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AI models don’t inherently remember previous messages — each request is processed independently. To keep a conversation coherent, Pria includes your recent exchanges with every new prompt, so the model can follow references like “add the error codes section” without you re-explaining what you’re working on. That context isn’t free: every included exchange adds to the tokens processed per request. The Remember History setting is your control over the balance between context depth and cost.

Session-Based Context

Only includes exchanges from the current conversation — unrelated threads never bleed in

Adjustable 0–15

A slider from 0 (no history) to 15 dialogue exchanges; the default is 3

Cost-Aware

More history = more tokens per request (1 credit ≈ 10,000 tokens)

Smart Compaction

At 6 or higher, older exchanges are automatically summarized to keep costs down

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Adjusting Remember History

Open the sidebar and find Remember History under the Knowledge sub-menu (it’s also in your profile’s Conversation Preferences). The slider runs from 0 to 15 with named marks: None (0) · Default (3) · Conversation (6) · Research (12). Conversation History Setting
Setting it to 0 turns history off entirely — every prompt stands alone. Handy for batches of unrelated one-shot questions.

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What it costs

Every exchange included in history adds its tokens to each new request. As a rough illustration: if each exchange averages 2,500 tokens, a setting of 8 adds ~20,000 history tokens to every prompt — about 2 credits before your new question is even counted. Three habits keep costs in check:
  • Match the setting to the task — high for deep work, low for quick questions.
  • Start a new conversation when the topic changes — unrelated history is pure waste.
  • Store lasting preferences in User Memory instead of repeating them in chat — memory parameters cost almost nothing compared to carried history.

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Smart history compaction

When Remember History is 6 or higher, Pria automatically compacts older history instead of sending it word-for-word:
  • Your 3 most recent exchanges are always included verbatim — full detail on what you just discussed.
  • Older exchanges are summarized into a concise context block that preserves key topics and decisions at a fraction of the tokens.
  • Summaries are reused between requests in the same conversation, so follow-ups don’t pay to re-summarize the same history.
  • If compaction is ever unavailable, your full history is used instead — nothing breaks.
Example: with the setting at 12 and 12 exchanges in the conversation, sending everything verbatim might cost ~30,000 history tokens per request. With compaction, exchanges 1–9 compress to ~3,000 tokens plus ~7,500 verbatim for the last three — roughly a 65% reduction with no visible difference in how the AI responds.
Because of compaction, 6–8 is a sweet spot for general use and 10–12 for complex projects — you get long-range context without the proportional cost.

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Boundaries

  • Each conversation keeps its own history — starting a new conversation starts a clean context.
  • Assistants don’t share history — switching assistants switches threads.
  • History is distinct from User Memory — history is the recent back-and-forth; User Memory is the durable facts Pria keeps about you across all conversations.

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Troubleshooting