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Runtime error
Runtime error
Commit Β·
e4d2ebb
1
Parent(s): 8ac9631
fix: sort records in descending time
Browse files
app.py
CHANGED
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@@ -71,7 +71,7 @@ def get_user_transcripts(username):
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arr.append([trans_dict['date'], trans_dict['transcription'], trans_dict['sentiment_output']])
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if (len(arr) == 0):
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arr = ['', '', '']
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-
return arr
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def get_user_score(username):
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doc = db.document(f'Users/{username}').get()
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@@ -180,8 +180,8 @@ def inference(username, audio, sentiment_option):
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title = """<h1 align="center">β Lim Kopi Call Center Service π¬</h1>"""
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image_path = "coffee_logo.jpg"
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description = """
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π» This
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βοΈ
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<br>
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- Language identification<br>
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- Real-time multilingual speech recognition<br>
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arr.append([trans_dict['date'], trans_dict['transcription'], trans_dict['sentiment_output']])
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if (len(arr) == 0):
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arr = ['', '', '']
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return sorted(arr, key=lambda x:x[0], reverse=True)
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def get_user_score(username):
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doc = db.document(f'Users/{username}').get()
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title = """<h1 align="center">β Lim Kopi Call Center Service π¬</h1>"""
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image_path = "coffee_logo.jpg"
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description = """
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π» This MVP uses Whisper to conduct audio sentiment analysis on voice recordings of customer service agents. Whisper is a general speech recognition model built by OpenAI. It is trained on a huge dataset of diverse audio, and supports multilingual speech recognition, speech translation, and language identification tasks.<br><br>
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βοΈ MVP Components:<br>
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<br>
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- Language identification<br>
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- Real-time multilingual speech recognition<br>
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