Welcome back! Let's continue our path to implementing the Audio/Video Transcriber using the OpenAI Whisper API! In this lesson, we will wrap up the main functionality by putting together the media file split functionality we've done in the previous lesson and the Whisper API call on a small media chunk that we've done in the previous course. On top of that, we will make sure to properly handle all potential errors and make sure we don't leave any redundant garbage on our disk not to waste the disk space. Ensuring robust error handling and cleanup is key to avoiding data loss and maintaining efficiency, even in unexpected scenarios.

Let's step in to see how exciting this all is!

Let's examine our main transcription function and understand how it handles errors and cleanup:

Python
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1def transcribe(file_path):
2    """ Transcribe a large media file by splitting it into chunks """
3    chunks = []
4    try:
5        # split_media is implemented in the previous lesson
6        # it splits a large media file into smaller chunks
7        chunks = split_media(file_path, 1)
8        transcriptions = []
9        
10        for chunk in chunks:
11            # transcribe_small_media uses OpenAI Whisper API
12            # to transcribe chunks under 25MB
13            text = transcribe_small_media(chunk)
14            if text:
15                transcriptions.append(text)
16        return ' '.join(transcriptions)
17    except Exception as e:
18        print(f"Error processing large file: {e}")
19        return None
20    finally:
21        # Clean up all chunks in the finally block
22        for chunk in chunks:
23            cleanup_temp_files(chunk)

The function works in several steps:

1. We initialize an empty chunks list outside the try block to ensure it's accessible in the finally block
2. Using split_media (implemented in our previous lesson), we split the large media file into manageable chunks
3. For each chunk, we use transcribe_small_media (which wraps the OpenAI Whisper API call we learned about earlier) to get the text transcription
4. Finally, we join all transcriptions into a single text

Notice how we've placed the chunks list initialization outside the try block. This ensures that even if an error occurs during splitting or transcription, we'll still have access to any chunks that were created, allowing us to clean them up properly.

The cleanup process is handled by our cleanup_temp_files function:

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1def cleanup_temp_files(file_path):
2    """Clean up temporary files and directories"""
3    try:
4        if os.path.isfile(file_path):
5            os.unlink(file_path)
6        elif os.path.isdir(file_path):
7            for root, dirs, files in os.walk(file_path, topdown=False):
8                for name in files:
9                    os.unlink(os.path.join(root, name))
10                for name in dirs:
11                    os.rmdir(os.path.join(root, name))
12            os.rmdir(file_path)
13    except Exception as e:
14        print(f"Warning: Could not clean up {file_path}: {e}")

The cleanup is guaranteed to work because:

1. We initialize the chunks list before any operations
2. We use a finally block which executes regardless of success or failure
3. Each cleanup operation is wrapped in its own try-except block
4. We handle both files and directories systematically
5. Any cleanup failures are logged but don't prevent the cleanup of other files

In this lesson, we've learned how to implement a robust error handling and cleanup system for our media file transcription process. We've covered:

• Building a comprehensive transcription function that gracefully handles errors
• Implementing systematic cleanup of temporary files and directories
• Using try-except-finally blocks to ensure cleanup occurs regardless of execution outcome
• Proper initialization of variables to ensure accessibility in cleanup blocks
• Logging errors without disrupting the cleanup process

These practices are fundamental for creating reliable applications that efficiently manage system resources and provide clear feedback when issues occur. As you move to the practice section, you'll have the opportunity to implement these concepts in real-world scenarios.