Update app.py
Browse files
app.py
CHANGED
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import os
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os.system("python -m pip install --upgrade pip")
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import openai
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import gradio as gr
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from gradio.components import Audio, Textbox
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import re
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import tiktoken
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import whisper
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from datetime import datetime, timezone, timedelta
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import notion_df
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import concurrent.futures
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from IPython.core.display import HTML
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os.system("pip install transformers>=4.0.0 pandas numpy spacy")
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from transformers import GPT2Tokenizer
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import pandas as pd
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import numpy as np
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import spacy
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from spacy import displacy
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nlp = spacy.load("en_core_web_sm")
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# Define the tokenizer and model
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tokenizer = GPT2Tokenizer.from_pretrained('gpt2-medium')
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df = pd.DataFrame([chat_transcript])
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notion_df.upload(df, 'https://www.notion.so/YENA-be569d0a40c940e7b6e0679318215790?pvs=4', title=str(published_date), api_key=API_KEY)
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#
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# Return the colorized chat transcript
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return colorized_system_message
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def colorize_text(text):
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doc = nlp(text)
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colorized_text = ""
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for token in doc:
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if token.ent_type_:
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colorized_text += f'<span style="background-color: yellow;">{token.text_with_ws}</span>'
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elif token.pos_ in {'NOUN'}:
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colorized_text += f'<span style="color: blue;">{token.text_with_ws}</span>'
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else:
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colorized_text += token.text_with_ws
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return colorized_text
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# Define the input and output components for Gradio
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audio_input = Audio(source="microphone", type="filepath", label="Record your message")
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text_input = Textbox(label="Type your message", max_length=4096)
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output_text =
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# Define the Gradio interface
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iface = gr.Interface(
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)
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# Run the Gradio interface
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iface.launch(
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import openai
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import gradio as gr
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from gradio.components import Audio, Textbox
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import os
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import re
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import tiktoken
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from transformers import GPT2Tokenizer
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import whisper
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import pandas as pd
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from datetime import datetime, timezone, timedelta
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import notion_df
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import concurrent.futures
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# Define the tokenizer and model
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tokenizer = GPT2Tokenizer.from_pretrained('gpt2-medium')
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df = pd.DataFrame([chat_transcript])
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notion_df.upload(df, 'https://www.notion.so/YENA-be569d0a40c940e7b6e0679318215790?pvs=4', title=str(published_date), api_key=API_KEY)
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# Return the chat transcript
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return system_message['content']
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# Define the input and output components for Gradio
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audio_input = Audio(source="microphone", type="filepath", label="Record your message")
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text_input = Textbox(label="Type your message", max_length=4096)
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output_text = gr.outputs.Textbox(label="Response")
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output_audio = Audio()
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# Define the Gradio interface
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iface = gr.Interface(
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)
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# Run the Gradio interface
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iface.launch()
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