Memory & Prompting

Juno uses ephemeral session memory to retain context across interactions. This memory feeds into prompt construction for the AI assistant and improves interface responsiveness without relying on persistent storage.

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Memory Model

Memory is scoped per session and tied to the active wallet. When a user connects or switches, memory is reset.

Stored fields:

{
  address: string,
  signals: Signal[],
  tokenRisks: Record<string, TokenRisk>,
  filter: string,
  promptHistory: string[]
}

• signals holds recent signal objects (type, confidence, timestamp)

• tokenRisks maps token addresses to known risk flags

• filter tracks the current UI signal filter

• promptHistory stores the last few assistant interactions

Memory is stored in client state, no backend persistence or database.

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Prompt Construction

When the assistant is triggered, Juno assembles a prompt using current memory + interface state.

Example output:

Wallet 9gzL...vU7W is holding 3 tokens. Total value is $1,450.

Recent signals:
- trend-reversal (0.88 confidence)
- deployer-active (0.81 confidence)

Token ZAZA is mintable and unverified.

The user is filtering by: trend-reversal

Respond with the most important updates based on this state.

This prompt is sent directly to the language model. No on-the-fly blockchain queries are made at prompt time. All data is preloaded and scoped.

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Behavior

• On wallet disconnect: memory is cleared

• On signal update: memory is patched in place

• On assistant reply: promptHistory is appended

• On refresh: memory is rebuilt from scratch

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