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Build error
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1572793 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 | import gradio as gr
import pandas as pd
from sentiment_analysis.vader_analyzer import analyze_sentiment_vader
from sentiment_analysis.transformers_analyzer import analyze_sentiment_transformers
def analyze_reviews(file, use_vader, use_transformers):
# Read the uploaded file
if file.name.endswith(".csv"):
df = pd.read_csv(file)
elif file.name.endswith(".xlsx"):
df = pd.read_excel(file)
else:
return "Please upload a CSV or Excel file."
# Check the number of entries and truncate if needed
if len(df) > 1000:
df = df.head(1000)
error_message = "The file contains more than 1,000 entries. Only the first 1,000 reviews are processed."
else:
error_message = "No Errors Found"
# Ensure the "review" column exists
df.columns = df.columns.str.lower()
if 'review' not in df.columns:
return "Please make sure the file has a 'review' column with review text."
# Apply selected sentiment analysis models
if use_vader:
vader_results = analyze_sentiment_vader(df["review"])
df = pd.concat([df, vader_results], axis=1)
if use_transformers:
transformers_results = analyze_sentiment_transformers(df["review"])
df = pd.concat([df, transformers_results], axis=1)
# Save the result to a CSV file
output_file = "sentiment_analysis_results.csv"
df.to_csv(output_file, index=False)
return output_file, error_message, df.head() # Return the output file, error message, and preview
# Define Gradio interface
interface = gr.Interface(
fn=analyze_reviews,
inputs=[
gr.File(label="Upload your review file (CSV or XLSX)"),
gr.Radio(["Vader", "Transformers"], label="Select Sentiment Analysis Model"),
],
outputs=[
gr.File(label="Download CSV"),
gr.Textbox(label="Error Message"),
gr.Dataframe(label="Data Preview"),
],
title="Bulk Sentiment Analysis for Reviews",
description="Upload a file with a 'review' column to analyze sentiment using Vader and Transformers models."
)
# Launch the Gradio app
interface.launch(share=True)
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