Delete app.py

app.py

@@ -1,75 +0,0 @@
-import torch
-import gradio as gr
-import pandas as pd
-import matplotlib.pyplot as plt
-
-# Use a pipeline as a high-level helper
-from transformers import pipeline
-# model_path = ("../Models/models--distilbert--distilbert-base-uncased-finetuned-sst-2-english"
-#               "/snapshots/714eb0fa89d2f80546fda750413ed43d93601a13")
-
-analyzer = pipeline("text-classification",
-                model="distilbert/distilbert-base-uncased-finetuned-sst-2-english")
-
-# analyzer = pipeline("text-classification",
-#                 model=model_path)
-
-
-
-# print(analyzer(["This production is good", "This product was quite expensive"]))
-
-def sentiment_analyzer(review):
-    sentiment = analyzer(review)
-    return sentiment[0]['label']
-
-def sentiment_bar_chart(df):
-    sentiment_counts = df['Sentiment'].value_counts()
-
-    # Create a bar chart
-    fig, ax = plt.subplots()
-    sentiment_counts.plot(kind='pie', ax=ax, autopct='%1.1f%%', color=['green', 'red'])
-    ax.set_title('Review Sentiment Counts')
-    ax.set_xlabel('Sentiment')
-    ax.set_ylabel('Count')
-    # ax.set_xticklabels(['Positive', 'Negative'], rotation=0)
-
-    # Return the figure object
-    return fig
-
-
-def read_reviews_and_analyze_sentiment(file_object):
-    # Load the Excel file into a DataFrame
-    df = pd.read_excel(file_object)
-
-    # Check if 'Review' column is in the DataFrame
-    if 'Reviews' not in df.columns:
-        raise ValueError("Excel file must contain a 'Review' column.")
-
-    # Apply the get_sentiment function to each review in the DataFrame
-    df['Sentiment'] = df['Reviews'].apply(sentiment_analyzer)
-    chart_object = sentiment_bar_chart(df)
-    return df, chart_object
-
-# result = read_reviews_and_analyze_sentiment("../Files/Prod-review.xlsx")
-# print(result)
-# Example usage:
-# df = read_reviews_and_analyze_sentiment('path_to_your_excel_file.xlsx')
-# print(df)
-
-
-demo = gr.Interface(fn=read_reviews_and_analyze_sentiment,
-                    inputs=[gr.File(file_types=["xlsx"], label="Upload your review comment file")],
-                    outputs=[gr.Dataframe(label="Sentiments"), gr.Plot(label="Sentiment Analysis")],
-                    title="@GenAILearniverse Project 3: Sentiment Analyzer",
-                    description="THIS APPLICATION WILL BE USED TO ANALYZE THE SENTIMENT BASED ON FILE UPLAODED.")
-demo.launch()
-
-
-
-
-
-
-# Example usage:
-# Assuming you have a dataframe `df` with appropriate data
-# fig = sentiment_bar_chart(df)
-# fig.show()  # This line is just to visualize the plot in a local environment