handle dead CUDA contexts and empty ASR results

- detect unrecoverable CUDA errors before OOM retries and clear model caches\n- keep normal OOM retries to two attempts (configured batch, then 1)\n- do not create text.txt when ASR returns only whitespace\n- warn per file and report empty_result / lrc+empty in the summary\n- keep at least 12 log lines visible in the GUI

core/lrc_pipeline.py

@@ -146,6 +146,13 @@ def run_lrc_pipeline(
             )
 
             lrc_content = segments_to_lrc(segments)
+            if not lrc_content.strip():
+                log(f"  ⚠ {f.name}: текст не извлечён (пустой результат ASR)")
+                results.append(FileResult(
+                    f, None, None,
+                    "EmptyResult: ASR returned no text", "lrc+empty",
+                ))
+                continue
             lrc_path.write_text(lrc_content, encoding="utf-8")
             log(f"  ✓ text.lrc ({len(segments)} строк, язык: {detected})")
 

core/pipeline.py

@@ -836,14 +836,21 @@ def _run_sequential(
                     gigaam_provider=config.transcribe.gigaam_provider,
                     local_files_only=config.transcribe.local_files_only,
                 )
+                text = (text or "").strip()
                 source = config.transcribe.engine
-                log(f"  ✓ распознано {len(text)} символов")
-                if (config.lyrics.enabled and config.lyrics.try_after_asr):
-                    matched = _try_post_asr_match(text, config, log)
-                    if matched:
-                        text = matched
-                        source = f"{source}+lrclib"
-                (tmp_root / "text.txt").write_text(text, encoding="utf-8")
+                if not text:
+                    text = None
+                    source = "empty_result"
+                    error = "EmptyResult: ASR returned no text"
+                    log(f"  ⚠ {f.name}: текст не извлечён (пустой результат ASR)")
+                else:
+                    log(f"  ✓ распознано {len(text)} символов")
+                    if (config.lyrics.enabled and config.lyrics.try_after_asr):
+                        matched = _try_post_asr_match(text, config, log)
+                        if matched:
+                            text = matched
+                            source = f"{source}+lrclib"
+                    (tmp_root / "text.txt").write_text(text, encoding="utf-8")
 
             metadata_dict = _build_metadata_dict(
                 ident.metadata, ident.shazam, source, input_path=f,
@@ -873,7 +880,7 @@ def _run_sequential(
         except CudaOOMError as e:
             error = f"CudaOOMError: {e}"
             source = "oom_skipped"
-            log(f"  ⊘ {f.name}: OOM после 3 попыток — пропущен, идём дальше")
+            log(f"  ⊘ {f.name}: OOM после ретраев — пропущен, идём дальше")
         except Exception as e:  # noqa: BLE001
             error = f"{type(e).__name__}: {e}"
             log(f"  ✗ Ошибка: {error}")
@@ -1293,9 +1300,16 @@ def _run_staged_batch(
                         gigaam_provider=config.transcribe.gigaam_provider,
                         local_files_only=config.transcribe.local_files_only,
                     )
-                    state[f]["text"] = text
-                    state[f]["source"] = config.transcribe.engine
-                    log(f"  ✓ {f.name} ({len(text)} символов)")
+                    text = (text or "").strip()
+                    if not text:
+                        state[f]["text"] = None
+                        state[f]["source"] = "empty_result"
+                        state[f]["error"] = "EmptyResult: ASR returned no text"
+                        log(f"  ⚠ {f.name}: текст не извлечён (пустой результат ASR)")
+                    else:
+                        state[f]["text"] = text
+                        state[f]["source"] = config.transcribe.engine
+                        log(f"  ✓ {f.name} ({len(text)} символов)")
                 except CudaOOMError as e:
                     state[f]["error"] = f"CudaOOMError: {e}"
                     state[f]["source"] = "oom_skipped"

core/transcribe.py

@@ -20,6 +20,27 @@ from typing import Optional
 _MODEL_LOCK = threading.RLock()
 _REUSE_LOGGED: set = set()
 
+# CUDA context failures that cannot be recovered by retrying or empty_cache().
+# They require restarting the app (or switching to CPU).
+_DEAD_CUDA_MARKERS = (
+    "invalid device ordinal",
+    "cudaerrorinvaliddevice",
+    "device-side assert",
+    "unspecified launch failure",
+)
+
+
+def _is_dead_cuda(exc: BaseException) -> bool:
+    err = str(exc).lower()
+    return any(m in err for m in _DEAD_CUDA_MARKERS)
+
+
+def _clear_model_caches() -> None:
+    _WhisperXModels._cache.clear()
+    _AlignModels._cache.clear()
+    _GigaAMModels._cache.clear()
+    _REUSE_LOGGED.clear()
+
 
 class CudaOOMError(RuntimeError):
     """CUDA OOM, переживший все стратегии понижения нагрузки."""
@@ -91,11 +112,13 @@ def _model_transcribe_with_retry(
     The loaded model is intentionally kept in the cache between attempts:
     reloading it costs minutes and does not help with an OOM caused by a long
     audio file. VAD is not touched here — WhisperX expects it at model-load
-    time (``vad_model``/``vad_options``), not per transcription call. If even
-    batch=1 fails, raise CudaOOMError so the caller can skip this file and
-    continue with the rest of the batch.
+    time (``vad_model``/``vad_options``), not per transcription call. A dead
+    CUDA context is never retried: caches are dropped and CudaOOMError is
+    raised immediately. If even batch=1 fails with a normal OOM, raise
+    CudaOOMError so the caller can skip this file and continue with the rest
+    of the batch.
     """
-    attempts = [batch_size, 1, 1]
+    attempts = [batch_size, 1]
     last: Optional[Exception] = None
     for i, bs in enumerate(attempts, 1):
         try:
@@ -103,12 +126,20 @@ def _model_transcribe_with_retry(
                 audio, batch_size=bs, language=language,
             )
         except Exception as e:  # noqa: BLE001
+            if _is_dead_cuda(e):
+                _clear_model_caches()
+                raise CudaOOMError(
+                    f"CUDA context died on {name}: {e}. "
+                    "GPU state is unrecoverable — restart the app or switch to CPU."
+                ) from e
             if not _is_cuda_error(e):
                 raise
             last = e
-            print(f"  [ASR] OOM on {name} (attempt {i}/3, bs={bs}): {e}")
+            print(f"  [ASR] OOM on {name} (attempt {i}/{len(attempts)}, bs={bs}): {e}")
             _free_vram()
-    raise CudaOOMError(f"OOM after 3 attempts on {name}: {last}") from last
+    raise CudaOOMError(
+        f"OOM after {len(attempts)} attempts on {name}: {last}"
+    ) from last
 
 
 class _WhisperXModels: