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from transformers import pipeline
import pandas as pd
import gradio as gr
# Define the models
models = {
"GTQA (google/tapas-large-finetuned-wtq)": pipeline(task="table-question-answering", model="google/tapas-large-finetuned-wtq"),
"GTSQA (google/tapas-large-finetuned-sqa)": pipeline(task="table-question-answering", model="google/tapas-large-finetuned-sqa"),
"MSWTQA (microsoft/tapex-large-finetuned-wtq)": pipeline(task="table-question-answering", model="microsoft/tapex-large-finetuned-wtq"),
"MSTQA (microsoft/tapex-large-finetuned-wikisql)": pipeline(task="table-question-answering", model="microsoft/tapex-large-finetuned-wikisql")
}
def main(model_choice, file_path, text):
# Read the Excel file
table_df = pd.read_excel(file_path, engine='openpyxl').astype(str)
# Prepare the input for the model
tqa_pipeline_input = {
"table": table_df,
"query": text
}
# Get the selected model
model = models[model_choice]
# Run the model
result = model(tqa_pipeline_input)["answer"]
return result
iface = gr.Interface(
fn=main,
inputs=[
gr.Dropdown(choices=list(models.keys()), label="Select Model"),
gr.File(type="filepath", label="Upload XLSX file"),
gr.Textbox(type="text", label="Enter text"),
],
outputs=[gr.Textbox(type="text", label="Text Input Output")],
title="Multi-input Processor",
description="Upload an XLSX file and/or enter text, and the processed output will be displayed.",
examples=[
["","https://huggingface.co/spaces/Abbasid/TableQA/blob/main/Literature%20review_Test.xlsx", "How many papers are before the year 2020?"],
["","https://huggingface.co/spaces/Abbasid/TableQA/blob/main/Literature%20review_Test.xlsx", "How many papers are after the year 2020?"],
["","https://huggingface.co/spaces/Abbasid/TableQA/blob/main/Literature%20review_Test.xlsx", "what is the paper with NISIT in the title?"],
],
)
# Launch the Gradio interface
iface.launch(debug=True)
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