Association Graph
Memory Relationships
The Association Graph is how QUI connects related memories.
Instead of treating each memory as a separate note, QUI builds relationships between memories that belong together. This helps a character remember not only one useful detail, but also nearby context that may matter.
Why It Matters
A character may remember that you prefer a certain workflow.
The graph can help connect that preference to past projects, previous decisions, or related conversations.
This makes memory feel less like a search box and more like a web of connected understanding.
How Connections Grow
Connections form naturally as you use QUI.
Memories that appear together, support the same topic, or are often useful in the same kind of conversation become more closely related.
Over time, this creates clusters around important themes such as:
- A project you work on often
- A character’s identity or personality
- Your recurring preferences
- Important decisions
- Long-running conversations
- Related tools, workflows, or topics
Connected Context
The Association Graph helps QUI bring in nearby context when it may be useful.
This means a character can respond with a better sense of continuity, without needing to retrieve every memory separately.
For example, a memory about your preferred workflow may connect to:
- A project where you used that workflow
- A previous decision about how you like work organized
- A related tool or process
- A recurring preference you have expressed before
These connections help the character understand the broader pattern, not just the isolated fact.
Memory as a Network
The Association Graph allows memory to become more than a list of saved details.
As the character’s history grows, related memories can form a network of meaning. This helps the character recognize patterns, connect old and new context, and keep long-running conversations more coherent.
The result is memory that feels more natural, connected, and useful over time.
