diff --git a/README.md b/README.md index bf2498b1..58327510 100644 --- a/README.md +++ b/README.md @@ -13,7 +13,7 @@ OpenAI's [Whisper](https://github.com/openai/whisper). ![GitHub release (latest by date)](https://img.shields.io/github/v/release/chidiwilliams/buzz) [![Github all releases](https://img.shields.io/github/downloads/chidiwilliams/buzz/total.svg)](https://GitHub.com/chidiwilliams/buzz/releases/) -![Buzz](./buzz/assets/buzz-banner.jpg) +![Buzz](https://raw.githubusercontent.com/chidiwilliams/buzz/refs/heads/main/buzz/assets/buzz-banner.jpg) ## Features - Transcribe audio and video files or Youtube links @@ -91,12 +91,12 @@ For info on how to get latest development version with latest features and bug f ### Screenshots
- File import - Main screen - Preferences - Model preferences - Transcript - Live recording - Resize + File import + Main screen + Preferences + Model preferences + Transcript + Live recording + Resize
diff --git a/buzz/transcriber/whisper_file_transcriber.py b/buzz/transcriber/whisper_file_transcriber.py index 0badcdbf..ef75885f 100644 --- a/buzz/transcriber/whisper_file_transcriber.py +++ b/buzz/transcriber/whisper_file_transcriber.py @@ -28,6 +28,7 @@ from buzz.transcriber.file_transcriber import FileTranscriber from buzz.transcriber.transcriber import FileTranscriptionTask, Segment, Task from buzz.transcriber.whisper_cpp import WhisperCpp +import av import faster_whisper import whisper import stable_whisper @@ -36,6 +37,22 @@ from stable_whisper import WhisperResult PROGRESS_REGEX = re.compile(r"\d+(\.\d+)?%") +def check_file_has_audio_stream(file_path: str) -> None: + """Check if a media file has at least one audio stream. + + Raises: + ValueError: If the file has no audio streams. + """ + try: + with av.open(file_path) as container: + if len(container.streams.audio) == 0: + raise ValueError("No audio streams found") + except av.error.InvalidDataError as e: + raise ValueError(f"Invalid media file: {e}") + except av.error.FileNotFoundError: + raise ValueError("File not found") + + class WhisperFileTranscriber(FileTranscriber): """WhisperFileTranscriber transcribes an audio file to text, writes the text to a file, and then opens the file using the default program for opening txt files.""" @@ -54,6 +71,7 @@ class WhisperFileTranscriber(FileTranscriber): self.stopped = False self.recv_pipe = None self.send_pipe = None + self.error_message = None def transcribe(self) -> List[Segment]: time_started = datetime.datetime.now() @@ -119,7 +137,7 @@ class WhisperFileTranscriber(FileTranscriber): logging.debug("Whisper process was terminated (exit code: %s), treating as cancellation", self.current_process.exitcode) raise Exception("Transcription was canceled") else: - raise Exception("Unknown error") + raise Exception(self.error_message or "Unknown error") return self.segments @@ -158,27 +176,36 @@ class WhisperFileTranscriber(FileTranscriber): subprocess.run = _patched_run subprocess.Popen = _PatchedPopen - with pipe_stderr(stderr_conn): - if task.transcription_options.model.model_type == ModelType.WHISPER_CPP: - segments = cls.transcribe_whisper_cpp(task) - elif task.transcription_options.model.model_type == ModelType.HUGGING_FACE: - sys.stderr.write("0%\n") - segments = cls.transcribe_hugging_face(task) - sys.stderr.write("100%\n") - elif ( - task.transcription_options.model.model_type == ModelType.FASTER_WHISPER - ): - segments = cls.transcribe_faster_whisper(task) - elif task.transcription_options.model.model_type == ModelType.WHISPER: - segments = cls.transcribe_openai_whisper(task) - else: - raise Exception( - f"Invalid model type: {task.transcription_options.model.model_type}" - ) + try: + # Check if the file has audio streams before processing + check_file_has_audio_stream(task.file_path) - segments_json = json.dumps(segments, ensure_ascii=True, default=vars) - sys.stderr.write(f"segments = {segments_json}\n") - sys.stderr.write(WhisperFileTranscriber.READ_LINE_THREAD_STOP_TOKEN + "\n") + with pipe_stderr(stderr_conn): + if task.transcription_options.model.model_type == ModelType.WHISPER_CPP: + segments = cls.transcribe_whisper_cpp(task) + elif task.transcription_options.model.model_type == ModelType.HUGGING_FACE: + sys.stderr.write("0%\n") + segments = cls.transcribe_hugging_face(task) + sys.stderr.write("100%\n") + elif ( + task.transcription_options.model.model_type == ModelType.FASTER_WHISPER + ): + segments = cls.transcribe_faster_whisper(task) + elif task.transcription_options.model.model_type == ModelType.WHISPER: + segments = cls.transcribe_openai_whisper(task) + else: + raise Exception( + f"Invalid model type: {task.transcription_options.model.model_type}" + ) + + segments_json = json.dumps(segments, ensure_ascii=True, default=vars) + sys.stderr.write(f"segments = {segments_json}\n") + sys.stderr.write(WhisperFileTranscriber.READ_LINE_THREAD_STOP_TOKEN + "\n") + except Exception as e: + # Send error message back to the parent process + stderr_conn.send(f"error = {str(e)}\n") + stderr_conn.send(WhisperFileTranscriber.READ_LINE_THREAD_STOP_TOKEN + "\n") + raise @classmethod def transcribe_whisper_cpp(cls, task: FileTranscriptionTask) -> List[Segment]: @@ -415,6 +442,8 @@ class WhisperFileTranscriber(FileTranscriber): for segment in segments_dict ] self.segments = segments + elif line.startswith("error = "): + self.error_message = line[8:] else: try: match = PROGRESS_REGEX.search(line)