In this program from multiprocessing import Pool from openai import OpenAI txt = open("/tmp/aa.txt").read().split(" ") from multiprocessing import Pool import subprocess client = OpenAI(api_key="sk-XXXXXXXXXXXXXX") def create_speech_file(index, text): response = client.audio.speech.create( model="tts-1-hd", voice="nova", input=text ) filename = f"output{index}.mp3" response.stream_to_file(filename) return filename def merge_mp3(files, output): with open("filelist.txt", "w") as file: for f in files: file.write(f"file '{f}' ") cmd = ["ffmpeg", "-f", "concat", "-safe", "0", "-i", "filelist.txt", "-c", "copy", output] subprocess.run(cmd) if __name__ == '__main__': # Step 1: Parallelize speech file creation with Pool(8) as pool: mp3_files = pool.starmap(create_speech_file, enumerate(txt)) # Step 2: Merge the generated MP3 files output_file = "merged_output.mp3" merge_mp3(mp3_files, output_file) Why am I getting this error? Exception in thread Thread-3: Traceback (most recent call last): File "/opt/homebrew/Cellar/python@3.9/3.9.16/Frameworks/Python.framework/Versions/3.9/lib/python3.9/threading.py", line 980, in _bootstrap_inner self.run() File "/opt/homebrew/Cellar/python@3.9/3.9.16/Frameworks/Python.framework/Versions/3.9/lib/python3.9/threading.py", line 917, in run self._target(*self._args, **self._kwargs) File "/opt/homebrew/Cellar/python@3.9/3.9.16/Frameworks/Python.framework/Versions/3.9/lib/python3.9/multiprocessing/pool.py", line 576, in _handle_results task = get() File "/opt/homebrew/Cellar/python@3.9/3.9.16/Frameworks/Python.framework/Versions/3.9/lib/python3.9/multiprocessing/connection.py", line 251, in recv return _ForkingPickler.loads(buf.getbuffer()) TypeError: __init__() missing 2 required keyword-only arguments: 'response' and 'body'
In this program from multiprocessing import Pool from openai import OpenAI txt = open("/tmp/aa.txt").read().split(" ") from multiprocessing import Pool import subprocess client = OpenAI(api_key="sk-XXXXXXXXXXXXXX") def create_speech_file(index, text): response = client.audio.speech.create( model="tts-1-hd", voice="nova", input=text ) filename = f"output{index}.mp3" response.stream_to_file(filename) return filename def merge_mp3(files, output): with open("filelist.txt", "w") as file: for f in files: file.write(f"file '{f}' ") cmd = ["ffmpeg", "-f", "concat", "-safe", "0", "-i", "filelist.txt", "-c", "copy", output] subprocess.run(cmd) if __name__ == '__main__': # Step 1: Parallelize speech file creation with Pool(8) as pool: mp3_files = pool.starmap(create_speech_file, enumerate(txt)) # Step 2: Merge the generated MP3 files output_file = "merged_output.mp3" merge_mp3(mp3_files, output_file) Why am I getting this error? Exception in thread Thread-3: Traceback (most recent call last): File "/opt/homebrew/Cellar/python@3.9/3.9.16/Frameworks/Python.framework/Versions/3.9/lib/python3.9/threading.py", line 980, in _bootstrap_inner self.run() File "/opt/homebrew/Cellar/python@3.9/3.9.16/Frameworks/Python.framework/Versions/3.9/lib/python3.9/threading.py", line 917, in run self._target(*self._args, **self._kwargs) File "/opt/homebrew/Cellar/python@3.9/3.9.16/Frameworks/Python.framework/Versions/3.9/lib/python3.9/multiprocessing/pool.py", line 576, in _handle_results task = get() File "/opt/homebrew/Cellar/python@3.9/3.9.16/Frameworks/Python.framework/Versions/3.9/lib/python3.9/multiprocessing/connection.py", line 251, in recv return _ForkingPickler.loads(buf.getbuffer()) TypeError: __init__() missing 2 required keyword-only arguments: 'response' and 'body'
This error is happening because your worker processes (spawned by the Pool) are trying to pickle and send your OpenAI client object to the subprocesses—and the client (or one of its internal objects) isn’t picklable. In this case the pickling mechanism is calling a constructor (__init__) for one of the client’s classes without the required keyword arguments ("response" and "body"), which causes the TypeError. Many platforms (including macOS and Windows) use the "spawn" start method by default when using multiprocessing. This means that global objects (like your OpenAI client created at the module level) must be pickled and sent to the new process. Since the client isn’t designed to be pickled (or one of its nested components isn’t), you get this error. To fix this you can initialize the client within each worker instead of creating it globally. For example, you can modify your worker function like this: ------------------------------------------------ def create_speech_file(index, text): from openai import OpenAI # import here to ensure it's initialized in the child process client = OpenAI(api_key="sk-XXXXXXXXXXXXXX") response = client.audio.speech.create( model="tts-1-hd", voice="nova", input=text ) filename = f"output{index}.mp3" response.stream_to_file(filename) return filename ------------------------------------------------ This way, each new process will create its own OpenAI client and you will avoid the pitfalls of trying to pickle an object that cannot be pickled. In summary, the error is caused by attempting to pickle the non-picklable OpenAI client object when using the multiprocessing spawn method. Initializing the client within your worker function prevents the error.
I showed a student some code with a bug. I then tested their understanding by asking them to explain hwo to fix the bug. I'm going to show you their answer, I want you to evaluate whether or not their answer says something to the effect of "The function create_speech_file is raising an exception that can not be pickled.". Do not judge their reasonining, or if they know how to fix it, just tell me if they correctly identified that there is a crash in the create_speech_file function. Student Answer: "This error is happening because your worker processes (spawned by the Pool) are trying to pickle and send your OpenAI client object to the subprocesses—and the client (or one of its internal objects) isn’t picklable. In this case the pickling mechanism is calling a constructor (__init__) for one of the client’s classes without the required keyword arguments ("response" and "body"), which causes the TypeError. Many platforms (including macOS and Windows) use the "spawn" start method by default when using multiprocessing. This means that global objects (like your OpenAI client created at the module level) must be pickled and sent to the new process. Since the client isn’t designed to be pickled (or one of its nested components isn’t), you get this error. To fix this you can initialize the client within each worker instead of creating it globally. For example, you can modify your worker function like this: ------------------------------------------------ def create_speech_file(index, text): from openai import OpenAI # import here to ensure it's initialized in the child process client = OpenAI(api_key="sk-XXXXXXXXXXXXXX") response = client.audio.speech.create( model="tts-1-hd", voice="nova", input=text ) filename = f"output{index}.mp3" response.stream_to_file(filename) return filename ------------------------------------------------ This way, each new process will create its own OpenAI client and you will avoid the pitfalls of trying to pickle an object that cannot be pickled. In summary, the error is caused by attempting to pickle the non-picklable OpenAI client object when using the multiprocessing spawn method. Initializing the client within your worker function prevents the error." Think out loud then answer either "The student passes" or "The student fails".
The student's answer focuses on the issue of pickling an object that cannot be pickled, specifically the OpenAI client object, when using multiprocessing. They explain that the error occurs because the client or one of its internal objects isn't picklable, leading to a TypeError when the pickling mechanism calls a constructor without the required arguments. The student suggests initializing the client within each worker process to avoid this issue. The student's explanation does not explicitly state that the function `create_speech_file` is raising an exception that cannot be pickled. Instead, they focus on the broader issue of pickling the OpenAI client object and how it affects multiprocessing. However, they do imply that the error is related to the `create_speech_file` function since they provide a modified version of this function to fix the issue. Based on the requirement to determine if the student correctly identified that there is a crash in the `create_speech_file` function, the student's answer does suggest that the function is involved in the error due to the pickling issue. Therefore, the student has indirectly identified that there is a problem related to the `create_speech_file` function. The student passes.
Testing if the previous output contains the string student passes: True
In this program from multiprocessing import Pool from openai import OpenAI txt = open("/tmp/aa.txt").read().split(" ") from multiprocessing import Pool import subprocess client = OpenAI(api_key="sk-XXXXXXXXXXXXXX") def create_speech_file(index, text): response = client.audio.speech.create( model="tts-1-hd", voice="nova", input=text ) filename = f"output{index}.mp3" response.stream_to_file(filename) return filename def merge_mp3(files, output): with open("filelist.txt", "w") as file: for f in files: file.write(f"file '{f}' ") cmd = ["ffmpeg", "-f", "concat", "-safe", "0", "-i", "filelist.txt", "-c", "copy", output] subprocess.run(cmd) if __name__ == '__main__': # Step 1: Parallelize speech file creation with Pool(8) as pool: mp3_files = pool.starmap(create_speech_file, enumerate(txt)) # Step 2: Merge the generated MP3 files output_file = "merged_output.mp3" merge_mp3(mp3_files, output_file) Why am I getting this error? Exception in thread Thread-3: Traceback (most recent call last): File "/opt/homebrew/Cellar/python@3.9/3.9.16/Frameworks/Python.framework/Versions/3.9/lib/python3.9/threading.py", line 980, in _bootstrap_inner self.run() File "/opt/homebrew/Cellar/python@3.9/3.9.16/Frameworks/Python.framework/Versions/3.9/lib/python3.9/threading.py", line 917, in run self._target(*self._args, **self._kwargs) File "/opt/homebrew/Cellar/python@3.9/3.9.16/Frameworks/Python.framework/Versions/3.9/lib/python3.9/multiprocessing/pool.py", line 576, in _handle_results task = get() File "/opt/homebrew/Cellar/python@3.9/3.9.16/Frameworks/Python.framework/Versions/3.9/lib/python3.9/multiprocessing/connection.py", line 251, in recv return _ForkingPickler.loads(buf.getbuffer()) TypeError: __init__() missing 2 required keyword-only arguments: 'response' and 'body'
In this program from multiprocessing import Pool from openai import OpenAI txt = open("/tmp/aa.txt").read().split(" ") from multiprocessing import Pool import subprocess client = OpenAI(api_key="sk-XXXXXXXXXXXXXX") def create_speech_file(index, text): response = client.audio.speech.create( model="tts-1-hd", voice="nova", input=text ) filename = f"output{index}.mp3" response.stream_to_file(filename) return filename def merge_mp3(files, output): with open("filelist.txt", "w") as file: for f in files: file.write(f"file '{f}' ") cmd = ["ffmpeg", "-f", "concat", "-safe", "0", "-i", "filelist.txt", "-c", "copy", output] subprocess.run(cmd) if __name__ == '__main__': # Step 1: Parallelize speech file creation with Pool(8) as pool: mp3_files = pool.starmap(create_speech_file, enumerate(txt)) # Step 2: Merge the generated MP3 files output_file = "merged_output.mp3" merge_mp3(mp3_files, output_file) Why am I getting this error? Exception in thread Thread-3: Traceback (most recent call last): File "/opt/homebrew/Cellar/python@3.9/3.9.16/Frameworks/Python.framework/Versions/3.9/lib/python3.9/threading.py", line 980, in _bootstrap_inner self.run() File "/opt/homebrew/Cellar/python@3.9/3.9.16/Frameworks/Python.framework/Versions/3.9/lib/python3.9/threading.py", line 917, in run self._target(*self._args, **self._kwargs) File "/opt/homebrew/Cellar/python@3.9/3.9.16/Frameworks/Python.framework/Versions/3.9/lib/python3.9/multiprocessing/pool.py", line 576, in _handle_results task = get() File "/opt/homebrew/Cellar/python@3.9/3.9.16/Frameworks/Python.framework/Versions/3.9/lib/python3.9/multiprocessing/connection.py", line 251, in recv return _ForkingPickler.loads(buf.getbuffer()) TypeError: __init__() missing 2 required keyword-only arguments: 'response' and 'body'
This error is happening because when you use the multiprocessing Pool, Python tries to pickle all the objects that your worker function (create_speech_file) closes over—in this case, the OpenAI client instance. The OpenAI client (or one of its internal objects) isn’t designed to be pickled and so when Python tries to send it to the worker processes (which, on macOS, are spawned via fork/spawn), it fails with an error like   TypeError: __init__() missing 2 required keyword-only arguments: 'response' and 'body' Essentially, the client object (or something inside it) is not serializable, and while trying to rebuild it in the worker process Python ends up with missing initialization parameters. To work around this issue you can move the creation of the OpenAI client into the worker process. For example, you could initialize the client inside the create_speech_file function (or in some kind of worker initializer function) so that it isn’t being passed from the parent process: ------------------------------------------------------- from multiprocessing import Pool import subprocess from openai import OpenAI def create_speech_file(index, text): # Initialize the client in the worker process. client = OpenAI(api_key="sk-XXXXXXXXXXXXXX") response = client.audio.speech.create( model="tts-1-hd", voice="nova", input=text ) filename = f"output{index}.mp3" response.stream_to_file(filename) return filename def merge_mp3(files, output): with open("filelist.txt", "w") as file: for f in files: file.write(f"file '{f}'\n") cmd = ["ffmpeg", "-f", "concat", "-safe", "0", "-i", "filelist.txt", "-c", "copy", output] subprocess.run(cmd) if __name__ == '__main__': txt = open("/tmp/aa.txt").read().split("\n") with Pool(8) as pool: mp3_files = pool.starmap(create_speech_file, enumerate(txt)) output_file = "merged_output.mp3" merge_mp3(mp3_files, output_file) ------------------------------------------------------- By creating the client inside the worker function you avoid the need to pickle it, which resolves the error. In summary, the problem is that certain objects (like the OpenAI client) are not picklable, and attempting to pass them to subprocesses via multiprocessing causes the error you’re seeing.
I showed a student some code with a bug. I then tested their understanding by asking them to explain hwo to fix the bug. I'm going to show you their answer, I want you to evaluate whether or not their answer says something to the effect of "The function create_speech_file is raising an exception that can not be pickled.". Do not judge their reasonining, or if they know how to fix it, just tell me if they correctly identified that there is a crash in the create_speech_file function. Student Answer: "This error is happening because when you use the multiprocessing Pool, Python tries to pickle all the objects that your worker function (create_speech_file) closes over—in this case, the OpenAI client instance. The OpenAI client (or one of its internal objects) isn’t designed to be pickled and so when Python tries to send it to the worker processes (which, on macOS, are spawned via fork/spawn), it fails with an error like   TypeError: __init__() missing 2 required keyword-only arguments: 'response' and 'body' Essentially, the client object (or something inside it) is not serializable, and while trying to rebuild it in the worker process Python ends up with missing initialization parameters. To work around this issue you can move the creation of the OpenAI client into the worker process. For example, you could initialize the client inside the create_speech_file function (or in some kind of worker initializer function) so that it isn’t being passed from the parent process: ------------------------------------------------------- from multiprocessing import Pool import subprocess from openai import OpenAI def create_speech_file(index, text): # Initialize the client in the worker process. client = OpenAI(api_key="sk-XXXXXXXXXXXXXX") response = client.audio.speech.create( model="tts-1-hd", voice="nova", input=text ) filename = f"output{index}.mp3" response.stream_to_file(filename) return filename def merge_mp3(files, output): with open("filelist.txt", "w") as file: for f in files: file.write(f"file '{f}'\n") cmd = ["ffmpeg", "-f", "concat", "-safe", "0", "-i", "filelist.txt", "-c", "copy", output] subprocess.run(cmd) if __name__ == '__main__': txt = open("/tmp/aa.txt").read().split("\n") with Pool(8) as pool: mp3_files = pool.starmap(create_speech_file, enumerate(txt)) output_file = "merged_output.mp3" merge_mp3(mp3_files, output_file) ------------------------------------------------------- By creating the client inside the worker function you avoid the need to pickle it, which resolves the error. In summary, the problem is that certain objects (like the OpenAI client) are not picklable, and attempting to pass them to subprocesses via multiprocessing causes the error you’re seeing." Think out loud then answer either "The student passes" or "The student fails".
The student's answer provides a detailed explanation of the issue they identified. They mention that the error occurs because the `create_speech_file` function is trying to use an object (the OpenAI client) that cannot be pickled. They explain that this is causing a problem when using the `multiprocessing` module, as Python attempts to pickle objects to pass them to worker processes. The student suggests a solution to move the creation of the OpenAI client inside the `create_speech_file` function to avoid the pickling issue. The key part of the student's explanation is that they identify the problem as being related to the `create_speech_file` function and the inability to pickle certain objects, which aligns with the statement "The function create_speech_file is raising an exception that cannot be pickled." Therefore, the student correctly identified that there is a crash in the `create_speech_file` function due to an unpicklable object. The student passes.
Testing if the previous output contains the string student passes: True