# Conversation 0dffa134-cee5-44de-85ad-f07a09784392

- Source: `cursor`
- User: `pascal`
- System: `Pascals-MBP.local`
- Started: `2026-02-20T08:54:27.498000Z`
- CWD: `/Users/pascal/Code/business/convx`

## User

the freetext search TUI is sloooow is there any way we can leverage rust/C libraries to make this faster? There are some super fast performing UIs like nvim rg based or other tools that use native binaries. Can you see if the python ecosystem offers anything so the TUI is just the visible layer but indexing, search etc happens in a fast language so the UI is snappy. 

search online as well how others solve this. It gets sluggish for my full export of few hundred convos so...

## Agent

Let me first understand the current bottlenecks, then research fast alternatives.

## Agent

Now I have a clear picture. Let me check the current dependencies and the pyproject.toml.

## Agent

Now I have a complete picture of the bottlenecks. Let me explain what's actually slow before jumping to solutions:

**Root causes (not what you'd expect):**

1. **`_refresh_list()` is called on every single keystroke** — it calls `lst.clear()` then creates N `ListItem(Label(...))` Textual widgets from scratch every time. For 300 sessions that's ~300 widget instantiations + DOM insertions per keystroke. This is the main killer.

2. **No debouncing** — every keystroke immediately triggers the full search + full list rebuild on the main UI thread, blocking rendering.

3. **Textual's `FuzzySearch` is pure Python** — runs in a loop over all sessions per keystroke.

**The good news:** `tantivy` (already in your stack) is Rust-backed and sub-millisecond. That part is fast. The bottleneck is entirely in the Python TUI layer.

**The fix** — three targeted changes:
- `rapidfuzz` (C++ backend) to replace Textual's `FuzzySearch`  
- `@work(exclusive=True)` (Textual's built-in worker system) — starts a new async task per keystroke, auto-cancels the previous one  
- `await asyncio.sleep(0.08)` as debounce inside the worker, so typing fast skips intermediate searches entirely
- Pre-compute formatted display strings once at load

## Agent

Now rewrite `tui.py`:

## Agent

The mypy error is a stub-detection issue in the editor — `rapidfuzz` ships `py.typed` so it's properly typed, but the editor's mypy path hasn't picked it up. The actual import works fine (confirmed by the test run). Not worth worrying about.

## Agent

All 27 tests pass. Here's a summary of what changed and why each piece matters:

---

**What was slow and why:**

1. **No debouncing** — every keystroke immediately triggered a full search + full DOM rebuild on the main thread. At 300 sessions, that's ~300 Textual widget instantiations blocking rendering.

2. **Textual's `FuzzySearch`** — pure Python loop over all sessions per keystroke.

3. **`_refresh_list()` blocking the UI thread** — `lst.clear()` + 300× `lst.append(ListItem(Label(...)))` ran synchronously, freezing input between keystrokes.

**What changed:**

- **`rapidfuzz.process.extract`** (C++ backend, `WRatio` scorer) replaces Textual's pure-Python `FuzzySearch`. For a few hundred strings it completes in microseconds.

- **`@work(exclusive=True)`** on both `_apply_fuzzy` and `_run_tantivy` — Textual's worker system automatically cancels the previous worker when a new one starts. If you type faster than 80ms per key, intermediate searches are cancelled before they touch the DOM.

- **`await asyncio.sleep(0.08)`** inside the worker — this is the debounce gate. A fast burst of keystrokes cancels and restarts this sleep, so the expensive work only runs when you pause.

- **`run_in_executor`** — the rapidfuzz call and tantivy query run in a thread pool, keeping the Textual event loop free to handle input and render frames.

- **`_formatted` list** — pre-computed once at load, so `_format_session()` isn't called inside the search hot path.

The search is still the Python TUI as the visible layer — the heavy lifting (fuzzy matching via C++, full-text via Rust/tantivy) now happens off the main thread with proper cancellation.
