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README.md

@@ -1,12 +1,6 @@
 ---
 title: TableQA
-emoji: 💻
-colorFrom: indigo
-colorTo: indigo
+app_file: TableQAGradio.py
 sdk: gradio
 sdk_version: 4.12.0
-app_file: app.py
-pinned: false
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

TableQAGradio.py

@@ -0,0 +1,162 @@
+#!/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[12]:
+
+
+from collections import Counter
+Counter(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[21]:
+
+
+get_ipython().system('pip install notebook')
+
+
+# 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')
+
+
+# In[32]:
+
+
+from google.colab import drive
+drive.mount('/content/drive')
+
+
+# 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.