Not able to retrieve the json from the transcript as I used to.

[cowanAI]

Which Deepgram product are you using?

Deepgram SDKs

Details

Logs:

Traceback (most recent call last):
File "/app/main.py", line 98, in transcribe_audio
paragraphs = transcript_response["results"]["channels"][0]["alternatives"][0]["paragraphs"]["paragraphs"]
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^
KeyError: 'paragraphs'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "/usr/local/lib/python3.11/site-packages/gradio/queueing.py", line 388, in call_prediction
output = await route_utils.call_process_api(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/site-packages/gradio/route_utils.py", line 219, in call_process_api
output = await app.get_blocks().process_api(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/site-packages/gradio/blocks.py", line 1437, in process_api
result = await self.call_function(
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/site-packages/gradio/blocks.py", line 1107, in call_function
prediction = await fn(*processed_input)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/site-packages/gradio/utils.py", line 616, in async_wrapper
response = await f(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^
File "/app/main.py", line 134, in transcribe_route
transcript = await transcribe_audio(upload)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

If you are making a request to the Deepgram API, what is the full Deepgram URL you are making a request to?

No response

If you are making a request to the Deepgram API and have a request ID, please paste it below:

No response

If possible, please attach your code or paste it into the text box.

async def transcribe_audio(file):
try:
# Using Temporary files
tmp_audio_file_name = None
try:
# Creating and using the temporary file
tmp_audio_file = tempfile.NamedTemporaryFile(delete=False, suffix=".mp3")
tmp_audio_file_name = tmp_audio_file.name
audio_mp3 = AudioSegment.from_wav(file)
audio_mp3.export(tmp_audio_file.name, format="mp3")
tmp_audio_file.close()

        deepgram = Deepgram(config.DEEPGRAM_API_KEY)
        MIMETYPE = 'audio/mp3'

        with open(tmp_audio_file_name, 'rb') as audio_file_mp3:
            source = {'buffer': audio_file_mp3, 'mimetype': MIMETYPE}
                
            transcript_response = await asyncio.wait_for(
                asyncio.create_task(
                    deepgram.transcription.prerecorded(
                        source, {
                            'smart_format': True, 
                            'model': 'nova-2-ea', 
                            'diarize': True,
                            'profanity_filter': True, 
                            'detect_entities': True,
                            'detect_language': True, 
                            'utterance': True, 
                            'punctuate': True
                        }
                    )
                ), timeout=120
            )

        paragraphs = transcript_response["results"]["channels"][0]["alternatives"][0]["paragraphs"]["paragraphs"]
        transcript = ""
        for paragraph in paragraphs:
            speaker = paragraph["speaker"]
            sentences = paragraph["sentences"]
            paragraph_text = ""
            for sentence in sentences:
                paragraph_text += sentence['text'] + " "
            paragraph_text = paragraph_text.rstrip()
            speaker_text = f"Speaker {speaker + 1}:\n{paragraph_text}\n"
            transcript += speaker_text + "\n"

               # Write the response to the console
        print(json.dumps(transcript_response, indent=4))

        return transcript
    
    finally:
        # Ensure the temporary file is cleaned up
        if tmp_audio_file_name and os.path.exists(tmp_audio_file_name):
            os.remove(tmp_audio_file_name)

 
        

except httpx.RequestError as e:  # Adjusting for `httpx`
    print(f"Network error: {e}")  
    raise gr.Error(f"Please click 'Submit' again. We are currently experiencing unexpected heavy traffic. Our team is working on scaling our servers. Thank you for your patience. Error details: {e}")
except Exception as e:
    print(f"Error during transcription: {e}")
    raise gr.Error(f"Please click 'Submit' again. We are currently experiencing unexpected heavy traffic. Our team is working on scaling our servers. Thank you for your patience. Error details: {e}")

If possible, please attach an example audio file to reproduce the issue.

No response

[cowanAI]

it seems that it now has been resolved by my users

[lukeocodes]

Hi @cowanAI, you users might have found a way around it. But, we discovered a regression in our API related to this. A fix was created about an hour ago and we hope to get this deployed today. Thanks for your patience!

[jpvajda]

Thanks for letting know this is resolved on your end @cowanAI.