#!/usr/bin/env python # coding: utf-8 # ## Using Gradio to create a simple interface. # # Check out the library on [github](https://github.com/gradio-app/gradio-UI) and see the [getting started](https://gradio.app/getting_started.html) page for more demos. # We'll start with a basic function that greets an input name. # In[1]: # get_ipython().system('pip install -q gradio') # Now we'll wrap this function with a Gradio interface. # In[2]: from transformers import pipeline import pandas as pd tqa = pipeline(task="table-question-answering", model="google/tapas-large-finetuned-wtq") # In[ ]: tsqa = pipeline(task="table-question-answering", model="google/tapas-large-finetuned-sqa") # In[ ]: mstqa = pipeline(task="table-question-answering", model="microsoft/tapex-large-finetuned-wikisql") # In[ ]: mswtqa = pipeline(task="table-question-answering", model="microsoft/tapex-large-finetuned-wtq") # In[6]: # table2 = pd.read_excel("/content/Sample.xlsx").astype(str) # table3 = table2.head(20) # In[7]: # table3 # In[ ]: #t4 = table3.reset_index() # table4 # In[9]: query = "what is the highest delta onu rx power?" query2 = "what is the lowest delta onu rx power?" query3 = "what is the most frequent login id?" query4 = "how many rows with nan values are there?" query5 = "how many S2 values are there" # In[11]: # result = tsqa(table=table3, query=query5)["answer"] # result # In[13]: #mstqa(table=table4, query=query1)["answer"] # In[14]: # mswtqa(table=table3, query=query5)["answer"] # In[15]: def main(filepath, query): table5 = pd.read_excel(filepath).head(20).astype(str) result = tsqa(table=table5, query=query)["answer"] return result #greet("World") # In[16]: import gradio as gr iface = gr.Interface( fn=main, inputs=[ 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.", ) # Launch the Gradio interface iface.launch() # In[34]: import os import subprocess # Use subprocess to execute the shell command subprocess.run(["jupyter", "nbconvert", "--to", "script", "--format", "script", "--output", "/content/", "/content/drive/MyDrive/Colab Notebooks/NEW TableQA-GRADIO: Hello World.ipynb"]) # In[19]: # get_ipython().system('gradio deploy') # That's all! Go ahead and open that share link in a new tab. Check out our [getting started](https://gradio.app/getting_started.html) page for more complicated demos.