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Created a class for the whatsapp module #106

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merged 1 commit into from
Jan 9, 2025
Merged

Created a class for the whatsapp module #106

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124 changes: 62 additions & 62 deletions app/routers/tasks.py
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Original file line number Diff line number Diff line change
Expand Up @@ -761,54 +761,54 @@ async def verify_webhook(mode: str, token: str, challenge: str):
# # Step 5: Initialize the Runpod endpoint for transcription
# endpoint = runpod.Endpoint(RUNPOD_ENDPOINT_ID)

logging.info("Audio data found for langauge detection")
data = {
"input": {
"task": "auto_detect_audio_language",
"audio_file": blob_name,
}
}

start_time = time.time()

try:
logging.info("Audio file ready for langauge detection")
audio_lang_response = call_endpoint_with_retry(endpoint, data)
except TimeoutError as e:

logging.error("Job timed out %s", str(e))
raise HTTPException(
status_code=503, detail="Service unavailable due to timeout."
) from e

except ConnectionError as e:

logging.error("Connection lost: %s", str(e))
raise HTTPException(
status_code=503, detail="Service unavailable due to connection error."
) from e

end_time = time.time()
logging.info(
"Audio language auto detection response: %s ",
audio_lang_response.get("detected_language"),
)

# Calculate the elapsed time
elapsed_time = end_time - start_time
logging.info(
"Audio language auto detection elapsed time: %s seconds", elapsed_time
)

audio_language = audio_lang_response.get("detected_language")
request_response = {}

if audio_language in language_mapping:
# Language is in the mapping
logging.info("Language detected in audio is %s", audio_language)
else:
# Language is not in our scope
return "Audio Language not detected"
# logging.info("Audio data found for langauge detection")
# data = {
# "input": {
# "task": "auto_detect_audio_language",
# "audio_file": blob_name,
# }
# }

# start_time = time.time()

# try:
# logging.info("Audio file ready for langauge detection")
# audio_lang_response = call_endpoint_with_retry(endpoint, data)
# except TimeoutError as e:

# logging.error("Job timed out %s", str(e))
# raise HTTPException(
# status_code=503, detail="Service unavailable due to timeout."
# ) from e

# except ConnectionError as e:

# logging.error("Connection lost: %s", str(e))
# raise HTTPException(
# status_code=503, detail="Service unavailable due to connection error."
# ) from e

# end_time = time.time()
# logging.info(
# "Audio language auto detection response: %s ",
# audio_lang_response.get("detected_language"),
# )

# # Calculate the elapsed time
# elapsed_time = end_time - start_time
# logging.info(
# "Audio language auto detection elapsed time: %s seconds", elapsed_time
# )

# audio_language = audio_lang_response.get("detected_language")
# request_response = {}

# if audio_language in language_mapping:
# # Language is in the mapping
# logging.info("Language detected in audio is %s", audio_language)
# else:
# # Language is not in our scope
# return "Audio Language not detected"

# try:

Expand All @@ -822,20 +822,20 @@ async def verify_webhook(mode: str, token: str, challenge: str):
# phone_number_id,
# )

try:
# Step 7: Call the transcription service with the correct parameters
request_response = endpoint.run_sync(
{
"input": {
"task": "transcribe",
"target_lang": audio_language,
"adapter": audio_language,
"audio_file": blob_name, # Corrected to pass local file path
"recognise_speakers": False,
}
},
timeout=150, # Set a timeout for the transcription job.
)
# try:
# # Step 7: Call the transcription service with the correct parameters
# request_response = endpoint.run_sync(
# {
# "input": {
# "task": "transcribe",
# "target_lang": audio_language,
# "adapter": audio_language,
# "audio_file": blob_name, # Corrected to pass local file path
# "recognise_speakers": False,
# }
# },
# timeout=150, # Set a timeout for the transcription job.
# )

# # Step 8: Notify the user that transcription is in progress
# send_message(
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