feat(whisper): feed profile_terms into initial_prompt at decode time

Previously profile_terms only reached the LLM cleanup stage as the
dictionary_terms suffix. Whisper decoded without any vocabulary hint, so
domain names ('Wren', 'CORBEL') were misspelled on the first pass and the
LLM had to guess at the correction.

build_initial_prompt (src-tauri/src/commands/mod.rs) collapses caller /
profile / terms into a single Whisper prompt:
  caller_prompt > profile_prompt + "Vocabulary: <terms>." > None

transcribe_pcm, transcribe_file, and start_live_transcription_session all
route through the helper, so the three paths stay in lockstep.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

src-tauri/src/commands/live.rs

@@ -12,6 +12,7 @@ use serde::{Deserialize, Serialize};
 use tauri::ipc::Channel;
 
 use crate::commands::audio::persist_audio_samples;
+use crate::commands::build_initial_prompt;
 use crate::commands::models::{default_model_id_for_engine, ensure_model_loaded};
 use crate::AppState;
 use kon_ai_formatting::{post_process_segments, FormatMode, PostProcessOptions};
@@ -214,16 +215,13 @@ pub async fn start_live_transcription_session(
 
     // Collapse the effective initial_prompt on the struct so downstream
     // `TranscriptionOptions` construction (see `maybe_dispatch_chunk`) picks
-    // up profile fallback without further plumbing.
+    // up profile fallback + vocabulary injection without further plumbing.
-    let effective_prompt = match config.initial_prompt.as_deref() {
+    let request_prompt = config.initial_prompt.clone().unwrap_or_default();
-        Some(p) if !p.is_empty() => p.to_string(),
+    config.initial_prompt = build_initial_prompt(
-        _ => profile.initial_prompt.clone(),
+        &request_prompt,
-    };
+        &profile.initial_prompt,
-    config.initial_prompt = if effective_prompt.is_empty() {
+        &profile_terms,
-        None
+    );
-    } else {
-        Some(effective_prompt)
-    };
 
     let model_id = config
         .model_id

src-tauri/src/commands/mod.rs

@@ -12,3 +12,93 @@ pub mod transcription;
 pub mod transcripts;
 pub mod update;
 pub mod windows;
+
+/// Build the Whisper `initial_prompt` for a transcription request.
+///
+/// Precedence:
+/// 1. Caller-supplied `request_prompt` (non-empty wins outright — the caller
+///    has already made the decision).
+/// 2. Profile's stored prompt + profile terms (joined: the prompt frames the
+///    task, the vocabulary biases recognition toward domain terms).
+/// 3. Profile prompt alone, or vocabulary alone.
+/// 4. `None` if nothing is set.
+///
+/// Feeding `profile_terms` into `initial_prompt` (the OpenWhispr pattern) lets
+/// whisper.cpp bias its decoder toward the correct spelling of user-specific
+/// vocabulary at decode time, before any LLM cleanup pass.
+pub fn build_initial_prompt(
+    request_prompt: &str,
+    profile_prompt: &str,
+    profile_terms: &[String],
+) -> Option<String> {
+    let trimmed_request = request_prompt.trim();
+    if !trimmed_request.is_empty() {
+        return Some(trimmed_request.to_string());
+    }
+
+    let trimmed_profile = profile_prompt.trim();
+    let terms_list = profile_terms
+        .iter()
+        .map(|term| term.trim())
+        .filter(|term| !term.is_empty())
+        .collect::<Vec<_>>()
+        .join(", ");
+
+    match (trimmed_profile.is_empty(), terms_list.is_empty()) {
+        (true, true) => None,
+        (false, true) => Some(trimmed_profile.to_string()),
+        (true, false) => Some(format!("Vocabulary: {terms_list}.")),
+        (false, false) => Some(format!("{trimmed_profile} Vocabulary: {terms_list}.")),
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::build_initial_prompt;
+
+    #[test]
+    fn caller_prompt_overrides_everything() {
+        let got = build_initial_prompt(
+            "caller wins",
+            "profile prompt",
+            &["Wren".into(), "CORBEL".into()],
+        );
+        assert_eq!(got.as_deref(), Some("caller wins"));
+    }
+
+    #[test]
+    fn profile_prompt_and_terms_are_joined() {
+        let got = build_initial_prompt(
+            "",
+            "You are a meeting notes assistant.",
+            &["Wren".into(), "CORBEL".into()],
+        );
+        assert_eq!(
+            got.as_deref(),
+            Some("You are a meeting notes assistant. Vocabulary: Wren, CORBEL."),
+        );
+    }
+
+    #[test]
+    fn terms_only_produces_vocabulary_sentence() {
+        let got = build_initial_prompt("", "", &["Wren".into(), "CORBEL".into()]);
+        assert_eq!(got.as_deref(), Some("Vocabulary: Wren, CORBEL."));
+    }
+
+    #[test]
+    fn profile_prompt_alone_is_passed_through() {
+        let got = build_initial_prompt("", "Be concise.", &[]);
+        assert_eq!(got.as_deref(), Some("Be concise."));
+    }
+
+    #[test]
+    fn all_empty_returns_none() {
+        assert_eq!(build_initial_prompt("", "", &[]), None);
+    }
+
+    #[test]
+    fn whitespace_only_terms_are_skipped() {
+        let got = build_initial_prompt("", "", &["  ".into(), "Wren".into(), "".into()]);
+        assert_eq!(got.as_deref(), Some("Vocabulary: Wren."));
+    }
+}

src-tauri/src/commands/transcription.rs

@@ -7,6 +7,7 @@ use std::sync::Arc;
 
 use tauri::Emitter;
 
+use crate::commands::build_initial_prompt;
 use crate::commands::models::{default_model_id_for_engine, ensure_model_loaded};
 use crate::AppState;
 use kon_ai_formatting::{post_process_segments, FormatMode, PostProcessOptions};
@@ -165,20 +166,14 @@ pub async fn transcribe_pcm(
             .map(|t| t.term)
             .collect();
 
-    let effective_prompt = if !initial_prompt.is_empty() {
-        initial_prompt
-    } else {
-        profile.initial_prompt.clone()
-    };
-
     let engine = state.whisper_engine.clone();
     let options = TranscriptionOptions {
         language: Some(language),
-        initial_prompt: if effective_prompt.is_empty() {
+        initial_prompt: build_initial_prompt(
-            None
+            &initial_prompt,
-        } else {
+            &profile.initial_prompt,
-            Some(effective_prompt)
+            &profile_terms,
-        },
+        ),
     };
 
     let timed = tokio::task::spawn_blocking(move || {
@@ -252,12 +247,6 @@ pub async fn transcribe_file(
             .map(|t| t.term)
             .collect();
 
-    let effective_prompt = if !initial_prompt.is_empty() {
-        initial_prompt
-    } else {
-        profile.initial_prompt.clone()
-    };
-
     let engine_name = engine.unwrap_or_else(|| "whisper".to_string());
     let model_id =
         model_id.unwrap_or_else(|| default_model_id_for_engine(&engine_name).to_string());
@@ -266,11 +255,11 @@ pub async fn transcribe_file(
     let engine = pick_engine(&state, &engine_name)?;
     let options = TranscriptionOptions {
         language: Some(language),
-        initial_prompt: if effective_prompt.is_empty() {
+        initial_prompt: build_initial_prompt(
-            None
+            &initial_prompt,
-        } else {
+            &profile.initial_prompt,
-            Some(effective_prompt)
+            &profile_terms,
-        },
+        ),
     };
     let engine_name_for_worker = engine_name.clone();