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Update app.py
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app.py
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@@ -1,16 +1,10 @@
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import os
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#import re
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#import functools
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from functools import partial
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#import requests
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#import pandas as pd
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import torch
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import gradio as gr
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from transformers import pipeline, Wav2Vec2ProcessorWithLM
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from pyannote.audio import Pipeline
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import whisperx
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from utils import split
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from utils import speech_to_text as stt
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@@ -35,7 +29,7 @@ speech_to_text = partial(
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whisper_device=whisper_device
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)
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#
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emotion_pipeline = pipeline(
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"text-classification",
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model="bhadresh-savani/distilbert-base-uncased-emotion",
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@@ -45,6 +39,7 @@ summarization_pipeline = pipeline(
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model="knkarthick/MEETING_SUMMARY",
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)
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def summarize(diarized, summarization_pipeline):
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text = ""
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for d in diarized:
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import os
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import torch
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import gradio as gr
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from transformers import pipeline, Wav2Vec2ProcessorWithLM
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from pyannote.audio import Pipeline
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import whisperx
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from functools import partial
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from utils import split
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from utils import speech_to_text as stt
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whisper_device=whisper_device
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)
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# Get Transformer Models
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emotion_pipeline = pipeline(
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"text-classification",
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model="bhadresh-savani/distilbert-base-uncased-emotion",
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model="knkarthick/MEETING_SUMMARY",
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)
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# Apply models to transcripts
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def summarize(diarized, summarization_pipeline):
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text = ""
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for d in diarized:
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