{"record":{"id":"2be15dd892a139d3","repo":"Zackriya-Solutions/meetily","slug":"vad-task-panicked","errorCode":null,"errorMessage":"VAD task panicked: {}","messagePattern":"VAD task panicked: (.+?)","errorType":"exception","errorClass":null,"httpStatus":null,"severity":"error","filePath":"frontend/src-tauri/src/audio/import.rs","lineNumber":453,"sourceCode":"            &audio_samples,\n            VAD_REDEMPTION_TIME_MS,\n            |vad_progress, segments_found| {\n                let overall_progress = 25 + (vad_progress as f32 * 0.05) as u32;\n                emit_progress(\n                    &app_for_vad,\n                    \"vad\",\n                    overall_progress,\n                    &format!(\n                        \"Detecting speech segments... {}% ({} found)\",\n                        vad_progress, segments_found\n                    ),\n                );\n                !IMPORT_CANCELLED.load(Ordering::SeqCst)\n            },\n        )\n    })\n    .await\n    .map_err(|e| anyhow!(\"VAD task panicked: {}\", e))?\n    .map_err(|e| anyhow!(\"VAD processing failed: {}\", e))?;\n\n    let total_segments = speech_segments.len();\n    info!(\"VAD detected {} speech segments (redemption_time={}ms)\", total_segments, VAD_REDEMPTION_TIME_MS);\n\n    // Diagnostic: log segment duration distribution\n    if !speech_segments.is_empty() {\n        let durations_ms: Vec<f64> = speech_segments.iter()\n            .map(|s| s.end_timestamp_ms - s.start_timestamp_ms)\n            .collect();\n        let total_speech_ms: f64 = durations_ms.iter().sum();\n        let avg_duration = total_speech_ms / durations_ms.len() as f64;\n        let min_duration = durations_ms.iter().cloned().fold(f64::INFINITY, f64::min);\n        let max_duration = durations_ms.iter().cloned().fold(f64::NEG_INFINITY, f64::max);\n        info!(\n            \"VAD segment stats: avg={:.0}ms, min={:.0}ms, max={:.0}ms, total_speech={:.1}s/{:.1}s ({:.0}%)\",\n            avg_duration, min_duration, max_duration,\n            total_speech_ms / 1000.0, duration_seconds,","sourceCodeStart":435,"sourceCodeEnd":471,"githubUrl":"https://github.com/Zackriya-Solutions/meetily/blob/0281737d87d26352fb0adc78c8c0975f691b23d1/frontend/src-tauri/src/audio/import.rs#L435-L471","documentation":"The blocking task running `get_speech_chunks_with_progress` (VAD speech segmentation) panicked, so the JoinError branch fired instead of the function's own Result (which is the separate 'VAD processing failed' error on the next line). Note the callback shown returns `!IMPORT_CANCELLED` — cancellation makes VAD return early with a normal value, so this error specifically indicates a panic, not cancellation.","triggerScenarios":"A panic inside VAD: window slicing out of bounds when the audio is shorter than one analysis window, NaN/inf samples fed to the model after a marginal decode/resample, or an unwrap on a missing/unloaded VAD model resource.","commonSituations":"Importing clips shorter than a second, silence-only files after resample glitches, or a models directory missing the VAD (onnx) resource after an app update or manual cleanup.","solutions":["Run with RUST_BACKTRACE=1 and use try_into_panic() — the frame points into vad.rs (window slicing or model unwrap)","Log audio_samples.len() before VAD and reject files with too little audio (e.g. under 1 second) earlier in the pipeline","Verify VAD model assets exist and load; re-download if the models dir was cleaned","Reject non-finite samples after resample: `if audio_samples.iter().any(|s| !s.is_finite())`"],"exampleFix":"// before\nlet speech_segments = tokio::task::spawn_blocking(move || {\n    get_speech_chunks_with_progress(&audio_samples, VAD_REDEMPTION_TIME_MS, /*progress cb*/)\n}).await.map_err(|e| anyhow!(\"VAD task panicked: {}\", e))?\n.map_err(|e| anyhow!(\"VAD processing failed: {}\", e))?;\n\n// after — pre-validate samples so panics never reach VAD\nif audio_samples.len() < 16_000 {\n    let _ = std::fs::remove_dir_all(&meeting_folder);\n    return Err(anyhow!(\"Audio shorter than 1s — nothing for VAD to segment\"));\n}\nif audio_samples.iter().any(|s| !s.is_finite()) {\n    let _ = std::fs::remove_dir_all(&meeting_folder);\n    return Err(anyhow!(\"Resampled audio contains non-finite samples\"));\n}","handlingStrategy":"validation","validationCode":"// reject inputs that panic VAD\nif audio_samples.len() < 16_000 {\n    return Err(anyhow!(\"Audio shorter than 1s — nothing for VAD to segment\"));\n}\nif audio_samples.iter().any(|s| !s.is_finite()) {\n    return Err(anyhow!(\"Resampled audio contains non-finite samples\"));\n}","typeGuard":null,"tryCatchPattern":"Distinguish the two VAD failures explicitly: JoinError ('VAD task panicked') means a bug — capture try_into_panic() with RUST_BACKTRACE=1; the second map_err ('VAD processing failed') is a normal VAD error worth retrying with different audio.","preventionTips":["Reject sub-second clips before the VAD stage","Verify VAD model assets exist after app updates that touch the models dir","Sanitize resampler output for non-finite samples before feeding VAD"],"tags":["tokio","join-error","vad","speech-detection","panic","rust"],"backgroundTag":"tokio-join-error","analyzedSha":"0281737d87d26352fb0adc78c8c0975f691b23d1","analyzedAt":"2026-08-16T20:57:52.567Z","schemaVersion":2},"datasetVersion":"2026-08-16T23:17:17.608Z"}