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Update app.py
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app.py
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@@ -3,10 +3,9 @@ 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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def linkify():
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import pandas as pd
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import streamlit as st
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link1 = "https://stackoverflow.com/questions/71641666/hyperlink-in-streamlit-dataframe"
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@@ -49,7 +48,6 @@ def bulk_function(filename):
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print(filename, type(filename))
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print(filename.name)
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# check type of input file
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if filename.name.split(".")[1] == "csv":
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print("entered")
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@@ -65,12 +63,6 @@ def bulk_function(filename):
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else:
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return
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# read csv
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# even if index given, drop it
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#df_input = pd.read_csv(filename.name, index_col=False)
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#print("df_input", df_input)
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# expect csv format to be in:
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# 1: ID
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# 2: Texts
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@@ -130,13 +122,16 @@ def bulk_function(filename):
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# return dataframe for space output
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return YOUR_FILENAME
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gr.Interface(
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outputs=[gr.outputs.File(label="Output file")],
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allow_flagging=False,
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).launch(debug=True)
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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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from transformers import AutoTokenizer,AutoModelForSequenceClassification, Trainer
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def linkifyHTML():
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import pandas as pd
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import streamlit as st
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link1 = "https://stackoverflow.com/questions/71641666/hyperlink-in-streamlit-dataframe"
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print(filename, type(filename))
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print(filename.name)
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# check type of input file
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if filename.name.split(".")[1] == "csv":
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print("entered")
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else:
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return
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# expect csv format to be in:
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# 1: ID
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# 2: Texts
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# return dataframe for space output
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return YOUR_FILENAME
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gr.Interface(
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bulk_function,
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inputs=[gr.inputs.File(file_count="single",
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type="file",
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label="Upload file",
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optional=False),
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],
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outputs=[gr.outputs.File(label="Output file")],
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theme="huggingface",
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title="CSV File to Sentence Emotion Classification",
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description="Upload csv file with 2 columns (in order): (a) ID column, (b) text column. Model: https://huggingface.co/j-hartmann/emotion-english-distilroberta-base.",
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allow_flagging=False,
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).launch(debug=True)
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