Hi everyone,
Recently, I’ve been using Cursor to fine-tune a chat UI demo that focuses on seamless multi-model switching, persistent conversations, and context recovery.
Here’s the basic setup:
After user input, the system determines the intent (e.g., casual chat vs. storyline progression) and dynamically switches models — for example, using Model A for emotional responses and Model B for plot logic.
The conversation context is stored in **IndexedDB, so the chat session resumes quickly after reload, offering a “pick-up-where-you-left-off” experience.
Using Flow hooks in Cursor, I implemented token-level lazy loading: when users scroll the chat window, it triggers upstream/downstream content fill-in. This avoids flickering and keeps the UX smooth.
As a use case, I framed it around a lightweight “AI girlfriend” simulator (inspired by some top ai girlfriend platforms like crushonai, janitor ai, where characters retain memories and emotional states). The current setup feels surprisingly natural.
So far:
Context recovery time is under 200ms, and on refresh, the conversation picks up almost instantly — feels like there was never a break.
Model transitions are seamless, with no noticeable disruption in tone or content.
Chat scrolling is fluid, even with longer threads and multi-model context switches.
Would love to hear feedback from others who’ve experimented with multi-model routing or async context handling in Cursor.