Make the README user-focused

README.md

@@ -1,15 +1,12 @@
-# Local Wisper
-
-Local speech-to-text for x86_64 Linux. Record from the command line or a Sway
-keybinding, transcribe locally with NVIDIA Parakeet, and send the result to the
-clipboard or focused window.
+<p align="center">
+  <img src="assets/logo.svg" alt="Local Wisper logo" width="160">
+</p>
 
-Local Wisper keeps one model warm for fast repeated transcription. It selects
-FP16 CUDA inference when CUDA works and falls back to INT8 CPU inference. Users
-do not need to choose a model, device, or weight format.
+# Local Wisper
 
-This release is experimental. It installs a native `lw` executable and does
-not need Python during normal use. Faster Whisper is no longer supported.
+Local speech-to-text for Linux, built around Sway. Press a shortcut, speak, and
+the transcript appears in the focused window without sending your audio to the
+cloud.
 
 ## Requirements
 
@@ -19,59 +16,32 @@ not need Python during normal use. Faster Whisper is no longer supported.
 - `wtype` for typing into the focused Sway window
 - BAML 0.16, `cargo`, `curl`, and `sha256sum` to build and install
 
-An NVIDIA GPU is optional. Systems without working CUDA use the CPU
-automatically.
-
 ## Install
 
 ```bash
 git clone https://github.com/none23/local-wisper.git
 cd local-wisper
 ./install.sh
-lw preload
 ```
 
-The installer creates:
-
-- `~/.local/bin/lw`
-- `~/.config/local-wisper/env`
-- `~/.config/local-wisper/glossary.txt`
-
-It leaves existing configuration files untouched. Make sure `~/.local/bin` is
-in `PATH`.
-
-The first `lw preload` downloads and verifies the Parakeet files for the
-selected device. Later commands reuse the same cached files and warm model.
-Local Wisper allows only one model process per user to avoid duplicate RAM or
-VRAM use.
-
-On a Manjaro system with an NVIDIA GPU, the installer can place a private copy
-of cuDNN 9 under `~/.local/lib/local-wisper` when the system does not provide
-it. CPU-only systems skip CUDA setup. Normal use needs neither Python, Cargo,
-nor the BAML CLI.
+The installer adds `lw` to `~/.local/bin`. Make sure that directory is in your
+`PATH`.
 
 ## Usage
 
-- `lw`: record until Enter, transcribe, print the result, and copy it
-- `lw preload`: load the model before the first recording
-- `lw sway-start`: begin a detached recording
-- `lw sway-stop`: stop, transcribe, and deliver the recording
-- `lw sway-cancel`: discard the active Sway recording
-
-Run `lw --help` to print the command summary.
+Sway is the primary integration. The `lw` CLI is available for debugging; run
+`lw --help` when you need it.
 
-## Sway integration
-
-Install the supplied wrapper:
+Install the supplied Sway wrapper:
 
 ```bash
 install -Dm755 integrations/sway/local-wisper.sh \
   ~/.config/sway/scripts/local-wisper.sh
 ```
 
-A minimal Sway configuration looks like this:
+Add the following to your Sway configuration:
 
-```text
+```sway
 set $local_wisper $HOME/.config/sway/scripts/local-wisper.sh
 set $mode_local_wisper local-wisper
 
@@ -86,87 +56,16 @@ mode "$mode_local_wisper" {
 bindsym $mod+grave exec $local_wisper sway-start, mode "$mode_local_wisper"
 ```
 
-The wrapper reads `~/.config/local-wisper/env` and types completed transcripts
-into the focused window by default. Existing Sway wrappers remain compatible.
-
-Speech-to-text works better as a system-level feature than an editor feature,
-so this version removes the Neovim plugin. Sway is the only bundled
-integration.
+Press <kbd>Mod</kbd>+<kbd>`</kbd> to start recording. Press it again, or press
+<kbd>Enter</kbd>, to transcribe and type into the focused window. Press
+<kbd>Escape</kbd> to cancel.
 
-## Transcript cleanup
+## Configuration
 
-Local cleanup handles spoken decimals, phrases such as `numeric three`,
-statement formatting, and deterministic glossary replacements.
-
-Optional OpenAI cleanup improves punctuation and recurring technical terms.
-When enabled, transcripts with six or more words are sent to `gpt-5.6-luna`.
-Add the following values to `~/.config/local-wisper/env`:
+Local Wisper works without an API key. OpenAI can optionally post-process
+transcripts. Enable it in `~/.config/local-wisper/env`:
 
 ```bash
 export OPENAI_API_KEY='...'
 export LW_POST_PROCESS_MODEL='gpt-5.6-luna'
-export LW_POST_PROCESS_TIMEOUT='20'
-export LW_POST_PROCESS_GLOSSARY_FILE="$HOME/.config/local-wisper/glossary.txt"
-```
-
-If model cleanup fails or reaches the deadline, Local Wisper returns the local
-result. The glossary supports four sections:
-
-```text
-[always]
-engine x -> nginx
-
-[likely]
-cloud code -> Claude Code
-
-[contextual]
-codecs -> Codex
-
-[terms]
-TypeScript
 ```
-
-- `[always]` applies a local replacement every time.
-- `[likely]` asks model cleanup to prefer the replacement.
-- `[contextual]` applies when the surrounding text supports it.
-- `[terms]` supplies preferred spelling and capitalization.
-
-## Performance
-
-On the development machine, an 11.04-second recording took 0.36 seconds with
-FP16 CUDA and 0.80 seconds with INT8 CPU. The CPU model process used about 1 GB
-of memory. Results depend on the machine.
-
-## Technical notes
-
-The `lw` executable runs the application in BAML and uses a small Rust host for
-native Parakeet ONNX inference and Linux process operations. A per-user model
-service keeps Parakeet warm. Its authenticated loopback endpoint is available
-only through a private user runtime directory.
-
-The model files are pinned and verified before use. A per-user lock covers
-model selection, download, and loading so concurrent commands cannot create a
-second model process.
-
-## Development
-
-Install `pre-commit` and `shellcheck`, then enable the fast local checks:
-
-```bash
-pre-commit install
-pre-commit run --all-files
-```
-
-After changing a `.baml` file, run:
-
-```bash
-baml fmt
-baml check
-baml test
-baml generate
-cargo test
-```
-
-The generated Rust SDK is build output and is not committed. Run
-`baml generate` before a direct Cargo build. The installer performs this step
-automatically.