feat: template

src-tauri/src/lib.rs

@@ -316,15 +316,40 @@ fn start_recording(
     Ok("Recording started".to_string())
 }
 
-/// Stop recording and return the transcript.
+/// Stop recording (for real-time mode, transcription already happened during recording).
 #[tauri::command]
 async fn stop_recording(
     state: State<'_, AppState>,
     app_handle: tauri::AppHandle,
+) -> Result<String, String> {
+    let logs = Arc::clone(&state.logs);
+
+    emit_log(&app_handle, &logs, "[Audio] Stopping recording...");
+
+    // Stop the recording and get the duration
+    let duration = {
+        let mut audio_guard = state.audio_capture.lock();
+        if let Some(ref mut capture) = *audio_guard {
+            let samples = capture.stop_recording();
+            samples.len() as f32 / 16000.0
+        } else {
+            return Err("No active recording".to_string());
+        }
+    };
+
+    emit_log(&app_handle, &logs, &format!("[Audio] Recording stopped. Total duration: {:.1}s", duration));
+    Ok("Recording stopped".to_string())
+}
+
+/// Stop recording and transcribe all at once (batch mode).
+#[tauri::command]
+async fn stop_recording_batch(
+    state: State<'_, AppState>,
+    app_handle: tauri::AppHandle,
 ) -> Result<Vec<TranscriptSegment>, String> {
     let logs = Arc::clone(&state.logs);
 
-    emit_log(&app_handle, &logs, "[Audio] Stopping recording...");
+    emit_log(&app_handle, &logs, "[Audio] Stopping recording (batch mode)...");
 
     // Get the audio samples
     let audio_samples = {

src-tauri/src/ml/summarizer.rs

@@ -78,15 +78,17 @@ impl LlamaSummarizer {
 
         let prompt = format!(
             "<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\n\
-             You are a helpful assistant that creates concise meeting summaries. Focus on:\n\
-             - Key decisions made\n\
-             - Action items and who owns them\n\
-             - Important discussions and their outcomes\n\
-             - Next steps\n\n\
-             Keep the summary structured and easy to scan.<|eot_id|><|start_header_id|>user<|end_header_id|>\n\n\
+             You are a helpful assistant that creates structured meeting summaries. \
+             Format your response using the following template:\n\n\
+             **Summary:** A high level overview of the meeting.\n\n\
+             **Key decisions:** Any important resolutions that the meeting reached.\n\n\
+             **Action Items:**\n\
+             - list of things that must be addressed\n\n\
+             **Discussion points:**\n\
+             - a list of each topic/argument/counterpoint brought up in the meeting.\n\n\
+             Be concise but comprehensive. Focus on capturing all important information.<|eot_id|><|start_header_id|>user<|end_header_id|>\n\n\
              Please summarize this meeting transcript:\n\n\
-             {}<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n\
-             Meeting Summary:\n",
+             {}<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n",
             transcript
         );
 

src/App.tsx

@@ -165,7 +165,7 @@ function App() {
 
   const stopRecording = async () => {
     try {
-      // Stop the timers
+      // Stop the timers first
       if (recordingTimer.current) {
         clearInterval(recordingTimer.current);
         recordingTimer.current = null;
@@ -178,36 +178,43 @@ function App() {
       setAppState("transcribing");
       setStatusMessage("Processing final audio...");
 
-      // Process any remaining audio
-      const finalChunk = await invoke<number[]>("get_remaining_audio", {
-        lastOffset: audioOffset.current
-      });
-
-      if (finalChunk.length > 0) {
-        const finalSegments = await invoke<TranscriptSegment[]>("transcribe_chunk", {
-          audioData: finalChunk
+      // First, process any audio that hasn't been processed yet
+      try {
+        const finalChunk = await invoke<number[]>("get_remaining_audio", {
+          lastOffset: audioOffset.current
         });
 
-        if (finalSegments.length > 0) {
-          const baseTime = totalProcessedSamples.current / 16000;
-          const adjustedSegments = finalSegments.map(seg => ({
-            ...seg,
-            start: seg.start + baseTime,
-            end: seg.end + baseTime,
-          }));
+        if (finalChunk.length > 0) {
+          console.log(`Processing final chunk of ${finalChunk.length} samples`);
+          const finalSegments = await invoke<TranscriptSegment[]>("transcribe_chunk", {
+            audioData: finalChunk
+          });
 
-          setTranscriptSegments(prev => [...prev, ...adjustedSegments]);
+          if (finalSegments.length > 0) {
+            const baseTime = totalProcessedSamples.current / 16000;
+            const adjustedSegments = finalSegments.map(seg => ({
+              ...seg,
+              start: seg.start + baseTime,
+              end: seg.end + baseTime,
+            }));
+
+            setTranscriptSegments(prev => [...prev, ...adjustedSegments]);
+          }
         }
+      } catch (chunkError) {
+        console.error("Error processing final chunk:", chunkError);
+        // Continue with stopping even if final chunk fails
       }
 
-      // Stop the recording
-      await invoke("stop_recording");
+      // Now stop the recording
+      await invoke<string>("stop_recording");
 
       setAppState("ready");
       setStatusMessage("");
     } catch (error) {
       console.error("Failed to stop recording:", error);
       setAppState("ready");
+      setStatusMessage("");
       setErrorMessage(String(error));
     }
   };