development and Management

As the memory systems work in tandem, they create sophisticated profiles that capture both static facts and dynamic observations about your channel and community. These profiles serve as comprehensive reference points for AI interactions, combining manually input information with learned patterns and behaviours.

The beauty of this profile system lies in its flexibility - while the bot continuously updates its understanding through observation, you retain the ability to edit and refine these profiles manually. This ensures that the accumulated knowledge remains accurate and aligned with your channel’s evolving nature.

Document Uploads

You can upload documents in .txt, .docx, and .pdf formats (10MB Max) to significantly enhance your bot’s understanding of you as a streamer and your community. These documents serve as valuable knowledge sources that allow the bot to learn about your specific content style, frequently asked questions, community inside jokes, and established traditions. By providing these files, you enable the bot to deliver more personalised and contextually appropriate responses to your viewers, creating a more seamless and authentic interaction experience. Rather than relying solely on generic knowledge, your bot will be able to reference the exact information you’ve shared, resulting in a digital assistant that genuinely reflects your unique streaming persona and community culture

Technical Implementation

The implementation of this dual-memory architecture creates a robust foundation for sophisticated channel interactions. The static memory provides unwavering reference points, while the dynamic memory adds layers of contextual understanding through continuous learning. This combination enables the bot to generate responses that feel both consistent and personal, drawing from both established facts and observed patterns.

Through this architecture, the system can maintain appropriate contextual awareness across various stream scenarios, from casual chat interactions to moderation decisions. The bot’s responses become increasingly refined over time as it builds a more nuanced understanding of your channel’s unique characteristics and community dynamics.

Future Learning and Adaptation

The Memory function’s true power lies in its ability to grow alongside your channel. As static memory provides stable foundations, dynamic memory continues to evolve, creating an increasingly sophisticated understanding of your streaming environment. This ongoing development ensures that the bot’s interactions remain relevant and appropriate as your channel grows and changes over time.

Remember that while the system learns automatically through its dynamic memory component, you maintain control over its knowledge base through the ability to edit both static and dynamic memory elements. This balance ensures that the bot’s understanding aligns with your channel’s goals while continuously adapting to your community’s evolving nature.