def get(self):
"""Fetches NLP API results from GCS and sends to frontend.
Args:
text: String representing section of transcription to get results.
file_name: String of audio file to retrieve chunk of text from.
Returns:
List of entity objects holding type, name, and sentiment score.
"""
try:
text = request.args['text']
file_name = request.args['file_name']
gcs_client = gcs_transcript_utils.authenticate_gcs()
bucket_list = list(gcs_client.list_buckets())
nlp_bucket = gcs_transcript_utils.find_bucket_with_prefix(
bucket_list, 'output-files')
nlp_path = f'nlp-files/{file_name}'
nlp_json = gcs_transcript_utils.get_gcs_object(
gcs_client, nlp_bucket, nlp_path)
if nlp_json:
text_section = [
section for section in nlp_json if section['text'] == text
]
sentiments = text_section[0]['nlp_response']
sentiments.sort(key=lambda entity: entity['score'])
return jsonify(sentiment_result=sentiments)
else:
raise NotFound
except NotFound as e:
logging.error('Fetching entity failed.')
logging.error(e)
return jsonify(e.to_dict())
def get(self):
"""Fetches transcript and toxicity from GCS to send to frontend.
Args:
'file_name': String holding audio file name.
Returns:
File_name: String of audio file.
transcript: String holding entire audio file transcription.
per_segment_toxicity: Array of objects holding toxicity probability
per segment, start_time, end_time.
"""
try:
file_name = request.args['file_name']
gcs_client = gcs_transcript_utils.authenticate_gcs()
bucket_list = list(gcs_client.list_buckets())
transcript_bucket = gcs_transcript_utils.find_bucket_with_prefix(
bucket_list, 'transcript')
transcript_per_segment = gcs_transcript_utils.get_gcs_object(
gcs_client, transcript_bucket, file_name)
if transcript_per_segment:
transcript_json = transcript_per_segment['json_payload']
transcript = gcs_transcript_utils.extract_full_transcript(
transcript_json)
output_bucket = gcs_transcript_utils.find_bucket_with_prefix(
bucket_list, 'output-files')
toxicity_path = f'toxicity-files/{file_name}'
toxicity = gcs_transcript_utils.get_gcs_object(
gcs_client, output_bucket, toxicity_path)
if toxicity:
toxicity.sort(key=lambda text: text['toxicity'],
reverse=True)
return jsonify(file_name=file_name,
transcript=transcript,
per_segment_toxicity=toxicity)
else:
raise NotFound
else:
raise NotFound
except NotFound as e:
logging.error(e)
logging.error('Failed to retrieve analysis.')
return jsonify(e.to_dict())
def get(self):
"""Fetches list of files from GCS to send to front-end.
Returns:
Array of objects holding object name and type for audio files.
"""
try:
gcs_client = gcs_transcript_utils.authenticate_gcs()
bucket_list = list(gcs_client.list_buckets())
processed_audio_bucket = gcs_transcript_utils.find_bucket_with_prefix(
bucket_list, 'processed-audio-files')
files = gcs_transcript_utils.get_files(gcs_client,
processed_audio_bucket)
return jsonify(files=files)
except NotFound as e:
logging.error(e)
return jsonify(e.to_dict())